Sample records for sequence features involved
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Effective automated feature construction and selection for classification of biological sequences.
Directory of Open Access Journals (Sweden)
Uday Kamath
Full Text Available Many open problems in bioinformatics involve elucidating underlying functional signals in biological sequences. DNA sequences, in particular, are characterized by rich architectures in which functional signals are increasingly found to combine local and distal interactions at the nucleotide level. Problems of interest include detection of regulatory regions, splice sites, exons, hypersensitive sites, and more. These problems naturally lend themselves to formulation as classification problems in machine learning. When classification is based on features extracted from the sequences under investigation, success is critically dependent on the chosen set of features.We present an algorithmic framework (EFFECT for automated detection of functional signals in biological sequences. We focus here on classification problems involving DNA sequences which state-of-the-art work in machine learning shows to be challenging and involve complex combinations of local and distal features. EFFECT uses a two-stage process to first construct a set of candidate sequence-based features and then select a most effective subset for the classification task at hand. Both stages make heavy use of evolutionary algorithms to efficiently guide the search towards informative features capable of discriminating between sequences that contain a particular functional signal and those that do not.To demonstrate its generality, EFFECT is applied to three separate problems of importance in DNA research: the recognition of hypersensitive sites, splice sites, and ALU sites. Comparisons with state-of-the-art algorithms show that the framework is both general and powerful. In addition, a detailed analysis of the constructed features shows that they contain valuable biological information about DNA architecture, allowing biologists and other researchers to directly inspect the features and potentially use the insights obtained to assist wet-laboratory studies on retainment or modification
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Effective Feature Selection for Classification of Promoter Sequences.
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Kouser K
Full Text Available Exploring novel computational methods in making sense of biological data has not only been a necessity, but also productive. A part of this trend is the search for more efficient in silico methods/tools for analysis of promoters, which are parts of DNA sequences that are involved in regulation of expression of genes into other functional molecules. Promoter regions vary greatly in their function based on the sequence of nucleotides and the arrangement of protein-binding short-regions called motifs. In fact, the regulatory nature of the promoters seems to be largely driven by the selective presence and/or the arrangement of these motifs. Here, we explore computational classification of promoter sequences based on the pattern of motif distributions, as such classification can pave a new way of functional analysis of promoters and to discover the functionally crucial motifs. We make use of Position Specific Motif Matrix (PSMM features for exploring the possibility of accurately classifying promoter sequences using some of the popular classification techniques. The classification results on the complete feature set are low, perhaps due to the huge number of features. We propose two ways of reducing features. Our test results show improvement in the classification output after the reduction of features. The results also show that decision trees outperform SVM (Support Vector Machine, KNN (K Nearest Neighbor and ensemble classifier LibD3C, particularly with reduced features. The proposed feature selection methods outperform some of the popular feature transformation methods such as PCA and SVD. Also, the methods proposed are as accurate as MRMR (feature selection method but much faster than MRMR. Such methods could be useful to categorize new promoters and explore regulatory mechanisms of gene expressions in complex eukaryotic species.
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Domino effect in chemical accidents: main features and accident sequences.
Darbra, R M; Palacios, Adriana; Casal, Joaquim
2010-11-15
The main features of domino accidents in process/storage plants and in the transportation of hazardous materials were studied through an analysis of 225 accidents involving this effect. Data on these accidents, which occurred after 1961, were taken from several sources. Aspects analyzed included the accident scenario, the type of accident, the materials involved, the causes and consequences and the most common accident sequences. The analysis showed that the most frequent causes are external events (31%) and mechanical failure (29%). Storage areas (35%) and process plants (28%) are by far the most common settings for domino accidents. Eighty-nine per cent of the accidents involved flammable materials, the most frequent of which was LPG. The domino effect sequences were analyzed using relative probability event trees. The most frequent sequences were explosion→fire (27.6%), fire→explosion (27.5%) and fire→fire (17.8%). Copyright © 2010 Elsevier B.V. All rights reserved.
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Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics
Faye, Ibrahima; Samir, Brahim Belhaouari; Md Said, Abas
2014-01-01
Bioinformatics has been an emerging area of research for the last three decades. The ultimate aims of bioinformatics were to store and manage the biological data, and develop and analyze computational tools to enhance their understanding. The size of data accumulated under various sequencing projects is increasing exponentially, which presents difficulties for the experimental methods. To reduce the gap between newly sequenced protein and proteins with known functions, many computational techniques involving classification and clustering algorithms were proposed in the past. The classification of protein sequences into existing superfamilies is helpful in predicting the structure and function of large amount of newly discovered proteins. The existing classification results are unsatisfactory due to a huge size of features obtained through various feature encoding methods. In this work, a statistical metric-based feature selection technique has been proposed in order to reduce the size of the extracted feature vector. The proposed method of protein classification shows significant improvement in terms of performance measure metrics: accuracy, sensitivity, specificity, recall, F-measure, and so forth. PMID:25045727
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Domino effect in chemical accidents: main features and accident sequences
Casal Fàbrega, Joaquim; Darbra Roman, Rosa Maria
2010-01-01
The main features of domino accidents in process/storage plants and in the transportation of hazardous materials were studied through an analysis of 225 accidents involving this effect. Data on these accidents, which occurred after 1961, were taken from several sources. Aspects analyzed included the accident scenario, the type of accident, the materials involved, the causes and consequences and the most common accident sequences. The analysis showed that the most frequent causes a...
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Directory of Open Access Journals (Sweden)
Khader Shameer
2010-06-01
Full Text Available 3-dimensional domain swapping is a mechanism where two or more protein molecules form higher order oligomers by exchanging identical or similar subunits. Recently, this phenomenon has received much attention in the context of prions and neuro-degenerative diseases, due to its role in the functional regulation, formation of higher oligomers, protein misfolding, aggregation etc. While 3-dimensional domain swap mechanism can be detected from three-dimensional structures, it remains a formidable challenge to derive common sequence or structural patterns from proteins involved in swapping. We have developed a SVM-based classifier to predict domain swapping events using a set of features derived from sequence and structural data. The SVM classifier was trained on features derived from 150 proteins reported to be involved in 3D domain swapping and 150 proteins not known to be involved in swapped conformation or related to proteins involved in swapping phenomenon. The testing was performed using 63 proteins from the positive dataset and 63 proteins from the negative dataset. We obtained 76.33% accuracy from training and 73.81% accuracy from testing. Due to high diversity in the sequence, structure and functions of proteins involved in domain swapping, availability of such an algorithm to predict swapping events from sequence and structure-derived features will be an initial step towards identification of more putative proteins that may be involved in swapping or proteins involved in deposition disease. Further, the top features emerging in our feature selection method may be analysed further to understand their roles in the mechanism of domain swapping.
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Sequence-based classification using discriminatory motif feature selection.
Directory of Open Access Journals (Sweden)
Hao Xiong
Full Text Available Most existing methods for sequence-based classification use exhaustive feature generation, employing, for example, all k-mer patterns. The motivation behind such (enumerative approaches is to minimize the potential for overlooking important features. However, there are shortcomings to this strategy. First, practical constraints limit the scope of exhaustive feature generation to patterns of length ≤ k, such that potentially important, longer (> k predictors are not considered. Second, features so generated exhibit strong dependencies, which can complicate understanding of derived classification rules. Third, and most importantly, numerous irrelevant features are created. These concerns can compromise prediction and interpretation. While remedies have been proposed, they tend to be problem-specific and not broadly applicable. Here, we develop a generally applicable methodology, and an attendant software pipeline, that is predicated on discriminatory motif finding. In addition to the traditional training and validation partitions, our framework entails a third level of data partitioning, a discovery partition. A discriminatory motif finder is used on sequences and associated class labels in the discovery partition to yield a (small set of features. These features are then used as inputs to a classifier in the training partition. Finally, performance assessment occurs on the validation partition. Important attributes of our approach are its modularity (any discriminatory motif finder and any classifier can be deployed and its universality (all data, including sequences that are unaligned and/or of unequal length, can be accommodated. We illustrate our approach on two nucleosome occupancy datasets and a protein solubility dataset, previously analyzed using enumerative feature generation. Our method achieves excellent performance results, with and without optimization of classifier tuning parameters. A Python pipeline implementing the approach is
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Tu, Shiqi; Yuan, Guo-Cheng; Shao, Zhen
2017-01-01
Recently, long non-coding RNAs (lncRNAs) have emerged as an important class of molecules involved in many cellular processes. One of their primary functions is to shape epigenetic landscape through interactions with chromatin modifying proteins. However, mechanisms contributing to the specificity of such interactions remain poorly understood. Here we took the human and mouse lncRNAs that were experimentally determined to have physical interactions with Polycomb repressive complex 2 (PRC2), and systematically investigated the sequence features of these lncRNAs by developing a new computational pipeline for sequences composition analysis, in which each sequence is considered as a series of transitions between adjacent nucleotides. Through that, PRC2-binding lncRNAs were found to be associated with a set of distinctive and evolutionarily conserved sequence features, which can be utilized to distinguish them from the others with considerable accuracy. We further identified fragments of PRC2-binding lncRNAs that are enriched with these sequence features, and found they show strong PRC2-binding signals and are more highly conserved across species than the other parts, implying their functional importance.
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SeqVISTA: a graphical tool for sequence feature visualization and comparison
Directory of Open Access Journals (Sweden)
Niu Tianhua
2003-01-01
Full Text Available Abstract Background Many readers will sympathize with the following story. You are viewing a gene sequence in Entrez, and you want to find whether it contains a particular sequence motif. You reach for the browser's "find in page" button, but those darn spaces every 10 bp get in the way. And what if the motif is on the opposite strand? Subsequently, your favorite sequence analysis software informs you that there is an interesting feature at position 13982–14013. By painstakingly counting the 10 bp blocks, you are able to examine the sequence at this location. But now you want to see what other features have been annotated close by, and this information is buried several screenfuls higher up the web page. Results SeqVISTA presents a holistic, graphical view of features annotated on nucleotide or protein sequences. This interactive tool highlights the residues in the sequence that correspond to features chosen by the user, and allows easy searching for sequence motifs or extraction of particular subsequences. SeqVISTA is able to display results from diverse sequence analysis tools in an integrated fashion, and aims to provide much-needed unity to the bioinformatics resources scattered around the Internet. Our viewer may be launched on a GenBank record by a single click of a button installed in the web browser. Conclusion SeqVISTA allows insights to be gained by viewing the totality of sequence annotations and predictions, which may be more revealing than the sum of their parts. SeqVISTA runs on any operating system with a Java 1.4 virtual machine. It is freely available to academic users at http://zlab.bu.edu/SeqVISTA.
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Coding visual features extracted from video sequences.
Baroffio, Luca; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano
2014-05-01
Visual features are successfully exploited in several applications (e.g., visual search, object recognition and tracking, etc.) due to their ability to efficiently represent image content. Several visual analysis tasks require features to be transmitted over a bandwidth-limited network, thus calling for coding techniques to reduce the required bit budget, while attaining a target level of efficiency. In this paper, we propose, for the first time, a coding architecture designed for local features (e.g., SIFT, SURF) extracted from video sequences. To achieve high coding efficiency, we exploit both spatial and temporal redundancy by means of intraframe and interframe coding modes. In addition, we propose a coding mode decision based on rate-distortion optimization. The proposed coding scheme can be conveniently adopted to implement the analyze-then-compress (ATC) paradigm in the context of visual sensor networks. That is, sets of visual features are extracted from video frames, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast to the traditional compress-then-analyze (CTA) paradigm, in which video sequences acquired at a node are compressed and then sent to a central unit for further processing. In this paper, we compare these coding paradigms using metrics that are routinely adopted to evaluate the suitability of visual features in the context of content-based retrieval, object recognition, and tracking. Experimental results demonstrate that, thanks to the significant coding gains achieved by the proposed coding scheme, ATC outperforms CTA with respect to all evaluation metrics.
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Poly(A) motif prediction using spectral latent features from human DNA sequences
Xie, Bo; Jankovic, Boris R.; Bajic, Vladimir B.; Song, Le; Gao, Xin
2013-01-01
Motivation: Polyadenylation is the addition of a poly(A) tail to an RNA molecule. Identifying DNA sequence motifs that signal the addition of poly(A) tails is essential to improved genome annotation and better understanding of the regulatory mechanisms and stability of mRNA.Existing poly(A) motif predictors demonstrate that information extracted from the surrounding nucleotide sequences of candidate poly(A) motifs can differentiate true motifs from the false ones to a great extent. A variety of sophisticated features has been explored, including sequential, structural, statistical, thermodynamic and evolutionary properties. However, most of these methods involve extensive manual feature engineering, which can be time-consuming and can require in-depth domain knowledge.Results: We propose a novel machine-learning method for poly(A) motif prediction by marrying generative learning (hidden Markov models) and discriminative learning (support vector machines). Generative learning provides a rich palette on which the uncertainty and diversity of sequence information can be handled, while discriminative learning allows the performance of the classification task to be directly optimized. Here, we used hidden Markov models for fitting the DNA sequence dynamics, and developed an efficient spectral algorithm for extracting latent variable information from these models. These spectral latent features were then fed into support vector machines to fine-tune the classification performance.We evaluated our proposed method on a comprehensive human poly(A) dataset that consists of 14 740 samples from 12 of the most abundant variants of human poly(A) motifs. Compared with one of the previous state-of-the-art methods in the literature (the random forest model with expert-crafted features), our method reduces the average error rate, false-negative rate and false-positive rate by 26, 15 and 35%, respectively. Meanwhile, our method makes ?30% fewer error predictions relative to the other
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Poly(A) motif prediction using spectral latent features from human DNA sequences
Xie, Bo
2013-06-21
Motivation: Polyadenylation is the addition of a poly(A) tail to an RNA molecule. Identifying DNA sequence motifs that signal the addition of poly(A) tails is essential to improved genome annotation and better understanding of the regulatory mechanisms and stability of mRNA.Existing poly(A) motif predictors demonstrate that information extracted from the surrounding nucleotide sequences of candidate poly(A) motifs can differentiate true motifs from the false ones to a great extent. A variety of sophisticated features has been explored, including sequential, structural, statistical, thermodynamic and evolutionary properties. However, most of these methods involve extensive manual feature engineering, which can be time-consuming and can require in-depth domain knowledge.Results: We propose a novel machine-learning method for poly(A) motif prediction by marrying generative learning (hidden Markov models) and discriminative learning (support vector machines). Generative learning provides a rich palette on which the uncertainty and diversity of sequence information can be handled, while discriminative learning allows the performance of the classification task to be directly optimized. Here, we used hidden Markov models for fitting the DNA sequence dynamics, and developed an efficient spectral algorithm for extracting latent variable information from these models. These spectral latent features were then fed into support vector machines to fine-tune the classification performance.We evaluated our proposed method on a comprehensive human poly(A) dataset that consists of 14 740 samples from 12 of the most abundant variants of human poly(A) motifs. Compared with one of the previous state-of-the-art methods in the literature (the random forest model with expert-crafted features), our method reduces the average error rate, false-negative rate and false-positive rate by 26, 15 and 35%, respectively. Meanwhile, our method makes ?30% fewer error predictions relative to the other
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Prediction of novel archaeal enzymes from sequence-derived features
DEFF Research Database (Denmark)
Jensen, Lars Juhl; Skovgaard, Marie; Brunak, Søren
2002-01-01
The completely sequenced archaeal genomes potentially encode, among their many functionally uncharacterized genes, novel enzymes of biotechnological interest. We have developed a prediction method for detection and classification of enzymes from sequence alone (available at http://www.cbs.dtu.dk/......The completely sequenced archaeal genomes potentially encode, among their many functionally uncharacterized genes, novel enzymes of biotechnological interest. We have developed a prediction method for detection and classification of enzymes from sequence alone (available at http......://www.cbs.dtu.dk/services/ArchaeaFun/). The method does not make use of sequence similarity; rather, it relies on predicted protein features like cotranslational and posttranslational modifications, secondary structure, and simple physical/chemical properties....
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Enhanced regulatory sequence prediction using gapped k-mer features.
Ghandi, Mahmoud; Lee, Dongwon; Mohammad-Noori, Morteza; Beer, Michael A
2014-07-01
Oligomers of length k, or k-mers, are convenient and widely used features for modeling the properties and functions of DNA and protein sequences. However, k-mers suffer from the inherent limitation that if the parameter k is increased to resolve longer features, the probability of observing any specific k-mer becomes very small, and k-mer counts approach a binary variable, with most k-mers absent and a few present once. Thus, any statistical learning approach using k-mers as features becomes susceptible to noisy training set k-mer frequencies once k becomes large. To address this problem, we introduce alternative feature sets using gapped k-mers, a new classifier, gkm-SVM, and a general method for robust estimation of k-mer frequencies. To make the method applicable to large-scale genome wide applications, we develop an efficient tree data structure for computing the kernel matrix. We show that compared to our original kmer-SVM and alternative approaches, our gkm-SVM predicts functional genomic regulatory elements and tissue specific enhancers with significantly improved accuracy, increasing the precision by up to a factor of two. We then show that gkm-SVM consistently outperforms kmer-SVM on human ENCODE ChIP-seq datasets, and further demonstrate the general utility of our method using a Naïve-Bayes classifier. Although developed for regulatory sequence analysis, these methods can be applied to any sequence classification problem.
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Enhanced regulatory sequence prediction using gapped k-mer features.
Directory of Open Access Journals (Sweden)
Mahmoud Ghandi
2014-07-01
Full Text Available Oligomers of length k, or k-mers, are convenient and widely used features for modeling the properties and functions of DNA and protein sequences. However, k-mers suffer from the inherent limitation that if the parameter k is increased to resolve longer features, the probability of observing any specific k-mer becomes very small, and k-mer counts approach a binary variable, with most k-mers absent and a few present once. Thus, any statistical learning approach using k-mers as features becomes susceptible to noisy training set k-mer frequencies once k becomes large. To address this problem, we introduce alternative feature sets using gapped k-mers, a new classifier, gkm-SVM, and a general method for robust estimation of k-mer frequencies. To make the method applicable to large-scale genome wide applications, we develop an efficient tree data structure for computing the kernel matrix. We show that compared to our original kmer-SVM and alternative approaches, our gkm-SVM predicts functional genomic regulatory elements and tissue specific enhancers with significantly improved accuracy, increasing the precision by up to a factor of two. We then show that gkm-SVM consistently outperforms kmer-SVM on human ENCODE ChIP-seq datasets, and further demonstrate the general utility of our method using a Naïve-Bayes classifier. Although developed for regulatory sequence analysis, these methods can be applied to any sequence classification problem.
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Deep sequencing of foot-and-mouth disease virus reveals RNA sequences involved in genome packaging.
Logan, Grace; Newman, Joseph; Wright, Caroline F; Lasecka-Dykes, Lidia; Haydon, Daniel T; Cottam, Eleanor M; Tuthill, Tobias J
2017-10-18
Non-enveloped viruses protect their genomes by packaging them into an outer shell or capsid of virus-encoded proteins. Packaging and capsid assembly in RNA viruses can involve interactions between capsid proteins and secondary structures in the viral genome as exemplified by the RNA bacteriophage MS2 and as proposed for other RNA viruses of plants, animals and human. In the picornavirus family of non-enveloped RNA viruses, the requirements for genome packaging remain poorly understood. Here we show a novel and simple approach to identify predicted RNA secondary structures involved in genome packaging in the picornavirus foot-and-mouth disease virus (FMDV). By interrogating deep sequencing data generated from both packaged and unpackaged populations of RNA we have determined multiple regions of the genome with constrained variation in the packaged population. Predicted secondary structures of these regions revealed stem loops with conservation of structure and a common motif at the loop. Disruption of these features resulted in attenuation of virus growth in cell culture due to a reduction in assembly of mature virions. This study provides evidence for the involvement of predicted RNA structures in picornavirus packaging and offers a readily transferable methodology for identifying packaging requirements in many other viruses. Importance In order to transmit their genetic material to a new host, non-enveloped viruses must protect their genomes by packaging them into an outer shell or capsid of virus-encoded proteins. For many non-enveloped RNA viruses the requirements for this critical part of the viral life cycle remain poorly understood. We have identified RNA sequences involved in genome packaging of the picornavirus foot-and-mouth disease virus. This virus causes an economically devastating disease of livestock affecting both the developed and developing world. The experimental methods developed to carry out this work are novel, simple and transferable to the
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Automatic discovery of cross-family sequence features associated with protein function
Directory of Open Access Journals (Sweden)
Krings Andrea
2006-01-01
Full Text Available Abstract Background Methods for predicting protein function directly from amino acid sequences are useful tools in the study of uncharacterised protein families and in comparative genomics. Until now, this problem has been approached using machine learning techniques that attempt to predict membership, or otherwise, to predefined functional categories or subcellular locations. A potential drawback of this approach is that the human-designated functional classes may not accurately reflect the underlying biology, and consequently important sequence-to-function relationships may be missed. Results We show that a self-supervised data mining approach is able to find relationships between sequence features and functional annotations. No preconceived ideas about functional categories are required, and the training data is simply a set of protein sequences and their UniProt/Swiss-Prot annotations. The main technical aspect of the approach is the co-evolution of amino acid-based regular expressions and keyword-based logical expressions with genetic programming. Our experiments on a strictly non-redundant set of eukaryotic proteins reveal that the strongest and most easily detected sequence-to-function relationships are concerned with targeting to various cellular compartments, which is an area already well studied both experimentally and computationally. Of more interest are a number of broad functional roles which can also be correlated with sequence features. These include inhibition, biosynthesis, transcription and defence against bacteria. Despite substantial overlaps between these functions and their corresponding cellular compartments, we find clear differences in the sequence motifs used to predict some of these functions. For example, the presence of polyglutamine repeats appears to be linked more strongly to the "transcription" function than to the general "nuclear" function/location. Conclusion We have developed a novel and useful approach for
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DEFF Research Database (Denmark)
Wernersson, Rasmus; Rapacki, Krzysztof; Stærfeldt, Hans Henrik
2006-01-01
FeatureMap3D is a web-based tool that maps protein features onto 3D structures. The user provides sequences annotated with any feature of interest, such as post-translational modifications, protease cleavage sites or exonic structure and FeatureMap3D will then search the Protein Data Bank (PDB) f...
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The sequence, structure and evolutionary features of HOTAIR in mammals
2011-01-01
Background An increasing number of long noncoding RNAs (lncRNAs) have been identified recently. Different from all the others that function in cis to regulate local gene expression, the newly identified HOTAIR is located between HoxC11 and HoxC12 in the human genome and regulates HoxD expression in multiple tissues. Like the well-characterised lncRNA Xist, HOTAIR binds to polycomb proteins to methylate histones at multiple HoxD loci, but unlike Xist, many details of its structure and function, as well as the trans regulation, remain unclear. Moreover, HOTAIR is involved in the aberrant regulation of gene expression in cancer. Results To identify conserved domains in HOTAIR and study the phylogenetic distribution of this lncRNA, we searched the genomes of 10 mammalian and 3 non-mammalian vertebrates for matches to its 6 exons and the two conserved domains within the 1800 bp exon6 using Infernal. There was just one high-scoring hit for each mammal, but many low-scoring hits were found in both mammals and non-mammalian vertebrates. These hits and their flanking genes in four placental mammals and platypus were examined to determine whether HOTAIR contained elements shared by other lncRNAs. Several of the hits were within unknown transcripts or ncRNAs, many were within introns of, or antisense to, protein-coding genes, and conservation of the flanking genes was observed only between human and chimpanzee. Phylogenetic analysis revealed discrete evolutionary dynamics for orthologous sequences of HOTAIR exons. Exon1 at the 5' end and a domain in exon6 near the 3' end, which contain domains that bind to multiple proteins, have evolved faster in primates than in other mammals. Structures were predicted for exon1, two domains of exon6 and the full HOTAIR sequence. The sequence and structure of two fragments, in exon1 and the domain B of exon6 respectively, were identified to robustly occur in predicted structures of exon1, domain B of exon6 and the full HOTAIR in mammals
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Visual Localization across Seasons Using Sequence Matching Based on Multi-Feature Combination.
Qiao, Yongliang
2017-10-25
Visual localization is widely used in autonomous navigation system and Advanced Driver Assistance Systems (ADAS). However, visual-based localization in seasonal changing situations is one of the most challenging topics in computer vision and the intelligent vehicle community. The difficulty of this task is related to the strong appearance changes that occur in scenes due to weather or season changes. In this paper, a place recognition based visual localization method is proposed, which realizes the localization by identifying previously visited places using the sequence matching method. It operates by matching query image sequences to an image database acquired previously (video acquired during traveling period). In this method, in order to improve matching accuracy, multi-feature is constructed by combining a global GIST descriptor and local binary feature CSLBP (Center-symmetric local binary patterns) to represent image sequence. Then, similarity measurement according to Chi-square distance is used for effective sequences matching. For experimental evaluation, the relationship between image sequence length and sequences matching performance is studied. To show its effectiveness, the proposed method is tested and evaluated in four seasons outdoor environments. The results have shown improved precision-recall performance against the state-of-the-art SeqSLAM algorithm.
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Liu, Bin; Liu, Fule; Fang, Longyun; Wang, Xiaolong; Chou, Kuo-Chen
2015-04-15
In order to develop powerful computational predictors for identifying the biological features or attributes of DNAs, one of the most challenging problems is to find a suitable approach to effectively represent the DNA sequences. To facilitate the studies of DNAs and nucleotides, we developed a Python package called representations of DNAs (repDNA) for generating the widely used features reflecting the physicochemical properties and sequence-order effects of DNAs and nucleotides. There are three feature groups composed of 15 features. The first group calculates three nucleic acid composition features describing the local sequence information by means of kmers; the second group calculates six autocorrelation features describing the level of correlation between two oligonucleotides along a DNA sequence in terms of their specific physicochemical properties; the third group calculates six pseudo nucleotide composition features, which can be used to represent a DNA sequence with a discrete model or vector yet still keep considerable sequence-order information via the physicochemical properties of its constituent oligonucleotides. In addition, these features can be easily calculated based on both the built-in and user-defined properties via using repDNA. The repDNA Python package is freely accessible to the public at http://bioinformatics.hitsz.edu.cn/repDNA/. bliu@insun.hit.edu.cn or kcchou@gordonlifescience.org Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Visualization of protein sequence features using JavaScript and SVG with pViz.js.
Mukhyala, Kiran; Masselot, Alexandre
2014-12-01
pViz.js is a visualization library for displaying protein sequence features in a Web browser. By simply providing a sequence and the locations of its features, this lightweight, yet versatile, JavaScript library renders an interactive view of the protein features. Interactive exploration of protein sequence features over the Web is a common need in Bioinformatics. Although many Web sites have developed viewers to display these features, their implementations are usually focused on data from a specific source or use case. Some of these viewers can be adapted to fit other use cases but are not designed to be reusable. pViz makes it easy to display features as boxes aligned to a protein sequence with zooming functionality but also includes predefined renderings for secondary structure and post-translational modifications. The library is designed to further customize this view. We demonstrate such applications of pViz using two examples: a proteomic data visualization tool with an embedded viewer for displaying features on protein structure, and a tool to visualize the results of the variant_effect_predictor tool from Ensembl. pViz.js is a JavaScript library, available on github at https://github.com/Genentech/pviz. This site includes examples and functional applications, installation instructions and usage documentation. A Readme file, which explains how to use pViz with examples, is available as Supplementary Material A. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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An HMM posterior decoder for sequence feature prediction that includes homology information
DEFF Research Database (Denmark)
Käll, Lukas; Krogh, Anders Stærmose; Sonnhammer, Erik L. L.
2005-01-01
Motivation: When predicting sequence features like transmembrane topology, signal peptides, coil-coil structures, protein secondary structure or genes, extra support can be gained from homologs. Results: We present here a general hidden Markov model (HMM) decoding algorithm that combines probabil......Motivation: When predicting sequence features like transmembrane topology, signal peptides, coil-coil structures, protein secondary structure or genes, extra support can be gained from homologs. Results: We present here a general hidden Markov model (HMM) decoding algorithm that combines......://phobius.cgb.ki.se/poly.html . An implementation of the algorithm is available on request from the authors....
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Visual Localization across Seasons Using Sequence Matching Based on Multi-Feature Combination
Directory of Open Access Journals (Sweden)
Yongliang Qiao
2017-10-01
Full Text Available Visual localization is widely used in autonomous navigation system and Advanced Driver Assistance Systems (ADAS. However, visual-based localization in seasonal changing situations is one of the most challenging topics in computer vision and the intelligent vehicle community. The difficulty of this task is related to the strong appearance changes that occur in scenes due to weather or season changes. In this paper, a place recognition based visual localization method is proposed, which realizes the localization by identifying previously visited places using the sequence matching method. It operates by matching query image sequences to an image database acquired previously (video acquired during traveling period. In this method, in order to improve matching accuracy, multi-feature is constructed by combining a global GIST descriptor and local binary feature CSLBP (Center-symmetric local binary patterns to represent image sequence. Then, similarity measurement according to Chi-square distance is used for effective sequences matching. For experimental evaluation, the relationship between image sequence length and sequences matching performance is studied. To show its effectiveness, the proposed method is tested and evaluated in four seasons outdoor environments. The results have shown improved precision–recall performance against the state-of-the-art SeqSLAM algorithm.
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Involvement of Disperse Repetitive Sequences in Wheat/Rye Genome Adjustment
Directory of Open Access Journals (Sweden)
Manuela Silva
2012-07-01
Full Text Available The union of different genomes in the same nucleus frequently results in hybrid genotypes with improved genome plasticity related to both genome remodeling events and changes in gene expression. Most modern cereal crops are polyploid species. Triticale, synthesized by the cross between wheat and rye, constitutes an excellent model to study polyploidization functional implications. We intend to attain a deeper knowledge of dispersed repetitive sequence involvement in parental genome reshuffle in triticale and in wheat-rye addition lines that have the entire wheat genome plus each rye chromosome pair. Through Random Amplified Polymorphic DNA (RAPD analysis with OPH20 10-mer primer we unraveled clear alterations corresponding to the loss of specific bands from both parental genomes. Moreover, the sequential nature of those events was revealed by the increased absence of rye-origin bands in wheat-rye addition lines in comparison with triticale. Remodeled band sequencing revealed that both repetitive and coding genome domains are affected in wheat-rye hybrid genotypes. Additionally, the amplification and sequencing of pSc20H internal segments showed that the disappearance of parental bands may result from restricted sequence alterations and unraveled the involvement of wheat/rye related repetitive sequences in genome adjustment needed for hybrid plant stabilization.
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Ping, Zheng; Siegal, Gene P.; Almeida, Jonas S.; Schnitt, Stuart J.; Shen, Dejun
2014-01-01
Background: Genetics and genomics have radically altered our understanding of breast cancer progression. However, the genomic basis of various histopathologic features of breast cancer is not yet well-defined. Materials and Methods: The Cancer Genome Atlas (TCGA) is an international database containing a large collection of human cancer genome sequencing data. cBioPortal is a web tool developed for mining these sequencing data. We performed mining of TCGA sequencing data in an attempt to characterize the genomic features correlated with breast cancer histopathology. We first assessed the quality of the TCGA data using a group of genes with known alterations in various cancers. Both genome-wide gene mutation and copy number changes as well as a group of genes with a high frequency of genetic changes were then correlated with various histopathologic features of invasive breast cancer. Results: Validation of TCGA data using a group of genes with known alterations in breast cancer suggests that the TCGA has accurately documented the genomic abnormalities of multiple malignancies. Further analysis of TCGA breast cancer sequencing data shows that accumulation of specific genomic defects is associated with higher tumor grade, larger tumor size and receptor negativity. Distinct groups of genomic changes were found to be associated with the different grades of invasive ductal carcinoma. The mutator role of the TP53 gene was validated by genomic sequencing data of invasive breast cancer and TP53 mutation was found to play a critical role in defining high tumor grade. Conclusions: Data mining of the TCGA genome sequencing data is an innovative and reliable method to help characterize the genomic abnormalities associated with histopathologic features of invasive breast cancer. PMID:24672738
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Directory of Open Access Journals (Sweden)
Zheng Ping
2014-01-01
Full Text Available Background: Genetics and genomics have radically altered our understanding of breast cancer progression. However, the genomic basis of various histopathologic features of breast cancer is not yet well-defined. Materials and Methods: The Cancer Genome Atlas (TCGA is an international database containing a large collection of human cancer genome sequencing data. cBioPortal is a web tool developed for mining these sequencing data. We performed mining of TCGA sequencing data in an attempt to characterize the genomic features correlated with breast cancer histopathology. We first assessed the quality of the TCGA data using a group of genes with known alterations in various cancers. Both genome-wide gene mutation and copy number changes as well as a group of genes with a high frequency of genetic changes were then correlated with various histopathologic features of invasive breast cancer. Results: Validation of TCGA data using a group of genes with known alterations in breast cancer suggests that the TCGA has accurately documented the genomic abnormalities of multiple malignancies. Further analysis of TCGA breast cancer sequencing data shows that accumulation of specific genomic defects is associated with higher tumor grade, larger tumor size and receptor negativity. Distinct groups of genomic changes were found to be associated with the different grades of invasive ductal carcinoma. The mutator role of the TP53 gene was validated by genomic sequencing data of invasive breast cancer and TP53 mutation was found to play a critical role in defining high tumor grade. Conclusions: Data mining of the TCGA genome sequencing data is an innovative and reliable method to help characterize the genomic abnormalities associated with histopathologic features of invasive breast cancer.
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Noise-robust speech recognition through auditory feature detection and spike sequence decoding.
Schafer, Phillip B; Jin, Dezhe Z
2014-03-01
Speech recognition in noisy conditions is a major challenge for computer systems, but the human brain performs it routinely and accurately. Automatic speech recognition (ASR) systems that are inspired by neuroscience can potentially bridge the performance gap between humans and machines. We present a system for noise-robust isolated word recognition that works by decoding sequences of spikes from a population of simulated auditory feature-detecting neurons. Each neuron is trained to respond selectively to a brief spectrotemporal pattern, or feature, drawn from the simulated auditory nerve response to speech. The neural population conveys the time-dependent structure of a sound by its sequence of spikes. We compare two methods for decoding the spike sequences--one using a hidden Markov model-based recognizer, the other using a novel template-based recognition scheme. In the latter case, words are recognized by comparing their spike sequences to template sequences obtained from clean training data, using a similarity measure based on the length of the longest common sub-sequence. Using isolated spoken digits from the AURORA-2 database, we show that our combined system outperforms a state-of-the-art robust speech recognizer at low signal-to-noise ratios. Both the spike-based encoding scheme and the template-based decoding offer gains in noise robustness over traditional speech recognition methods. Our system highlights potential advantages of spike-based acoustic coding and provides a biologically motivated framework for robust ASR development.
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Directory of Open Access Journals (Sweden)
Jian Zhang
2014-06-01
Full Text Available S-nitrosylation (SNO is one of the most universal reversible post-translational modifications involved in many biological processes. Malfunction or dysregulation of SNO leads to a series of severe diseases, such as developmental abnormalities and various diseases. Therefore, the identification of SNO sites (SNOs provides insights into disease progression and drug development. In this paper, a new bioinformatics tool, named PSNO, is proposed to identify SNOs from protein sequences. Firstly, we explore various promising sequence-derived discriminative features, including the evolutionary profile, the predicted secondary structure and the physicochemical properties. Secondly, rather than simply combining the features, which may bring about information redundancy and unwanted noise, we use the relative entropy selection and incremental feature selection approach to select the optimal feature subsets. Thirdly, we train our model by the technique of the k-nearest neighbor algorithm. Using both informative features and an elaborate feature selection scheme, our method, PSNO, achieves good prediction performance with a mean Mathews correlation coefficient (MCC value of about 0.5119 on the training dataset using 10-fold cross-validation. These results indicate that PSNO can be used as a competitive predictor among the state-of-the-art SNOs prediction tools. A web-server, named PSNO, which implements the proposed method, is freely available at http://59.73.198.144:8088/PSNO/.
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An improved classification of G-protein-coupled receptors using sequence-derived features
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Peng Zhen-Ling
2010-08-01
Full Text Available Abstract Background G-protein-coupled receptors (GPCRs play a key role in diverse physiological processes and are the targets of almost two-thirds of the marketed drugs. The 3 D structures of GPCRs are largely unavailable; however, a large number of GPCR primary sequences are known. To facilitate the identification and characterization of novel receptors, it is therefore very valuable to develop a computational method to accurately predict GPCRs from the protein primary sequences. Results We propose a new method called PCA-GPCR, to predict GPCRs using a comprehensive set of 1497 sequence-derived features. The principal component analysis is first employed to reduce the dimension of the feature space to 32. Then, the resulting 32-dimensional feature vectors are fed into a simple yet powerful classification algorithm, called intimate sorting, to predict GPCRs at five levels. The prediction at the first level determines whether a protein is a GPCR or a non-GPCR. If it is predicted to be a GPCR, then it will be further predicted into certain family, subfamily, sub-subfamily and subtype by the classifiers at the second, third, fourth, and fifth levels, respectively. To train the classifiers applied at five levels, a non-redundant dataset is carefully constructed, which contains 3178, 1589, 4772, 4924, and 2741 protein sequences at the respective levels. Jackknife tests on this training dataset show that the overall accuracies of PCA-GPCR at five levels (from the first to the fifth can achieve up to 99.5%, 88.8%, 80.47%, 80.3%, and 92.34%, respectively. We further perform predictions on a dataset of 1238 GPCRs at the second level, and on another two datasets of 167 and 566 GPCRs respectively at the fourth level. The overall prediction accuracies of our method are consistently higher than those of the existing methods to be compared. Conclusions The comprehensive set of 1497 features is believed to be capable of capturing information about amino acid
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FASTERp: A Feature Array Search Tool for Estimating Resemblance of Protein Sequences
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Macklin, Derek; Egan, Rob; Wang, Zhong
2014-03-14
Metagenome sequencing efforts have provided a large pool of billions of genes for identifying enzymes with desirable biochemical traits. However, homology search with billions of genes in a rapidly growing database has become increasingly computationally impractical. Here we present our pilot efforts to develop a novel alignment-free algorithm for homology search. Specifically, we represent individual proteins as feature vectors that denote the presence or absence of short kmers in the protein sequence. Similarity between feature vectors is then computed using the Tanimoto score, a distance metric that can be rapidly computed on bit string representations of feature vectors. Preliminary results indicate good correlation with optimal alignment algorithms (Spearman r of 0.87, ~;;1,000,000 proteins from Pfam), as well as with heuristic algorithms such as BLAST (Spearman r of 0.86, ~;;1,000,000 proteins). Furthermore, a prototype of FASTERp implemented in Python runs approximately four times faster than BLAST on a small scale dataset (~;;1000 proteins). We are optimizing and scaling to improve FASTERp to enable rapid homology searches against billion-protein databases, thereby enabling more comprehensive gene annotation efforts.
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Predicting protein amidation sites by orchestrating amino acid sequence features
Zhao, Shuqiu; Yu, Hua; Gong, Xiujun
2017-08-01
Amidation is the fourth major category of post-translational modifications, which plays an important role in physiological and pathological processes. Identifying amidation sites can help us understanding the amidation and recognizing the original reason of many kinds of diseases. But the traditional experimental methods for predicting amidation sites are often time-consuming and expensive. In this study, we propose a computational method for predicting amidation sites by orchestrating amino acid sequence features. Three kinds of feature extraction methods are used to build a feature vector enabling to capture not only the physicochemical properties but also position related information of the amino acids. An extremely randomized trees algorithm is applied to choose the optimal features to remove redundancy and dependence among components of the feature vector by a supervised fashion. Finally the support vector machine classifier is used to label the amidation sites. When tested on an independent data set, it shows that the proposed method performs better than all the previous ones with the prediction accuracy of 0.962 at the Matthew's correlation coefficient of 0.89 and area under curve of 0.964.
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An Observational Study of Children's Involvement in Informed Consent for Exome Sequencing Research.
Miller, Victoria A; Werner-Lin, Allison; Walser, Sarah A; Biswas, Sawona; Bernhardt, Barbara A
2017-02-01
The goal of this study was to examine children's involvement in consent sessions for exome sequencing research and associations of involvement with provider and parent communication. Participants included 44 children (8-17 years) from five cohorts who were offered participation in an exome sequencing study. The consent sessions were audiotaped, transcribed, and coded. Providers attempted to facilitate the child's involvement in the majority (73%) of sessions, and most (75%) children also verbally participated. Provider facilitation was strongly associated with likelihood of child participation. These findings underscore that strategies such as asking for children's opinions and soliciting their questions show respect for children and may increase the likelihood that they are engaged and involved in decisions about research participation.
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Directory of Open Access Journals (Sweden)
Steven N Hart
Full Text Available BACKGROUND: Structural variation (SV represents a significant, yet poorly understood contribution to an individual's genetic makeup. Advanced next-generation sequencing technologies are widely used to discover such variations, but there is no single detection tool that is considered a community standard. In an attempt to fulfil this need, we developed an algorithm, SoftSearch, for discovering structural variant breakpoints in Illumina paired-end next-generation sequencing data. SoftSearch combines multiple strategies for detecting SV including split-read, discordant read-pair, and unmated pairs. Co-localized split-reads and discordant read pairs are used to refine the breakpoints. RESULTS: We developed and validated SoftSearch using real and synthetic datasets. SoftSearch's key features are 1 not requiring secondary (or exhaustive primary alignment, 2 portability into established sequencing workflows, and 3 is applicable to any DNA-sequencing experiment (e.g. whole genome, exome, custom capture, etc.. SoftSearch identifies breakpoints from a small number of soft-clipped bases from split reads and a few discordant read-pairs which on their own would not be sufficient to make an SV call. CONCLUSIONS: We show that SoftSearch can identify more true SVs by combining multiple sequence features. SoftSearch was able to call clinically relevant SVs in the BRCA2 gene not reported by other tools while offering significantly improved overall performance.
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Sequence features responsible for intron retention in human
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Sakabe Noboru
2007-02-01
Full Text Available Abstract Background One of the least common types of alternative splicing is the complete retention of an intron in a mature transcript. Intron retention (IR is believed to be the result of intron, rather than exon, definition associated with failure of the recognition of weak splice sites flanking short introns. Although studies on individual retained introns have been published, few systematic surveys of large amounts of data have been conducted on the mechanisms that lead to IR. Results TTo understand how sequence features are associated with or control IR, and to produce a generalized model that could reveal previously unknown signals that regulate this type of alternative splicing, we partitioned intron retention events observed in human cDNAs into two groups based on the relative abundance of both isoforms and compared relevant features. We found that a higher frequency of IR in human is associated with individual introns that have weaker splice sites, genes with shorter intron lengths, higher expression levels and lower density of both a set of exon splicing silencers (ESSs and the intronic splicing enhancer GGG. Both groups of retained introns presented events conserved in mouse, in which the retained introns were also short and presented weaker splice sites. Conclusion Although our results confirmed that weaker splice sites are associated with IR, they showed that this feature alone cannot explain a non-negligible fraction of events. Our analysis suggests that cis-regulatory elements are likely to play a crucial role in regulating IR and also reveals previously unknown features that seem to influence its occurrence. These results highlight the importance of considering the interplay among these features in the regulation of the relative frequency of IR.
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Structural and sequence features of two residue turns in beta-hairpins.
Madan, Bharat; Seo, Sung Yong; Lee, Sun-Gu
2014-09-01
Beta-turns in beta-hairpins have been implicated as important sites in protein folding. In particular, two residue β-turns, the most abundant connecting elements in beta-hairpins, have been a major target for engineering protein stability and folding. In this study, we attempted to investigate and update the structural and sequence properties of two residue turns in beta-hairpins with a large data set. For this, 3977 beta-turns were extracted from 2394 nonhomologous protein chains and analyzed. First, the distribution, dihedral angles and twists of two residue turn types were determined, and compared with previous data. The trend of turn type occurrence and most structural features of the turn types were similar to previous results, but for the first time Type II turns in beta-hairpins were identified. Second, sequence motifs for the turn types were devised based on amino acid positional potentials of two-residue turns, and their distributions were examined. From this study, we could identify code-like sequence motifs for the two residue beta-turn types. Finally, structural and sequence properties of beta-strands in the beta-hairpins were analyzed, which revealed that the beta-strands showed no specific sequence and structural patterns for turn types. The analytical results in this study are expected to be a reference in the engineering or design of beta-hairpin turn structures and sequences. © 2014 Wiley Periodicals, Inc.
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kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic data sets
Fletez-Brant, Christopher; Lee, Dongwon; McCallion, Andrew S.; Beer, Michael A.
2013-01-01
Massively parallel sequencing technologies have made the generation of genomic data sets a routine component of many biological investigations. For example, Chromatin immunoprecipitation followed by sequence assays detect genomic regions bound (directly or indirectly) by specific factors, and DNase-seq identifies regions of open chromatin. A major bottleneck in the interpretation of these data is the identification of the underlying DNA sequence code that defines, and ultimately facilitates prediction of, these transcription factor (TF) bound or open chromatin regions. We have recently developed a novel computational methodology, which uses a support vector machine (SVM) with kmer sequence features (kmer-SVM) to identify predictive combinations of short transcription factor-binding sites, which determine the tissue specificity of these genomic assays (Lee, Karchin and Beer, Discriminative prediction of mammalian enhancers from DNA sequence. Genome Res. 2011; 21:2167–80). This regulatory information can (i) give confidence in genomic experiments by recovering previously known binding sites, and (ii) reveal novel sequence features for subsequent experimental testing of cooperative mechanisms. Here, we describe the development and implementation of a web server to allow the broader research community to independently apply our kmer-SVM to analyze and interpret their genomic datasets. We analyze five recently published data sets and demonstrate how this tool identifies accessory factors and repressive sequence elements. kmer-SVM is available at http://kmersvm.beerlab.org. PMID:23771147
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Mapping genomic features to functional traits through microbial whole genome sequences.
Zhang, Wei; Zeng, Erliang; Liu, Dan; Jones, Stuart E; Emrich, Scott
2014-01-01
Recently, the utility of trait-based approaches for microbial communities has been identified. Increasing availability of whole genome sequences provide the opportunity to explore the genetic foundations of a variety of functional traits. We proposed a machine learning framework to quantitatively link the genomic features with functional traits. Genes from bacteria genomes belonging to different functional traits were grouped to Cluster of Orthologs (COGs), and were used as features. Then, TF-IDF technique from the text mining domain was applied to transform the data to accommodate the abundance and importance of each COG. After TF-IDF processing, COGs were ranked using feature selection methods to identify their relevance to the functional trait of interest. Extensive experimental results demonstrated that functional trait related genes can be detected using our method. Further, the method has the potential to provide novel biological insights.
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Directory of Open Access Journals (Sweden)
Wang Yong
2011-07-01
Full Text Available Abstract Background Systematic mutagenesis studies have shown that only a few interface residues termed hot spots contribute significantly to the binding free energy of protein-protein interactions. Therefore, hot spots prediction becomes increasingly important for well understanding the essence of proteins interactions and helping narrow down the search space for drug design. Currently many computational methods have been developed by proposing different features. However comparative assessment of these features and furthermore effective and accurate methods are still in pressing need. Results In this study, we first comprehensively collect the features to discriminate hot spots and non-hot spots and analyze their distributions. We find that hot spots have lower relASA and larger relative change in ASA, suggesting hot spots tend to be protected from bulk solvent. In addition, hot spots have more contacts including hydrogen bonds, salt bridges, and atomic contacts, which favor complexes formation. Interestingly, we find that conservation score and sequence entropy are not significantly different between hot spots and non-hot spots in Ab+ dataset (all complexes. While in Ab- dataset (antigen-antibody complexes are excluded, there are significant differences in two features between hot pots and non-hot spots. Secondly, we explore the predictive ability for each feature and the combinations of features by support vector machines (SVMs. The results indicate that sequence-based feature outperforms other combinations of features with reasonable accuracy, with a precision of 0.69, a recall of 0.68, an F1 score of 0.68, and an AUC of 0.68 on independent test set. Compared with other machine learning methods and two energy-based approaches, our approach achieves the best performance. Moreover, we demonstrate the applicability of our method to predict hot spots of two protein complexes. Conclusion Experimental results show that support vector machine
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2011-01-01
Background Systematic mutagenesis studies have shown that only a few interface residues termed hot spots contribute significantly to the binding free energy of protein-protein interactions. Therefore, hot spots prediction becomes increasingly important for well understanding the essence of proteins interactions and helping narrow down the search space for drug design. Currently many computational methods have been developed by proposing different features. However comparative assessment of these features and furthermore effective and accurate methods are still in pressing need. Results In this study, we first comprehensively collect the features to discriminate hot spots and non-hot spots and analyze their distributions. We find that hot spots have lower relASA and larger relative change in ASA, suggesting hot spots tend to be protected from bulk solvent. In addition, hot spots have more contacts including hydrogen bonds, salt bridges, and atomic contacts, which favor complexes formation. Interestingly, we find that conservation score and sequence entropy are not significantly different between hot spots and non-hot spots in Ab+ dataset (all complexes). While in Ab- dataset (antigen-antibody complexes are excluded), there are significant differences in two features between hot pots and non-hot spots. Secondly, we explore the predictive ability for each feature and the combinations of features by support vector machines (SVMs). The results indicate that sequence-based feature outperforms other combinations of features with reasonable accuracy, with a precision of 0.69, a recall of 0.68, an F1 score of 0.68, and an AUC of 0.68 on independent test set. Compared with other machine learning methods and two energy-based approaches, our approach achieves the best performance. Moreover, we demonstrate the applicability of our method to predict hot spots of two protein complexes. Conclusion Experimental results show that support vector machine classifiers are quite
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Radiological features of endocrine orbitopathy involving lacrimal gland
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V. G. Likhvantseva
2014-07-01
Full Text Available According to orbit computer tomography, lacrimal gland is involved in autoimmune process in 26.8% of patients with Graves’ orbitopathy. A short orbit is a predisposing factor of the lacrimal gland (LG involvement in the autoimmune process. In addition to increasing of the size of the lacrimal gland, formed thickening of the optic nerve in 1 cm from the eye posterior pole (in 60% of cases, the increase in x-ray density of orbital portions of optic nerve, proved «shortening» of length in axial projection with reliable reduc- tion of length to width ratio (with increase in width at the same time up to 5.8±0.2 are roentgenological features of this сlinical form. Change of spatial topography in orbit with reduction of the conversion rate was associated with increased rate of optic neuropathydevelopment.
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Hayat, Maqsood; Khan, Asifullah
2011-02-21
Membrane proteins are vital type of proteins that serve as channels, receptors, and energy transducers in a cell. Prediction of membrane protein types is an important research area in bioinformatics. Knowledge of membrane protein types provides some valuable information for predicting novel example of the membrane protein types. However, classification of membrane protein types can be both time consuming and susceptible to errors due to the inherent similarity of membrane protein types. In this paper, neural networks based membrane protein type prediction system is proposed. Composite protein sequence representation (CPSR) is used to extract the features of a protein sequence, which includes seven feature sets; amino acid composition, sequence length, 2 gram exchange group frequency, hydrophobic group, electronic group, sum of hydrophobicity, and R-group. Principal component analysis is then employed to reduce the dimensionality of the feature vector. The probabilistic neural network (PNN), generalized regression neural network, and support vector machine (SVM) are used as classifiers. A high success rate of 86.01% is obtained using SVM for the jackknife test. In case of independent dataset test, PNN yields the highest accuracy of 95.73%. These classifiers exhibit improved performance using other performance measures such as sensitivity, specificity, Mathew's correlation coefficient, and F-measure. The experimental results show that the prediction performance of the proposed scheme for classifying membrane protein types is the best reported, so far. This performance improvement may largely be credited to the learning capabilities of neural networks and the composite feature extraction strategy, which exploits seven different properties of protein sequences. The proposed Mem-Predictor can be accessed at http://111.68.99.218/Mem-Predictor. Copyright © 2010 Elsevier Ltd. All rights reserved.
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Directory of Open Access Journals (Sweden)
Green Eric D
2004-05-01
Full Text Available Abstract Background The elastin gene (ELN is implicated as a factor in both supravalvular aortic stenosis (SVAS and Williams Beuren Syndrome (WBS, two diseases involving pronounced complications in mental or physical development. Although the complete spectrum of functional roles of the processed gene product remains to be established, these roles are inferred to be analogous in human and mouse. This view is supported by genomic sequence comparison, in which there are no large-scale differences in the ~1.8 Mb sequence block encompassing the common region deleted in WBS, with the exception of an overall reversed physical orientation between human and mouse. Results Conserved synteny around ELN does not translate to a high level of conservation in the gene itself. In fact, ELN orthologs in mammals show more sequence divergence than expected for a gene with a critical role in development. The pattern of divergence is non-conventional due to an unusually high ratio of gaps to substitutions. Specifically, multi-sequence alignments of eight mammalian sequences reveal numerous non-aligning regions caused by species-specific insertions and deletions, in spite of the fact that the vast majority of aligning sites appear to be conserved and undergoing purifying selection. Conclusions The pattern of lineage-specific, in-frame insertions/deletions in the coding exons of ELN orthologous genes is unusual and has led to unique features of the gene in each lineage. These differences may indicate that the gene has a slightly different functional mechanism in mammalian lineages, or that the corresponding regions are functionally inert. Identified regions that undergo purifying selection reflect a functional importance associated with evolutionary pressure to retain those features.
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Clinical and biological features of multiple myeloma involving the gastrointestinal system.
Talamo, Giampaolo; Cavallo, Federica; Zangari, Maurizio; Barlogie, Bart; Lee, Choon-Kee; Pineda-Roman, Mauricio; Kiwan, Elias; Krishna, Somashekar; Tricot, Guido
2006-07-01
We report 24 cases of multiple myeloma (MM) with involvement of the gastrointestinal (GI) system. We found a strong association with high A lactate dehydrogenase levels, plasmablastic morphology, and A unfavorable karyotype. GI involvement at the time of initial diagnosis was much rarer than later in the course of the disease. The A median survival after diagnosis of GI involvement was 7 months. Among 13 patients treated with stem cell transplantation, the response rate was 92%, and median progression-free survival was 4 months. We conclude that MM involving the GI system is associated with adverse biological features and with short-lasting remissions, even after A high-dose chemotherapy.
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Sequencing of bovine herpesvirus 4 v.test strain reveals important genome features
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Gillet Laurent
2011-08-01
Full Text Available Abstract Background Bovine herpesvirus 4 (BoHV-4 is a useful model for the human pathogenic gammaherpesviruses Epstein-Barr virus and Kaposi's Sarcoma-associated Herpesvirus. Although genome manipulations of this virus have been greatly facilitated by the cloning of the BoHV-4 V.test strain as a Bacterial Artificial Chromosome (BAC, the lack of a complete genome sequence for this strain limits its experimental use. Methods In this study, we have determined the complete sequence of BoHV-4 V.test strain by a pyrosequencing approach. Results The long unique coding region (LUR consists of 108,241 bp encoding at least 79 open reading frames and is flanked by several polyrepetitive DNA units (prDNA. As previously suggested, we showed that the prDNA unit located at the left prDNA-LUR junction (prDNA-G differs from the other prDNA units (prDNA-inner. Namely, the prDNA-G unit lacks the conserved pac-2 cleavage and packaging signal in its right terminal region. Based on the mechanisms of cleavage and packaging of herpesvirus genomes, this feature implies that only genomes bearing left and right end prDNA units are encapsulated into virions. Conclusions In this study, we have determined the complete genome sequence of the BAC-cloned BoHV-4 V.test strain and identified genome organization features that could be important in other herpesviruses.
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Directory of Open Access Journals (Sweden)
Xin Ma
2015-01-01
Full Text Available The prediction of RNA-binding proteins is one of the most challenging problems in computation biology. Although some studies have investigated this problem, the accuracy of prediction is still not sufficient. In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the minimum redundancy maximum relevance (mRMR method, followed by incremental feature selection (IFS. We incorporated features of conjoint triad features and three novel features: binding propensity (BP, nonbinding propensity (NBP, and evolutionary information combined with physicochemical properties (EIPP. The results showed that these novel features have important roles in improving the performance of the predictor. Using the mRMR-IFS method, our predictor achieved the best performance (86.62% accuracy and 0.737 Matthews correlation coefficient. High prediction accuracy and successful prediction performance suggested that our method can be a useful approach to identify RNA-binding proteins from sequence information.
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Directory of Open Access Journals (Sweden)
Huilin Wang
Full Text Available X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed 'PredPPCrys' using the support vector machine (SVM. Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I. Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II, which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization
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Unusual acute encephalitis involving the thalamus: imaging features
Energy Technology Data Exchange (ETDEWEB)
Kim, Sam Soo [Kangwon National University Hospital, Chuncheon (Korea, Republic of); Chang, Kee Hyun; Kim, Kyung Won; Han Moon Hee [Seoul National University College of Medicine, Seoul (Korea, Republic of); Park, Sung Ho; Nam, Hyun Woo [Seoul City Boramae Hospital, Seoul (Korea, Republic of); Choi, Kyu Ho [Kangnam St. Mary' s Hospital, Seoul (Korea, Republic of); Cho, Woo Ho [Sanggyo Paik Hospital, Seoul (Korea, Republic of)
2001-06-01
To describe the brain CT and MR imaging findings of unusual acute encephalitis involving the thalamus. We retrospectively reviewed the medical records and CT and/or MR imaging findings of six patients with acute encephalitis involving the thalamus. CT (n=6) and MR imaging (n=6) were performed during the acute and/or convalescent stage of the illness. Brain CT showed brain swelling (n=2), low attenuation of both thalami (n=1) or normal findings (n=3). Initial MR imaging indicated that in all patients the thalamus was involved either bilaterally (n=5) or unilaterally (n=1). Lesions were also present in the midbrain (n=5), medial temporal lobe (n=4), pons (n=3), both hippocampi (n=3) the insular cortex (n=2), medulla (n=2), lateral temporal lobe cortex (n=1), both cingulate gyri (n=1), both basal ganglia (n=1), and the left hemispheric cortex (n=1). These CT or MR imaging findings of acute encephalitis of unknown etiology were similar to a combination of those of Japanese encephalitis and herpes simplex encephalitis. In order to document the specific causative agents which lead to the appearance of these imaging features, further investigation is required.
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Real-time UAV trajectory generation using feature points matching between video image sequences
Byun, Younggi; Song, Jeongheon; Han, Dongyeob
2017-09-01
Unmanned aerial vehicles (UAVs), equipped with navigation systems and video capability, are currently being deployed for intelligence, reconnaissance and surveillance mission. In this paper, we present a systematic approach for the generation of UAV trajectory using a video image matching system based on SURF (Speeded up Robust Feature) and Preemptive RANSAC (Random Sample Consensus). Video image matching to find matching points is one of the most important steps for the accurate generation of UAV trajectory (sequence of poses in 3D space). We used the SURF algorithm to find the matching points between video image sequences, and removed mismatching by using the Preemptive RANSAC which divides all matching points to outliers and inliers. The inliers are only used to determine the epipolar geometry for estimating the relative pose (rotation and translation) between image sequences. Experimental results from simulated video image sequences showed that our approach has a good potential to be applied to the automatic geo-localization of the UAVs system
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Speeding disease gene discovery by sequence based candidate prioritization
Directory of Open Access Journals (Sweden)
Porteous David J
2005-03-01
Full Text Available Abstract Background Regions of interest identified through genetic linkage studies regularly exceed 30 centimorgans in size and can contain hundreds of genes. Traditionally this number is reduced by matching functional annotation to knowledge of the disease or phenotype in question. However, here we show that disease genes share patterns of sequence-based features that can provide a good basis for automatic prioritization of candidates by machine learning. Results We examined a variety of sequence-based features and found that for many of them there are significant differences between the sets of genes known to be involved in human hereditary disease and those not known to be involved in disease. We have created an automatic classifier called PROSPECTR based on those features using the alternating decision tree algorithm which ranks genes in the order of likelihood of involvement in disease. On average, PROSPECTR enriches lists for disease genes two-fold 77% of the time, five-fold 37% of the time and twenty-fold 11% of the time. Conclusion PROSPECTR is a simple and effective way to identify genes involved in Mendelian and oligogenic disorders. It performs markedly better than the single existing sequence-based classifier on novel data. PROSPECTR could save investigators looking at large regions of interest time and effort by prioritizing positional candidate genes for mutation detection and case-control association studies.
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Spiral CT features and anatomic basis of posterior pararenal space involvement in acute pancreatitis
International Nuclear Information System (INIS)
Min Pengqiu; Yan Zhihan; Yang Hengxuan; Liu Zaiyi; Song Bin; Wu Bing; Zhang Jin; Liu Rongbo
2005-01-01
Objective: To evaluate spiral CT features and anatomic basis of the posterior pararenal space (PPS) involvement in acute pancreatitis (AP). Methods: CT images of 87 cases with AP were retrospectively studied with focus on spiral CT features, incidence of the PPS involvement, and its correlations with the posterior renal fascia or lateroconal fascia. Results: Our study showed that the incidence of the PPS involvement was 47% (41/87), with Grade A 53% (46/87), Grade B 24%(21/87), and Grade C 23% (20/87), and Grade 0 53% (46/87), Grade I 22% (19/87), and Grade II 25% (22/87), respectively. The pancreatitis fluid collection in the PPS was continuous with that in the anterior pararenal space or with the fluid between the two laminae of the posterior renal fascia. In 3 follow-up cases, pseudocysts in the PPS were continuous with that in anterior pararenal space below the cone of renal fascia. Conclusion: Spiral CT features of the PPS involvement varies from mild inflammatory changes to fluid collection or phlegmonous mass. Fluid within anterior pararenal space in AP flows into the PPS by three routes. (authors)
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DEFF Research Database (Denmark)
Levinsen, Mette; Taskinen, Mervi; Abrahamsson, Jonas
2014-01-01
BACKGROUND: Central nervous system (CNS) involvement in childhood acute lymphoblastic leukemia (ALL) remains a therapeutic challenge. PROCEDURE: To explore leukemia characteristics of patients with CNS involvement at ALL diagnosis, we analyzed clinical features and early treatment response of 744...... leukemia and patients without such characteristics (0.50 vs. 0.61; P = 0.2). CONCLUSION: CNS involvement at diagnosis is associated with adverse prognostic features but does not indicate a less chemosensitive leukemia....
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Analysis and prediction of translation rate based on sequence and functional features of the mRNA.
Directory of Open Access Journals (Sweden)
Tao Huang
Full Text Available Protein concentrations depend not only on the mRNA level, but also on the translation rate and the degradation rate. Prediction of mRNA's translation rate would provide valuable information for in-depth understanding of the translation mechanism and dynamic proteome. In this study, we developed a new computational model to predict the translation rate, featured by (1 integrating various sequence-derived and functional features, (2 applying the maximum relevance & minimum redundancy method and incremental feature selection to select features to optimize the prediction model, and (3 being able to predict the translation rate of RNA into high or low translation rate category. The prediction accuracies under rich and starvation condition were 68.8% and 70.0%, respectively, evaluated by jackknife cross-validation. It was found that the following features were correlated with translation rate: codon usage frequency, some gene ontology enrichment scores, number of RNA binding proteins known to bind its mRNA product, coding sequence length, protein abundance and 5'UTR free energy. These findings might provide useful information for understanding the mechanisms of translation and dynamic proteome. Our translation rate prediction model might become a high throughput tool for annotating the translation rate of mRNAs in large-scale.
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Voltage-Gated Sodium Channels: Evolutionary History and Distinctive Sequence Features.
Kasimova, M A; Granata, D; Carnevale, V
2016-01-01
Voltage-gated sodium channels (Nav) are responsible for the rising phase of the action potential. Their role in electrical signal transmission is so relevant that their emergence is believed to be one of the crucial factors enabling development of nervous system. The presence of voltage-gated sodium-selective channels in bacteria (BacNav) has raised questions concerning the evolutionary history of the ones in animals. Here we review some of the milestones in the field of Nav phylogenetic analysis and discuss some of the most important sequence features that distinguish these channels from voltage-gated potassium channels and transient receptor potential channels. Copyright © 2016 Elsevier Inc. All rights reserved.
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Robin sequence associated with karyotypic mosaicism involving chromosome 22 abnormalities
Energy Technology Data Exchange (ETDEWEB)
Salinas, C.F.; Jastrzab, J.M.; Centu, E.S. [Medical Univ. of South Carolina, Charleston, SC (United States)
1994-09-01
Robin sequence is characterized by cleft palate, hypoplastic mandible, glossoptosis and respiratory difficulties. The Robin sequence may be observed as an isolated defect or as part of about 33 syndromes; however, to our knowledge, it has never been reported associated with chromosome 22 abnormalities. We examined a two-month-old black boy with a severe case of Robin sequence. Exam revealed a small child with hypoplastic mandible, glossoptosis, high palate and respiratory difficulty with continuous apnea episodes resulting in cyanotic lips and nails. In order to relieve the upper airway obstruction, his tongue was attached to the lower lip. Later a tracheostomy was performed. On follow-up exam, this patient was found to have developmental delay. Cytogenetic studies of both peripheral blood and fibroblast cells showed mosaicism involving chromosome 22 abnormalities which were designated as follows: 45,XY,-22/46,XY,-22,+r(22)/46,XY. Fluorescence in situ hybridization (FISH) studies confirmed the identity of the r(22) and showed the presence of the DiGeorge locus (D22575) but the absence of the D22539 locus which maps to 22q13.3. Reported cases of r(22) show no association with Robin sequence. However, r(22) has been associated with flat bridge of the nose, bulbous tip of the nose, epicanthus and high palate, all characteristics that we also observed in this case. These unusual cytogenetic findings may be causally related to the dysmorphology found in the patient we report.
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DEFF Research Database (Denmark)
Wernersson, Rasmus
2006-01-01
of alternative start codons. ( ii) Integration of sequences feature annotation - in particular, native support for working with files containing intron/ exon structure annotation. The software is available for both download and online use at http://www.cbs.dtu.dk/services/VirtualRibosome/....
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Domain general sequence operations contribute to pre-SMA involvement in visuo-spatial processing
Directory of Open Access Journals (Sweden)
E. Charles eLeek
2016-01-01
Full Text Available This study used 3T MRI to elucidate the functional role of supplementary motor area (SMA in relation to visuo-spatial processing. A localizer task contrasting sequential number subtraction and repetitive button pressing was used to functionally delineate non-motor sequence processing in pre-SMA, and activity in SMA-proper associated with motor sequencing. Patterns of BOLD responses in these regions were then contrasted to those from two tasks of visuo-spatial processing. In one task participants performed mental rotation in which recognition memory judgments were made to previously memorized 2D novel patterns across image-plane rotations. The other task involved abstract grid navigation in which observers computed a series of imagined location shifts in response to directional (arrow cues around a mental grid. The results showed overlapping activation in pre-SMA for sequential subtraction and both visuo-spatial tasks. These results suggest that visuo-spatial processing is supported by non-motor sequence operations that involve pre-SMA. More broadly, these data further highlight the functional heterogeneity of pre-SMA, and show that its role extends to processes beyond the planning and online control of movement.
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Jaschob, Daniel; Davis, Trisha N; Riffle, Michael
2015-03-07
Sequence feature annotations (e.g., protein domain boundaries, binding sites, and secondary structure predictions) are an essential part of biological research. Annotations are widely used by scientists during research and experimental design, and are frequently the result of biological studies. A generalized and simple means of disseminating and visualizing these data via the web would be of value to the research community. Mason is a web site widget designed to visualize and compare annotated features of one or more nucleotide or protein sequence. Annotated features may be of virtually any type, ranging from annotating transcription binding sites or exons and introns in DNA to secondary structure or domain boundaries in proteins. Mason is simple to use and easy to integrate into web sites. Mason has a highly dynamic and configurable interface supporting multiple sets of annotations per sequence, overlapping regions, customization of interface and user-driven events (e.g., clicks and text to appear for tooltips). It is written purely in JavaScript and SVG, requiring no 3(rd) party plugins or browser customization. Mason is a solution for dissemination of sequence annotation data on the web. It is highly flexible, customizable, simple to use, and is designed to be easily integrated into web sites. Mason is open source and freely available at https://github.com/yeastrc/mason.
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Prediction of peptide drift time in ion mobility mass spectrometry from sequence-based features
Wang, Bing; Zhang, Jun; Chen, Peng; Ji, Zhiwei; Deng, Shuping; Li, Chi
2013-01-01
Background: Ion mobility-mass spectrometry (IMMS), an analytical technique which combines the features of ion mobility spectrometry (IMS) and mass spectrometry (MS), can rapidly separates ions on a millisecond time-scale. IMMS becomes a powerful tool to analyzing complex mixtures, especially for the analysis of peptides in proteomics. The high-throughput nature of this technique provides a challenge for the identification of peptides in complex biological samples. As an important parameter, peptide drift time can be used for enhancing downstream data analysis in IMMS-based proteomics.Results: In this paper, a model is presented based on least square support vectors regression (LS-SVR) method to predict peptide ion drift time in IMMS from the sequence-based features of peptide. Four descriptors were extracted from peptide sequence to represent peptide ions by a 34-component vector. The parameters of LS-SVR were selected by a grid searching strategy, and a 10-fold cross-validation approach was employed for the model training and testing. Our proposed method was tested on three datasets with different charge states. The high prediction performance achieve demonstrate the effectiveness and efficiency of the prediction model.Conclusions: Our proposed LS-SVR model can predict peptide drift time from sequence information in relative high prediction accuracy by a test on a dataset of 595 peptides. This work can enhance the confidence of protein identification by combining with current protein searching techniques. 2013 Wang et al.; licensee BioMed Central Ltd.
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Prediction of peptide drift time in ion mobility mass spectrometry from sequence-based features
Wang, Bing
2013-05-09
Background: Ion mobility-mass spectrometry (IMMS), an analytical technique which combines the features of ion mobility spectrometry (IMS) and mass spectrometry (MS), can rapidly separates ions on a millisecond time-scale. IMMS becomes a powerful tool to analyzing complex mixtures, especially for the analysis of peptides in proteomics. The high-throughput nature of this technique provides a challenge for the identification of peptides in complex biological samples. As an important parameter, peptide drift time can be used for enhancing downstream data analysis in IMMS-based proteomics.Results: In this paper, a model is presented based on least square support vectors regression (LS-SVR) method to predict peptide ion drift time in IMMS from the sequence-based features of peptide. Four descriptors were extracted from peptide sequence to represent peptide ions by a 34-component vector. The parameters of LS-SVR were selected by a grid searching strategy, and a 10-fold cross-validation approach was employed for the model training and testing. Our proposed method was tested on three datasets with different charge states. The high prediction performance achieve demonstrate the effectiveness and efficiency of the prediction model.Conclusions: Our proposed LS-SVR model can predict peptide drift time from sequence information in relative high prediction accuracy by a test on a dataset of 595 peptides. This work can enhance the confidence of protein identification by combining with current protein searching techniques. 2013 Wang et al.; licensee BioMed Central Ltd.
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Imaging features of nontumorous conditions involving the trachea and main-stem bronchi
International Nuclear Information System (INIS)
Jeon, Kyung Nyeo; Kang, Duk Sik; Bae, Kyung Soo
2002-01-01
A number of nontumorous diseases may affect the trachea and main-stem bronchi, and their nonspecific symptoms may include coughing, dyspnea, wheezing and stridor. The clinical course is often long-term and a misdiagnosis of bronchial asthma is common. The imaging findings of these nontumorous conditions are, however, relatively characteristic, and diagnosis either without or in conjunction with clinical information is often possible. For specific diagnosis, recognition of their imaging features is therefore of prime importance. In this pictorial essay, we illustrate the imaging features of various nontumorous conditions involving the trachea and main-stem bronchi
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Elouej, Sahar; Beleza-Meireles, Ana; Caswell, Richard; Colclough, Kevin; Ellard, Sian; Desvignes, Jean Pierre; Béroud, Christophe; Lévy, Nicolas; Mohammed, Shehla; De Sandre-Giovannoli, Annachiara
2017-06-01
Mandibular hypoplasia, deafness, progeroid features, and lipodystrophy syndrome (MDPL) is an autosomal dominant systemic disorder characterized by prominent loss of subcutaneous fat, a characteristic facial appearance and metabolic abnormalities. This syndrome is caused by heterozygous de novo mutations in the POLD1 gene. To date, 19 patients with MDPL have been reported in the literature and among them 14 patients have been characterized at the molecular level. Twelve unrelated patients carried a recurrent in-frame deletion of a single codon (p.Ser605del) and two other patients carried a novel heterozygous mutation in exon 13 (p.Arg507Cys). Additionally and interestingly, germline mutations of the same gene have been involved in familial polyposis and colorectal cancer (CRC) predisposition. We describe a male and a female patient with MDPL respectively affected with mild and severe phenotypes. Both of them showed mandibular hypoplasia, a beaked nose with bird-like facies, prominent eyes, a small mouth, growth retardation, muscle and skin atrophy, but the female patient showed such a severe and early phenotype that a first working diagnosis of Hutchinson-Gilford Progeria was made. The exploration was performed by direct sequencing of POLD1 gene exon 15 in the male patient with a classical MDPL phenotype and by whole exome sequencing in the female patient and her unaffected parents. Exome sequencing identified in the latter patient a de novo heterozygous undescribed mutation in the POLD1 gene (NM_002691.3: c.3209T>A), predicted to cause the missense change p.Ile1070Asn in the ZnF2 (Zinc Finger 2) domain of the protein. This mutation was not reported in the 1000 Genome Project, dbSNP and Exome sequencing databases. Furthermore, the Isoleucine1070 residue of POLD1 is highly conserved among various species, suggesting that this substitution may cause a major impairment of POLD1 activity. For the second patient, affected with a typical MDPL phenotype, direct sequencing
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Gloger, Oliver; Bülow, Robin; Tönnies, Klaus; Völzke, Henry
2017-11-24
We aimed to develop the first fully automated 3D gallbladder segmentation approach to perform volumetric analysis in volume data of magnetic resonance (MR) cholangiopancreatography (MRCP) sequences. Volumetric gallbladder analysis is performed for non-contrast-enhanced and secretin-enhanced MRCP sequences. Native and secretin-enhanced MRCP volume data were produced with a 1.5-T MR system. Images of coronal maximum intensity projections (MIP) are used to automatically compute 2D characteristic shape features of the gallbladder in the MIP images. A gallbladder shape space is generated to derive 3D gallbladder shape features, which are then combined with 2D gallbladder shape features in a support vector machine approach to detect gallbladder regions in MRCP volume data. A region-based level set approach is used for fine segmentation. Volumetric analysis is performed for both sequences to calculate gallbladder volume differences between both sequences. The approach presented achieves segmentation results with mean Dice coefficients of 0.917 in non-contrast-enhanced sequences and 0.904 in secretin-enhanced sequences. This is the first approach developed to detect and segment gallbladders in MR-based volume data automatically in both sequences. It can be used to perform gallbladder volume determination in epidemiological studies and to detect abnormal gallbladder volumes or shapes. The positive volume differences between both sequences may indicate the quantity of the pancreatobiliary reflux.
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DEFF Research Database (Denmark)
Duarte, Vinicius da Silva; Treu, Laura; Campanaro, Stefano
2017-01-01
We present here the complete genome sequence of Trueperella pyogenes UFV1. The 2.3-Mbp genome contains an extremely interesting AI-2 transporter and processing system related to the quorum-sensing signal response. This specific feature is described in this species for the first time and might be ...... be responsible for a new pathogenic behavior.......We present here the complete genome sequence of Trueperella pyogenes UFV1. The 2.3-Mbp genome contains an extremely interesting AI-2 transporter and processing system related to the quorum-sensing signal response. This specific feature is described in this species for the first time and might...
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Zhang, Wen; Zhu, Xiaopeng; Fu, Yu; Tsuji, Junko; Weng, Zhiping
2017-12-01
Alternative splicing is the critical process in a single gene coding, which removes introns and joins exons, and splicing branchpoints are indicators for the alternative splicing. Wet experiments have identified a great number of human splicing branchpoints, but many branchpoints are still unknown. In order to guide wet experiments, we develop computational methods to predict human splicing branchpoints. Considering the fact that an intron may have multiple branchpoints, we transform the branchpoint prediction as the multi-label learning problem, and attempt to predict branchpoint sites from intron sequences. First, we investigate a variety of intron sequence-derived features, such as sparse profile, dinucleotide profile, position weight matrix profile, Markov motif profile and polypyrimidine tract profile. Second, we consider several multi-label learning methods: partial least squares regression, canonical correlation analysis and regularized canonical correlation analysis, and use them as the basic classification engines. Third, we propose two ensemble learning schemes which integrate different features and different classifiers to build ensemble learning systems for the branchpoint prediction. One is the genetic algorithm-based weighted average ensemble method; the other is the logistic regression-based ensemble method. In the computational experiments, two ensemble learning methods outperform benchmark branchpoint prediction methods, and can produce high-accuracy results on the benchmark dataset.
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Noronha, Jyothi M; Liu, Mengya; Squires, R Burke; Pickett, Brett E; Hale, Benjamin G; Air, Gillian M; Galloway, Summer E; Takimoto, Toru; Schmolke, Mirco; Hunt, Victoria; Klem, Edward; García-Sastre, Adolfo; McGee, Monnie; Scheuermann, Richard H
2012-05-01
Genetic drift of influenza virus genomic sequences occurs through the combined effects of sequence alterations introduced by a low-fidelity polymerase and the varying selective pressures experienced as the virus migrates through different host environments. While traditional phylogenetic analysis is useful in tracking the evolutionary heritage of these viruses, the specific genetic determinants that dictate important phenotypic characteristics are often difficult to discern within the complex genetic background arising through evolution. Here we describe a novel influenza virus sequence feature variant type (Flu-SFVT) approach, made available through the public Influenza Research Database resource (www.fludb.org), in which variant types (VTs) identified in defined influenza virus protein sequence features (SFs) are used for genotype-phenotype association studies. Since SFs have been defined for all influenza virus proteins based on known structural, functional, and immune epitope recognition properties, the Flu-SFVT approach allows the rapid identification of the molecular genetic determinants of important influenza virus characteristics and their connection to underlying biological functions. We demonstrate the use of the SFVT approach to obtain statistical evidence for effects of NS1 protein sequence variations in dictating influenza virus host range restriction.
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Idiopathic hypereosinophilic syndrome involving the liver: CT features vs. peripheral eosinophilia
Energy Technology Data Exchange (ETDEWEB)
Kim, Kyung Sook; Lee, Moon Gyu; Won, Young Chul; Lee, Eun Hye; Noh, Han Na; Ha, Hyun Kwon; Kim, Pyo Nyun; Auh, Yong Ho [Ulsan Univ. College of Medicine, Seoul (Korea, Republic of)
1997-10-01
To correlate CT features with peripheral eosinophilia in patients with idiopathic hypereosinophilic syndrome involving the liver. During the last three years, features of liver involvement in nine of 20 patients with idiopathic hypereosinophilic syndrome were evaluated on CT. The shape and distribution of intrahepatic low densities and the presence of hepatomegaly and/or splenomegaly were reviewed on CT, and the percentage of eosinophils in peripheral blood was also determined. In seven cases, interval change in hepatic lesion and the percentage of eosinophils were reviewed on follow-up examination. On initial CT, varying low-density patterns were seen in the liver in all cases; hepatomegaly was seen in four cases, and hepatosplenomegaly in two. The percentage of eosinophils was 89% in a case with diffuse patch low densities in the liver, 65-85% in three cases with numerous nodular low density lesions, 12-29% in four cases with multiple (below ten) nodular or small geographic hypodense lesions, and 24% in a case with a single nodular hypodense lesion. On follow-up CT, seven patients showed a decrease in the percentage of eosinophils, and in six, improved intrahepatic low densities were seen. On CT, intrahepatic low densities were seen in patients with idiopathic hypereosinophilic syndrome, and these were distributed more extensively when peripheral eosinophilia was more severe. With improvement in peripheral eosinophilia, the low densities also improved.
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Idiopathic hypereosinophilic syndrome involving the liver: CT features vs. peripheral eosinophilia
International Nuclear Information System (INIS)
Kim, Kyung Sook; Lee, Moon Gyu; Won, Young Chul; Lee, Eun Hye; Noh, Han Na; Ha, Hyun Kwon; Kim, Pyo Nyun; Auh, Yong Ho
1997-01-01
To correlate CT features with peripheral eosinophilia in patients with idiopathic hypereosinophilic syndrome involving the liver. During the last three years, features of liver involvement in nine of 20 patients with idiopathic hypereosinophilic syndrome were evaluated on CT. The shape and distribution of intrahepatic low densities and the presence of hepatomegaly and/or splenomegaly were reviewed on CT, and the percentage of eosinophils in peripheral blood was also determined. In seven cases, interval change in hepatic lesion and the percentage of eosinophils were reviewed on follow-up examination. On initial CT, varying low-density patterns were seen in the liver in all cases; hepatomegaly was seen in four cases, and hepatosplenomegaly in two. The percentage of eosinophils was 89% in a case with diffuse patch low densities in the liver, 65-85% in three cases with numerous nodular low density lesions, 12-29% in four cases with multiple (below ten) nodular or small geographic hypodense lesions, and 24% in a case with a single nodular hypodense lesion. On follow-up CT, seven patients showed a decrease in the percentage of eosinophils, and in six, improved intrahepatic low densities were seen. On CT, intrahepatic low densities were seen in patients with idiopathic hypereosinophilic syndrome, and these were distributed more extensively when peripheral eosinophilia was more severe. With improvement in peripheral eosinophilia, the low densities also improved
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Newell, Nicholas E
2011-12-15
The extraction of the set of features most relevant to function from classified biological sequence sets is still a challenging problem. A central issue is the determination of expected counts for higher order features so that artifact features may be screened. Cascade detection (CD), a new algorithm for the extraction of localized features from sequence sets, is introduced. CD is a natural extension of the proportional modeling techniques used in contingency table analysis into the domain of feature detection. The algorithm is successfully tested on synthetic data and then applied to feature detection problems from two different domains to demonstrate its broad utility. An analysis of HIV-1 protease specificity reveals patterns of strong first-order features that group hydrophobic residues by side chain geometry and exhibit substantial symmetry about the cleavage site. Higher order results suggest that favorable cooperativity is weak by comparison and broadly distributed, but indicate possible synergies between negative charge and hydrophobicity in the substrate. Structure-function results for the Schellman loop, a helix-capping motif in proteins, contain strong first-order features and also show statistically significant cooperativities that provide new insights into the design of the motif. These include a new 'hydrophobic staple' and multiple amphipathic and electrostatic pair features. CD should prove useful not only for sequence analysis, but also for the detection of multifactor synergies in cross-classified data from clinical studies or other sources. Windows XP/7 application and data files available at: https://sites.google.com/site/cascadedetect/home. nacnewell@comcast.net Supplementary information is available at Bioinformatics online.
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Energy Technology Data Exchange (ETDEWEB)
Hegde, Vinay; Bhat, Maya; Prasad, Chandrajit; Gupta, A.K.; Saini, Jitender [National Institute of Mental Health and Neurosciences, Department of Neuroimaging and Interventional Radiology, Bangalore, Karnataka (India); Aziz, Zarina [Sri Sathya Sai Institute of Medical Science, Department of Radiology, Bangalore (India); Kumar, Sharath [Apollo Hospital, Department of Neuroradiology, Bangalore (India); Netravathi, M. [National Institute of Mental Health and Neurosciences, Department of Neurology, Bangalore (India)
2014-11-01
CNS dengue infection is a rare condition and the pattern of brain involvement has not been well described. We report the MR imaging (MRI) features in eight cases of dengue encephalitis. We retrospectively searched cases of dengue encephalitis in which imaging was performed. Eight cases (three men, five women; age range: 8-42 years) diagnosed with dengue encephalitis were included in the study. MR studies were performed on 3-T and 1.5-T MR clinical systems. Two neuroradiologists retrospectively reviewed the MR images and analysed the type of lesions, as well as their distribution and imaging features. All eight cases exhibited MRI abnormalities and the cerebellum was involved in all cases. In addition, MRI signal changes were also noted in the brainstem, thalamus, basal ganglia, internal capsule, insula, mesial temporal lobe, and cortical and cerebral white matter. Areas of susceptibility, diffusion restriction, and patchy post-contrast enhancement were the salient imaging features in our cohort of cases. A pattern of symmetrical cerebellar involvement and presence of microbleeds/haemorrhage may serve as a useful imaging marker and may help in the diagnosis of dengue encephalitis. (orig.)
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International Nuclear Information System (INIS)
Hegde, Vinay; Bhat, Maya; Prasad, Chandrajit; Gupta, A.K.; Saini, Jitender; Aziz, Zarina; Kumar, Sharath; Netravathi, M.
2015-01-01
CNS dengue infection is a rare condition and the pattern of brain involvement has not been well described. We report the MR imaging (MRI) features in eight cases of dengue encephalitis. We retrospectively searched cases of dengue encephalitis in which imaging was performed. Eight cases (three men, five women; age range: 8-42 years) diagnosed with dengue encephalitis were included in the study. MR studies were performed on 3-T and 1.5-T MR clinical systems. Two neuroradiologists retrospectively reviewed the MR images and analysed the type of lesions, as well as their distribution and imaging features. All eight cases exhibited MRI abnormalities and the cerebellum was involved in all cases. In addition, MRI signal changes were also noted in the brainstem, thalamus, basal ganglia, internal capsule, insula, mesial temporal lobe, and cortical and cerebral white matter. Areas of susceptibility, diffusion restriction, and patchy post-contrast enhancement were the salient imaging features in our cohort of cases. A pattern of symmetrical cerebellar involvement and presence of microbleeds/haemorrhage may serve as a useful imaging marker and may help in the diagnosis of dengue encephalitis. (orig.)
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Feature-Space Clustering for fMRI Meta-Analysis
DEFF Research Database (Denmark)
Goutte, Cyril; Hansen, Lars Kai; Liptrot, Mathew G.
2001-01-01
MRI sequences containing several hundreds of images, it is sometimes necessary to invoke feature extraction to reduce the dimensionality of the data space. A second interesting application is in the meta-analysis of fMRI experiment, where features are obtained from a possibly large number of single......-voxel analyses. In particular this allows the checking of the differences and agreements between different methods of analysis. Both approaches are illustrated on a fMRI data set involving visual stimulation, and we show that the feature space clustering approach yields nontrivial results and, in particular......, shows interesting differences between individual voxel analysis performed with traditional methods. © 2001 Wiley-Liss, Inc....
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DEFF Research Database (Denmark)
Tümer, Zeynep; López-Hernández, Julia Angélica; Netchine, Irène
2018-01-01
data of these patients. The clinical features are scored according to the Netchine-Harbison clinical scoring system (NH-CSS), which has recently been accepted as standard by consensus. The structural and sequence variations are reviewed and where necessary redescribed according to recent...
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Energy Technology Data Exchange (ETDEWEB)
Park, Hyo Jung; Kim, Hyun Jin; Park, Seung Ho; Lee, Jong Seok; Kim, Ah Young [Dept. of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul (Korea, Republic of); Ha, Hyun Kwon [Dept. of Radiology, Gangneung Asan Hospital, University of Ulsan College of Medicine, Gangneung (Korea, Republic of)
2017-06-15
To retrospectively evaluate the CT findings and clinicopathologic features in patients with gastrointestinal (GI) involvement of recurrent renal cell carcinoma (RCC). The medical records were reviewed for 15 patients with 19 pathologically proven GI tract metastases of RCC. The CT findings were analyzed to determine the involved sites and type of involvement; lesion size, morphology, and contrast enhancement pattern; and occurrence of lymphadenopathy, ascites and other complications. The most common presentation was GI bleeding (66.7%). The average interval between nephrectomy and the detection of GI involvement was 30.4 ± 37.4 months. GI lesions were most commonly found in the ileum (36.8%) and duodenum (31.6%). A distant metastasis (80%) was more common than a direct invasion from metastatic lesions. The mean lesion size was 34.1 ± 15.0 mm. Intraluminal polypoid masses (63.2%) with hyperenhancement (78.9%) and heterogeneous enhancement (63.2%) were the most common findings. No patients had regional lymphadenopathy. Complications occurred in four patients, with one each of bowel obstruction, intussusception, bile duct dilatation, and pancreatic duct dilatation. GI involvement of recurrent RCC could be included in the differential diagnosis of patients with heterogeneous, hyperenhanced intraluminal polypoid masses in the small bowel on CT scans along with a relative paucity of lymphadenopathy.
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MR imaging features of foot involvement in ankylosing spondylitis
Energy Technology Data Exchange (ETDEWEB)
Erdem, C. Zuhal E-mail: sunarerdem@yahoo.com; Sarikaya, Selda; Erdem, L. Oktay; Ozdolap, Senay; Gundogdu, Sadi
2005-01-01
Objective: To determine alterations of the soft tissue, tendon, cartilage, joint space, and bone of the foot using magnetic resonance (MR) imaging in ankylosing spondylitis (AS) patients. Materials and Method: Clinical and MR examination of the foot was performed in 23 AS patients (46 feet). Ten asymptomatic volunteers (20 feet) were studied on MR imaging, as a control group. MR imaging protocol included; T1-weighted spin-echo, T2-weighted fast-field echo (FFE) and fat-suppressed short tau inversion recovery (STIR) sequences in sagittal, sagittal oblique, and coronal planes using a head coil. Specifically, we examined: bone erosions, tendinitis (acute and chronic), para-articular enthesophyte, joint effusion, plantar fasciitis, joint space narrowing, soft tissue edema, bone marrow edema, enthesopathy in the Achilles tendon and plantar fascia attachment, subchondral signal intensity abnormalities (edema and sclerosis), tenosynovitis, retrocalcaneal bursitis, subchondral cysts, subchondral fissures, and bony ankylosis. Midfoot, hindfoot, and ankle were included in examined anatomic regions. Results: Clinical signs and symptoms (pain and swelling) due to foot involvement were present in 3 (13%) of the patients while frequency of involvement was 21 (91%) with MR imaging assessment. The MR imaging findings were bone erosions (65%), Achilles tendinitis (acute and chronic) (61%), para-articular enthesophyte (48%), joint effusion (43%), plantar fasciitis (40%), joint space narrowing (40%), subchondral sclerosis (35%), soft tissue edema (30%), bone marrow edema (30%), enthesopathy of the Achilles attachment (30%), subchondral edema (26%), enthesopathy in the plantar fascia attachment (22%), retrocalcaneal bursitis (22%), subchondral cysts (17%), subchondral fissures (17%), tendinitis and enthesopathy of the plantar ligament (13%), and bony ankylosis (9%). The most common involved anatomical region was the hindfoot (83%) following by midfoot (69% ) and ankle (22
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MR imaging features of foot involvement in ankylosing spondylitis
International Nuclear Information System (INIS)
Erdem, C. Zuhal; Sarikaya, Selda; Erdem, L. Oktay; Ozdolap, Senay; Gundogdu, Sadi
2005-01-01
Objective: To determine alterations of the soft tissue, tendon, cartilage, joint space, and bone of the foot using magnetic resonance (MR) imaging in ankylosing spondylitis (AS) patients. Materials and Method: Clinical and MR examination of the foot was performed in 23 AS patients (46 feet). Ten asymptomatic volunteers (20 feet) were studied on MR imaging, as a control group. MR imaging protocol included; T1-weighted spin-echo, T2-weighted fast-field echo (FFE) and fat-suppressed short tau inversion recovery (STIR) sequences in sagittal, sagittal oblique, and coronal planes using a head coil. Specifically, we examined: bone erosions, tendinitis (acute and chronic), para-articular enthesophyte, joint effusion, plantar fasciitis, joint space narrowing, soft tissue edema, bone marrow edema, enthesopathy in the Achilles tendon and plantar fascia attachment, subchondral signal intensity abnormalities (edema and sclerosis), tenosynovitis, retrocalcaneal bursitis, subchondral cysts, subchondral fissures, and bony ankylosis. Midfoot, hindfoot, and ankle were included in examined anatomic regions. Results: Clinical signs and symptoms (pain and swelling) due to foot involvement were present in 3 (13%) of the patients while frequency of involvement was 21 (91%) with MR imaging assessment. The MR imaging findings were bone erosions (65%), Achilles tendinitis (acute and chronic) (61%), para-articular enthesophyte (48%), joint effusion (43%), plantar fasciitis (40%), joint space narrowing (40%), subchondral sclerosis (35%), soft tissue edema (30%), bone marrow edema (30%), enthesopathy of the Achilles attachment (30%), subchondral edema (26%), enthesopathy in the plantar fascia attachment (22%), retrocalcaneal bursitis (22%), subchondral cysts (17%), subchondral fissures (17%), tendinitis and enthesopathy of the plantar ligament (13%), and bony ankylosis (9%). The most common involved anatomical region was the hindfoot (83%) following by midfoot (69% ) and ankle (22
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Diagnostics of Primary Immunodeficiencies through Next Generation Sequencing
Directory of Open Access Journals (Sweden)
Vera Gallo
2016-11-01
Full Text Available Background: Recently, a growing number of novel genetic defects underlying primary immunodeficiencies (PID have been identified, increasing the number of PID up to more than 250 well-defined forms. Next-generation sequencing (NGS technologies and proper filtering strategies greatly contributed to this rapid evolution, providing the possibility to rapidly and simultaneously analyze large numbers of genes or the whole exome. Objective: To evaluate the role of targeted next-generation sequencing and whole exome sequencing in the diagnosis of a case series, characterized by complex or atypical clinical features suggesting a PID, difficult to diagnose using the current diagnostic procedures.Methods: We retrospectively analyzed genetic variants identified through targeted next-generation sequencing or whole exome sequencing in 45 patients with complex PID of unknown etiology. Results: 40 variants were identified using targeted next-generation sequencing, while 5 were identified using whole exome sequencing. Newly identified genetic variants were classified into 4 groups: I variations associated with a well-defined PID; II variations associated with atypical features of a well-defined PID; III functionally relevant variations potentially involved in the immunological features; IV non-diagnostic genotype, in whom the link with phenotype is missing. We reached a conclusive genetic diagnosis in 7/45 patients (~16%. Among them, 4 patients presented with a typical well-defined PID. In the remaining 3 cases, mutations were associated with unexpected clinical features, expanding the phenotypic spectrum of typical PIDs. In addition, we identified 31 variants in 10 patients with complex phenotype, individually not causative per se of the disorder.Conclusion: NGS technologies represent a cost-effective and rapid first-line genetic approaches for the evaluation of complex PIDs. Whole exome sequencing, despite a moderate higher cost compared to targeted, is
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Jamal, Salma; Goyal, Sukriti; Shanker, Asheesh; Grover, Abhinav
2016-10-18
Alzheimer's disease (AD) is a complex progressive neurodegenerative disorder commonly characterized by short term memory loss. Presently no effective therapeutic treatments exist that can completely cure this disease. The cause of Alzheimer's is still unclear, however one of the other major factors involved in AD pathogenesis are the genetic factors and around 70 % risk of the disease is assumed to be due to the large number of genes involved. Although genetic association studies have revealed a number of potential AD susceptibility genes, there still exists a need for identification of unidentified AD-associated genes and therapeutic targets to have better understanding of the disease-causing mechanisms of Alzheimer's towards development of effective AD therapeutics. In the present study, we have used machine learning approach to identify candidate AD associated genes by integrating topological properties of the genes from the protein-protein interaction networks, sequence features and functional annotations. We also used molecular docking approach and screened already known anti-Alzheimer drugs against the novel predicted probable targets of AD and observed that an investigational drug, AL-108, had high affinity for majority of the possible therapeutic targets. Furthermore, we performed molecular dynamics simulations and MM/GBSA calculations on the docked complexes to validate our preliminary findings. To the best of our knowledge, this is the first comprehensive study of its kind for identification of putative Alzheimer-associated genes using machine learning approaches and we propose that such computational studies can improve our understanding on the core etiology of AD which could lead to the development of effective anti-Alzheimer drugs.
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Gao, Bin; Liu, Wanyu; Wang, Liang; Liu, Zhengjun; Croisille, Pierre; Delachartre, Philippe; Clarysse, Patrick
2016-12-01
Cine-MRI is widely used for the analysis of cardiac function in clinical routine, because of its high soft tissue contrast and relatively short acquisition time in comparison with other cardiac MRI techniques. The gray level distribution in cardiac cine-MRI is relatively homogenous within the myocardium, and can therefore make motion quantification difficult. To ensure that the motion estimation problem is well posed, more image features have to be considered. This work is inspired by a method previously developed for color image processing. The monogenic signal provides a framework to estimate the local phase, orientation, and amplitude, of an image, three features which locally characterize the 2D intensity profile. The independent monogenic features are combined into a 3D matrix for motion estimation. To improve motion estimation accuracy, we chose the zero-mean normalized cross-correlation as a matching measure, and implemented a bilateral filter for denoising and edge-preservation. The monogenic features distance is used in lieu of the color space distance in the bilateral filter. Results obtained from four realistic simulated sequences outperformed two other state of the art methods even in the presence of noise. The motion estimation errors (end point error) using our proposed method were reduced by about 20% in comparison with those obtained by the other tested methods. The new methodology was evaluated on four clinical sequences from patients presenting with cardiac motion dysfunctions and one healthy volunteer. The derived strain fields were analyzed favorably in their ability to identify myocardial regions with impaired motion.
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Unique features of a global human ectoparasite identified through sequencing of the bed bug genome.
Benoit, Joshua B; Adelman, Zach N; Reinhardt, Klaus; Dolan, Amanda; Poelchau, Monica; Jennings, Emily C; Szuter, Elise M; Hagan, Richard W; Gujar, Hemant; Shukla, Jayendra Nath; Zhu, Fang; Mohan, M; Nelson, David R; Rosendale, Andrew J; Derst, Christian; Resnik, Valentina; Wernig, Sebastian; Menegazzi, Pamela; Wegener, Christian; Peschel, Nicolai; Hendershot, Jacob M; Blenau, Wolfgang; Predel, Reinhard; Johnston, Paul R; Ioannidis, Panagiotis; Waterhouse, Robert M; Nauen, Ralf; Schorn, Corinna; Ott, Mark-Christoph; Maiwald, Frank; Johnston, J Spencer; Gondhalekar, Ameya D; Scharf, Michael E; Peterson, Brittany F; Raje, Kapil R; Hottel, Benjamin A; Armisén, David; Crumière, Antonin Jean Johan; Refki, Peter Nagui; Santos, Maria Emilia; Sghaier, Essia; Viala, Sèverine; Khila, Abderrahman; Ahn, Seung-Joon; Childers, Christopher; Lee, Chien-Yueh; Lin, Han; Hughes, Daniel S T; Duncan, Elizabeth J; Murali, Shwetha C; Qu, Jiaxin; Dugan, Shannon; Lee, Sandra L; Chao, Hsu; Dinh, Huyen; Han, Yi; Doddapaneni, Harshavardhan; Worley, Kim C; Muzny, Donna M; Wheeler, David; Panfilio, Kristen A; Vargas Jentzsch, Iris M; Vargo, Edward L; Booth, Warren; Friedrich, Markus; Weirauch, Matthew T; Anderson, Michelle A E; Jones, Jeffery W; Mittapalli, Omprakash; Zhao, Chaoyang; Zhou, Jing-Jiang; Evans, Jay D; Attardo, Geoffrey M; Robertson, Hugh M; Zdobnov, Evgeny M; Ribeiro, Jose M C; Gibbs, Richard A; Werren, John H; Palli, Subba R; Schal, Coby; Richards, Stephen
2016-02-02
The bed bug, Cimex lectularius, has re-established itself as a ubiquitous human ectoparasite throughout much of the world during the past two decades. This global resurgence is likely linked to increased international travel and commerce in addition to widespread insecticide resistance. Analyses of the C. lectularius sequenced genome (650 Mb) and 14,220 predicted protein-coding genes provide a comprehensive representation of genes that are linked to traumatic insemination, a reduced chemosensory repertoire of genes related to obligate hematophagy, host-symbiont interactions, and several mechanisms of insecticide resistance. In addition, we document the presence of multiple putative lateral gene transfer events. Genome sequencing and annotation establish a solid foundation for future research on mechanisms of insecticide resistance, human-bed bug and symbiont-bed bug associations, and unique features of bed bug biology that contribute to the unprecedented success of C. lectularius as a human ectoparasite.
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Unique features of a global human ectoparasite identified through sequencing of the bed bug genome
Benoit, Joshua B.; Adelman, Zach N.; Reinhardt, Klaus; Dolan, Amanda; Poelchau, Monica; Jennings, Emily C.; Szuter, Elise M.; Hagan, Richard W.; Gujar, Hemant; Shukla, Jayendra Nath; Zhu, Fang; Mohan, M.; Nelson, David R.; Rosendale, Andrew J.; Derst, Christian; Resnik, Valentina; Wernig, Sebastian; Menegazzi, Pamela; Wegener, Christian; Peschel, Nicolai; Hendershot, Jacob M.; Blenau, Wolfgang; Predel, Reinhard; Johnston, Paul R.; Ioannidis, Panagiotis; Waterhouse, Robert M.; Nauen, Ralf; Schorn, Corinna; Ott, Mark-Christoph; Maiwald, Frank; Johnston, J. Spencer; Gondhalekar, Ameya D.; Scharf, Michael E.; Peterson, Brittany F.; Raje, Kapil R.; Hottel, Benjamin A.; Armisén, David; Crumière, Antonin Jean Johan; Refki, Peter Nagui; Santos, Maria Emilia; Sghaier, Essia; Viala, Sèverine; Khila, Abderrahman; Ahn, Seung-Joon; Childers, Christopher; Lee, Chien-Yueh; Lin, Han; Hughes, Daniel S. T.; Duncan, Elizabeth J.; Murali, Shwetha C.; Qu, Jiaxin; Dugan, Shannon; Lee, Sandra L.; Chao, Hsu; Dinh, Huyen; Han, Yi; Doddapaneni, Harshavardhan; Worley, Kim C.; Muzny, Donna M.; Wheeler, David; Panfilio, Kristen A.; Vargas Jentzsch, Iris M.; Vargo, Edward L.; Booth, Warren; Friedrich, Markus; Weirauch, Matthew T.; Anderson, Michelle A. E.; Jones, Jeffery W.; Mittapalli, Omprakash; Zhao, Chaoyang; Zhou, Jing-Jiang; Evans, Jay D.; Attardo, Geoffrey M.; Robertson, Hugh M.; Zdobnov, Evgeny M.; Ribeiro, Jose M. C.; Gibbs, Richard A.; Werren, John H.; Palli, Subba R.; Schal, Coby; Richards, Stephen
2016-01-01
The bed bug, Cimex lectularius, has re-established itself as a ubiquitous human ectoparasite throughout much of the world during the past two decades. This global resurgence is likely linked to increased international travel and commerce in addition to widespread insecticide resistance. Analyses of the C. lectularius sequenced genome (650 Mb) and 14,220 predicted protein-coding genes provide a comprehensive representation of genes that are linked to traumatic insemination, a reduced chemosensory repertoire of genes related to obligate hematophagy, host–symbiont interactions, and several mechanisms of insecticide resistance. In addition, we document the presence of multiple putative lateral gene transfer events. Genome sequencing and annotation establish a solid foundation for future research on mechanisms of insecticide resistance, human–bed bug and symbiont–bed bug associations, and unique features of bed bug biology that contribute to the unprecedented success of C. lectularius as a human ectoparasite. PMID:26836814
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Dynamic encoding of speech sequence probability in human temporal cortex.
Leonard, Matthew K; Bouchard, Kristofer E; Tang, Claire; Chang, Edward F
2015-05-06
Sensory processing involves identification of stimulus features, but also integration with the surrounding sensory and cognitive context. Previous work in animals and humans has shown fine-scale sensitivity to context in the form of learned knowledge about the statistics of the sensory environment, including relative probabilities of discrete units in a stream of sequential auditory input. These statistics are a defining characteristic of one of the most important sequential signals humans encounter: speech. For speech, extensive exposure to a language tunes listeners to the statistics of sound sequences. To address how speech sequence statistics are neurally encoded, we used high-resolution direct cortical recordings from human lateral superior temporal cortex as subjects listened to words and nonwords with varying transition probabilities between sound segments. In addition to their sensitivity to acoustic features (including contextual features, such as coarticulation), we found that neural responses dynamically encoded the language-level probability of both preceding and upcoming speech sounds. Transition probability first negatively modulated neural responses, followed by positive modulation of neural responses, consistent with coordinated predictive and retrospective recognition processes, respectively. Furthermore, transition probability encoding was different for real English words compared with nonwords, providing evidence for online interactions with high-order linguistic knowledge. These results demonstrate that sensory processing of deeply learned stimuli involves integrating physical stimulus features with their contextual sequential structure. Despite not being consciously aware of phoneme sequence statistics, listeners use this information to process spoken input and to link low-level acoustic representations with linguistic information about word identity and meaning. Copyright © 2015 the authors 0270-6474/15/357203-12$15.00/0.
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Li, Na; Gong, Xingyu; Li, Hongan; Jia, Pengtao
2018-01-01
For faded relics, such as Terracotta Army, the 2D-3D registration between an optical camera and point cloud model is an important part for color texture reconstruction and further applications. This paper proposes a nonuniform multiview color texture mapping for the image sequence and the three-dimensional (3D) model of point cloud collected by Handyscan3D. We first introduce nonuniform multiview calibration, including the explanation of its algorithm principle and the analysis of its advantages. We then establish transformation equations based on sift feature points for the multiview image sequence. At the same time, the selection of nonuniform multiview sift feature points is introduced in detail. Finally, the solving process of the collinear equations based on multiview perspective projection is given with three steps and the flowchart. In the experiment, this method is applied to the color reconstruction of the kneeling figurine, Tangsancai lady, and general figurine. These results demonstrate that the proposed method provides an effective support for the color reconstruction of the faded cultural relics and be able to improve the accuracy of 2D-3D registration between the image sequence and the point cloud model.
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Song, Jiangning; Li, Fuyi; Takemoto, Kazuhiro; Haffari, Gholamreza; Akutsu, Tatsuya; Chou, Kuo-Chen; Webb, Geoffrey I
2018-04-14
Determining the catalytic residues in an enzyme is critical to our understanding the relationship between protein sequence, structure, function, and enhancing our ability to design novel enzymes and their inhibitors. Although many enzymes have been sequenced, and their primary and tertiary structures determined, experimental methods for enzyme functional characterization lag behind. Because experimental methods used for identifying catalytic residues are resource- and labor-intensive, computational approaches have considerable value and are highly desirable for their ability to complement experimental studies in identifying catalytic residues and helping to bridge the sequence-structure-function gap. In this study, we describe a new computational method called PREvaIL for predicting enzyme catalytic residues. This method was developed by leveraging a comprehensive set of informative features extracted from multiple levels, including sequence, structure, and residue-contact network, in a random forest machine-learning framework. Extensive benchmarking experiments on eight different datasets based on 10-fold cross-validation and independent tests, as well as side-by-side performance comparisons with seven modern sequence- and structure-based methods, showed that PREvaIL achieved competitive predictive performance, with an area under the receiver operating characteristic curve and area under the precision-recall curve ranging from 0.896 to 0.973 and from 0.294 to 0.523, respectively. We demonstrated that this method was able to capture useful signals arising from different levels, leveraging such differential but useful types of features and allowing us to significantly improve the performance of catalytic residue prediction. We believe that this new method can be utilized as a valuable tool for both understanding the complex sequence-structure-function relationships of proteins and facilitating the characterization of novel enzymes lacking functional annotations
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Li, Yun-He; Zhang, Hong-Na; Wu, Qing-Song; Muday, Gloria K
2017-06-01
A total of 74,745 unigenes were generated and 1975 DEGs were identified. Candidate genes that may be involved in the adventitious root formation of mango cotyledon segment were revealed. Adventitious root formation is a crucial step in plant vegetative propagation, but the molecular mechanism of adventitious root formation remains unclear. Adventitious roots formed only at the proximal cut surface (PCS) of mango cotyledon segments, whereas no roots were formed on the opposite, distal cut surface (DCS). To identify the transcript abundance changes linked to adventitious root development, RNA was isolated from PCS and DCS at 0, 4 and 7 days after culture, respectively. Illumina sequencing of libraries generated from these samples yielded 62.36 Gb high-quality reads that were assembled into 74,745 unigenes with an average sequence length of 807 base pairs, and 33,252 of the assembled unigenes at least had homologs in one of the public databases. Comparative analysis of these transcriptome databases revealed that between the different time points at PCS there were 1966 differentially expressed genes (DEGs), while there were only 51 DEGs for the PCS vs. DCS when time-matched samples were compared. Of these DEGs, 1636 were assigned to gene ontology (GO) classes, the majority of that was involved in cellular processes, metabolic processes and single-organism processes. Candidate genes that may be involved in the adventitious root formation of mango cotyledon segment are predicted to encode polar auxin transport carriers, auxin-regulated proteins, cell wall remodeling enzymes and ethylene-related proteins. In order to validate RNA-sequencing results, we further analyzed the expression profiles of 20 genes by quantitative real-time PCR. This study expands the transcriptome information for Mangifera indica and identifies candidate genes involved in adventitious root formation in cotyledon segments of mango.
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Directory of Open Access Journals (Sweden)
Zhang Ya-Nan
2012-05-01
Full Text Available Abstract Background Adenosine-5′-triphosphate (ATP is one of multifunctional nucleotides and plays an important role in cell biology as a coenzyme interacting with proteins. Revealing the binding sites between protein and ATP is significantly important to understand the functionality of the proteins and the mechanisms of protein-ATP complex. Results In this paper, we propose a novel framework for predicting the proteins’ functional residues, through which they can bind with ATP molecules. The new prediction protocol is achieved by combination of sequence evolutional information and bi-profile sampling of multi-view sequential features and the sequence derived structural features. The hypothesis for this strategy is single-view feature can only represent partial target’s knowledge and multiple sources of descriptors can be complementary. Conclusions Prediction performances evaluated by both 5-fold and leave-one-out jackknife cross-validation tests on two benchmark datasets consisting of 168 and 227 non-homologous ATP binding proteins respectively demonstrate the efficacy of the proposed protocol. Our experimental results also reveal that the residue structural characteristics of real protein-ATP binding sites are significant different from those normal ones, for example the binding residues do not show high solvent accessibility propensities, and the bindings prefer to occur at the conjoint points between different secondary structure segments. Furthermore, results also show that performance is affected by the imbalanced training datasets by testing multiple ratios between positive and negative samples in the experiments. Increasing the dataset scale is also demonstrated useful for improving the prediction performances.
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Statistical Features of the 2010 Beni-Ilmane, Algeria, Aftershock Sequence
Hamdache, M.; Peláez, J. A.; Gospodinov, D.; Henares, J.
2018-03-01
The aftershock sequence of the 2010 Beni-Ilmane ( M W 5.5) earthquake is studied in depth to analyze the spatial and temporal variability of seismicity parameters of the relationships modeling the sequence. The b value of the frequency-magnitude distribution is examined rigorously. A threshold magnitude of completeness equal to 2.1, using the maximum curvature procedure or the changing point algorithm, and a b value equal to 0.96 ± 0.03 have been obtained for the entire sequence. Two clusters have been identified and characterized by their faulting type, exhibiting b values equal to 0.99 ± 0.05 and 1.04 ± 0.05. Additionally, the temporal decay of the aftershock sequence was examined using a stochastic point process. The analysis was done through the restricted epidemic-type aftershock sequence (RETAS) stochastic model, which allows the possibility to recognize the prevailing clustering pattern of the relaxation process in the examined area. The analysis selected the epidemic-type aftershock sequence (ETAS) model to offer the most appropriate description of the temporal distribution, which presumes that all events in the sequence can cause secondary aftershocks. Finally, the fractal dimensions are estimated using the integral correlation. The obtained D 2 values are 2.15 ± 0.01, 2.23 ± 0.01 and 2.17 ± 0.02 for the entire sequence, and for the first and second cluster, respectively. An analysis of the temporal evolution of the fractal dimensions D -2, D 0, D 2 and the spectral slope has been also performed to derive and characterize the different clusters included in the sequence.
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SIFT based algorithm for point feature tracking
Directory of Open Access Journals (Sweden)
Adrian BURLACU
2007-12-01
Full Text Available In this paper a tracking algorithm for SIFT features in image sequences is developed. For each point feature extracted using SIFT algorithm a descriptor is computed using information from its neighborhood. Using an algorithm based on minimizing the distance between two descriptors tracking point features throughout image sequences is engaged. Experimental results, obtained from image sequences that capture scaling of different geometrical type object, reveal the performances of the tracking algorithm.
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Li, Jianping; Yang, Bisheng; Chen, Chi; Huang, Ronggang; Dong, Zhen; Xiao, Wen
2018-02-01
Inaccurate exterior orientation parameters (EoPs) between sensors obtained by pre-calibration leads to failure of registration between panoramic image sequence and mobile laser scanning data. To address this challenge, this paper proposes an automatic registration method based on semantic features extracted from panoramic images and point clouds. Firstly, accurate rotation parameters between the panoramic camera and the laser scanner are estimated using GPS and IMU aided structure from motion (SfM). The initial EoPs of panoramic images are obtained at the same time. Secondly, vehicles in panoramic images are extracted by the Faster-RCNN as candidate primitives to be matched with potential corresponding primitives in point clouds according to the initial EoPs. Finally, translation between the panoramic camera and the laser scanner is refined by maximizing the overlapping area of corresponding primitive pairs based on the Particle Swarm Optimization (PSO), resulting in a finer registration between panoramic image sequences and point clouds. Two challenging urban scenes were experimented to assess the proposed method, and the final registration errors of these two scenes were both less than three pixels, which demonstrates a high level of automation, robustness and accuracy.
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Salmonella Kentucky is a polyphyletic member of S. enterica subclade A1 with multiple sequence types that often colonize the same hosts but in different frequencies on different continents. To evaluate the genomic features involved in S. Kentucky host specificity we sequenced the genomes of four iso...
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Directory of Open Access Journals (Sweden)
Amy L Bauer
2010-11-01
Full Text Available An important step in understanding gene regulation is to identify the DNA binding sites recognized by each transcription factor (TF. Conventional approaches to prediction of TF binding sites involve the definition of consensus sequences or position-specific weight matrices and rely on statistical analysis of DNA sequences of known binding sites. Here, we present a method called SiteSleuth in which DNA structure prediction, computational chemistry, and machine learning are applied to develop models for TF binding sites. In this approach, binary classifiers are trained to discriminate between true and false binding sites based on the sequence-specific chemical and structural features of DNA. These features are determined via molecular dynamics calculations in which we consider each base in different local neighborhoods. For each of 54 TFs in Escherichia coli, for which at least five DNA binding sites are documented in RegulonDB, the TF binding sites and portions of the non-coding genome sequence are mapped to feature vectors and used in training. According to cross-validation analysis and a comparison of computational predictions against ChIP-chip data available for the TF Fis, SiteSleuth outperforms three conventional approaches: Match, MATRIX SEARCH, and the method of Berg and von Hippel. SiteSleuth also outperforms QPMEME, a method similar to SiteSleuth in that it involves a learning algorithm. The main advantage of SiteSleuth is a lower false positive rate.
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Faraggi, Eshel; Zhou, Yaoqi; Kloczkowski, Andrzej
2014-03-01
We present a new approach for predicting the accessible surface area of proteins. The novelty of this approach lies in not using residue mutation profiles generated by multiple sequence alignments as descriptive inputs. Rather, sequential window information and the global monomer and dimer compositions of the chain are used. We find that much of the lost accuracy due to the elimination of evolutionary information is recouped by the use of global features. Furthermore, this new predictor produces similar results for proteins with or without sequence homologs deposited in the Protein Data Bank, and hence shows generalizability. Finally, these predictions are obtained in a small fraction (1/1000) of the time required to run mutation profile based prediction. All these factors indicate the possible usability of this work in de-novo protein structure prediction and in de-novo protein design using iterative searches. Funded in part by the financial support of the National Institutes of Health through Grants R01GM072014 and R01GM073095, and the National Science Foundation through Grant NSF MCB 1071785.
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Creveaux, Thomas; Sevrez, Violaine; Dumas, Raphaël; Chèze, Laurence; Rogowski, Isabelle
2018-03-01
The aim of this study was to examine the respective aptitudes of three rotation sequences (Y t X f 'Y h '', Z t X f 'Y h '', and X t Z f 'Y h '') to effectively describe the orientation of the humerus relative to the thorax during a movement involving a large horizontal abduction/adduction component: the tennis forehand drive. An optoelectronic system was used to record the movements of eight elite male players, each performing ten forehand drives. The occurrences of gimbal lock, phase angle discontinuity and incoherency in the time course of the three angles defining humerothoracic rotation were examined for each rotation sequence. Our results demonstrated that no single sequence effectively describes humerothoracic motion without discontinuities throughout the forehand motion. The humerothoracic joint angles can nevertheless be described without singularities when considering the backswing/forward-swing and the follow-through phases separately. Our findings stress that the sequence choice may have implications for the report and interpretation of 3D joint kinematics during large shoulder range of motion. Consequently, the use of Euler/Cardan angles to represent 3D orientation of the humerothoracic joint in sport tasks requires the evaluation of the rotation sequence regarding singularity occurrence before analysing the kinematic data, especially when the task involves a large shoulder range of motion in the horizontal plane.
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Temporality of Features in Near-Death Experience Narratives
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Charlotte Martial
2017-06-01
Full Text Available Background: After an occurrence of a Near-Death Experience (NDE, Near-Death Experiencers (NDErs usually report extremely rich and detailed narratives. Phenomenologically, a NDE can be described as a set of distinguishable features. Some authors have proposed regular patterns of NDEs, however, the actual temporality sequence of NDE core features remains a little explored area.Objectives: The aim of the present study was to investigate the frequency distribution of these features (globally and according to the position of features in narratives as well as the most frequently reported temporality sequences of features.Methods: We collected 154 French freely expressed written NDE narratives (i.e., Greyson NDE scale total score ≥ 7/32. A text analysis was conducted on all narratives in order to infer temporal ordering and frequency distribution of NDE features.Results: Our analyses highlighted the following most frequently reported sequence of consecutive NDE features: Out-of-Body Experience, Experiencing a tunnel, Seeing a bright light, Feeling of peace. Yet, this sequence was encountered in a very limited number of NDErs.Conclusion: These findings may suggest that NDEs temporality sequences can vary across NDErs. Exploring associations and relationships among features encountered during NDEs may complete the rigorous definition and scientific comprehension of the phenomenon.
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CloudAligner: A fast and full-featured MapReduce based tool for sequence mapping
Directory of Open Access Journals (Sweden)
Shi Weisong
2011-06-01
Full Text Available Abstract Background Research in genetics has developed rapidly recently due to the aid of next generation sequencing (NGS. However, massively-parallel NGS produces enormous amounts of data, which leads to storage, compatibility, scalability, and performance issues. The Cloud Computing and MapReduce framework, which utilizes hundreds or thousands of shared computers to map sequencing reads quickly and efficiently to reference genome sequences, appears to be a very promising solution for these issues. Consequently, it has been adopted by many organizations recently, and the initial results are very promising. However, since these are only initial steps toward this trend, the developed software does not provide adequate primary functions like bisulfite, pair-end mapping, etc., in on-site software such as RMAP or BS Seeker. In addition, existing MapReduce-based applications were not designed to process the long reads produced by the most recent second-generation and third-generation NGS instruments and, therefore, are inefficient. Last, it is difficult for a majority of biologists untrained in programming skills to use these tools because most were developed on Linux with a command line interface. Results To urge the trend of using Cloud technologies in genomics and prepare for advances in second- and third-generation DNA sequencing, we have built a Hadoop MapReduce-based application, CloudAligner, which achieves higher performance, covers most primary features, is more accurate, and has a user-friendly interface. It was also designed to be able to deal with long sequences. The performance gain of CloudAligner over Cloud-based counterparts (35 to 80% mainly comes from the omission of the reduce phase. In comparison to local-based approaches, the performance gain of CloudAligner is from the partition and parallel processing of the huge reference genome as well as the reads. The source code of CloudAligner is available at http
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CloudAligner: A fast and full-featured MapReduce based tool for sequence mapping.
Nguyen, Tung; Shi, Weisong; Ruden, Douglas
2011-06-06
Research in genetics has developed rapidly recently due to the aid of next generation sequencing (NGS). However, massively-parallel NGS produces enormous amounts of data, which leads to storage, compatibility, scalability, and performance issues. The Cloud Computing and MapReduce framework, which utilizes hundreds or thousands of shared computers to map sequencing reads quickly and efficiently to reference genome sequences, appears to be a very promising solution for these issues. Consequently, it has been adopted by many organizations recently, and the initial results are very promising. However, since these are only initial steps toward this trend, the developed software does not provide adequate primary functions like bisulfite, pair-end mapping, etc., in on-site software such as RMAP or BS Seeker. In addition, existing MapReduce-based applications were not designed to process the long reads produced by the most recent second-generation and third-generation NGS instruments and, therefore, are inefficient. Last, it is difficult for a majority of biologists untrained in programming skills to use these tools because most were developed on Linux with a command line interface. To urge the trend of using Cloud technologies in genomics and prepare for advances in second- and third-generation DNA sequencing, we have built a Hadoop MapReduce-based application, CloudAligner, which achieves higher performance, covers most primary features, is more accurate, and has a user-friendly interface. It was also designed to be able to deal with long sequences. The performance gain of CloudAligner over Cloud-based counterparts (35 to 80%) mainly comes from the omission of the reduce phase. In comparison to local-based approaches, the performance gain of CloudAligner is from the partition and parallel processing of the huge reference genome as well as the reads. The source code of CloudAligner is available at http://cloudaligner.sourceforge.net/ and its web version is at http
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International Nuclear Information System (INIS)
Grenier, N.; Filiatrault, D.; Garel, L.; Dube, J.; Paille, P.; Grenier, N.
1986-01-01
A retrospective study of all patients presenting with abdominal malignancies since November 1982 was undertaken in order to assess the CT features of peritoneal and mesenteric involvement in childhood. Thirteen cases, including 4 cases of malignant lymphomas, 1 case of Hodgkin's disease, 5 cases of adrenal tumors and 3 cases of ovarian tumors, were selected. Providing a good technique, CT appears as the best imaging modality of the mesentery. CT is also reliable in showing peritoneal implants, even without ascites. A high quality vascular opacification is needed in order to recognize the involvement of the lesser omentum (6/13 cases in our series). Precise knowledge of the intra-abdominal extension of the primary neoplasm has a definite impact upon the surgical indications and therefore upon the prognosis [fr
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Sugarcane expressed sequences tags (ESTs encoding enzymes involved in lignin biosynthesis pathways
Directory of Open Access Journals (Sweden)
Ramos Rose Lucia Braz
2001-01-01
Full Text Available Lignins are phenolic polymers found in the secondary wall of plant conductive systems where they play an important role by reducing the permeability of the cell wall to water. Lignins are also responsible for the rigidity of the cell wall and are involved in mechanisms of resistance to pathogens. The metabolic routes and enzymes involved in synthesis of lignins have been largely characterized and representative genes that encode enzymes involved in these processes have been cloned from several plant species. The synthesis of lignins is liked to the general metabolism of the phenylpropanoids in plants, having enzymes (e.g. phenylalanine ammonia-lyase (PAL, cinnamate 4-hydroxylase (C4H and caffeic acid O-methyltransferase (COMT common to other processes as well as specific enzymes such as cinnamoyl-CoA reductase (CCR and cinnamyl alcohol dehydrogenase (CAD. Some maize and sorghum mutants, shown to have defective in CAD and/or COMT activity, are easier to digest because they have a reduced lignin content, something which has motivated different research groups to alter the lignin content and composition of model plants by genetic engineering try to improve, for example, the efficiency of paper pulping and digestibility. In the work reported in this paper, we have made an inventory of the sugarcane expressed sequence tag (EST coding for enzymes involved in lignin metabolism which are present in the sugarcane EST genome project (SUCEST database. Our analysis focused on the key enzymes ferulate-5-hydroxylase (F5H, caffeic acid O-methyltransferase (COMT, caffeoyl CoA O-methyltransferase (CCoAOMT, hydroxycinnamate CoA ligase (4CL, cinnamoyl-CoA reductase (CCR and cinnamyl alcohol dehydrogenase (CAD. The comparative analysis of these genes with those described in other species could be used as molecular markers for breeding as well as for the manipulation of lignin metabolism in sugarcane.
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Ma, Jun; Kanakala, S; He, Yehua; Zhang, Junli; Zhong, Xiaolan
2015-01-01
Ananas comosus var. bracteatus (Red Pineapple) is an important ornamental plant for its colorful leaves and decorative red fruits. Because of its complex genome, it is difficult to understand the molecular mechanisms involved in the growth and development. Thus high-throughput transcriptome sequencing of Ananas comosus var. bracteatus is necessary to generate large quantities of transcript sequences for the purpose of gene discovery and functional genomic studies. The Ananas comosus var. bracteatus transcriptome was sequenced by the Illumina paired-end sequencing technology. We obtained a total of 23.5 million high quality sequencing reads, 1,555,808 contigs and 41,052 unigenes. In total 41,052 unigenes of Ananas comosus var. bracteatus, 23,275 unigenes were annotated in the NCBI non-redundant protein database and 23,134 unigenes were annotated in the Swiss-Port database. Out of these, 17,748 and 8,505 unigenes were assigned to gene ontology categories and clusters of orthologous groups, respectively. Functional annotation against Kyoto Encyclopedia of Genes and Genomes Pathway database identified 5,825 unigenes which were mapped to 117 pathways. The assembly predicted many unigenes that were previously unknown. The annotated unigenes were compared against pineapple, rice, maize, Arabidopsis, and sorghum. Unigenes that did not match any of those five sequence datasets are considered to be Ananas comosus var. bracteatus unique. We predicted unigenes encoding enzymes involved in terpenoid and phenylpropanoid biosynthesis. The sequence data provide the most comprehensive transcriptomic resource currently available for Ananas comosus var. bracteatus. To our knowledge; this is the first report on the de novo transcriptome sequencing of the Ananas comosus var. bracteatus. Unigenes obtained in this study, may help improve future gene expression, genetic and genomics studies in Ananas comosus var. bracteatus.
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Directory of Open Access Journals (Sweden)
Jun Ma
Full Text Available Ananas comosus var. bracteatus (Red Pineapple is an important ornamental plant for its colorful leaves and decorative red fruits. Because of its complex genome, it is difficult to understand the molecular mechanisms involved in the growth and development. Thus high-throughput transcriptome sequencing of Ananas comosus var. bracteatus is necessary to generate large quantities of transcript sequences for the purpose of gene discovery and functional genomic studies.The Ananas comosus var. bracteatus transcriptome was sequenced by the Illumina paired-end sequencing technology. We obtained a total of 23.5 million high quality sequencing reads, 1,555,808 contigs and 41,052 unigenes. In total 41,052 unigenes of Ananas comosus var. bracteatus, 23,275 unigenes were annotated in the NCBI non-redundant protein database and 23,134 unigenes were annotated in the Swiss-Port database. Out of these, 17,748 and 8,505 unigenes were assigned to gene ontology categories and clusters of orthologous groups, respectively. Functional annotation against Kyoto Encyclopedia of Genes and Genomes Pathway database identified 5,825 unigenes which were mapped to 117 pathways. The assembly predicted many unigenes that were previously unknown. The annotated unigenes were compared against pineapple, rice, maize, Arabidopsis, and sorghum. Unigenes that did not match any of those five sequence datasets are considered to be Ananas comosus var. bracteatus unique. We predicted unigenes encoding enzymes involved in terpenoid and phenylpropanoid biosynthesis.The sequence data provide the most comprehensive transcriptomic resource currently available for Ananas comosus var. bracteatus. To our knowledge; this is the first report on the de novo transcriptome sequencing of the Ananas comosus var. bracteatus. Unigenes obtained in this study, may help improve future gene expression, genetic and genomics studies in Ananas comosus var. bracteatus.
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MACSIMS : multiple alignment of complete sequences information management system
Directory of Open Access Journals (Sweden)
Plewniak Frédéric
2006-06-01
Full Text Available Abstract Background In the post-genomic era, systems-level studies are being performed that seek to explain complex biological systems by integrating diverse resources from fields such as genomics, proteomics or transcriptomics. New information management systems are now needed for the collection, validation and analysis of the vast amount of heterogeneous data available. Multiple alignments of complete sequences provide an ideal environment for the integration of this information in the context of the protein family. Results MACSIMS is a multiple alignment-based information management program that combines the advantages of both knowledge-based and ab initio sequence analysis methods. Structural and functional information is retrieved automatically from the public databases. In the multiple alignment, homologous regions are identified and the retrieved data is evaluated and propagated from known to unknown sequences with these reliable regions. In a large-scale evaluation, the specificity of the propagated sequence features is estimated to be >99%, i.e. very few false positive predictions are made. MACSIMS is then used to characterise mutations in a test set of 100 proteins that are known to be involved in human genetic diseases. The number of sequence features associated with these proteins was increased by 60%, compared to the features available in the public databases. An XML format output file allows automatic parsing of the MACSIM results, while a graphical display using the JalView program allows manual analysis. Conclusion MACSIMS is a new information management system that incorporates detailed analyses of protein families at the structural, functional and evolutionary levels. MACSIMS thus provides a unique environment that facilitates knowledge extraction and the presentation of the most pertinent information to the biologist. A web server and the source code are available at http://bips.u-strasbg.fr/MACSIMS/.
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Barik, Amita; Das, Santasabuj
2018-01-02
Small RNAs (sRNAs) in bacteria have emerged as key players in transcriptional and post-transcriptional regulation of gene expression. Here, we present a statistical analysis of different sequence- and structure-related features of bacterial sRNAs to identify the descriptors that could discriminate sRNAs from other bacterial RNAs. We investigated a comprehensive and heterogeneous collection of 816 sRNAs, identified by northern blotting across 33 bacterial species and compared their various features with other classes of bacterial RNAs, such as tRNAs, rRNAs and mRNAs. We observed that sRNAs differed significantly from the rest with respect to G+C composition, normalized minimum free energy of folding, motif frequency and several RNA-folding parameters like base-pairing propensity, Shannon entropy and base-pair distance. Based on the selected features, we developed a predictive model using Random Forests (RF) method to classify the above four classes of RNAs. Our model displayed an overall predictive accuracy of 89.5%. These findings would help to differentiate bacterial sRNAs from other RNAs and further promote prediction of novel sRNAs in different bacterial species.
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Directory of Open Access Journals (Sweden)
Sheng Yang
2015-01-01
Full Text Available Sequencing is widely used to discover associations between microRNAs (miRNAs and diseases. However, the negative binomial distribution (NB and high dimensionality of data obtained using sequencing can lead to low-power results and low reproducibility. Several statistical learning algorithms have been proposed to address sequencing data, and although evaluation of these methods is essential, such studies are relatively rare. The performance of seven feature selection (FS algorithms, including baySeq, DESeq, edgeR, the rank sum test, lasso, particle swarm optimistic decision tree, and random forest (RF, was compared by simulation under different conditions based on the difference of the mean, the dispersion parameter of the NB, and the signal to noise ratio. Real data were used to evaluate the performance of RF, logistic regression, and support vector machine. Based on the simulation and real data, we discuss the behaviour of the FS and classification algorithms. The Apriori algorithm identified frequent item sets (mir-133a, mir-133b, mir-183, mir-937, and mir-96 from among the deregulated miRNAs of six datasets from The Cancer Genomics Atlas. Taking these findings altogether and considering computational memory requirements, we propose a strategy that combines edgeR and DESeq for large sample sizes.
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Ma, Jun; Kanakala, S.; He, Yehua; Zhang, Junli; Zhong, Xiaolan
2015-01-01
Background Ananas comosus var. bracteatus (Red Pineapple) is an important ornamental plant for its colorful leaves and decorative red fruits. Because of its complex genome, it is difficult to understand the molecular mechanisms involved in the growth and development. Thus high-throughput transcriptome sequencing of Ananas comosus var. bracteatus is necessary to generate large quantities of transcript sequences for the purpose of gene discovery and functional genomic studies. Results The Anana...
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Li, Man; Ling, Cheng; Xu, Qi; Gao, Jingyang
2018-02-01
Sequence classification is crucial in predicting the function of newly discovered sequences. In recent years, the prediction of the incremental large-scale and diversity of sequences has heavily relied on the involvement of machine-learning algorithms. To improve prediction accuracy, these algorithms must confront the key challenge of extracting valuable features. In this work, we propose a feature-enhanced protein classification approach, considering the rich generation of multiple sequence alignment algorithms, N-gram probabilistic language model and the deep learning technique. The essence behind the proposed method is that if each group of sequences can be represented by one feature sequence, composed of homologous sites, there should be less loss when the sequence is rebuilt, when a more relevant sequence is added to the group. On the basis of this consideration, the prediction becomes whether a query sequence belonging to a group of sequences can be transferred to calculate the probability that the new feature sequence evolves from the original one. The proposed work focuses on the hierarchical classification of G-protein Coupled Receptors (GPCRs), which begins by extracting the feature sequences from the multiple sequence alignment results of the GPCRs sub-subfamilies. The N-gram model is then applied to construct the input vectors. Finally, these vectors are imported into a convolutional neural network to make a prediction. The experimental results elucidate that the proposed method provides significant performance improvements. The classification error rate of the proposed method is reduced by at least 4.67% (family level I) and 5.75% (family Level II), in comparison with the current state-of-the-art methods. The implementation program of the proposed work is freely available at: https://github.com/alanFchina/CNN .
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Pairwise Sequence Alignment Library
Energy Technology Data Exchange (ETDEWEB)
2015-05-20
Vector extensions, such as SSE, have been part of the x86 CPU since the 1990s, with applications in graphics, signal processing, and scientific applications. Although many algorithms and applications can naturally benefit from automatic vectorization techniques, there are still many that are difficult to vectorize due to their dependence on irregular data structures, dense branch operations, or data dependencies. Sequence alignment, one of the most widely used operations in bioinformatics workflows, has a computational footprint that features complex data dependencies. The trend of widening vector registers adversely affects the state-of-the-art sequence alignment algorithm based on striped data layouts. Therefore, a novel SIMD implementation of a parallel scan-based sequence alignment algorithm that can better exploit wider SIMD units was implemented as part of the Parallel Sequence Alignment Library (parasail). Parasail features: Reference implementations of all known vectorized sequence alignment approaches. Implementations of Smith Waterman (SW), semi-global (SG), and Needleman Wunsch (NW) sequence alignment algorithms. Implementations across all modern CPU instruction sets including AVX2 and KNC. Language interfaces for C/C++ and Python.
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Litho-structural and geophysics features of the Alto Paranaiba Uplift
International Nuclear Information System (INIS)
Hasui, Y.
1991-01-01
The Alto Paranaiba Uplift (APU) is an almost elliptical tectonic feature of the Western Minas Gerais/Southern Goias region, which was active mostly during the Cretaceous. It separated the Parana Basin, during the formation of the Sao Bento, Uberaba and Bauru sequences, from the Alto-Sanfranciscana Basin, at the time of formation of the Areado, Patos, Capacete and Urucuia sequences. The Bouguer anomaly data indicate that the APU developed at the southwestern border of the ancient Brasilia crustal block and is represented by an almost elliptical gravity high of 15 mgal, locally disturbed by positive and negative the presence of important lineaments of a NW-SE set, mostly crossing the southwestern half of the APU. The APU development, the magmatism and the lateral basin formation involved reactivation of preexisting discontinuities and are related to a mantle plume. The tectonic development was aborted at the uplift stage during Cretaceous, after the deposition of the Bauru and Urucuia sequences, as is indicated by the Pratinha peneplane, now elevated at about 1.100 m altitude, which sculpture ended at the beginning of the Tertiary. The APU is one tectonic feature like other similar anomalies also aborted in the uplift stage or in the rift stage, which developed in Southern Brazil during the time of Atlantic Ocean opening. (author)
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Using expected sequence features to improve basecalling accuracy of amplicon pyrosequencing data
DEFF Research Database (Denmark)
Rask, Thomas Salhøj; Petersen, Bent; Chen, Donald S.
2016-01-01
. The new basecalling method described here, named Multipass, implements a probabilistic framework for working with the raw flowgrams obtained by pyrosequencing. For each sequence variant Multipass calculates the likelihood and nucleotide sequence of several most likely sequences given the flowgram data....... This probabilistic approach enables integration of basecalling into a larger model where other parameters can be incorporated, such as the likelihood for observing a full-length open reading frame at the targeted region. We apply the method to 454 amplicon pyrosequencing data obtained from a malaria virulence gene...... family, where Multipass generates 20 % more error-free sequences than current state of the art methods, and provides sequence characteristics that allow generation of a set of high confidence error-free sequences. This novel method can be used to increase accuracy of existing and future amplicon...
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Yeast prions and human prion-like proteins: sequence features and prediction methods.
Cascarina, Sean M; Ross, Eric D
2014-06-01
Prions are self-propagating infectious protein isoforms. A growing number of prions have been identified in yeast, each resulting from the conversion of soluble proteins into an insoluble amyloid form. These yeast prions have served as a powerful model system for studying the causes and consequences of prion aggregation. Remarkably, a number of human proteins containing prion-like domains, defined as domains with compositional similarity to yeast prion domains, have recently been linked to various human degenerative diseases, including amyotrophic lateral sclerosis. This suggests that the lessons learned from yeast prions may help in understanding these human diseases. In this review, we examine what has been learned about the amino acid sequence basis for prion aggregation in yeast, and how this information has been used to develop methods to predict aggregation propensity. We then discuss how this information is being applied to understand human disease, and the challenges involved in applying yeast prediction methods to higher organisms.
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Directory of Open Access Journals (Sweden)
Sette Alessandro
2005-05-01
Full Text Available Abstract Background Many processes in molecular biology involve the recognition of short sequences of nucleic-or amino acids, such as the binding of immunogenic peptides to major histocompatibility complex (MHC molecules. From experimental data, a model of the sequence specificity of these processes can be constructed, such as a sequence motif, a scoring matrix or an artificial neural network. The purpose of these models is two-fold. First, they can provide a summary of experimental results, allowing for a deeper understanding of the mechanisms involved in sequence recognition. Second, such models can be used to predict the experimental outcome for yet untested sequences. In the past we reported the development of a method to generate such models called the Stabilized Matrix Method (SMM. This method has been successfully applied to predicting peptide binding to MHC molecules, peptide transport by the transporter associated with antigen presentation (TAP and proteasomal cleavage of protein sequences. Results Herein we report the implementation of the SMM algorithm as a publicly available software package. Specific features determining the type of problems the method is most appropriate for are discussed. Advantageous features of the package are: (1 the output generated is easy to interpret, (2 input and output are both quantitative, (3 specific computational strategies to handle experimental noise are built in, (4 the algorithm is designed to effectively handle bounded experimental data, (5 experimental data from randomized peptide libraries and conventional peptides can easily be combined, and (6 it is possible to incorporate pair interactions between positions of a sequence. Conclusion Making the SMM method publicly available enables bioinformaticians and experimental biologists to easily access it, to compare its performance to other prediction methods, and to extend it to other applications.
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Tsai, Zing Tsung-Yeh; Shiu, Shin-Han; Tsai, Huai-Kuang
2015-08-01
Transcription factor (TF) binding is determined by the presence of specific sequence motifs (SM) and chromatin accessibility, where the latter is influenced by both chromatin state (CS) and DNA structure (DS) properties. Although SM, CS, and DS have been used to predict TF binding sites, a predictive model that jointly considers CS and DS has not been developed to predict either TF-specific binding or general binding properties of TFs. Using budding yeast as model, we found that machine learning classifiers trained with either CS or DS features alone perform better in predicting TF-specific binding compared to SM-based classifiers. In addition, simultaneously considering CS and DS further improves the accuracy of the TF binding predictions, indicating the highly complementary nature of these two properties. The contributions of SM, CS, and DS features to binding site predictions differ greatly between TFs, allowing TF-specific predictions and potentially reflecting different TF binding mechanisms. In addition, a "TF-agnostic" predictive model based on three DNA "intrinsic properties" (in silico predicted nucleosome occupancy, major groove geometry, and dinucleotide free energy) that can be calculated from genomic sequences alone has performance that rivals the model incorporating experiment-derived data. This intrinsic property model allows prediction of binding regions not only across TFs, but also across DNA-binding domain families with distinct structural folds. Furthermore, these predicted binding regions can help identify TF binding sites that have a significant impact on target gene expression. Because the intrinsic property model allows prediction of binding regions across DNA-binding domain families, it is TF agnostic and likely describes general binding potential of TFs. Thus, our findings suggest that it is feasible to establish a TF agnostic model for identifying functional regulatory regions in potentially any sequenced genome.
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Directory of Open Access Journals (Sweden)
Zing Tsung-Yeh Tsai
2015-08-01
Full Text Available Transcription factor (TF binding is determined by the presence of specific sequence motifs (SM and chromatin accessibility, where the latter is influenced by both chromatin state (CS and DNA structure (DS properties. Although SM, CS, and DS have been used to predict TF binding sites, a predictive model that jointly considers CS and DS has not been developed to predict either TF-specific binding or general binding properties of TFs. Using budding yeast as model, we found that machine learning classifiers trained with either CS or DS features alone perform better in predicting TF-specific binding compared to SM-based classifiers. In addition, simultaneously considering CS and DS further improves the accuracy of the TF binding predictions, indicating the highly complementary nature of these two properties. The contributions of SM, CS, and DS features to binding site predictions differ greatly between TFs, allowing TF-specific predictions and potentially reflecting different TF binding mechanisms. In addition, a "TF-agnostic" predictive model based on three DNA "intrinsic properties" (in silico predicted nucleosome occupancy, major groove geometry, and dinucleotide free energy that can be calculated from genomic sequences alone has performance that rivals the model incorporating experiment-derived data. This intrinsic property model allows prediction of binding regions not only across TFs, but also across DNA-binding domain families with distinct structural folds. Furthermore, these predicted binding regions can help identify TF binding sites that have a significant impact on target gene expression. Because the intrinsic property model allows prediction of binding regions across DNA-binding domain families, it is TF agnostic and likely describes general binding potential of TFs. Thus, our findings suggest that it is feasible to establish a TF agnostic model for identifying functional regulatory regions in potentially any sequenced genome.
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Directory of Open Access Journals (Sweden)
L. Sarti
2010-04-01
Full Text Available To ascertain the effects of a different feed sequence, which could modify digestion rate and sites as well as metabolic - endocrine status and milk features, 6 lactating dairy cows have received the same diet with a different time of concentrate administration when close to the two daily forage meals: 30’ before or 60’ after them. Cows were tied in a barn with controlled temperature, humidity and light, individually fed and monitored for: daily dry matter intake, milk yield and its features at 2 milkings, concentrate passage rate and faecal traits. The results have showed that DMI, feeding behaviour, milk yield and milk features were not significantly affected (except fat content, increased when forage was supplied as first feed. The digesta passage rate was also different: concentrate escaped more rapidly from the rumen when fed before forage or 4 hours after them. This effect has not modified the faeces, but some endocrine and /or metabolic changes can be hypothesized, because milk fat content was increased when concentrate was supplied after forage.
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Jones, Kenneth Lyons; Robinson, Luther K; Benirschke, Kurt
2006-09-01
Amniotic bands can cause disruption of the cranial end of the developing fetus, leading in some cases to a neural tube closure defect. Although recurrence for unaffected parents of an affected child with a defect in which the neural tube closed normally but was subsequently disrupted by amniotic bands is negligible; for a primary defect in closure of the neural tube to which amnion has subsequently adhered, recurrence risk is 1.7%. In that primary defects of neural tube closure are characterized by typical abnormalities of the base of the skull, evaluation of the cranial base in such fetuses provides an approach for making a distinction between these 2 mechanisms. This distinction has implications regarding recurrence risk. The skull base of 2 fetuses with amnion rupture sequence involving the cranial end of the neural tube were compared to that of 1 fetus with anencephaly as well as that of a structurally normal fetus. The skulls were cleaned, fixed in 10% formalin, recleaned, and then exposed to 10% KOH solution. After washing and recleaning, the skulls were exposed to hydrogen peroxide for bleaching and photography. Despite involvement of the anterior neural tube in both fetuses with amnion rupture sequence, in Case 3 the cranial base was normal while in Case 4 the cranial base was similar to that seen in anencephaly. This technique provides a method for determining the developmental pathogenesis of anterior neural tube defects in cases of amnion rupture sequence. As such, it provides information that can be used to counsel parents of affected children with respect to recurrence risk.
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Directory of Open Access Journals (Sweden)
Yi-Jen Chen
2017-11-01
Full Text Available The role of osteoblasts in peri-articular bone loss and bone erosion in rheumatoid arthritis (RA has gained much attention, and microRNAs are hypothesized to play critical roles in the regulation of osteoblast function in RA. The aim of this study is to explore novel microRNAs differentially expressed in RA osteoblasts and to identify genes potentially involved in the dysregulated bone homeostasis in RA. RNAs were extracted from cultured normal and RA osteoblasts for sequencing. Using the next generation sequencing and bioinformatics approaches, we identified 35 differentially expressed microRNAs and 13 differentially expressed genes with potential microRNA–mRNA interactions in RA osteoblasts. The 13 candidate genes were involved mainly in cell–matrix adhesion, as classified by the Gene Ontology. Two genes of interest identified from RA osteoblasts, A-kinase anchoring protein 12 (AKAP12 and leucin rich repeat containing 15 (LRRC15, were found to express more consistently in the related RA synovial tissue arrays in the Gene Expression Omnibus database, with the predicted interactions with miR-183-5p and miR-146a-5p, respectively. The Ingenuity Pathway Analysis identified AKAP12 as one of the genes involved in protein kinase A signaling and the function of chemotaxis, interconnecting with molecules related to neovascularization. The findings indicate new candidate genes as the potential indicators in evaluating therapies targeting chemotaxis and neovascularization to control joint destruction in RA.
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Chuzhanova, Nadia; Abeysinghe, Shaun S; Krawczak, Michael; Cooper, David N
2003-09-01
Translocations and gross deletions are responsible for a significant proportion of both cancer and inherited disease. Although such gene rearrangements are nonuniformly distributed in the human genome, the underlying mutational mechanisms remain unclear. We have studied the potential involvement of various types of repetitive sequence elements in the formation of secondary structure intermediates between the single-stranded DNA ends that recombine during rearrangements. Complexity analysis was used to assess the potential of these ends to form secondary structures, the maximum decrease in complexity consequent to a gross rearrangement being used as an indicator of the type of repeat and the specific DNA ends involved. A total of 175 pairs of deletion/translocation breakpoint junction sequences available from the Gross Rearrangement Breakpoint Database [GRaBD; www.uwcm.ac.uk/uwcm/mg/grabd/grabd.html] were analyzed. Potential secondary structure was noted between the 5' flanking sequence of the first breakpoint and the 3' flanking sequence of the second breakpoint in 49% of rearrangements and between the 5' flanking sequence of the second breakpoint and the 3' flanking sequence of the first breakpoint in 36% of rearrangements. Inverted repeats, inversions of inverted repeats, and symmetric elements were found in association with gross rearrangements at approximately the same frequency. However, inverted repeats and inversions of inverted repeats accounted for the vast majority (83%) of deletions plus small insertions, symmetric elements for one-half of all antigen receptor-mediated translocations, while direct repeats appear only to be involved in mediating simple deletions. These findings extend our understanding of illegitimate recombination by highlighting the importance of secondary structure formation between single-stranded DNA ends at breakpoint junctions. Copyright 2003 Wiley-Liss, Inc.
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Gaucher disease: MR evaluation of bone marrow features during treatment with enzyme replacement
International Nuclear Information System (INIS)
Poll, L.W.; Koch, J.A.; Boerner, D.; Cohnen, M.; Jung, G.; Scherer, A.; Moedder, U.; Niederau, C.
2001-01-01
Purpose: Enzyme replacement therapy (ERT) arrests and reverses the hematological and visceral symptoms of adult Gaucher disease, the most frequent lysosomal storage disorder. There are only a few studies available evaluating bone disease during ERT. The aim of this study was to investigate the features of bone marrow (bm) by magnetic resonance imaging (MRI) in these patients during ERT. Materials and Methods: MRI was performed prospectively in thirty adult type I Gaucher patients before and during ERT with a mean follow-up of 3 years. Spin-echo sequences (T 1 /T 2 ) of the lower extremities were obtained and the reconversion (response) or lack of reconversion (non-response) to fatty marrow during treatment was analyzed. The morphological features of bm involvement, a homogeneous or non-homogeneous distribution of bm changes and focal bone lesions surrounded by a rim of reduced signal intensity (SI), were analyzed. Results: Infiltration of bm by Gaucher cells is characterized by a reduction of Sl on both T 1 - and T 2 -weighted sequences. Bone marrow responses were seen in 19 patients (63%) during treatment. Focal bone lesions, surrounded by a rim of reduced Sl, did not respond to ERT and correlated with a non-homogenous distribution of bone involvement and splenectomy. (orig.) [de
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Complete genome sequence of Cryptobacterium curtum type strain (12-3T)
Energy Technology Data Exchange (ETDEWEB)
Mavromatis, Konstantinos; Pukall, Rudiger; Rohde, Christine; Sims, David; Brettin, Thomas; Kuske, Cheryl; Detter, John C.; Han, Cliff; Lapidus, Alla; Copeland, Alex; Glavina Del Rio, Tijana; Nolan, Matt; Lucas, Susan; Tice, Hope; Cheng, Jan-Fang; Bruce, David; Goodwin, Lynne; Pitluck, Sam; Ovchinnikova, Galina; Pati, Amrita; Ivanova, Natalia; Chen, Amy; Palaniappan, Krishna; Chain, Patrick; D' haeseleer, Patrik; Bristow, Jim; Eisen, Jonathan A.; Markowitz, Victor; Hugenholtz, Philip; Rohde, Manfred; Klenk, Hans-Peter; Kyrpides, Nikos C.
2009-05-20
Cryptobacterium curtum Nakazawa et al. 1999 is the type species of the genus, and is of phylogenetic interest because of its very distant and isolated position within the family Coriobacteriaceae. C. curtum is an asaccharolytic, opportunistic pathogen with a typical occurrence in the oral cavity, involved in dental and oral infections like periodontitis, inflammations and abscesses. Here we describe the features of this organism, together with the complete genome sequence, and annotation. This is the first complete genome sequence of the actinobacterial family Coriobacteriaceae, and this 1,617,804 bp long single replicon genome with its 1364 protein-coding and 58 RNA genes is part of the Genomic Encyclopedia of Bacteria and Archaea project.
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Directory of Open Access Journals (Sweden)
Wibisono Adianto
2008-08-01
Full Text Available Abstract Background Chromosome location is often used as a scaffold to organize genomic information in both the living cell and molecular biological research. Thus, ever-increasing amounts of data about genomic features are stored in public databases and can be readily visualized by genome browsers. To perform in silico experimentation conveniently with this genomics data, biologists need tools to process and compare datasets routinely and explore the obtained results interactively. The complexity of such experimentation requires these tools to be based on an e-Science approach, hence generic, modular, and reusable. A virtual laboratory environment with workflows, workflow management systems, and Grid computation are therefore essential. Findings Here we apply an e-Science approach to develop SigWin-detector, a workflow-based tool that can detect significantly enriched windows of (genomic features in a (DNA sequence in a fast and reproducible way. For proof-of-principle, we utilize a biological use case to detect regions of increased and decreased gene expression (RIDGEs and anti-RIDGEs in human transcriptome maps. We improved the original method for RIDGE detection by replacing the costly step of estimation by random sampling with a faster analytical formula for computing the distribution of the null hypothesis being tested and by developing a new algorithm for computing moving medians. SigWin-detector was developed using the WS-VLAM workflow management system and consists of several reusable modules that are linked together in a basic workflow. The configuration of this basic workflow can be adapted to satisfy the requirements of the specific in silico experiment. Conclusion As we show with the results from analyses in the biological use case on RIDGEs, SigWin-detector is an efficient and reusable Grid-based tool for discovering windows enriched for features of a particular type in any sequence of values. Thus, SigWin-detector provides the
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Inda, Márcia A; van Batenburg, Marinus F; Roos, Marco; Belloum, Adam S Z; Vasunin, Dmitry; Wibisono, Adianto; van Kampen, Antoine H C; Breit, Timo M
2008-08-08
Chromosome location is often used as a scaffold to organize genomic information in both the living cell and molecular biological research. Thus, ever-increasing amounts of data about genomic features are stored in public databases and can be readily visualized by genome browsers. To perform in silico experimentation conveniently with this genomics data, biologists need tools to process and compare datasets routinely and explore the obtained results interactively. The complexity of such experimentation requires these tools to be based on an e-Science approach, hence generic, modular, and reusable. A virtual laboratory environment with workflows, workflow management systems, and Grid computation are therefore essential. Here we apply an e-Science approach to develop SigWin-detector, a workflow-based tool that can detect significantly enriched windows of (genomic) features in a (DNA) sequence in a fast and reproducible way. For proof-of-principle, we utilize a biological use case to detect regions of increased and decreased gene expression (RIDGEs and anti-RIDGEs) in human transcriptome maps. We improved the original method for RIDGE detection by replacing the costly step of estimation by random sampling with a faster analytical formula for computing the distribution of the null hypothesis being tested and by developing a new algorithm for computing moving medians. SigWin-detector was developed using the WS-VLAM workflow management system and consists of several reusable modules that are linked together in a basic workflow. The configuration of this basic workflow can be adapted to satisfy the requirements of the specific in silico experiment. As we show with the results from analyses in the biological use case on RIDGEs, SigWin-detector is an efficient and reusable Grid-based tool for discovering windows enriched for features of a particular type in any sequence of values. Thus, SigWin-detector provides the proof-of-principle for the modular e-Science based concept
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Sequence homology at the breakpoint and clinical phenotype of mitochondrial DNA deletion syndromes.
Sadikovic, Bekim; Wang, Jing; El-Hattab, Ayman W; Landsverk, Megan; Douglas, Ganka; Brundage, Ellen K; Craigen, William J; Schmitt, Eric S; Wong, Lee-Jun C
2010-12-20
Mitochondrial DNA (mtDNA) deletions are a common cause of mitochondrial disorders. Large mtDNA deletions can lead to a broad spectrum of clinical features with different age of onset, ranging from mild mitochondrial myopathies (MM), progressive external ophthalmoplegia (PEO), and Kearns-Sayre syndrome (KSS), to severe Pearson syndrome. The aim of this study is to investigate the molecular signatures surrounding the deletion breakpoints and their association with the clinical phenotype and age at onset. MtDNA deletions in 67 patients were characterized using array comparative genomic hybridization (aCGH) followed by PCR-sequencing of the deletion junctions. Sequence homology including both perfect and imperfect short repeats flanking the deletion regions were analyzed and correlated with clinical features and patients' age group. In all age groups, there was a significant increase in sequence homology flanking the deletion compared to mtDNA background. The youngest patient group (deletion distribution in size and locations, with a significantly lower sequence homology flanking the deletion, and the highest percentage of deletion mutant heteroplasmy. The older age groups showed rather discrete pattern of deletions with 44% of all patients over 6 years old carrying the most common 5 kb mtDNA deletion, which was found mostly in muscle specimens (22/41). Only 15% (3/20) of the young patients (deletion, which is usually present in blood rather than muscle. This group of patients predominantly (16 out of 17) exhibit multisystem disorder and/or Pearson syndrome, while older patients had predominantly neuromuscular manifestations including KSS, PEO, and MM. In conclusion, sequence homology at the deletion flanking regions is a consistent feature of mtDNA deletions. Decreased levels of sequence homology and increased levels of deletion mutant heteroplasmy appear to correlate with earlier onset and more severe disease with multisystem involvement.
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MRI of spondylodiscities: contribution of gadolinium-DTPA and fat suppression sequence
International Nuclear Information System (INIS)
Cova, M.A.; Dalla Palma, L.; Pozzi-Mucelli, R.S.; Ricci, C.
1993-01-01
Twenty-six patients with a clinical diagnosis of spondylodiscitis were examined with non-contrast and contrast-enhanced MRI in order to define the contribution of gadolinium-DTPA (Gd-DTPA) and different pulse sequences, including a fat suppression sequence (SPIR). Spin echo (SE) T1-weighted images before and after Gd-DTPA injection and SE T2-weighted images were obtained in all patients. Twelve patients were also examined using the SPIR sequence following Gd-DTPA injection. Signal intensity and morphological features of the disc and vertebral lesions were then evaluated. The SE T1-weighted sequence with Gd-DTPA was very effective in showing the pathological changes at the level of the disc as an area of low signal intensity surrounded by a peripheral rim of enhancement in 24 of 26 cases (92%). This feature was not visible on non-enhanced images. As regards contiguous vertebral lesions this sequence was less informative, since in 8 of 26 cases (31%) the vertebral lesions became isointense and therefore not detectable. In 12 cases there was extension into the surrounding structures (spinal canal and/or paravertebral tissues). An enhanced SE T1-weighted sequence provided good anatomical definition of the extension of the infection in the spinal canal in all cases with this type of involvement (7 of 12). Regarding the 7 cases with paravertebral extension, no extension was visible in 1 case due to the reduced contrast with the surrounding fat following Gd-DTPA injection. The enhanced SPIR sequence was very effective, particularly in detecting the lesions in the vertebral bodies, avoiding the limitation of the enhanced SE T1-weighted sequence. The SPIR sequence was also effective in showing the extension within the spinal canal and the paravertebral fat. On the basis of our results the combination of a SE T1-weighted sequence without contrast and SPIR sequence with Gd-DTPA seems to be the best approach in cases of spondylodiscitis. (orig.)
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Directory of Open Access Journals (Sweden)
Cannon Charles H
2011-07-01
Full Text Available Abstract Background Acacia auriculiformis × Acacia mangium hybrids are commercially important trees for the timber and pulp industry in Southeast Asia. Increasing pulp yield while reducing pulping costs are major objectives of tree breeding programs. The general monolignol biosynthesis and secondary cell wall formation pathways are well-characterized but genes in these pathways are poorly characterized in Acacia hybrids. RNA-seq on short-read platforms is a rapid approach for obtaining comprehensive transcriptomic data and to discover informative sequence variants. Results We sequenced transcriptomes of A. auriculiformis and A. mangium from non-normalized cDNA libraries synthesized from pooled young stem and inner bark tissues using paired-end libraries and a single lane of an Illumina GAII machine. De novo assembly produced a total of 42,217 and 35,759 contigs with an average length of 496 bp and 498 bp for A. auriculiformis and A. mangium respectively. The assemblies of A. auriculiformis and A. mangium had a total length of 21,022,649 bp and 17,838,260 bp, respectively, with the largest contig 15,262 bp long. We detected all ten monolignol biosynthetic genes using Blastx and further analysis revealed 18 lignin isoforms for each species. We also identified five contigs homologous to R2R3-MYB proteins in other plant species that are involved in transcriptional regulation of secondary cell wall formation and lignin deposition. We searched the contigs against public microRNA database and predicted the stem-loop structures of six highly conserved microRNA families (miR319, miR396, miR160, miR172, miR162 and miR168 and one legume-specific family (miR2086. Three microRNA target genes were predicted to be involved in wood formation and flavonoid biosynthesis. By using the assemblies as a reference, we discovered 16,648 and 9,335 high quality putative Single Nucleotide Polymorphisms (SNPs in the transcriptomes of A. auriculiformis and A. mangium
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Bourget, Dominique; Whitehurst, Laurie
2004-11-01
Acts of violence have been frequently reported in cases of Capgras syndrome (CS), a misidentification syndrome characterized by the delusional belief that imposters have replaced people familiar to the individual. CS has been observed in many neuropsychiatric and organic disorders, and neuroimaging studies indicate an association between CS and right hemisphere abnormalities. However, CS has received limited attention from a forensic psychiatric perspective. We propose that elucidating demographic and clinical features noted in cases of violence secondary to CS may highlight important factors in the progression of CS to violence. We review the neurophysiological correlates and clinical factors observed in CS and present characteristics of a series of cases that demonstrate the potential of CS patients for severe physical violence toward the misidentified person. For patients with CS involving assault, we present and discuss commonly reported demographic and clinical features that may contribute to an increased risk for violence. An understanding of the presenting clinical features of CS resulting in aggressive acts may assist clinicians to assess the potential for violence in these patients.
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2013-01-01
Background Plastids are an important component of plant cells, being the site of manufacture and storage of chemical compounds used by the cell, and contain pigments such as those used in photosynthesis, starch synthesis/storage, cell color etc. They are essential organelles of the plant cell, also present in algae. Recent advances in genomic technology and sequencing efforts is generating a huge amount of DNA sequence data every day. The predicted proteome of these genomes needs annotation at a faster pace. In view of this, one such annotation need is to develop an automated system that can distinguish between plastid and non-plastid proteins accurately, and further classify plastid-types based on their functionality. We compared the amino acid compositions of plastid proteins with those of non-plastid ones and found significant differences, which were used as a basis to develop various feature-based prediction models using similarity-search and machine learning. Results In this study, we developed separate Support Vector Machine (SVM) trained classifiers for characterizing the plastids in two steps: first distinguishing the plastid vs. non-plastid proteins, and then classifying the identified plastids into their various types based on their function (chloroplast, chromoplast, etioplast, and amyloplast). Five diverse protein features: amino acid composition, dipeptide composition, the pseudo amino acid composition, Nterminal-Center-Cterminal composition and the protein physicochemical properties are used to develop SVM models. Overall, the dipeptide composition-based module shows the best performance with an accuracy of 86.80% and Matthews Correlation Coefficient (MCC) of 0.74 in phase-I and 78.60% with a MCC of 0.44 in phase-II. On independent test data, this model also performs better with an overall accuracy of 76.58% and 74.97% in phase-I and phase-II, respectively. The similarity-based PSI-BLAST module shows very low performance with about 50% prediction
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Sequence-based feature prediction and annotation of proteins
DEFF Research Database (Denmark)
Juncker, Agnieszka; Jensen, Lars J.; Pierleoni, Andrea
2009-01-01
A recent trend in computational methods for annotation of protein function is that many prediction tools are combined in complex workflows and pipelines to facilitate the analysis of feature combinations, for example, the entire repertoire of kinase-binding motifs in the human proteome....
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Iaria, Domenico; Chiappetta, Adriana; Muzzalupo, Innocenzo
2016-01-01
In olive (Olea europaea L.), the processes controlling self-incompatibility are still unclear and the molecular basis underlying this process are still not fully characterized. In order to determine compatibility relationships, using next-generation sequencing techniques and a de novo transcriptome assembly strategy, we show that pollen tubes from different olive plants, grown in vitro in a medium containing its own pistil and in combination pollen/pistil from self-sterile and self-fertile cultivars, have a distinct gene expression profile and many of the differentially expressed sequences between the samples fall within gene families involved in the development of the pollen tube, such as lipase, carboxylesterase, pectinesterase, pectin methylesterase, and callose synthase. Moreover, different genes involved in signal transduction, transcription, and growth are overrepresented. The analysis also allowed us to identify members in actin and actin depolymerization factor and fibrin gene family and member of the Ca(2+) binding gene family related to the development and polarization of pollen apical tip. The whole transcriptomic analysis, through the identification of the differentially expressed transcripts set and an extended functional annotation analysis, will lead to a better understanding of the mechanisms of pollen germination and pollen tube growth in the olive.
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Feature Selection and the Class Imbalance Problem in Predicting Protein Function from Sequence
Al-Shahib, A.; Breitling, R.; Gilbert, D.
2005-01-01
Abstract: When the standard approach to predict protein function by sequence homology fails, other alternative methods can be used that require only the amino acid sequence for predicting function. One such approach uses machine learning to predict protein function directly from amino acid sequence
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Multiple song features are related to paternal effort in common nightingales.
Bartsch, Conny; Weiss, Michael; Kipper, Silke
2015-06-18
Sexual ornamentation may be related to the degree of paternal care and the 'good-parent' model predicts that male secondary characters honestly advertise paternal investment. In most birds, males are involved in bringing up the young and successful reproduction highly depends on male contribution during breeding. In passerines, male song is indicative of male attributes and for few species it has been shown that song features also signal paternal investment to females. Males of nightingales Luscinia megarhynchos are famous for their elaborate singing but so far there is only little knowledge on the role of male song in intersexual communication, and it is unknown whether male song predicts male parenting abilities. Using RFID technology to record male feeding visits to the nest, we found that nightingale males substantially contribute to chick feeding. Also, we analyzed male nocturnal song with focus on song features that have been shown to signal male quality before. We found that several song features, namely measures of song complexity and song sequencing, were correlated with male feeding rates. Moreover, the combination of these song features had strong predictive power for male contribution to nestling feeding. Since male nightingales are involved in chick rearing, paternal investment might be a crucial variable for female mate choice in this species. Females may assess future paternal care on the basis of song features identified in our study and thus these features may have evolved to signal direct benefits to females. Additionally we underline the importance of multiple acoustic cues for female mating decisions especially in species with complex song such as the nightingale.
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Gupta, Radhey S
2012-11-01
The origin of photosynthesis and how this capability has spread to other bacterial phyla remain important unresolved questions. I describe here a number of conserved signature indels (CSIs) in key proteins involved in bacteriochlorophyll (Bchl) biosynthesis that provide important insights in these regards. The proteins BchL and BchX, which are essential for Bchl biosynthesis, are derived by gene duplication in a common ancestor of all phototrophs. More ancient gene duplication gave rise to the BchX-BchL proteins and the NifH protein of the nitrogenase complex. The sequence alignment of NifH-BchX-BchL proteins contain two CSIs that are uniquely shared by all NifH and BchX homologs, but not by any BchL homologs. These CSIs and phylogenetic analysis of NifH-BchX-BchL protein sequences strongly suggest that the BchX homologs are ancestral to BchL and that the Bchl-based anoxygenic photosynthesis originated prior to the chlorophyll (Chl)-based photosynthesis in cyanobacteria. Another CSI in the BchX-BchL sequence alignment that is uniquely shared by all BchX homologs and the BchL sequences from Heliobacteriaceae, but absent in all other BchL homologs, suggests that the BchL homologs from Heliobacteriaceae are primitive in comparison to all other photosynthetic lineages. Several other identified CSIs in the BchN homologs are commonly shared by all proteobacterial homologs and a clade consisting of the marine unicellular Cyanobacteria (Clade C). These CSIs in conjunction with the results of phylogenetic analyses and pair-wise sequence similarity on the BchL, BchN, and BchB proteins, where the homologs from Clade C Cyanobacteria and Proteobacteria exhibited close relationship, provide strong evidence that these two groups have incurred lateral gene transfers. Additionally, phylogenetic analyses and several CSIs in the BchL-N-B proteins that are uniquely shared by all Chlorobi and Chloroflexi homologs provide evidence that the genes for these proteins have also been
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Anatomic features involved in technical complexity of partial nephrectomy.
Hou, Weibin; Yan, Weigang; Ji, Zhigang
2015-01-01
Nephrometry score systems, including RENAL nephrometry, preoperative aspects and dimensions used for an anatomical classification system, C-index, diameter-axial-polar nephrometry, contact surface area score, calculating resected and ischemized volume, renal tumor invasion index, surgical approach renal ranking score, zonal NePhRO score, and renal pelvic score, have been reviewed. Moreover, salient anatomic features like the perinephric fat and vascular variants also have been discussed. We then extract 7 anatomic characteristics, namely tumor size, spatial location, adjacency, exophytic/endophytic extension, vascular variants, pelvic anatomy, and perinephric fat as important features for partial nephrectomy. For novice surgeons, comprehensive and adequate anatomic consideration may help them in their early clinical practice. Copyright © 2015 Elsevier Inc. All rights reserved.
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GuiTope: an application for mapping random-sequence peptides to protein sequences.
Halperin, Rebecca F; Stafford, Phillip; Emery, Jack S; Navalkar, Krupa Arun; Johnston, Stephen Albert
2012-01-03
Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC) at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net.
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GuiTope: an application for mapping random-sequence peptides to protein sequences
Directory of Open Access Journals (Sweden)
Halperin Rebecca F
2012-01-01
Full Text Available Abstract Background Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. Results GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. Conclusions GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net.
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Probabilistic Slow Features for Behavior Analysis
Zafeiriou, Lazaros; Nicolaou, Mihalis A.; Zafeiriou, Stefanos; Nikitidis, Symeon; Pantic, Maja
A recently introduced latent feature learning technique for time-varying dynamic phenomena analysis is the so-called slow feature analysis (SFA). SFA is a deterministic component analysis technique for multidimensional sequences that, by minimizing the variance of the first-order time derivative
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Learning slow features for behavior analysis
Zafeiriou, Lazaros; Nicolaou, Mihalis A.; Zafeiriou, Stefanos; Nikitids, Symeon; Pantic, Maja
2013-01-01
A recently introduced latent feature learning technique for time varying dynamic phenomena analysis is the socalled Slow Feature Analysis (SFA). SFA is a deterministic component analysis technique for multi-dimensional sequences that by minimizing the variance of the first order time derivative
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Büssow, Konrad; Hoffmann, Steve; Sievert, Volker
2002-12-19
Functional genomics involves the parallel experimentation with large sets of proteins. This requires management of large sets of open reading frames as a prerequisite of the cloning and recombinant expression of these proteins. A Java program was developed for retrieval of protein and nucleic acid sequences and annotations from NCBI GenBank, using the XML sequence format. Annotations retrieved by ORFer include sequence name, organism and also the completeness of the sequence. The program has a graphical user interface, although it can be used in a non-interactive mode. For protein sequences, the program also extracts the open reading frame sequence, if available, and checks its correct translation. ORFer accepts user input in the form of single or lists of GenBank GI identifiers or accession numbers. It can be used to extract complete sets of open reading frames and protein sequences from any kind of GenBank sequence entry, including complete genomes or chromosomes. Sequences are either stored with their features in a relational database or can be exported as text files in Fasta or tabulator delimited format. The ORFer program is freely available at http://www.proteinstrukturfabrik.de/orfer. The ORFer program allows for fast retrieval of DNA sequences, protein sequences and their open reading frames and sequence annotations from GenBank. Furthermore, storage of sequences and features in a relational database is supported. Such a database can supplement a laboratory information system (LIMS) with appropriate sequence information.
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Magnetic Resonance Features of Cerebral Malaria
Energy Technology Data Exchange (ETDEWEB)
Yadav, P.; Sharma, R.; Kumar, S.; Kumar, U. (Dept. of Radiodiagnosis and Dept. of Medicine, All India Institute of Medical Sciences, New Delhi (India))
2008-06-15
Background: Cerebral malaria is a major health hazard, with a high incidence of mortality. The disease is endemic in many developing countries, but with a greater increase in tourism, occasional cases may be detected in countries where the disease in not prevalent. Early diagnosis and evaluation of cerebral involvement in malaria utilizing modern imaging modalities have an impact on the treatment and clinical outcome. Purpose: To evaluate the magnetic resonance (MR) features of patients with cerebral malaria presenting with altered sensorium. Material and Methods: We present the findings in three patients with cerebral malaria presenting with altered sensorium. MR imaging using a 1.5-Tesla unit was carried out. The sequences performed were 5-mm-thick T1-weighted, T2-weighted, fluid-attenuated inversion-recovery (FLAIR), and T2-weighted gradient-echo axial sequences, and sagittal and coronal FLAIR. Diffusion-weighted imaging was performed with b values of 0 and 1000 s/mm2, and apparent diffusion coefficient (ADC) maps were obtained. Results: Focal hyperintensities in the bilateral periventricular white matter, corpus callosum, occipital subcortex, and bilateral thalami were noticed on T2-weighted and FLAIR sequences. The lesions were more marked in the splenium of the corpus callosum. No enhancement on postcontrast T1-weighted MR images was observed. There was no evidence of restricted diffusion on the diffusion-weighted sequence and ADC map. Conclusion: MR is a sensitive imaging modality, with a role in the assessment of cerebral lesions in malaria. Focal white matter and corpus callosal lesions without any restricted diffusion were the key findings in our patients
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Magnetic Resonance Features of Cerebral Malaria
International Nuclear Information System (INIS)
Yadav, P.; Sharma, R.; Kumar, S.; Kumar, U.
2008-01-01
Background: Cerebral malaria is a major health hazard, with a high incidence of mortality. The disease is endemic in many developing countries, but with a greater increase in tourism, occasional cases may be detected in countries where the disease in not prevalent. Early diagnosis and evaluation of cerebral involvement in malaria utilizing modern imaging modalities have an impact on the treatment and clinical outcome. Purpose: To evaluate the magnetic resonance (MR) features of patients with cerebral malaria presenting with altered sensorium. Material and Methods: We present the findings in three patients with cerebral malaria presenting with altered sensorium. MR imaging using a 1.5-Tesla unit was carried out. The sequences performed were 5-mm-thick T1-weighted, T2-weighted, fluid-attenuated inversion-recovery (FLAIR), and T2-weighted gradient-echo axial sequences, and sagittal and coronal FLAIR. Diffusion-weighted imaging was performed with b values of 0 and 1000 s/mm 2 , and apparent diffusion coefficient (ADC) maps were obtained. Results: Focal hyperintensities in the bilateral periventricular white matter, corpus callosum, occipital subcortex, and bilateral thalami were noticed on T2-weighted and FLAIR sequences. The lesions were more marked in the splenium of the corpus callosum. No enhancement on postcontrast T1-weighted MR images was observed. There was no evidence of restricted diffusion on the diffusion-weighted sequence and ADC map. Conclusion: MR is a sensitive imaging modality, with a role in the assessment of cerebral lesions in malaria. Focal white matter and corpus callosal lesions without any restricted diffusion were the key findings in our patients
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A Parvovirus B19 synthetic genome: sequence features and functional competence.
Manaresi, Elisabetta; Conti, Ilaria; Bua, Gloria; Bonvicini, Francesca; Gallinella, Giorgio
2017-08-01
Central to genetic studies for Parvovirus B19 (B19V) is the availability of genomic clones that may possess functional competence and ability to generate infectious virus. In our study, we established a new model genetic system for Parvovirus B19. A synthetic approach was followed, by design of a reference genome sequence, by generation of a corresponding artificial construct and its molecular cloning in a complete and functional form, and by setup of an efficient strategy to generate infectious virus, via transfection in UT7/EpoS1 cells and amplification in erythroid progenitor cells. The synthetic genome was able to generate virus with biological properties paralleling those of native virus, its infectious activity being dependent on the preservation of self-complementarity and sequence heterogeneity within the terminal regions. A virus of defined genome sequence, obtained from controlled cell culture conditions, can constitute a reference tool for investigation of the structural and functional characteristics of the virus. Copyright © 2017 Elsevier Inc. All rights reserved.
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Directory of Open Access Journals (Sweden)
Tsutomu Ogata
Full Text Available BACKGROUND: Although TBX1 mutations have been identified in patients with 22q11.2 deletion syndrome (22q11.2DS-like phenotypes including characteristic craniofacial features, cardiovascular anomalies, hypoparathyroidism, and thymic hypoplasia, the frequency of TBX1 mutations remains rare in deletion-negative patients. Thus, it would be reasonable to perform a comprehensive genetic analysis in deletion-negative patients with 22q11.2DS-like phenotypes. METHODOLOGY/PRINCIPAL FINDINGS: We studied three subjects with craniofacial features and hypocalcemia (group 1, two subjects with craniofacial features alone (group 2, and three subjects with normal phenotype within a single Japanese family. Fluorescence in situ hybridization analysis excluded chromosome 22q11.2 deletion, and genomewide array comparative genomic hybridization analysis revealed no copy number change specific to group 1 or groups 1+2. However, exome sequencing identified a heterozygous TBX1 frameshift mutation (c.1253delA, p.Y418fsX459 specific to groups 1+2, as well as six missense variants and two in-frame microdeletions specific to groups 1+2 and two missense variants specific to group 1. The TBX1 mutation resided at exon 9C and was predicted to produce a non-functional truncated protein missing the nuclear localization signal and most of the transactivation domain. CONCLUSIONS/SIGNIFICANCE: Clinical features in groups 1+2 are well explained by the TBX1 mutation, while the clinical effects of the remaining variants are largely unknown. Thus, the results exemplify the usefulness of exome sequencing in the identification of disease-causing mutations in familial disorders. Furthermore, the results, in conjunction with the previous data, imply that TBX1 isoform C is the biologically essential variant and that TBX1 mutations are associated with a wide phenotypic spectrum, including most of 22q11.2DS phenotypes.
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International Nuclear Information System (INIS)
Johnson, D.E.; Johnson, R.P.
1989-01-01
The Colliding Beam Sequencer (CBS) is a computer program used to operate the pbar-p Collider by synchronizing the applications programs and simulating the activities of the accelerator operators during filling and storage. The Sequencer acts as a meta-program, running otherwise stand alone applications programs, to do the set-up, beam transfers, acceleration, low beta turn on, and diagnostics for the transfers and storage. The Sequencer and its operational performance will be described along with its special features which include a periodic scheduler and command logger. 14 refs., 3 figs
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International Nuclear Information System (INIS)
Oner, A.Y.; Akpek, S.; Tali, T.
2007-01-01
Sinus histiocytosis with massive lymphadenopathy (SHML), or Rosai-Dorfman disease, is a rare histiocytic disorder that typically presents with chronic, self-limiting cervical lymphadenopathy. Although this disease mainly affects histiocytes, there are a few reports of bone marrow infiltration. Diffusion-weighted imaging (DWI) is a promising technology in differentiating between various bone marrow pathologies. We here present conventional magnetic resonance imaging and DWI features of a patient with SHML and bone marrow involvement
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Energy Technology Data Exchange (ETDEWEB)
Oner, A.Y.; Akpek, S.; Tali, T. [Dept. of Radiology, Gazi Univ. School of Medicine. Besevler-Ankara (Turkey)
2007-04-15
Sinus histiocytosis with massive lymphadenopathy (SHML), or Rosai-Dorfman disease, is a rare histiocytic disorder that typically presents with chronic, self-limiting cervical lymphadenopathy. Although this disease mainly affects histiocytes, there are a few reports of bone marrow infiltration. Diffusion-weighted imaging (DWI) is a promising technology in differentiating between various bone marrow pathologies. We here present conventional magnetic resonance imaging and DWI features of a patient with SHML and bone marrow involvement.
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FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation.
Bolleman, Jerven T; Mungall, Christopher J; Strozzi, Francesco; Baran, Joachim; Dumontier, Michel; Bonnal, Raoul J P; Buels, Robert; Hoehndorf, Robert; Fujisawa, Takatomo; Katayama, Toshiaki; Cock, Peter J A
2016-06-13
Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. We have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned "omics" areas. Using the same data format to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe - and potentially merge - sequence annotations from multiple sources. Data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.
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Exploration of noncoding sequences in metagenomes.
Directory of Open Access Journals (Sweden)
Fabián Tobar-Tosse
Full Text Available Environment-dependent genomic features have been defined for different metagenomes, whose genes and their associated processes are related to specific environments. Identification of ORFs and their functional categories are the most common methods for association between functional and environmental features. However, this analysis based on finding ORFs misses noncoding sequences and, therefore, some metagenome regulatory or structural information could be discarded. In this work we analyzed 23 whole metagenomes, including coding and noncoding sequences using the following sequence patterns: (G+C content, Codon Usage (Cd, Trinucleotide Usage (Tn, and functional assignments for ORF prediction. Herein, we present evidence of a high proportion of noncoding sequences discarded in common similarity-based methods in metagenomics, and the kind of relevant information present in those. We found a high density of trinucleotide repeat sequences (TRS in noncoding sequences, with a regulatory and adaptive function for metagenome communities. We present associations between trinucleotide values and gene function, where metagenome clustering correlate with microorganism adaptations and kinds of metagenomes. We propose here that noncoding sequences have relevant information to describe metagenomes that could be considered in a whole metagenome analysis in order to improve their organization, classification protocols, and their relation with the environment.
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Ghosh, Pritha; Mathew, Oommen K; Sowdhamini, Ramanathan
2016-10-07
RNA-binding proteins (RBPs) interact with their cognate RNA(s) to form large biomolecular assemblies. They are versatile in their functionality and are involved in a myriad of processes inside the cell. RBPs with similar structural features and common biological functions are grouped together into families and superfamilies. It will be useful to obtain an early understanding and association of RNA-binding property of sequences of gene products. Here, we report a web server, RStrucFam, to predict the structure, type of cognate RNA(s) and function(s) of proteins, where possible, from mere sequence information. The web server employs Hidden Markov Model scan (hmmscan) to enable association to a back-end database of structural and sequence families. The database (HMMRBP) comprises of 437 HMMs of RBP families of known structure that have been generated using structure-based sequence alignments and 746 sequence-centric RBP family HMMs. The input protein sequence is associated with structural or sequence domain families, if structure or sequence signatures exist. In case of association of the protein with a family of known structures, output features like, multiple structure-based sequence alignment (MSSA) of the query with all others members of that family is provided. Further, cognate RNA partner(s) for that protein, Gene Ontology (GO) annotations, if any and a homology model of the protein can be obtained. The users can also browse through the database for details pertaining to each family, protein or RNA and their related information based on keyword search or RNA motif search. RStrucFam is a web server that exploits structurally conserved features of RBPs, derived from known family members and imprinted in mathematical profiles, to predict putative RBPs from sequence information. Proteins that fail to associate with such structure-centric families are further queried against the sequence-centric RBP family HMMs in the HMMRBP database. Further, all other essential
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Directory of Open Access Journals (Sweden)
Beiko Robert G
2005-02-01
Full Text Available Abstract Background The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA structure and flexibility may also play a role in protein-DNA interactions, the simultaneous exploration of sequence- and structure-based hypotheses about the composition of binding sites and the ordering of features in a regulatory region should be considered as well. The consideration of structural features requires the development of new detection tools that can deal with data types other than primary sequence. Results GANN (available at http://bioinformatics.org.au/gann is a machine learning tool for the detection of conserved features in DNA. The software suite contains programs to extract different regions of genomic DNA from flat files and convert these sequences to indices that reflect sequence and structural composition or the presence of specific protein binding sites. The machine learning component allows the classification of different types of sequences based on subsamples of these indices, and can identify the best combinations of indices and machine learning architecture for sequence discrimination. Another key feature of GANN is the replicated splitting of data into training and test sets, and the implementation of negative controls. In validation experiments, GANN successfully merged important sequence and structural features to yield good predictive models for synthetic and real regulatory regions. Conclusion GANN is a flexible tool that can search through large sets of sequence and structural feature combinations to identify those that best characterize a set of sequences.
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Analysis and Visualization of ChIP-Seq and RNA-Seq Sequence Alignments Using ngs.plot.
Loh, Yong-Hwee Eddie; Shen, Li
2016-01-01
The continual maturation and increasing applications of next-generation sequencing technology in scientific research have yielded ever-increasing amounts of data that need to be effectively and efficiently analyzed and innovatively mined for new biological insights. We have developed ngs.plot-a quick and easy-to-use bioinformatics tool that performs visualizations of the spatial relationships between sequencing alignment enrichment and specific genomic features or regions. More importantly, ngs.plot is customizable beyond the use of standard genomic feature databases to allow the analysis and visualization of user-specified regions of interest generated by the user's own hypotheses. In this protocol, we demonstrate and explain the use of ngs.plot using command line executions, as well as a web-based workflow on the Galaxy framework. We replicate the underlying commands used in the analysis of a true biological dataset that we had reported and published earlier and demonstrate how ngs.plot can easily generate publication-ready figures. With ngs.plot, users would be able to efficiently and innovatively mine their own datasets without having to be involved in the technical aspects of sequence coverage calculations and genomic databases.
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Li, Shu-Fen; Zhang, Guo-Jun; Yuan, Jin-Hong; Deng, Chuan-Liang; Gao, Wu-Jun
2016-05-01
The present review discusses the roles of repetitive sequences played in plant sex chromosome evolution, and highlights epigenetic modification as potential mechanism of repetitive sequences involved in sex chromosome evolution. Sex determination in plants is mostly based on sex chromosomes. Classic theory proposes that sex chromosomes evolve from a specific pair of autosomes with emergence of a sex-determining gene(s). Subsequently, the newly formed sex chromosomes stop recombination in a small region around the sex-determining locus, and over time, the non-recombining region expands to almost all parts of the sex chromosomes. Accumulation of repetitive sequences, mostly transposable elements and tandem repeats, is a conspicuous feature of the non-recombining region of the Y chromosome, even in primitive one. Repetitive sequences may play multiple roles in sex chromosome evolution, such as triggering heterochromatization and causing recombination suppression, leading to structural and morphological differentiation of sex chromosomes, and promoting Y chromosome degeneration and X chromosome dosage compensation. In this article, we review the current status of this field, and based on preliminary evidence, we posit that repetitive sequences are involved in sex chromosome evolution probably via epigenetic modification, such as DNA and histone methylation, with small interfering RNAs as the mediator.
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Antony, Binu
2015-07-18
Background Insects use pheromones, chemical signals that underlie all animal behaviors, for communication and for attracting mates. Synthetic pheromones are widely used in pest control strategies because they are environmentally safe. The production of insect pheromones in transgenic plants, which could be more economical and effective in producing isomerically pure compounds, has recently been successfully demonstrated. This research requires information regarding the pheromone biosynthetic pathways and the characterization of pheromone biosynthetic enzymes (PBEs). We used Illumina sequencing to characterize the pheromone gland (PG) transcriptome of the Pyralid moth, Ephestia cautella, a destructive storage pest, to reveal putative candidate genes involved in pheromone biosynthesis, release, transport and degradation. Results We isolated the E. cautella pheromone compound as (Z,E)-9,12-tetradecadienyl acetate, and the major pheromone precursors 16:acyl, 14:acyl, E14-16:acyl, E12-14:acyl and Z9,E12-14:acyl. Based on the abundance of precursors, two possible pheromone biosynthetic pathways are proposed. Both pathways initiate from C16:acyl-CoA, with one involving ∆14 and ∆9 desaturation to generate Z9,E12-14:acyl, and the other involving the chain shortening of C16:acyl-CoA to C14:acyl-CoA, followed by ∆12 and ∆9 desaturation to generate Z9,E12-14:acyl-CoA. Then, a final reduction and acetylation generates Z9,E12-14:OAc. Illumina sequencing yielded 83,792 transcripts, and we obtained a PG transcriptome of ~49.5 Mb. A total of 191 PBE transcripts, which included pheromone biosynthesis activating neuropeptides, fatty acid transport proteins, acetyl-CoA carboxylases, fatty acid synthases, desaturases, β-oxidation enzymes, fatty acyl-CoA reductases (FARs) and fatty acetyltransferases (FATs), were selected from the dataset. A comparison of the E. cautella transcriptome data with three other Lepidoptera PG datasets revealed that 45 % of the sequences were shared
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Coding Local and Global Binary Visual Features Extracted From Video Sequences
Baroffio, Luca; Canclini, Antonio; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano
2015-11-01
Binary local features represent an effective alternative to real-valued descriptors, leading to comparable results for many visual analysis tasks, while being characterized by significantly lower computational complexity and memory requirements. When dealing with large collections, a more compact representation based on global features is often preferred, which can be obtained from local features by means of, e.g., the Bag-of-Visual-Word (BoVW) model. Several applications, including for example visual sensor networks and mobile augmented reality, require visual features to be transmitted over a bandwidth-limited network, thus calling for coding techniques that aim at reducing the required bit budget, while attaining a target level of efficiency. In this paper we investigate a coding scheme tailored to both local and global binary features, which aims at exploiting both spatial and temporal redundancy by means of intra- and inter-frame coding. In this respect, the proposed coding scheme can be conveniently adopted to support the Analyze-Then-Compress (ATC) paradigm. That is, visual features are extracted from the acquired content, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast with the traditional approach, in which visual content is acquired at a node, compressed and then sent to a central unit for further processing, according to the Compress-Then-Analyze (CTA) paradigm. In this paper we experimentally compare ATC and CTA by means of rate-efficiency curves in the context of two different visual analysis tasks: homography estimation and content-based retrieval. Our results show that the novel ATC paradigm based on the proposed coding primitives can be competitive with CTA, especially in bandwidth limited scenarios.
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Spatio-temporal features for tracking and quadruped/biped discrimination
Rickman, Rick; Copsey, Keith; Bamber, David C.; Page, Scott F.
2012-05-01
Techniques such as SIFT and SURF facilitate efficient and robust image processing operations through the use of sparse and compact spatial feature descriptors and show much potential for defence and security applications. This paper considers the extension of such techniques to include information from the temporal domain, to improve utility in applications involving moving imagery within video data. In particular, the paper demonstrates how spatio-temporal descriptors can be used very effectively as the basis of a target tracking system and as target discriminators which can distinguish between bipeds and quadrupeds. Results using sequences of video imagery of walking humans and dogs are presented, and the relative merits of the approach are discussed.
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He, Xueying; Wang, Huan; Yang, Jinfen; Deng, Ke; Wang, Teng
2018-02-01
Amomum villosum Lour. is an important Chinese medicinal plant that has diverse medicinal functions, and mainly contains volatile terpenes. This study aims to explore the WRKY transcription factors (TFs) and terpene synthase (TPS) unigenes that might be involved in terpene biosynthesis in A. villosum, and thus providing some new information on the regulation of terpenes in plants. RNA sequencing of A. villosum induced by methyl jasmonate (MeJA) revealed that the WRKY family was the second largest TF family in the transcriptome. Thirty-six complete WRKY domain sequences were expressed in response to MeJA. Further, six WRKY unigenes were highly correlated with eight deduced TPS unigenes. Ultimately, we combined the terpene abundance with the expression of candidate WRKY TFs and TPS unigenes to presume a possible model wherein AvWRKY61, AvWRKY28, and AvWRKY40 might coordinately trans-activate the AvNeoD promoter. We propose an approach to further investigate TF unigenes that might be involved in terpenoid biosynthesis, and identified four unigenes for further analyses.
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Coding Local and Global Binary Visual Features Extracted From Video Sequences.
Baroffio, Luca; Canclini, Antonio; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano
2015-11-01
Binary local features represent an effective alternative to real-valued descriptors, leading to comparable results for many visual analysis tasks while being characterized by significantly lower computational complexity and memory requirements. When dealing with large collections, a more compact representation based on global features is often preferred, which can be obtained from local features by means of, e.g., the bag-of-visual word model. Several applications, including, for example, visual sensor networks and mobile augmented reality, require visual features to be transmitted over a bandwidth-limited network, thus calling for coding techniques that aim at reducing the required bit budget while attaining a target level of efficiency. In this paper, we investigate a coding scheme tailored to both local and global binary features, which aims at exploiting both spatial and temporal redundancy by means of intra- and inter-frame coding. In this respect, the proposed coding scheme can conveniently be adopted to support the analyze-then-compress (ATC) paradigm. That is, visual features are extracted from the acquired content, encoded at remote nodes, and finally transmitted to a central controller that performs the visual analysis. This is in contrast with the traditional approach, in which visual content is acquired at a node, compressed and then sent to a central unit for further processing, according to the compress-then-analyze (CTA) paradigm. In this paper, we experimentally compare the ATC and the CTA by means of rate-efficiency curves in the context of two different visual analysis tasks: 1) homography estimation and 2) content-based retrieval. Our results show that the novel ATC paradigm based on the proposed coding primitives can be competitive with the CTA, especially in bandwidth limited scenarios.
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Templated sequence insertion polymorphisms in the human genome
Onozawa, Masahiro; Aplan, Peter
2016-11-01
Templated Sequence Insertion Polymorphism (TSIP) is a recently described form of polymorphism recognized in the human genome, in which a sequence that is templated from a distant genomic region is inserted into the genome, seemingly at random. TSIPs can be grouped into two classes based on nucleotide sequence features at the insertion junctions; Class 1 TSIPs show features of insertions that are mediated via the LINE-1 ORF2 protein, including 1) target-site duplication (TSD), 2) polyadenylation 10-30 nucleotides downstream of a “cryptic” polyadenylation signal, and 3) preference for insertion at a 5’-TTTT/A-3’ sequence. In contrast, class 2 TSIPs show features consistent with repair of a DNA double-strand break via insertion of a DNA “patch” that is derived from a distant genomic region. Survey of a large number of normal human volunteers demonstrates that most individuals have 25-30 TSIPs, and that these TSIPs track with specific geographic regions. Similar to other forms of human polymorphism, we suspect that these TSIPs may be important for the generation of human diversity and genetic diseases.
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Insight into Potential Probiotic Markers Predicted in Lactobacillus pentosus MP-10 Genome Sequence
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Hikmate Abriouel
2017-05-01
Full Text Available Lactobacillus pentosus MP-10 is a potential probiotic lactic acid bacterium originally isolated from naturally fermented Aloreña green table olives. The entire genome sequence was annotated to in silico analyze the molecular mechanisms involved in the adaptation of L. pentosus MP-10 to the human gastrointestinal tract (GIT, such as carbohydrate metabolism (related with prebiotic utilization and the proteins involved in bacteria–host interactions. We predicted an arsenal of genes coding for carbohydrate-modifying enzymes to modify oligo- and polysaccharides, such as glycoside hydrolases, glycoside transferases, and isomerases, and other enzymes involved in complex carbohydrate metabolism especially starch, raffinose, and levan. These enzymes represent key indicators of the bacteria’s adaptation to the GIT environment, since they involve the metabolism and assimilation of complex carbohydrates not digested by human enzymes. We also detected key probiotic ligands (surface proteins, excreted or secreted proteins involved in the adhesion to host cells such as adhesion to mucus, epithelial cells or extracellular matrix, and plasma components; also, moonlighting proteins or multifunctional proteins were found that could be involved in adhesion to epithelial cells and/or extracellular matrix proteins and also affect host immunomodulation. In silico analysis of the genome sequence of L. pentosus MP-10 is an important initial step to screen for genes encoding for proteins that may provide probiotic features, and thus provides one new routes for screening and studying this potentially probiotic bacterium.
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Hand and wrist involvement in systemic sclerosis: US features.
Freire, Véronique; Bazeli, Ramin; Elhai, Muriel; Campagna, Raphaël; Pessis, Éric; Avouac, Jérôme; Allanore, Yannick; Drapé, Jean-Luc; Guérini, Henri
2013-12-01
To characterize ultrasonographic (US) features in the hand of patients with systemic sclerosis (SSc) and to evaluate the sensitivity of US in the detection of calcinosis and acroosteolysis. The local ethics committee approved this study, and oral informed consent was obtained. A total of 44 consecutive patients with SSc (34 women; mean age, 56.1 years ± 12.1 [standard deviation]; 10 men; mean age, 45.0 years ± 14.0) and 30 healthy control subjects (20 women; mean age, 46.3 years ± 12.1; 10 men; mean age, 39.6 years ± 10.8) were included between October 2010 and December 2011. Bilateral US, including Doppler assessment of the wrists, hands, and fingers, was performed, and presence of synovitis, tenosynovitis with or without a layered appearance, calcifications, acroosteolysis, and distal vascularization was recorded. Radiography of both hands was performed to assess for acroosteolysis and calcinosis. Frequency of US features, sensitivity of US for calcinosis and acroosteolysis, and respective confidence intervals were calculated. Synovitis was found in 17 patients (39%). Tenosynovitis was found in 12 patients (27%), and it had a layered pattern in 15 (41%) of 37 cases. Calcinosis was found in 17 patients (39%) with US, with a sensitivity of 89%. Acroosteolysis was found in nine (20%) patients with US and in 10 (23%) patients with radiography, with 90% sensitivity for US. Distal vascularization was detected in 26 patients (59%) and 30 control subjects (100%) and was in contact with the acroosteolysis bed in seven (78%) of nine patients with SSc. US can be used to assess features of SSc, including synovitis, tenosynovitis, calcinosis, acroosteolysis, and distal vascularization and is sensitive for calcinosis and acroosteolysis detection. A layered pattern (similar to the appearance of an artichoke heart) of tenosynovitis was seen commonly. Online supplemental material is available for this article. © RSNA, 2013.
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O'Rahilly, R; Müller, F; Hutchins, G M; Moore, G W
1987-09-01
The sequence of events in the development of the brain in human embryos, already published for stages 8-15, is here continued for stages 16 and 17. With the aid of a computerized bubble-sort algorithm, 71 individual embryos were ranked in ascending order of the features present. Whereas these numbered 100 in the previous study, the increasing structural complexity gave 27 new features in the two stages now under investigation. The chief characteristics of stage 16 (approximately 37 postovulatory days) are protruding basal nuclei, the caudal olfactory elevation (olfactory tubercle), the tectobulbar tracts, and ascending fibers to the cerebellum. The main features of stage 17 (approximately 41 postovulatory days) are the cortical nucleus of the amygdaloid body, an intermediate layer in the tectum mesencephali, the posterior commissure, and the habenulo-interpeduncular tract. In addition, a typical feature at stage 17 is the crescentic shape of the lens cavity.
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Recurrence time statistics: versatile tools for genomic DNA sequence analysis.
Cao, Yinhe; Tung, Wen-Wen; Gao, J B
2004-01-01
With the completion of the human and a few model organisms' genomes, and the genomes of many other organisms waiting to be sequenced, it has become increasingly important to develop faster computational tools which are capable of easily identifying the structures and extracting features from DNA sequences. One of the more important structures in a DNA sequence is repeat-related. Often they have to be masked before protein coding regions along a DNA sequence are to be identified or redundant expressed sequence tags (ESTs) are to be sequenced. Here we report a novel recurrence time based method for sequence analysis. The method can conveniently study all kinds of periodicity and exhaustively find all repeat-related features from a genomic DNA sequence. An efficient codon index is also derived from the recurrence time statistics, which has the salient features of being largely species-independent and working well on very short sequences. Efficient codon indices are key elements of successful gene finding algorithms, and are particularly useful for determining whether a suspected EST belongs to a coding or non-coding region. We illustrate the power of the method by studying the genomes of E. coli, the yeast S. cervisivae, the nematode worm C. elegans, and the human, Homo sapiens. Computationally, our method is very efficient. It allows us to carry out analysis of genomes on the whole genomic scale by a PC.
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Feature curve extraction from point clouds via developable strip intersection
Directory of Open Access Journals (Sweden)
Kai Wah Lee
2016-04-01
Full Text Available In this paper, we study the problem of computing smooth feature curves from CAD type point clouds models. The proposed method reconstructs feature curves from the intersections of developable strip pairs which approximate the regions along both sides of the features. The generation of developable surfaces is based on a linear approximation of the given point cloud through a variational shape approximation approach. A line segment sequencing algorithm is proposed for collecting feature line segments into different feature sequences as well as sequential groups of data points. A developable surface approximation procedure is employed to refine incident approximation planes of data points into developable strips. Some experimental results are included to demonstrate the performance of the proposed method.
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Tools for integrated sequence-structure analysis with UCSF Chimera
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Huang Conrad C
2006-07-01
Full Text Available Abstract Background Comparing related structures and viewing the structures in the context of sequence alignments are important tasks in protein structure-function research. While many programs exist for individual aspects of such work, there is a need for interactive visualization tools that: (a provide a deep integration of sequence and structure, far beyond mapping where a sequence region falls in the structure and vice versa; (b facilitate changing data of one type based on the other (for example, using only sequence-conserved residues to match structures, or adjusting a sequence alignment based on spatial fit; (c can be used with a researcher's own data, including arbitrary sequence alignments and annotations, closely or distantly related sets of proteins, etc.; and (d interoperate with each other and with a full complement of molecular graphics features. We describe enhancements to UCSF Chimera to achieve these goals. Results The molecular graphics program UCSF Chimera includes a suite of tools for interactive analyses of sequences and structures. Structures automatically associate with sequences in imported alignments, allowing many kinds of crosstalk. A novel method is provided to superimpose structures in the absence of a pre-existing sequence alignment. The method uses both sequence and secondary structure, and can match even structures with very low sequence identity. Another tool constructs structure-based sequence alignments from superpositions of two or more proteins. Chimera is designed to be extensible, and mechanisms for incorporating user-specific data without Chimera code development are also provided. Conclusion The tools described here apply to many problems involving comparison and analysis of protein structures and their sequences. Chimera includes complete documentation and is intended for use by a wide range of scientists, not just those in the computational disciplines. UCSF Chimera is free for non-commercial use and is
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Directory of Open Access Journals (Sweden)
Sian Liu
2017-11-01
Full Text Available The passion fruit (Passiflora edulis Sims, also known as the purple granadilla, is widely cultivated as the new darling of the fruit market throughout southern China. This exotic and perennial climber is adapted to warm and humid climates, and thus is generally intolerant of cold. There is limited information about gene regulation and signaling pathways related to the cold stress response in this species. In this study, two transcriptome libraries (KEDU_AP vs. GX_AP were constructed from the aerial parts of cold-tolerant and cold-susceptible varieties of P. edulis, respectively. Overall, 126,284,018 clean reads were obtained, and 86,880 unigenes with a mean size of 1449 bp were assembled. Of these, there were 64,067 (73.74% unigenes with significant similarity to publicly available plant protein sequences. Expression profiles were generated, and 3045 genes were found to be significantly differentially expressed between the KEDU_AP and GX_AP libraries, including 1075 (35.3% up-regulated and 1970 (64.7% down-regulated. These included 36 genes in enriched pathways of plant hormone signal transduction, and 56 genes encoding putative transcription factors. Six genes involved in the ICE1–CBF–COR pathway were induced in the cold-tolerant variety, and their expression levels were further verified using quantitative real-time PCR. This report is the first to identify genes and signaling pathways involved in cold tolerance using high-throughput transcriptome sequencing in P. edulis. These findings may provide useful insights into the molecular mechanisms regulating cold tolerance and genetic breeding in Passiflora spp.
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Directory of Open Access Journals (Sweden)
Roepcke Stefan
2011-12-01
Full Text Available Abstract Background Bioinformatic analyses of expression control sequences in promoters of co-expressed or functionally related genes enable the discovery of common regulatory sequence motifs that might be involved in co-ordinated gene expression. By studying promoter sequences of the human ribosomal protein genes we recently identified a novel highly specific Localized Tandem Sequence Motif (LTSM. In this work we sought to identify additional genes and LTSM-binding proteins to elucidate potential regulatory mechanisms. Results Genome-wide analyses allowed finding a considerable number of additional LTSM-positive genes, the products of which are involved in translation, among them, translation initiation and elongation factors, and 5S rRNA. Electromobility shift assays then showed specific signals demonstrating the binding of protein complexes to LTSM in ribosomal protein gene promoters. Pull-down assays with LTSM-containing oligonucleotides and subsequent mass spectrometric analysis identified the related multifunctional nucleotide binding proteins NonO and SFPQ in the binding complex. Functional characterization then revealed that LTSM enhances the transcriptional activity of the promoters in dependency of the distance from the transcription start site. Conclusions Our data demonstrate the power of bioinformatic analyses for the identification of biologically relevant sequence motifs. LTSM and the here found LTSM-binding proteins NonO and SFPQ were discovered through a synergistic combination of bioinformatic and biochemical methods and are regulators of the expression of a set of genes of the translational apparatus in a distance-dependent manner.
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Multimodal emotional state recognition using sequence-dependent deep hierarchical features.
Barros, Pablo; Jirak, Doreen; Weber, Cornelius; Wermter, Stefan
2015-12-01
Emotional state recognition has become an important topic for human-robot interaction in the past years. By determining emotion expressions, robots can identify important variables of human behavior and use these to communicate in a more human-like fashion and thereby extend the interaction possibilities. Human emotions are multimodal and spontaneous, which makes them hard to be recognized by robots. Each modality has its own restrictions and constraints which, together with the non-structured behavior of spontaneous expressions, create several difficulties for the approaches present in the literature, which are based on several explicit feature extraction techniques and manual modality fusion. Our model uses a hierarchical feature representation to deal with spontaneous emotions, and learns how to integrate multiple modalities for non-verbal emotion recognition, making it suitable to be used in an HRI scenario. Our experiments show that a significant improvement of recognition accuracy is achieved when we use hierarchical features and multimodal information, and our model improves the accuracy of state-of-the-art approaches from 82.5% reported in the literature to 91.3% for a benchmark dataset on spontaneous emotion expressions. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
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Temporal Feature Integration for Music Organisation
DEFF Research Database (Denmark)
Meng, Anders
2006-01-01
This Ph.D. thesis focuses on temporal feature integration for music organisation. Temporal feature integration is the process of combining all the feature vectors of a given time-frame into a single new feature vector in order to capture relevant information in the frame. Several existing methods...... for handling sequences of features are formulated in the temporal feature integration framework. Two datasets for music genre classification have been considered as valid test-beds for music organisation. Human evaluations of these, have been obtained to access the subjectivity on the datasets. Temporal...... ranking' approach is proposed for ranking the short-time features at larger time-scales according to their discriminative power in a music genre classification task. The multivariate AR (MAR) model has been proposed for temporal feature integration. It effectively models local dynamical structure...
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Hsi, Andy C; Kreisel, Friederike H; Frater, John L; Nguyen, TuDung T
2014-02-01
Human T-cell lymphotropic virus type 1 is associated with adult T-cell leukemia/lymphoma (ATLL). Published series of ATLLs seen at a United States medical institution are rare. We present the features of 4 ATLLs diagnosed at our North American tertiary care medical center from 1990 to 2012. Despite the absence of a history of origin from an endemic region, all our ATLLs demonstrated evidence of human T-cell lymphotropic virus type 1 infection. Central nervous system (CNS) involvement by ATLL was uncommon in our series, and represented only 1.6% (1/64) of all CNS B-cell or T-cell lymphomas diagnosed over a 20+ year period at our institution. Review of the medical literature reveals that the majority of CNS-involved ATLLs present with the lymphoma or acute subtype, and complete remission is difficult to achieve in these cases. CNS involvement frequently occurs with a systemic disease, which carries an aggressive clinical course with poor prognosis. In addition, CNS involvement by ATLL can be the initial presentation or seen with relapsed disease, can be the only site or be associated with other tissue sites of involvement, and may manifest with variable clinical signs/symptoms. Our retrospective study reveals that ATLLs are rare mature T-cell lymphomas in a native North American population, but the clinical and histopathologic features of ATLLs from this nonendemic region are similar to those seen from other endemic regions. Early recognition of these rare ATLLs involving uncommon sites, such as the CNS, will help optimize treatment for these infrequent mature T-cell lymphomas.
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Directory of Open Access Journals (Sweden)
Yunyun Liang
2015-01-01
Full Text Available Prediction of protein structural classes for low-similarity sequences is useful for understanding fold patterns, regulation, functions, and interactions of proteins. It is well known that feature extraction is significant to prediction of protein structural class and it mainly uses protein primary sequence, predicted secondary structure sequence, and position-specific scoring matrix (PSSM. Currently, prediction solely based on the PSSM has played a key role in improving the prediction accuracy. In this paper, we propose a novel method called CSP-SegPseP-SegACP by fusing consensus sequence (CS, segmented PsePSSM, and segmented autocovariance transformation (ACT based on PSSM. Three widely used low-similarity datasets (1189, 25PDB, and 640 are adopted in this paper. Then a 700-dimensional (700D feature vector is constructed and the dimension is decreased to 224D by using principal component analysis (PCA. To verify the performance of our method, rigorous jackknife cross-validation tests are performed on 1189, 25PDB, and 640 datasets. Comparison of our results with the existing PSSM-based methods demonstrates that our method achieves the favorable and competitive performance. This will offer an important complementary to other PSSM-based methods for prediction of protein structural classes for low-similarity sequences.
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Cystic angiomatosis with splenic involvement: unusual MRI findings
Energy Technology Data Exchange (ETDEWEB)
Vanhoenacker, F.M. [Dept. of Radiology, Univ. Hospital Antwerp, Edegem (Belgium); Dept. of Radiology, AZ St-Maarten, Campus Duffel, Duffel (Belgium); Schepper, A.M. [Dept. of Radiology, Univ. Hospital Antwerp, Edegem (Belgium); Raeve, H. [Dept. of Pathology, Univ. Hospital Antwerp, Edegem (Belgium); Berneman, Z. [Dept. of Hematology, Univ. Hospital Antwerp, Edegem (Belgium)
2003-12-01
Cystic angiomatosis is a rare disorder with a poor prognosis. We describe a case of a 33-year-old woman who presented with longstanding bone pain, hemolytic anemia, and an enlarged spleen. Radiologically, multiple osseous lesions with a mixed pattern of lytic and sclerotic areas were seen within the shoulders, spine, and pelvis. On CT and MRI of the abdomen, the spleen was markedly enlarged, with internal hyperdense foci on non-contrast CT scan, corresponding to low signal intensity areas on all MR pulse sequences. After administration of contrast, a mottled enhancement pattern throughout the entire spleen was seen both on CT and MRI. Cystic angiomatosis was proven by histological analysis of a biopsy specimen of an involved vertebra and histopathological examination of the spleen after subsequent splenectomy. This is the first report of a patient with disseminated cystic angiomatosis with splenic involvement in which the MRI features differ from the previous reports. Instead of the usual pattern consisting of multiple well-defined cystic lesions, a diffuse involvement replacing the entire spleen, with heterogeneous signal intensities on T2-weighted images and heterogeneous enhancement pattern, was seen in our patient. (orig.)
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Cystic angiomatosis with splenic involvement: unusual MRI findings
International Nuclear Information System (INIS)
Vanhoenacker, F.M.; Schepper, A.M.; Raeve, H.; Berneman, Z.
2003-01-01
Cystic angiomatosis is a rare disorder with a poor prognosis. We describe a case of a 33-year-old woman who presented with longstanding bone pain, hemolytic anemia, and an enlarged spleen. Radiologically, multiple osseous lesions with a mixed pattern of lytic and sclerotic areas were seen within the shoulders, spine, and pelvis. On CT and MRI of the abdomen, the spleen was markedly enlarged, with internal hyperdense foci on non-contrast CT scan, corresponding to low signal intensity areas on all MR pulse sequences. After administration of contrast, a mottled enhancement pattern throughout the entire spleen was seen both on CT and MRI. Cystic angiomatosis was proven by histological analysis of a biopsy specimen of an involved vertebra and histopathological examination of the spleen after subsequent splenectomy. This is the first report of a patient with disseminated cystic angiomatosis with splenic involvement in which the MRI features differ from the previous reports. Instead of the usual pattern consisting of multiple well-defined cystic lesions, a diffuse involvement replacing the entire spleen, with heterogeneous signal intensities on T2-weighted images and heterogeneous enhancement pattern, was seen in our patient. (orig.)
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A feature-based approach to modeling protein-DNA interactions.
Directory of Open Access Journals (Sweden)
Eilon Sharon
Full Text Available Transcription factor (TF binding to its DNA target site is a fundamental regulatory interaction. The most common model used to represent TF binding specificities is a position specific scoring matrix (PSSM, which assumes independence between binding positions. However, in many cases, this simplifying assumption does not hold. Here, we present feature motif models (FMMs, a novel probabilistic method for modeling TF-DNA interactions, based on log-linear models. Our approach uses sequence features to represent TF binding specificities, where each feature may span multiple positions. We develop the mathematical formulation of our model and devise an algorithm for learning its structural features from binding site data. We also developed a discriminative motif finder, which discovers de novo FMMs that are enriched in target sets of sequences compared to background sets. We evaluate our approach on synthetic data and on the widely used TF chromatin immunoprecipitation (ChIP dataset of Harbison et al. We then apply our algorithm to high-throughput TF ChIP data from mouse and human, reveal sequence features that are present in the binding specificities of mouse and human TFs, and show that FMMs explain TF binding significantly better than PSSMs. Our FMM learning and motif finder software are available at http://genie.weizmann.ac.il/.
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Sequencing Events: Exploring Art and Art Jobs.
Stephens, Pamela Geiger; Shaddix, Robin K.
2000-01-01
Presents an activity for upper-elementary students that correlates the actions of archaeologists, patrons, and artists with the sequencing of events in a logical order. Features ancient Egyptian art images. Discusses the preparation of materials, motivation, a pre-writing activity, and writing a story in sequence. (CMK)
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TagDust2: a generic method to extract reads from sequencing data.
Lassmann, Timo
2015-01-28
Arguably the most basic step in the analysis of next generation sequencing data (NGS) involves the extraction of mappable reads from the raw reads produced by sequencing instruments. The presence of barcodes, adaptors and artifacts subject to sequencing errors makes this step non-trivial. Here I present TagDust2, a generic approach utilizing a library of hidden Markov models (HMM) to accurately extract reads from a wide array of possible read architectures. TagDust2 extracts more reads of higher quality compared to other approaches. Processing of multiplexed single, paired end and libraries containing unique molecular identifiers is fully supported. Two additional post processing steps are included to exclude known contaminants and filter out low complexity sequences. Finally, TagDust2 can automatically detect the library type of sequenced data from a predefined selection. Taken together TagDust2 is a feature rich, flexible and adaptive solution to go from raw to mappable NGS reads in a single step. The ability to recognize and record the contents of raw reads will help to automate and demystify the initial, and often poorly documented, steps in NGS data analysis pipelines. TagDust2 is freely available at: http://tagdust.sourceforge.net .
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Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset
Liu, Qiaoyuan; Wang, Yuru; Yin, Minghao; Ren, Jinchang; Li, Ruizhi
2017-11-01
Although various visual tracking algorithms have been proposed in the last 2-3 decades, it remains a challenging problem for effective tracking with fast motion, deformation, occlusion, etc. Under complex tracking conditions, most tracking models are not discriminative and adaptive enough. When the combined feature vectors are inputted to the visual models, this may lead to redundancy causing low efficiency and ambiguity causing poor performance. An effective tracking algorithm is proposed to decontaminate features for each video sequence adaptively, where the visual modeling is treated as an optimization problem from the perspective of evolution. Every feature vector is compared to a biological individual and then decontaminated via classical evolutionary algorithms. With the optimized subsets of features, the "curse of dimensionality" has been avoided while the accuracy of the visual model has been improved. The proposed algorithm has been tested on several publicly available datasets with various tracking challenges and benchmarked with a number of state-of-the-art approaches. The comprehensive experiments have demonstrated the efficacy of the proposed methodology.
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Directory of Open Access Journals (Sweden)
N Lance Hepler
2014-09-01
Full Text Available Since its identification in 1983, HIV-1 has been the focus of a research effort unprecedented in scope and difficulty, whose ultimate goals--a cure and a vaccine--remain elusive. One of the fundamental challenges in accomplishing these goals is the tremendous genetic variability of the virus, with some genes differing at as many as 40% of nucleotide positions among circulating strains. Because of this, the genetic bases of many viral phenotypes, most notably the susceptibility to neutralization by a particular antibody, are difficult to identify computationally. Drawing upon open-source general-purpose machine learning algorithms and libraries, we have developed a software package IDEPI (IDentify EPItopes for learning genotype-to-phenotype predictive models from sequences with known phenotypes. IDEPI can apply learned models to classify sequences of unknown phenotypes, and also identify specific sequence features which contribute to a particular phenotype. We demonstrate that IDEPI achieves performance similar to or better than that of previously published approaches on four well-studied problems: finding the epitopes of broadly neutralizing antibodies (bNab, determining coreceptor tropism of the virus, identifying compartment-specific genetic signatures of the virus, and deducing drug-resistance associated mutations. The cross-platform Python source code (released under the GPL 3.0 license, documentation, issue tracking, and a pre-configured virtual machine for IDEPI can be found at https://github.com/veg/idepi.
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Directory of Open Access Journals (Sweden)
Tianyuan Zhang
2017-11-01
Full Text Available Perilla frutescen is used as traditional food and medicine in East Asia. Its seeds contain high levels of α-linolenic acid (ALA, which is important for health, but is scarce in our daily meals. Previous reports on RNA-seq of perilla seed had identified fatty acid (FA and triacylglycerol (TAG synthesis genes, but the underlying mechanism of ALA biosynthesis and its regulation still need to be further explored. So we conducted Illumina RNA-sequencing in seven temporal developmental stages of perilla seeds. Sequencing generated a total of 127 million clean reads, containing 15.88 Gb of valid data. The de novo assembly of sequence reads yielded 64,156 unigenes with an average length of 777 bp. A total of 39,760 unigenes were annotated and 11,693 unigenes were found to be differentially expressed in all samples. According to Kyoto Encyclopedia of Genes and Genomes (KEGG pathway analysis, 486 unigenes were annotated in the “lipid metabolism” pathway. Of these, 150 unigenes were found to be involved in fatty acid (FA biosynthesis and triacylglycerol (TAG assembly in perilla seeds. A coexpression analysis showed that a total of 104 genes were highly coexpressed (r > 0.95. The coexpression network could be divided into two main subnetworks showing over expression in the medium or earlier and late phases, respectively. In order to identify the putative regulatory genes, a transcription factor (TF analysis was performed. This led to the identification of 45 gene families, mainly including the AP2-EREBP, bHLH, MYB, and NAC families, etc. After coexpression analysis of TFs with highly expression of FAD2 and FAD3 genes, 162 TFs were found to be significantly associated with two FAD genes (r > 0.95. Those TFs were predicted to be the key regulatory factors in ALA biosynthesis in perilla seed. The qRT-PCR analysis also verified the relevance of expression pattern between two FAD genes and partial candidate TFs. Although it has been reported that some TFs
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Directory of Open Access Journals (Sweden)
Bent Petersen
Full Text Available UNLABELLED: β-turns are the most common type of non-repetitive structures, and constitute on average 25% of the amino acids in proteins. The formation of β-turns plays an important role in protein folding, protein stability and molecular recognition processes. In this work we present the neural network method NetTurnP, for prediction of two-class β-turns and prediction of the individual β-turn types, by use of evolutionary information and predicted protein sequence features. It has been evaluated against a commonly used dataset BT426, and achieves a Matthews correlation coefficient of 0.50, which is the highest reported performance on a two-class prediction of β-turn and not-β-turn. Furthermore NetTurnP shows improved performance on some of the specific β-turn types. In the present work, neural network methods have been trained to predict β-turn or not and individual β-turn types from the primary amino acid sequence. The individual β-turn types I, I', II, II', VIII, VIa1, VIa2, VIba and IV have been predicted based on classifications by PROMOTIF, and the two-class prediction of β-turn or not is a superset comprised of all β-turn types. The performance is evaluated using a golden set of non-homologous sequences known as BT426. Our two-class prediction method achieves a performance of: MCC=0.50, Qtotal=82.1%, sensitivity=75.6%, PPV=68.8% and AUC=0.864. We have compared our performance to eleven other prediction methods that obtain Matthews correlation coefficients in the range of 0.17-0.47. For the type specific β-turn predictions, only type I and II can be predicted with reasonable Matthews correlation coefficients, where we obtain performance values of 0.36 and 0.31, respectively. CONCLUSION: The NetTurnP method has been implemented as a webserver, which is freely available at http://www.cbs.dtu.dk/services/NetTurnP/. NetTurnP is the only available webserver that allows submission of multiple sequences.
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Petersen, Bent; Lundegaard, Claus; Petersen, Thomas Nordahl
2010-11-30
β-turns are the most common type of non-repetitive structures, and constitute on average 25% of the amino acids in proteins. The formation of β-turns plays an important role in protein folding, protein stability and molecular recognition processes. In this work we present the neural network method NetTurnP, for prediction of two-class β-turns and prediction of the individual β-turn types, by use of evolutionary information and predicted protein sequence features. It has been evaluated against a commonly used dataset BT426, and achieves a Matthews correlation coefficient of 0.50, which is the highest reported performance on a two-class prediction of β-turn and not-β-turn. Furthermore NetTurnP shows improved performance on some of the specific β-turn types. In the present work, neural network methods have been trained to predict β-turn or not and individual β-turn types from the primary amino acid sequence. The individual β-turn types I, I', II, II', VIII, VIa1, VIa2, VIba and IV have been predicted based on classifications by PROMOTIF, and the two-class prediction of β-turn or not is a superset comprised of all β-turn types. The performance is evaluated using a golden set of non-homologous sequences known as BT426. Our two-class prediction method achieves a performance of: MCC=0.50, Qtotal=82.1%, sensitivity=75.6%, PPV=68.8% and AUC=0.864. We have compared our performance to eleven other prediction methods that obtain Matthews correlation coefficients in the range of 0.17-0.47. For the type specific β-turn predictions, only type I and II can be predicted with reasonable Matthews correlation coefficients, where we obtain performance values of 0.36 and 0.31, respectively. The NetTurnP method has been implemented as a webserver, which is freely available at http://www.cbs.dtu.dk/services/NetTurnP/. NetTurnP is the only available webserver that allows submission of multiple sequences.
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Directory of Open Access Journals (Sweden)
Takeru Nakazato
Full Text Available High-throughput sequencing technology, also called next-generation sequencing (NGS, has the potential to revolutionize the whole process of genome sequencing, transcriptomics, and epigenetics. Sequencing data is captured in a public primary data archive, the Sequence Read Archive (SRA. As of January 2013, data from more than 14,000 projects have been submitted to SRA, which is double that of the previous year. Researchers can download raw sequence data from SRA website to perform further analyses and to compare with their own data. However, it is extremely difficult to search entries and download raw sequences of interests with SRA because the data structure is complicated, and experimental conditions along with raw sequences are partly described in natural language. Additionally, some sequences are of inconsistent quality because anyone can submit sequencing data to SRA with no quality check. Therefore, as a criterion of data quality, we focused on SRA entries that were cited in journal articles. We extracted SRA IDs and PubMed IDs (PMIDs from SRA and full-text versions of journal articles and retrieved 2748 SRA ID-PMID pairs. We constructed a publication list referring to SRA entries. Since, one of the main themes of -omics analyses is clarification of disease mechanisms, we also characterized SRA entries by disease keywords, according to the Medical Subject Headings (MeSH extracted from articles assigned to each SRA entry. We obtained 989 SRA ID-MeSH disease term pairs, and constructed a disease list referring to SRA data. We previously developed feature profiles of diseases in a system called "Gendoo". We generated hyperlinks between diseases extracted from SRA and the feature profiles of it. The developed project, publication and disease lists resulting from this study are available at our web service, called "DBCLS SRA" (http://sra.dbcls.jp/. This service will improve accessibility to high-quality data from SRA.
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[Complete genome sequencing and sequence analysis of BCG Tice].
Wang, Zhiming; Pan, Yuanlong; Wu, Jun; Zhu, Baoli
2012-10-04
The objective of this study is to obtain the complete genome sequence of Bacillus Calmette-Guerin Tice (BCG Tice), in order to provide more information about the molecular biology of BCG Tice and design more reasonable vaccines to prevent tuberculosis. We assembled the data from high-throughput sequencing with SOAPdenovo software, with many contigs and scaffolds obtained. There are many sequence gaps and physical gaps remained as a result of regional low coverage and low quality. We designed primers at the end of contigs and performed PCR amplification in order to link these contigs and scaffolds. With various enzymes to perform PCR amplification, adjustment of PCR reaction conditions, and combined with clone construction to sequence, all the gaps were finished. We obtained the complete genome sequence of BCG Tice and submitted it to GenBank of National Center for Biotechnology Information (NCBI). The genome of BCG Tice is 4334064 base pairs in length, with GC content 65.65%. The problems and strategies during the finishing step of BCG Tice sequencing are illuminated here, with the hope of affording some experience to those who are involved in the finishing step of genome sequencing. The microarray data were verified by our results.
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Loucif, Lotfi; Kassah-Laouar, Ahmed; Saidi, Mahdia; Messala, Amina; Chelaghma, Widad; Rolain, Jean-Marc
2016-12-01
Seven nonredundant ertapenem-resistant Klebsiella pneumoniae isolates were collected between May 2014 and 19 January 2015 in the nephrology and hematology units of Batna University Hospital in Algeria. All strains coproduced the bla OXA-48 , bla CTX-M-15 , bla SHV-1 , and bla TEM-1D genes. Six of these isolates belonged to the pandemic clone sequence type 101 (ST101). The bla OXA-48 gene was located on a conjugative IncL/M-type plasmid. This is the first known outbreak of OXA-48-producing K. pneumoniae isolates involving an ST101 clone in Batna University Hospital. Copyright © 2016, American Society for Microbiology. All Rights Reserved.
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Protecting genomic sequence anonymity with generalization lattices.
Malin, B A
2005-01-01
Current genomic privacy technologies assume the identity of genomic sequence data is protected if personal information, such as demographics, are obscured, removed, or encrypted. While demographic features can directly compromise an individual's identity, recent research demonstrates such protections are insufficient because sequence data itself is susceptible to re-identification. To counteract this problem, we introduce an algorithm for anonymizing a collection of person-specific DNA sequences. The technique is termed DNA lattice anonymization (DNALA), and is based upon the formal privacy protection schema of k -anonymity. Under this model, it is impossible to observe or learn features that distinguish one genetic sequence from k-1 other entries in a collection. To maximize information retained in protected sequences, we incorporate a concept generalization lattice to learn the distance between two residues in a single nucleotide region. The lattice provides the most similar generalized concept for two residues (e.g. adenine and guanine are both purines). The method is tested and evaluated with several publicly available human population datasets ranging in size from 30 to 400 sequences. Our findings imply the anonymization schema is feasible for the protection of sequences privacy. The DNALA method is the first computational disclosure control technique for general DNA sequences. Given the computational nature of the method, guarantees of anonymity can be formally proven. There is room for improvement and validation, though this research provides the groundwork from which future researchers can construct genomics anonymization schemas tailored to specific datasharing scenarios.
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SPiCE : A web-based tool for sequence-based protein classification and exploration
Van den Berg, B.A.; Reinders, M.J.; Roubos, J.A.; De Ridder, D.
2014-01-01
Background Amino acid sequences and features extracted from such sequences have been used to predict many protein properties, such as subcellular localization or solubility, using classifier algorithms. Although software tools are available for both feature extraction and classifier construction,
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Directory of Open Access Journals (Sweden)
Crespo Andre LB
2009-06-01
Full Text Available Abstract Background Lepidoptera represents more than 160,000 insect species which include some of the most devastating pests of crops, forests, and stored products. However, the genomic information on lepidopteran insects is very limited. Only a few studies have focused on developing expressed sequence tag (EST libraries from the guts of lepidopteran larvae. Knowledge of the genes that are expressed in the insect gut are crucial for understanding basic physiology of food digestion, their interactions with Bacillus thuringiensis (Bt toxins, and for discovering new targets for novel toxins for use in pest management. This study analyzed the ESTs generated from the larval gut of the European corn borer (ECB, Ostrinia nubilalis, one of the most destructive pests of corn in North America and the western world. Our goals were to establish an ECB larval gut-specific EST database as a genomic resource for future research and to explore candidate genes potentially involved in insect-Bt interactions and Bt resistance in ECB. Results We constructed two cDNA libraries from the guts of the fifth-instar larvae of ECB and sequenced a total of 15,000 ESTs from these libraries. A total of 12,519 ESTs (83.4% appeared to be high quality with an average length of 656 bp. These ESTs represented 2,895 unique sequences, including 1,738 singletons and 1,157 contigs. Among the unique sequences, 62.7% encoded putative proteins that shared significant sequence similarities (E-value ≤ 10-3with the sequences available in GenBank. Our EST analysis revealed 52 candidate genes that potentially have roles in Bt toxicity and resistance. These genes encode 18 trypsin-like proteases, 18 chymotrypsin-like proteases, 13 aminopeptidases, 2 alkaline phosphatases and 1 cadherin-like protein. Comparisons of expression profiles of 41 selected candidate genes between Cry1Ab-susceptible and resistant strains of ECB by RT-PCR showed apparently decreased expressions in 2 trypsin-like and 2
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Feature-Based and String-Based Models for Predicting RNA-Protein Interaction
Directory of Open Access Journals (Sweden)
Donald Adjeroh
2018-03-01
Full Text Available In this work, we study two approaches for the problem of RNA-Protein Interaction (RPI. In the first approach, we use a feature-based technique by combining extracted features from both sequences and secondary structures. The feature-based approach enhanced the prediction accuracy as it included much more available information about the RNA-protein pairs. In the second approach, we apply search algorithms and data structures to extract effective string patterns for prediction of RPI, using both sequence information (protein and RNA sequences, and structure information (protein and RNA secondary structures. This led to different string-based models for predicting interacting RNA-protein pairs. We show results that demonstrate the effectiveness of the proposed approaches, including comparative results against leading state-of-the-art methods.
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Sequence embedding for fast construction of guide trees for multiple sequence alignment
LENUS (Irish Health Repository)
Blackshields, Gordon
2010-05-14
Abstract Background The most widely used multiple sequence alignment methods require sequences to be clustered as an initial step. Most sequence clustering methods require a full distance matrix to be computed between all pairs of sequences. This requires memory and time proportional to N 2 for N sequences. When N grows larger than 10,000 or so, this becomes increasingly prohibitive and can form a significant barrier to carrying out very large multiple alignments. Results In this paper, we have tested variations on a class of embedding methods that have been designed for clustering large numbers of complex objects where the individual distance calculations are expensive. These methods involve embedding the sequences in a space where the similarities within a set of sequences can be closely approximated without having to compute all pair-wise distances. Conclusions We show how this approach greatly reduces computation time and memory requirements for clustering large numbers of sequences and demonstrate the quality of the clusterings by benchmarking them as guide trees for multiple alignment. Source code is available for download from http:\\/\\/www.clustal.org\\/mbed.tgz.
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O'Rahilly, R; Müller, F; Hutchins, G M; Moore, G W
1984-11-01
The sequence of events in the development of the brain in staged human embryos was investigated in much greater detail than in previous studies by listing 100 features in 165 embryos of the first 5 weeks. Using a computerized bubble-sort algorithm, individual embryos were ranked in ascending order of the features present. This procedure made feasible an appreciation of the slight variation found in the developmental features. The vast majority of features appeared during either one or two stages (about 2 or 3 days). In general, the soundness of the Carnegie system of embryonic staging was amply confirmed. The rhombencephalon was found to show increasing complexity around stage 13, and the postoptic portion of the diencephalon underwent considerable differentiation by stage 15. The need for similar investigations of other systems of the body is emphasized, and the importance of such studies in assessing the timing of congenital malformations and in clarifying syndromic clusters is suggested.
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Directory of Open Access Journals (Sweden)
Chandrasekhar Natarajan
2015-12-01
Full Text Available A fundamental question in evolutionary genetics concerns the extent to which adaptive phenotypic convergence is attributable to convergent or parallel changes at the molecular sequence level. Here we report a comparative analysis of hemoglobin (Hb function in eight phylogenetically replicated pairs of high- and low-altitude waterfowl taxa to test for convergence in the oxygenation properties of Hb, and to assess the extent to which convergence in biochemical phenotype is attributable to repeated amino acid replacements. Functional experiments on native Hb variants and protein engineering experiments based on site-directed mutagenesis revealed the phenotypic effects of specific amino acid replacements that were responsible for convergent increases in Hb-O2 affinity in multiple high-altitude taxa. In six of the eight taxon pairs, high-altitude taxa evolved derived increases in Hb-O2 affinity that were caused by a combination of unique replacements, parallel replacements (involving identical-by-state variants with independent mutational origins in different lineages, and collateral replacements (involving shared, identical-by-descent variants derived via introgressive hybridization. In genome scans of nucleotide differentiation involving high- and low-altitude populations of three separate species, function-altering amino acid polymorphisms in the globin genes emerged as highly significant outliers, providing independent evidence for adaptive divergence in Hb function. The experimental results demonstrate that convergent changes in protein function can occur through multiple historical paths, and can involve multiple possible mutations. Most cases of convergence in Hb function did not involve parallel substitutions and most parallel substitutions did not affect Hb-O2 affinity, indicating that the repeatability of phenotypic evolution does not require parallelism at the molecular level.
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An atypical case of Noonan syndrome with mutation diagnosed by targeted exome sequencing
Directory of Open Access Journals (Sweden)
Jinsup Kim
2017-09-01
Full Text Available Noonan syndrome (NS is a genetic disorder caused by autosomal dominant inheritance and is characterized by a distinctive facial appearance, short stature, chest deformity, and congenital heart disease. In individuals with NS, germline mutations have been identified in several genes involved in the RAS/mitogen-activated protein kinase signal transduction pathway. Because of its clinical and genetic heterogeneity, the conventional diagnostic protocol with Sanger sequencing requires a multistep approach. Therefore, molecular genetic diagnosis using targeted exome sequencing (TES is considered a less expensive and faster method, particularly for patients who do not fulfill the clinical diagnostic criteria of NS. In this case, the patient showed short stature, dysmorphic facial features suggestive of NS, feeding intolerance, cryptorchidism, and intellectual disability in early childhood. At the age of 16, the patient still showed extreme short stature with delayed puberty and characteristic facial features suggestive of NS. Although the patient had no cardiac problems or chest wall deformities, which are commonly present in NS and are major concerns for patients and clinicians, the patient showed several other characteristic clinical features of NS. Considering the possibility of a genetic disorder, including NS, a molecular genetic study with TES was performed. With TES analysis, we detected a pathogenic variant of c.458A > T in KRAS in this patient with atypical NS phenotype and provided appropriate clinical management and genetic counseling. The application of TES enables accurate molecular diagnosis of patients with nonspecific or atypical features in genetic diseases with several responsible genes, such as NS.
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Spreadsheet macros for coloring sequence alignments.
Haygood, M G
1993-12-01
This article describes a set of Microsoft Excel macros designed to color amino acid and nucleotide sequence alignments for review and preparation of visual aids. The colored alignments can then be modified to emphasize features of interest. Procedures for importing and coloring sequences are described. The macro file adds a new menu to the menu bar containing sequence-related commands to enable users unfamiliar with Excel to use the macros more readily. The macros were designed for use with Macintosh computers but will also run with the DOS version of Excel.
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Filovirus Glycoprotein Sequence, Structure and Virulence
Phillips, J. C.
2014-01-01
Leading Ebola subtypes exhibit a wide mortality range, here explained at the molecular level by using fractal hydropathic scaling of amino acid sequences based on protein self-organized criticality. Specific hydrophobic features in the hydrophilic mucin-like domain suffice to account for the wide mortality range. Significance statement: Ebola virus is spreading rapidly in Africa. The connection between protein amino acid sequence and mortality is identified here.
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Mediastinal involvement in lymphangiomatosis: a previously unreported MRI sign
Energy Technology Data Exchange (ETDEWEB)
Shah, Vikas; Shah, Sachit; Barnacle, Alex; McHugh, Kieran [Great Ormond Street Hospital for Children, Department of Radiology, London (United Kingdom); Sebire, Neil J. [Great Ormond Street Hospital for Children, Department of Histopathology, London (United Kingdom); Brock, Penelope [Great Ormond Street Hospital for Children, Department of Oncology, London (United Kingdom); Harper, John I. [Great Ormond Street Hospital for Children, Department of Dermatology, London (United Kingdom)
2011-08-15
Multifocal lymphangiomatosis is a rare systemic disorder affecting children. Due to its rarity and wide spectrum of clinical, histological and imaging features, establishing the diagnosis of multifocal lymphangiomatosis can be challenging. The purpose of this study was to describe a new imaging sign in this disorder: paraspinal soft tissue and signal abnormality at MRI. We retrospectively reviewed the imaging, clinical and histopathological findings in a cohort of eight children with thoracic involvement from this condition. Evidence of paraspinal chest disease was identified at MRI and CT in all eight of these children. The changes comprise heterogeneous intermediate-to-high signal parallel to the thoracic vertebrae on T2-weighted sequences at MRI, with abnormal paraspinal soft tissue at CT and plain radiography. Multifocal lymphangiomatosis is a rare disorder with a broad range of clinicopathological and imaging features. MRI allows complete evaluation of disease extent without the use of ionising radiation and has allowed us to describe a previously unreported imaging sign in this disorder, namely, heterogeneous hyperintense signal in abnormal paraspinal tissue on T2-weighted images. (orig.)
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Complete genome sequence of Pedobacter heparinus type strain (HIM 762-3T)
Energy Technology Data Exchange (ETDEWEB)
Han, Cliff; Spring, Stefan; Lapidus, Alla; Glavina Del Rio, Tijana; Tice, Hope; Copeland, Alex; Cheng, Jan-Fang; Lucas, Susan; Chen, Feng; Nolan, Matt; Bruce, David; Goodwin, Lynne; Pitluck, Sam; Ivanova, Natalia; Mavrommatis, Konstantinos; Mikhailova, Natalia; Pati, Amrita; Chen, Amy; Palaniappan, Krishna; Land, Miriam; Hauser, Loren; Chang, Yun-Juan; Jefferies, Cynthia C.; Saunders, Elizabeth; Chertkov, Olga; Brettin, Thomas; Goker, Markus; Rohde, Manfred; Bristow, James; Eisen, Jonathan A.; Markowitz, Victor; Hugenholtz, Philip; Kyrpides, Nikos C.; Klenk, Hans-Peter; Detter, John C.
2009-05-20
Pedobacter heparinus (Payza and Korn 1956) Steyn et al. 1998 comb. nov. is the type species of the rapidly growing genus Pedobacter within the family Sphingobacteriaceae of the phylum 'Bacteroidetes'. P. heparinus is of interest, because it was the first isolated strain shown to grow with heparin as sole carbon and nitrogen source and because it produces several enzymes involved in the degradation of mucopolysaccharides. All available data about this species are based on a sole strain that was isolated from dry soil. Here we describe the features of this organism, together with the complete genome sequence, and annotation. This is the first report on a complete genome sequence of a member of the genus Pedobacter, and the 5,167,383 bp long single replicon genome with its 4287 protein-coding and 54 RNA genes is part of the Genomic Encyclopedia of Bacteria and Archaea project.
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Disruption of visual feature binding in working memory.
Ueno, Taiji; Allen, Richard J; Baddeley, Alan D; Hitch, Graham J; Saito, Satoru
2011-01-01
In a series of five experiments, we studied the effect of a visual suffix on the retention in short-term visual memory of both individual visual features and objects involving the binding of two features. Experiments 1A, 1B, and 2 involved suffixes consisting of features external to the to-be-remembered set and revealed a modest but equivalent disruption on individual and bound feature conditions. Experiments 3A and 3B involved suffixes comprising features that could potentially have formed part of the to-be-remembered set (but did not on that trial). Both experiments showed greater disruption of retention for objects comprising bound features than for their individual features. The results are interpreted as differentiating two components of suffix interference, one affecting memory for features and bindings equally, the other affecting memory for bindings. The general component is tentatively identified with the attentional cost of operating a filter to prevent the suffix from entering visual working memory, whereas the specific component is attributed to the particular fragility of bound representations when the filter fails.
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An Evolutionary Machine Learning Framework for Big Data Sequence Mining
Kamath, Uday Krishna
2014-01-01
Sequence classification is an important problem in many real-world applications. Unlike other machine learning data, there are no "explicit" features or signals in sequence data that can help traditional machine learning algorithms learn and predict from the data. Sequence data exhibits inter-relationships in the elements that are…
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Global features of the Alcanivorax borkumensis SK2 genome
DEFF Research Database (Denmark)
Reva, Oleg N.; Hallin, Peter Fischer; Willenbrock, Hanni
2008-01-01
The global feature of the completely sequenced Alcanivorax borkumensis SK2 type strain chromosome is its symmetry and homogeneity. The origin and terminus of replication are located opposite to each other in the chromosome and are discerned with high signal to noise ratios by maximal oligonucleot......The global feature of the completely sequenced Alcanivorax borkumensis SK2 type strain chromosome is its symmetry and homogeneity. The origin and terminus of replication are located opposite to each other in the chromosome and are discerned with high signal to noise ratios by maximal...... oligonucleotide usage biases on the leading and lagging strand. Genomic DNA structure is rather uniform throughout the chromosome with respect to intrinsic curvature, position preference or base stacking energy. The orthologs and paralogs of A. borkumensis genes with the highest sequence homology were found...
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Directory of Open Access Journals (Sweden)
Vierdy Sulfianto Rahmadani
2015-04-01
Full Text Available The purpose of this research is to apply the application of reverse engineering to determine interaction patterns of the Sequence diagram that can be used by system analysts as a template for designing UML sequence diagrams. Sample applications from android are used as dataset for reverse engineering and pattern identification. The first step is collecting application datasets. The next stage is identifying the features and applications activity, reverse engineering to obtain a sequence diagram model, and then synthesize all of the models into an interaction pattern of sequence diagram. The final step is to test the patterns by implementing it in an application development case stud. The evaluation results concludes that interaction patterns of sequence diagram designs obtained in reverse engineering steps is able to be implemented in software development that contained similar features with the obtained features in this research.
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A girl with early-onset epileptic encephalopathy associated with microdeletion involving CDKL5.
Saitsu, Hirotomo; Osaka, Hitoshi; Nishiyama, Kiyomi; Tsurusaki, Yoshinori; Doi, Hiroshi; Miyake, Noriko; Matsumoto, Naomichi
2012-05-01
Recent studies have shown that aberrations of CDKL5 in female patients cause early-onset intractable seizures, severe developmental delay or regression, and Rett syndrome-like features. We report on a Japanese girl with early-onset epileptic encephalopathy, hypotonia, developmental regression, and Rett syndrome-like features. The patient showed generalized tonic seizures, and later, massive myoclonus induced by phone and light stimuli. Brain magnetic resonance imaging showed no structural brain anomalies but cerebral atrophy. Electroencephalogram showed frontal dominant diffuse poly spikes and waves. Through copy number analysis by genomic microarray, we found a microdeletion at Xp22.13. A de novo 137-kb deletion, involving exons 5-21 of CDKL5, RS1, and part of PPEF1 gene, was confirmed by quantitative PCR and breakpoint specific PCR analyses. Our report suggests that the clinical features associated with CDKL5 deletions could be implicated in Japanese patients, and that genetic testing of CDKL5, including both sequencing and deletion analyses, should be considered in girls with early-onset epileptic encephalopathy and RTT-like features. Copyright © 2011 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.
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MR imaging features of foot involvement in patients with psoriasis
Energy Technology Data Exchange (ETDEWEB)
Erdem, C. Zuhal [Department of Radiology, Zonguldak Karaelmas University, School of Medicine, Zonguldak (Turkey)], E-mail: sunarerdem@yahoo.com; Tekin, Nilgun Solak [Department of Dermatology, Zonguldak Karaelmas University, School of Medicine, Zonguldak (Turkey); Sarikaya, Selda [Department of Physical Therapy and Rehabilitation, Zonguldak Karaelmas University, School of Medicine, Zonguldak (Turkey); Erdem, L. Oktay; Gulec, Sezen [Department of Radiology, Zonguldak Karaelmas University, School of Medicine, Zonguldak (Turkey)
2008-09-15
Objective: To determine alterations of the soft tissues, tendons, cartilage, joint spaces, and bones of the foot using magnetic resonance (MR) imaging in patients with psoriasis. Materials and methods: Clinical and MR examination of the foot was performed in 26 consecutive patients (52 ft) with psoriasis. As a control group, 10 healthy volunteers (20 ft) were also studied. Joint effusion/synovitis, retrocalcaneal bursitis, retroachilles bursitis, Achilles tendonitis, soft-tissue edema, para-articular enthesophytes, bone marrow edema, sinus tarsi syndrome, enthesopathy at the Achilles attachment and at the plantar fascia attachment, plantar fasciitis, tenosynovitis, subchondral cysts, and bone erosions, joint space narrowing, subchondral signal changes, osteolysis, luxation, and sub-luxation were examined. Results: Clinical signs and symptoms (pain and swelling) due to foot involvement were present in none of the patients while frequency of involvement was 92% (24/26) by MR imaging. The most common MR imaging findings were Achilles tendonitis (acute and peritendinitis) (57%), retrocalcaneal bursitis (50%), joint effusion/synovitis (46%), soft-tissue edema (46%), and para-articular enthesophytes (38%). The most commonly involved anatomical region was the hindfoot (73%). Conclusion: Our data showed that the incidence of foot involvement was very high in asymptomatic patients with psoriasis on MR imaging. Further MR studies are needed to confirm these data. We conclude that MR imaging may be of importance especially in early diagnosis and treatment of inflammatory changes in the foot.
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MR imaging features of foot involvement in patients with psoriasis
International Nuclear Information System (INIS)
Erdem, C. Zuhal; Tekin, Nilgun Solak; Sarikaya, Selda; Erdem, L. Oktay; Gulec, Sezen
2008-01-01
Objective: To determine alterations of the soft tissues, tendons, cartilage, joint spaces, and bones of the foot using magnetic resonance (MR) imaging in patients with psoriasis. Materials and methods: Clinical and MR examination of the foot was performed in 26 consecutive patients (52 ft) with psoriasis. As a control group, 10 healthy volunteers (20 ft) were also studied. Joint effusion/synovitis, retrocalcaneal bursitis, retroachilles bursitis, Achilles tendonitis, soft-tissue edema, para-articular enthesophytes, bone marrow edema, sinus tarsi syndrome, enthesopathy at the Achilles attachment and at the plantar fascia attachment, plantar fasciitis, tenosynovitis, subchondral cysts, and bone erosions, joint space narrowing, subchondral signal changes, osteolysis, luxation, and sub-luxation were examined. Results: Clinical signs and symptoms (pain and swelling) due to foot involvement were present in none of the patients while frequency of involvement was 92% (24/26) by MR imaging. The most common MR imaging findings were Achilles tendonitis (acute and peritendinitis) (57%), retrocalcaneal bursitis (50%), joint effusion/synovitis (46%), soft-tissue edema (46%), and para-articular enthesophytes (38%). The most commonly involved anatomical region was the hindfoot (73%). Conclusion: Our data showed that the incidence of foot involvement was very high in asymptomatic patients with psoriasis on MR imaging. Further MR studies are needed to confirm these data. We conclude that MR imaging may be of importance especially in early diagnosis and treatment of inflammatory changes in the foot
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Pesteie, Mehran; Abolmaesumi, Purang; Ashab, Hussam Al-Deen; Lessoway, Victoria A; Massey, Simon; Gunka, Vit; Rohling, Robert N
2015-06-01
Injection therapy is a commonly used solution for back pain management. This procedure typically involves percutaneous insertion of a needle between or around the vertebrae, to deliver anesthetics near nerve bundles. Most frequently, spinal injections are performed either blindly using palpation or under the guidance of fluoroscopy or computed tomography. Recently, due to the drawbacks of the ionizing radiation of such imaging modalities, there has been a growing interest in using ultrasound imaging as an alternative. However, the complex spinal anatomy with different wave-like structures, affected by speckle noise, makes the accurate identification of the appropriate injection plane difficult. The aim of this study was to propose an automated system that can identify the optimal plane for epidural steroid injections and facet joint injections. A multi-scale and multi-directional feature extraction system to provide automated identification of the appropriate plane is proposed. Local Hadamard coefficients are obtained using the sequency-ordered Hadamard transform at multiple scales. Directional features are extracted from local coefficients which correspond to different regions in the ultrasound images. An artificial neural network is trained based on the local directional Hadamard features for classification. The proposed method yields distinctive features for classification which successfully classified 1032 images out of 1090 for epidural steroid injection and 990 images out of 1052 for facet joint injection. In order to validate the proposed method, a leave-one-out cross-validation was performed. The average classification accuracy for leave-one-out validation was 94 % for epidural and 90 % for facet joint targets. Also, the feature extraction time for the proposed method was 20 ms for a native 2D ultrasound image. A real-time machine learning system based on the local directional Hadamard features extracted by the sequency-ordered Hadamard transform for
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O'Rahilly, R; Müller, F; Hutchins, G M; Moore, G W
1988-08-01
The sequence of events in the development of the brain in human embryos, already published for stages 8-17, is here continued for stages 18 and 19. With the aid of a computerized bubble-sort algorithm, 58 individual embryos were ranked in ascending order of the features present. The increasing structural complexity provided 40 new features in these two stages. The chief characteristics of stage 18 (approximately 44 postovulatory days) are rapidly growing basal nuclei; appearance of the extraventricular bulge of the cerebellum (flocculus), of the superior cerebellar peduncle, and of follicles in the epiphysis cerebri; and the presence of vomeronasal organ and ganglion, of the bucconasal membrane, and of isolated semicircular ducts. The main features of stage 19 (approximately 48 days) are the cochlear nuclei, the ganglion of the nervus terminalis, nuclei of the prosencephalic septum, the appearance of the subcommissural organ, the presence of villi in the choroid plexuses of the fourth and lateral ventricles, and the stria medullaris thalami.
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DEFF Research Database (Denmark)
Blomstrøm, Monica Marie
2016-01-01
several growth modulators and invasion modulators were identified and independently validated. These candidates revealed a group of genes with metastasis-related functions in vitro that are involved in RNA-related processes, such as RNA-processing. Moreover, a general feature was that proliferation......) and non-CSCs. The main goal of this project was to functionally characterize a set of candidate genes recovered from next-generation sequencing analysis for their role in breast cancer metastasis formation. The starting gene set comprised 104 gene variants; i.e. 57 wildtype and 47 mutated variants. During...
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PhyloSim - Monte Carlo simulation of sequence evolution in the R statistical computing environment
Directory of Open Access Journals (Sweden)
Massingham Tim
2011-04-01
Full Text Available Abstract Background The Monte Carlo simulation of sequence evolution is routinely used to assess the performance of phylogenetic inference methods and sequence alignment algorithms. Progress in the field of molecular evolution fuels the need for more realistic and hence more complex simulations, adapted to particular situations, yet current software makes unreasonable assumptions such as homogeneous substitution dynamics or a uniform distribution of indels across the simulated sequences. This calls for an extensible simulation framework written in a high-level functional language, offering new functionality and making it easy to incorporate further complexity. Results PhyloSim is an extensible framework for the Monte Carlo simulation of sequence evolution, written in R, using the Gillespie algorithm to integrate the actions of many concurrent processes such as substitutions, insertions and deletions. Uniquely among sequence simulation tools, PhyloSim can simulate arbitrarily complex patterns of rate variation and multiple indel processes, and allows for the incorporation of selective constraints on indel events. User-defined complex patterns of mutation and selection can be easily integrated into simulations, allowing PhyloSim to be adapted to specific needs. Conclusions Close integration with R and the wide range of features implemented offer unmatched flexibility, making it possible to simulate sequence evolution under a wide range of realistic settings. We believe that PhyloSim will be useful to future studies involving simulated alignments.
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Directory of Open Access Journals (Sweden)
Hiromi Daiyasu
2005-01-01
Full Text Available Cellular membrane lipids, of which phospholipids are the major constituents, form one of the characteristic features that distinguish Archaea from other organisms. In this study, we focused on the steps in archaeal phospholipid synthetic pathways that generate polar lipids such as archaetidylserine, archaetidylglycerol, and archaetidylinositol. Only archaetidylserine synthase (ASS, from Methanothermobacter thermautotrophicus, has been experimentally identified. Other enzymes have not been fully examined. Through database searching, we detected many archaeal hypothetical proteins that show sequence similarity to members of the CDP alcohol phosphatidyltransferase family, such as phosphatidylserine synthase (PSS, phosphatidylglycerol synthase (PGS and phosphatidylinositol synthase (PIS derived from Bacteria and Eukarya. The archaeal hypothetical proteins were classified into two groups, based on the sequence similarity. Members of the first group, including ASS from M. thermautotrophicus, were closely related to PSS. The rough agreement between PSS homologue distribution within Archaea and the experimentally identified distribution of archaetidylserine suggested that the hypothetical proteins are ASSs. We found that an open reading frame (ORF tends to be adjacent to that of ASS in the genome, and that the order of the two ORFs is conserved. The sequence similarity of phosphatidylserine decarboxylase to the product of the ORF next to the ASS gene, together with the genomic context conservation, suggests that the ORF encodes archaetidylserine decarboxylase, which may transform archaetidylserine to archaetidylethanolamine. The second group of archaeal hypothetical proteins was related to PGS and PIS. The members of this group were subjected to molecular phylogenetic analysis, together with PGSs and PISs and it was found that they formed two distinct clusters in the molecular phylogenetic tree. The distribution of members of each cluster within Archaea
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Toward a model for lexical access based on acoustic landmarks and distinctive features
Stevens, Kenneth N.
2002-04-01
This article describes a model in which the acoustic speech signal is processed to yield a discrete representation of the speech stream in terms of a sequence of segments, each of which is described by a set (or bundle) of binary distinctive features. These distinctive features specify the phonemic contrasts that are used in the language, such that a change in the value of a feature can potentially generate a new word. This model is a part of a more general model that derives a word sequence from this feature representation, the words being represented in a lexicon by sequences of feature bundles. The processing of the signal proceeds in three steps: (1) Detection of peaks, valleys, and discontinuities in particular frequency ranges of the signal leads to identification of acoustic landmarks. The type of landmark provides evidence for a subset of distinctive features called articulator-free features (e.g., [vowel], [consonant], [continuant]). (2) Acoustic parameters are derived from the signal near the landmarks to provide evidence for the actions of particular articulators, and acoustic cues are extracted by sampling selected attributes of these parameters in these regions. The selection of cues that are extracted depends on the type of landmark and on the environment in which it occurs. (3) The cues obtained in step (2) are combined, taking context into account, to provide estimates of ``articulator-bound'' features associated with each landmark (e.g., [lips], [high], [nasal]). These articulator-bound features, combined with the articulator-free features in (1), constitute the sequence of feature bundles that forms the output of the model. Examples of cues that are used, and justification for this selection, are given, as well as examples of the process of inferring the underlying features for a segment when there is variability in the signal due to enhancement gestures (recruited by a speaker to make a contrast more salient) or due to overlap of gestures from
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An Imaging And Graphics Workstation For Image Sequence Analysis
Mostafavi, Hassan
1990-01-01
This paper describes an application-specific engineering workstation designed and developed to analyze imagery sequences from a variety of sources. The system combines the software and hardware environment of the modern graphic-oriented workstations with the digital image acquisition, processing and display techniques. The objective is to achieve automation and high throughput for many data reduction tasks involving metric studies of image sequences. The applications of such an automated data reduction tool include analysis of the trajectory and attitude of aircraft, missile, stores and other flying objects in various flight regimes including launch and separation as well as regular flight maneuvers. The workstation can also be used in an on-line or off-line mode to study three-dimensional motion of aircraft models in simulated flight conditions such as wind tunnels. The system's key features are: 1) Acquisition and storage of image sequences by digitizing real-time video or frames from a film strip; 2) computer-controlled movie loop playback, slow motion and freeze frame display combined with digital image sharpening, noise reduction, contrast enhancement and interactive image magnification; 3) multiple leading edge tracking in addition to object centroids at up to 60 fields per second from both live input video or a stored image sequence; 4) automatic and manual field-of-view and spatial calibration; 5) image sequence data base generation and management, including the measurement data products; 6) off-line analysis software for trajectory plotting and statistical analysis; 7) model-based estimation and tracking of object attitude angles; and 8) interface to a variety of video players and film transport sub-systems.
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Directory of Open Access Journals (Sweden)
Seyed Mahdi Alhosseini Almodarresi
2015-12-01
Full Text Available Among the factors that are necessary to facilitate the consumer’s daily life with high mental involvement, fashion clothing is an important and significant factor for many consumers. According to the importance of the subject, this research reviewed the effect of religion, materialism and demographic features of the consumer on mental involvement in fashion clothing among citizens of Yazd. Confirmatory factor analysis method has been applied in analytical statistics of this research to determine the role and position of each one of the research elements by using Amos software. Correlation test has been used in order to review the relations between fashion clothing involvement and its dimensions, and linear regression test in order to determine the effect manner of involvement in fashion clothing and mental knowledge on confidence in fashion decision making. The statistical population includes all the individuals above 20 years old in Yazd City; the sample size was calculated 99 individuals by using Cochran formula. The research results showed that religion and materialism have significant effect on mental involvement in fashion clothing and involvement has a positive and significant effect on fashion decision making confidence. Furthermore, mental involvements in fashion clothing and mental knowledge have a positive and significant effect on fashion decision making confidence and it was specified in the reviewing of the relation between demographic factors (sex, age,… and the studied variables that the correlation between them was not significant even in the confidence level of 95 percent.
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Brooks, Kevin R; Kemp, Richard I
2007-01-01
Previous studies of face recognition and of face matching have shown a general improvement for the processing of internal features as a face becomes more familiar to the participant. In this study, we used a psychophysical two-alternative forced-choice paradigm to investigate thresholds for the detection of a displacement of the eyes, nose, mouth, or ears for familiar and unfamiliar faces. No clear division between internal and external features was observed. Rather, for familiar (compared to unfamiliar) faces participants were more sensitive to displacements of internal features such as the eyes or the nose; yet, for our third internal feature-the mouth no such difference was observed. Despite large displacements, many subjects were unable to perform above chance when stimuli involved shifts in the position of the ears. These results are consistent with the proposal that familiarity effects may be mediated by the construction of a robust representation of a face, although the involvement of attention in the encoding of face stimuli cannot be ruled out. Furthermore, these effects are mediated by information from a spatial configuration of features, rather than by purely feature-based information.
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Multimodal Feature Learning for Video Captioning
Directory of Open Access Journals (Sweden)
Sujin Lee
2018-01-01
Full Text Available Video captioning refers to the task of generating a natural language sentence that explains the content of the input video clips. This study proposes a deep neural network model for effective video captioning. Apart from visual features, the proposed model learns additionally semantic features that describe the video content effectively. In our model, visual features of the input video are extracted using convolutional neural networks such as C3D and ResNet, while semantic features are obtained using recurrent neural networks such as LSTM. In addition, our model includes an attention-based caption generation network to generate the correct natural language captions based on the multimodal video feature sequences. Various experiments, conducted with the two large benchmark datasets, Microsoft Video Description (MSVD and Microsoft Research Video-to-Text (MSR-VTT, demonstrate the performance of the proposed model.
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Directory of Open Access Journals (Sweden)
Francesco Italiano
2012-10-01
Full Text Available A periodic sampling of the groundwaters and dissolved and free gases in selected deep wells located in the area affected by the May-June 2012 southern Po Valley seismic sequence has provided insight into seismogenic-induced changes of the local aquifer systems. The results obtained show progressive changes in the fluid geochemistry, allowing it to be established that deep-seated fluids were mobilized during the seismic sequence and reached surface layers along faults and fractures, which generated significant geochemical anomalies. The May-June 2012 seismic swarm (mainshock on May 29, 2012, M 5.8; 7 shocks M >5, about 200 events 3 > M > 5 induced several modifications in the circulating fluids. This study reports the preliminary results obtained for the geochemical features of the waters and gases collected over the epicentral area from boreholes drilled at different depths, thus intercepting water and gases with different origins and circulation. The aim of the investigations was to improve our knowledge of the fluids circulating over the seismic area (e.g. origin, provenance, interactions, mixing of different components, temporal changes. This was achieved by collecting samples from both shallow and deep-drilled boreholes, and then, after the selection of the relevant sites, we looked for temporal changes with mid-to-long-term monitoring activity following a constant sampling rate. This allowed us to gain better insight into the relationships between the fluid circulation and the faulting activity. The sampling sites are listed in Table 1, along with the analytical results of the gas phase. […
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Abstract feature codes: The building blocks of the implicit learning system.
Eberhardt, Katharina; Esser, Sarah; Haider, Hilde
2017-07-01
According to the Theory of Event Coding (TEC; Hommel, Müsseler, Aschersleben, & Prinz, 2001), action and perception are represented in a shared format in the cognitive system by means of feature codes. In implicit sequence learning research, it is still common to make a conceptual difference between independent motor and perceptual sequences. This supposedly independent learning takes place in encapsulated modules (Keele, Ivry, Mayr, Hazeltine, & Heuer 2003) that process information along single dimensions. These dimensions have remained underspecified so far. It is especially not clear whether stimulus and response characteristics are processed in separate modules. Here, we suggest that feature dimensions as they are described in the TEC should be viewed as the basic content of modules of implicit learning. This means that the modules process all stimulus and response information related to certain feature dimensions of the perceptual environment. In 3 experiments, we investigated by means of a serial reaction time task the nature of the basic units of implicit learning. As a test case, we used stimulus location sequence learning. The results show that a stimulus location sequence and a response location sequence cannot be learned without interference (Experiment 2) unless one of the sequences can be coded via an alternative, nonspatial dimension (Experiment 3). These results support the notion that spatial location is one module of the implicit learning system and, consequently, that there are no separate processing units for stimulus versus response locations. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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Optimization of short amino acid sequences classifier
Barcz, Aleksy; Szymański, Zbigniew
This article describes processing methods used for short amino acid sequences classification. The data processed are 9-symbols string representations of amino acid sequences, divided into 49 data sets - each one containing samples labeled as reacting or not with given enzyme. The goal of the classification is to determine for a single enzyme, whether an amino acid sequence would react with it or not. Each data set is processed separately. Feature selection is performed to reduce the number of dimensions for each data set. The method used for feature selection consists of two phases. During the first phase, significant positions are selected using Classification and Regression Trees. Afterwards, symbols appearing at the selected positions are substituted with numeric values of amino acid properties taken from the AAindex database. In the second phase the new set of features is reduced using a correlation-based ranking formula and Gram-Schmidt orthogonalization. Finally, the preprocessed data is used for training LS-SVM classifiers. SPDE, an evolutionary algorithm, is used to obtain optimal hyperparameters for the LS-SVM classifier, such as error penalty parameter C and kernel-specific hyperparameters. A simple score penalty is used to adapt the SPDE algorithm to the task of selecting classifiers with best performance measures values.
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Radiographic features of esophageal involvement in chronic graft-vs.-host disease
International Nuclear Information System (INIS)
McDonald, G.B.; Sullivan, K.M.; Plumley, T.F.
1984-01-01
Chronic graft-vs.-host disease (GVHD) is an important late complication of allogeneic bone-marrow transplantation. It resembles several naturally occurring autoimmune diseases and involves the skin, mouth, eyes, liver, and esophagus. The radiographic findings of 14 symptomatic patients with chronic GVHD involving the esophagus were reviewed and found to include webs, ringlike narrowings, and tapering strictures in the mid and upper esophagus. Esophagoscopy revealed characteristic desquamation in the 13 patients studied, but barium studies detected this lesion in only one patient. Knowledge of the site and characteristics of esophageal involvement with chronic GVHD assists the radiologic evaluation of this disorder
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Maximum entropy methods for extracting the learned features of deep neural networks.
Finnegan, Alex; Song, Jun S
2017-10-01
New architectures of multilayer artificial neural networks and new methods for training them are rapidly revolutionizing the application of machine learning in diverse fields, including business, social science, physical sciences, and biology. Interpreting deep neural networks, however, currently remains elusive, and a critical challenge lies in understanding which meaningful features a network is actually learning. We present a general method for interpreting deep neural networks and extracting network-learned features from input data. We describe our algorithm in the context of biological sequence analysis. Our approach, based on ideas from statistical physics, samples from the maximum entropy distribution over possible sequences, anchored at an input sequence and subject to constraints implied by the empirical function learned by a network. Using our framework, we demonstrate that local transcription factor binding motifs can be identified from a network trained on ChIP-seq data and that nucleosome positioning signals are indeed learned by a network trained on chemical cleavage nucleosome maps. Imposing a further constraint on the maximum entropy distribution also allows us to probe whether a network is learning global sequence features, such as the high GC content in nucleosome-rich regions. This work thus provides valuable mathematical tools for interpreting and extracting learned features from feed-forward neural networks.
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Vitsios, Dimitrios M; Kentepozidou, Elissavet; Quintais, Leonor; Benito-Gutiérrez, Elia; van Dongen, Stijn; Davis, Matthew P; Enright, Anton J
2017-12-01
The discovery of microRNAs (miRNAs) remains an important problem, particularly given the growth of high-throughput sequencing, cell sorting and single cell biology. While a large number of miRNAs have already been annotated, there may well be large numbers of miRNAs that are expressed in very particular cell types and remain elusive. Sequencing allows us to quickly and accurately identify the expression of known miRNAs from small RNA-Seq data. The biogenesis of miRNAs leads to very specific characteristics observed in their sequences. In brief, miRNAs usually have a well-defined 5' end and a more flexible 3' end with the possibility of 3' tailing events, such as uridylation. Previous approaches to the prediction of novel miRNAs usually involve the analysis of structural features of miRNA precursor hairpin sequences obtained from genome sequence. We surmised that it may be possible to identify miRNAs by using these biogenesis features observed directly from sequenced reads, solely or in addition to structural analysis from genome data. To this end, we have developed mirnovo, a machine learning based algorithm, which is able to identify known and novel miRNAs in animals and plants directly from small RNA-Seq data, with or without a reference genome. This method performs comparably to existing tools, however is simpler to use with reduced run time. Its performance and accuracy has been tested on multiple datasets, including species with poorly assembled genomes, RNaseIII (Drosha and/or Dicer) deficient samples and single cells (at both embryonic and adult stage). © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
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Directory of Open Access Journals (Sweden)
Wangchao Lou
Full Text Available Developing an efficient method for determination of the DNA-binding proteins, due to their vital roles in gene regulation, is becoming highly desired since it would be invaluable to advance our understanding of protein functions. In this study, we proposed a new method for the prediction of the DNA-binding proteins, by performing the feature rank using random forest and the wrapper-based feature selection using forward best-first search strategy. The features comprise information from primary sequence, predicted secondary structure, predicted relative solvent accessibility, and position specific scoring matrix. The proposed method, called DBPPred, used Gaussian naïve Bayes as the underlying classifier since it outperformed five other classifiers, including decision tree, logistic regression, k-nearest neighbor, support vector machine with polynomial kernel, and support vector machine with radial basis function. As a result, the proposed DBPPred yields the highest average accuracy of 0.791 and average MCC of 0.583 according to the five-fold cross validation with ten runs on the training benchmark dataset PDB594. Subsequently, blind tests on the independent dataset PDB186 by the proposed model trained on the entire PDB594 dataset and by other five existing methods (including iDNA-Prot, DNA-Prot, DNAbinder, DNABIND and DBD-Threader were performed, resulting in that the proposed DBPPred yielded the highest accuracy of 0.769, MCC of 0.538, and AUC of 0.790. The independent tests performed by the proposed DBPPred on completely a large non-DNA binding protein dataset and two RNA binding protein datasets also showed improved or comparable quality when compared with the relevant prediction methods. Moreover, we observed that majority of the selected features by the proposed method are statistically significantly different between the mean feature values of the DNA-binding and the non DNA-binding proteins. All of the experimental results indicate that
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Quantiprot - a Python package for quantitative analysis of protein sequences.
Konopka, Bogumił M; Marciniak, Marta; Dyrka, Witold
2017-07-17
The field of protein sequence analysis is dominated by tools rooted in substitution matrices and alignments. A complementary approach is provided by methods of quantitative characterization. A major advantage of the approach is that quantitative properties defines a multidimensional solution space, where sequences can be related to each other and differences can be meaningfully interpreted. Quantiprot is a software package in Python, which provides a simple and consistent interface to multiple methods for quantitative characterization of protein sequences. The package can be used to calculate dozens of characteristics directly from sequences or using physico-chemical properties of amino acids. Besides basic measures, Quantiprot performs quantitative analysis of recurrence and determinism in the sequence, calculates distribution of n-grams and computes the Zipf's law coefficient. We propose three main fields of application of the Quantiprot package. First, quantitative characteristics can be used in alignment-free similarity searches, and in clustering of large and/or divergent sequence sets. Second, a feature space defined by quantitative properties can be used in comparative studies of protein families and organisms. Third, the feature space can be used for evaluating generative models, where large number of sequences generated by the model can be compared to actually observed sequences.
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DIALIGN: multiple DNA and protein sequence alignment at BiBiServ.
Morgenstern, Burkhard
2004-01-01
DIALIGN is a widely used software tool for multiple DNA and protein sequence alignment. The program combines local and global alignment features and can therefore be applied to sequence data that cannot be correctly aligned by more traditional approaches. DIALIGN is available online through Bielefeld Bioinformatics Server (BiBiServ). The downloadable version of the program offers several new program features. To compare the output of different alignment programs, we developed the program AltA...
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Nucleotide sequence determination of the region in adenovirus 5 DNA involved in cell transformation
International Nuclear Information System (INIS)
Maat, J.
1978-01-01
A description is given of investigations into the primary structure of the transforming region of adenovirus type 5 DNA. The phenomenon of cell transformation is discussed in general terms and the principles of a number of fairly recent techniques, which have been in use for DNA sequence determination since 1975 are dealt with. A few of the author's own techniques are described which deal both with nucleotide sequence analysis and with the determination of DNA cleavage sites of restriction endonucleases. The results are given of the mapping of cleavage sites in the HpaI-E fragment of adenovirus DNA of HpaII, HaeIII, AluI, HinfI and TaqI and of the determination of the nucleotide sequence in the transforming region of adenovirus type 5 DNA. The results of the sequence determination of the Ad5 HindIII-G fragment are discussed in relation with the investigation on the transforming proteins isolated from in vitro and in vivo synthesizing systems. Labelling procedures of DNA are described including the exonuclease III/DNA polymerase 1 method and TA polynucleotide kinase labelling of DNA fragments. (Auth.)
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Distribution of genotype network sizes in sequence-to-structure genotype-phenotype maps.
Manrubia, Susanna; Cuesta, José A
2017-04-01
An essential quantity to ensure evolvability of populations is the navigability of the genotype space. Navigability, understood as the ease with which alternative phenotypes are reached, relies on the existence of sufficiently large and mutually attainable genotype networks. The size of genotype networks (e.g. the number of RNA sequences folding into a particular secondary structure or the number of DNA sequences coding for the same protein structure) is astronomically large in all functional molecules investigated: an exhaustive experimental or computational study of all RNA folds or all protein structures becomes impossible even for moderately long sequences. Here, we analytically derive the distribution of genotype network sizes for a hierarchy of models which successively incorporate features of increasingly realistic sequence-to-structure genotype-phenotype maps. The main feature of these models relies on the characterization of each phenotype through a prototypical sequence whose sites admit a variable fraction of letters of the alphabet. Our models interpolate between two limit distributions: a power-law distribution, when the ordering of sites in the prototypical sequence is strongly constrained, and a lognormal distribution, as suggested for RNA, when different orderings of the same set of sites yield different phenotypes. Our main result is the qualitative and quantitative identification of those features of sequence-to-structure maps that lead to different distributions of genotype network sizes. © 2017 The Author(s).
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Amplification and chromosomal dispersion of human endogenous retroviral sequences
International Nuclear Information System (INIS)
Steele, P.E.; Martin, M.A.; Rabson, A.B.; Bryan, T.; O'Brien, S.J.
1986-01-01
Endogenous retroviral sequences have undergone amplification events involving both viral and flanking cellular sequences. The authors cloned members of an amplified family of full-length endogenous retroviral sequences. Genomic blotting, employing a flanking cellular DNA probe derived from a member of this family, revealed a similar array of reactive bands in both humans and chimpanzees, indicating that an amplification event involving retroviral and associated cellular DNA sequences occurred before the evolutionary separation of these two primates. Southern analyses of restricted somatic cell hybrid DNA preparations suggested that endogenous retroviral segments are widely dispersed in the human genome and that amplification and dispersion events may be linked
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Linear Co-occurrence Rate Networks (L-CRNs) for Sequence Labeling
Zhu, Zhemin; Hiemstra, Djoerd; Apers, Peter M.G.
2014-01-01
Sequence labeling has wide applications in natural language processing and speech processing. Popular sequence labeling models suffer from some known problems. Hidden Markov models (HMMs) are generative models and they cannot encode transition features; Conditional Markov models (CMMs) suffer from
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Feature Selection Has a Large Impact on One-Class Classification Accuracy for MicroRNAs in Plants.
Yousef, Malik; Saçar Demirci, Müşerref Duygu; Khalifa, Waleed; Allmer, Jens
2016-01-01
MicroRNAs (miRNAs) are short RNA sequences involved in posttranscriptional gene regulation. Their experimental analysis is complicated and, therefore, needs to be supplemented with computational miRNA detection. Currently computational miRNA detection is mainly performed using machine learning and in particular two-class classification. For machine learning, the miRNAs need to be parametrized and more than 700 features have been described. Positive training examples for machine learning are readily available, but negative data is hard to come by. Therefore, it seems prerogative to use one-class classification instead of two-class classification. Previously, we were able to almost reach two-class classification accuracy using one-class classifiers. In this work, we employ feature selection procedures in conjunction with one-class classification and show that there is up to 36% difference in accuracy among these feature selection methods. The best feature set allowed the training of a one-class classifier which achieved an average accuracy of ~95.6% thereby outperforming previous two-class-based plant miRNA detection approaches by about 0.5%. We believe that this can be improved upon in the future by rigorous filtering of the positive training examples and by improving current feature clustering algorithms to better target pre-miRNA feature selection.
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Nabavizadeh, Seyed Ali; Mamourian, Alexander; Schmitt, James E; Cloran, Francis; Vossough, Arastoo; Pukenas, Bryan; Loevner, Laurie A; Mohan, Suyash
2016-01-01
While haemangiomas are common benign vascular lesions involving the spine, some behave in an aggressive fashion. We investigated the utility of fat-suppressed sequences to differentiate between benign and aggressive vertebral haemangiomas. Patients with the diagnosis of aggressive vertebral haemangioma and available short tau inversion-recovery or T2 fat saturation sequence were included in the study. 11 patients with typical asymptomatic vertebral body haemangiomas were selected as the control group. Region of interest signal intensity (SI) analysis of the entire haemangioma as well as the portion of each haemangioma with highest signal on fat-saturation sequences was performed and normalized to a reference normal vertebral body. A total of 8 patients with aggressive vertebral haemangioma and 11 patients with asymptomatic typical vertebral haemangioma were included. There was a significant difference between total normalized mean SI ratio (3.14 vs 1.48, p = 0.0002), total normalized maximum SI ratio (5.72 vs 2.55, p = 0.0003), brightest normalized mean SI ratio (4.28 vs 1.72, p 88%) and specificity (>82%). In addition to the conventional imaging features such as vertebral expansion and presence of extravertebral component, quantitative evaluation of fat-suppression sequences is also another imaging feature that can differentiate aggressive haemangioma and typical asymptomatic haemangioma. The use of quantitative fat-suppressed MRI in vertebral haemangiomas is demonstrated. Quantitative fat-suppressed MRI can have a role in confirming the diagnosis of aggressive haemangiomas. In addition, this application can be further investigated in future studies to predict aggressiveness of vertebral haemangiomas in early stages.
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International Nuclear Information System (INIS)
Pirzio, L.
2004-07-01
As telomeres are crucial for chromosome integrity; we investigated the role played by telomeric sequences in the formation and in the transmission of radio-induced chromosome rearrangements in human cells. Starting from interstitial telomeric sequences (ITS) as putative region of breakage, we showed that the radiation sensitivity is not equally distributed along chromosomes and. is not affected by ITS. On the contrary, plasmid integration sites are prone to radio-induced breaks, suggesting a possible integration at sites already characterized by fragility. However plasmids do not preferentially insert at radio-induced breaks in human cells immortalized by telomerase. These cells showed remarkable karyotype stability even after irradiation, suggesting a role of telomerase in the genome maintenance despite functional telomeres. Finally, we showed that the presence of more breaks in a cell favors the repair, leading to an increase of transmissible rearrangements. (author)
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Human Chromosome 7: DNA Sequence and Biology
Scherer, Stephen W.; Cheung, Joseph; MacDonald, Jeffrey R.; Osborne, Lucy R.; Nakabayashi, Kazuhiko; Herbrick, Jo-Anne; Carson, Andrew R.; Parker-Katiraee, Layla; Skaug, Jennifer; Khaja, Razi; Zhang, Junjun; Hudek, Alexander K.; Li, Martin; Haddad, May; Duggan, Gavin E.
2003-01-01
DNA sequence and annotation of the entire human chromosome 7, encompassing nearly 158 million nucleotides of DNA and 1917 gene structures, are presented. To generate a higher order description, additional structural features such as imprinted genes, fragile sites, and segmental duplications were integrated at the level of the DNA sequence with medical genetic data, including 440 chromosome rearrangement breakpoints associated with disease. This approach enabled the discovery of candidate gene...
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Directory of Open Access Journals (Sweden)
Leyla Garcia
2014-02-01
Full Text Available Summary: FeatureViewer is a BioJS component that lays out, maps, orients, and renders position-based annotations for protein sequences. This component is highly flexible and customizable, allowing the presentation of annotations by rows, all centered, or distributed in non-overlapping tracks. It uses either lines or shapes for sites and rectangles for regions. The result is a powerful visualization tool that can be easily integrated into web applications as well as documents as it provides an export-to-image functionality. Availability: https://github.com/biojs/biojs/blob/master/src/main/javascript/Biojs.FeatureViewer.js; http://dx.doi.org/10.5281/zenodo.7719
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Inequalities Involving Upper Bounds for Certain Matrix Operators
Indian Academy of Sciences (India)
Home; Journals; Proceedings – Mathematical Sciences; Volume 116; Issue 3. Inequalities Involving Upper Bounds for Certain Matrix Operators. R Lashkaripour D Foroutannia. Volume ... Keywords. Inequality; norm; summability matrix; Hausdorff matrix; Hilbert matrix; weighted sequence space; Lorentz sequence space.
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Petersen, Bent; Lundegaard, Claus; Petersen, Thomas Nordahl
2010-01-01
β-turns are the most common type of non-repetitive structures, and constitute on average 25% of the amino acids in proteins. The formation of β-turns plays an important role in protein folding, protein stability and molecular recognition processes. In this work we present the neural network method NetTurnP, for prediction of two-class β-turns and prediction of the individual β-turn types, by use of evolutionary information and predicted protein sequence features. It has been evaluated against a commonly used dataset BT426, and achieves a Matthews correlation coefficient of 0.50, which is the highest reported performance on a two-class prediction of β-turn and not-β-turn. Furthermore NetTurnP shows improved performance on some of the specific β-turn types. In the present work, neural network methods have been trained to predict β-turn or not and individual β-turn types from the primary amino acid sequence. The individual β-turn types I, I', II, II', VIII, VIa1, VIa2, VIba and IV have been predicted based on classifications by PROMOTIF, and the two-class prediction of β-turn or not is a superset comprised of all β-turn types. The performance is evaluated using a golden set of non-homologous sequences known as BT426. Our two-class prediction method achieves a performance of: MCC = 0.50, Qtotal = 82.1%, sensitivity = 75.6%, PPV = 68.8% and AUC = 0.864. We have compared our performance to eleven other prediction methods that obtain Matthews correlation coefficients in the range of 0.17 – 0.47. For the type specific β-turn predictions, only type I and II can be predicted with reasonable Matthews correlation coefficients, where we obtain performance values of 0.36 and 0.31, respectively. Conclusion The NetTurnP method has been implemented as a webserver, which is freely available at http://www.cbs.dtu.dk/services/NetTurnP/. NetTurnP is the only available webserver that allows submission of multiple sequences. PMID:21152409
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Genome features of "Dark-fly", a Drosophila line reared long-term in a dark environment.
Directory of Open Access Journals (Sweden)
Minako Izutsu
Full Text Available Organisms are remarkably adapted to diverse environments by specialized metabolisms, morphology, or behaviors. To address the molecular mechanisms underlying environmental adaptation, we have utilized a Drosophila melanogaster line, termed "Dark-fly", which has been maintained in constant dark conditions for 57 years (1400 generations. We found that Dark-fly exhibited higher fecundity in dark than in light conditions, indicating that Dark-fly possesses some traits advantageous in darkness. Using next-generation sequencing technology, we determined the whole genome sequence of Dark-fly and identified approximately 220,000 single nucleotide polymorphisms (SNPs and 4,700 insertions or deletions (InDels in the Dark-fly genome compared to the genome of the Oregon-R-S strain, a control strain. 1.8% of SNPs were classified as non-synonymous SNPs (nsSNPs: i.e., they alter the amino acid sequence of gene products. Among them, we detected 28 nonsense mutations (i.e., they produce a stop codon in the protein sequence in the Dark-fly genome. These included genes encoding an olfactory receptor and a light receptor. We also searched runs of homozygosity (ROH regions as putative regions selected during the population history, and found 21 ROH regions in the Dark-fly genome. We identified 241 genes carrying nsSNPs or InDels in the ROH regions. These include a cluster of alpha-esterase genes that are involved in detoxification processes. Furthermore, analysis of structural variants in the Dark-fly genome showed the deletion of a gene related to fatty acid metabolism. Our results revealed unique features of the Dark-fly genome and provided a list of potential candidate genes involved in environmental adaptation.
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Formulaic Sequences and the Implications for Second Language Learning
Xu, Qi
2016-01-01
The present paper is a review of literature in relation to formulaic sequences and the implications for second language learning. The formulaic sequence is a significant part of our language, and plays an essential role in both first and second language learning. The paper first introduces the definition, classifications, and major features of…
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Directory of Open Access Journals (Sweden)
Bastiaan A van den Berg
Full Text Available Protein sequence features are explored in relation to the production of over-expressed extracellular proteins by fungi. Knowledge on features influencing protein production and secretion could be employed to improve enzyme production levels in industrial bioprocesses via protein engineering. A large set, over 600 homologous and nearly 2,000 heterologous fungal genes, were overexpressed in Aspergillus niger using a standardized expression cassette and scored for high versus no production. Subsequently, sequence-based machine learning techniques were applied for identifying relevant DNA and protein sequence features. The amino-acid composition of the protein sequence was found to be most predictive and interpretation revealed that, for both homologous and heterologous gene expression, the same features are important: tyrosine and asparagine composition was found to have a positive correlation with high-level production, whereas for unsuccessful production, contributions were found for methionine and lysine composition. The predictor is available online at http://bioinformatics.tudelft.nl/hipsec. Subsequent work aims at validating these findings by protein engineering as a method for increasing expression levels per gene copy.
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Processes involved in solving mathematical problems
Shahrill, Masitah; Putri, Ratu Ilma Indra; Zulkardi, Prahmana, Rully Charitas Indra
2018-04-01
This study examines one of the instructional practices features utilized within the Year 8 mathematics lessons in Brunei Darussalam. The codes from the TIMSS 1999 Video Study were applied and strictly followed, and from the 183 mathematics problems recorded, there were 95 problems with a solution presented during the public segments of the video-recorded lesson sequences of the four sampled teachers. The analyses involved firstly, identifying the processes related to mathematical problem statements, and secondly, examining the different processes used in solving the mathematical problems for each problem publicly completed during the lessons. The findings revealed that for three of the teachers, their problem statements coded as `using procedures' ranged from 64% to 83%, while the remaining teacher had 40% of his problem statements coded as `making connections.' The processes used when solving the problems were mainly `using procedures', and none of the problems were coded as `giving results only'. Furthermore, all four teachers made use of making the relevant connections in solving the problems given to their respective students.
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Zhao, Xiaowei; Ning, Qiao; Ai, Meiyue; Chai, Haiting; Yang, Guifu
2016-06-07
As a selective and reversible protein post-translational modification, S-glutathionylation generates mixed disulfides between glutathione (GSH) and cysteine residues, and plays an important role in regulating protein activity, stability, and redox regulation. To fully understand S-glutathionylation mechanisms, identification of substrates and specific S-Glutathionylated sites is crucial. Experimental identification of S-glutathionylated sites is labor-intensive and time consuming, so establishing an effective computational method is much desirable due to their convenient and fast speed. Therefore, in this study, a new bioinformatics tool named SSGlu (Species-Specific identification of Protein S-glutathionylation Sites) was developed to identify species-specific protein S-glutathionylated sites, utilizing support vector machines that combine multiple sequence-derived features with a two-step feature selection. By 5-fold cross validation, the performance of SSGlu was measured with an AUC of 0.8105 and 0.8041 for Homo sapiens and Mus musculus, respectively. Additionally, SSGlu was compared with the existing methods, and the higher MCC and AUC of SSGlu demonstrated that SSGlu was very promising to predict S-glutathionylated sites. Furthermore, a site-specific analysis showed that S-glutathionylation intimately correlated with the features derived from its surrounding sites. The conclusions derived from this study might help to understand more of the S-glutathionylation mechanism and guide the related experimental validation. For public access, SSGlu is freely accessible at http://59.73.198.144:8080/SSGlu/. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Yang, Hongxin; Su, Fulin
2018-01-01
We propose a moving target analysis algorithm using speeded-up robust features (SURF) and regular moment in inverse synthetic aperture radar (ISAR) image sequences. In our study, we first extract interest points from ISAR image sequences by SURF. Different from traditional feature point extraction methods, SURF-based feature points are invariant to scattering intensity, target rotation, and image size. Then, we employ a bilateral feature registering model to match these feature points. The feature registering scheme can not only search the isotropic feature points to link the image sequences but also reduce the error matching pairs. After that, the target centroid is detected by regular moment. Consequently, a cost function based on correlation coefficient is adopted to analyze the motion information. Experimental results based on simulated and real data validate the effectiveness and practicability of the proposed method.
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Implicit sequence learning in people with Parkinson’s disease
Directory of Open Access Journals (Sweden)
Katherine R Gamble
2014-08-01
Full Text Available Implicit sequence learning involves learning about dependencies in sequences of events without intent to learn or awareness of what has been learned. Sequence learning is related to striatal dopamine levels, striatal activation, and integrity of white matter connections. People with Parkinson’s disease (PD have degeneration of dopamine-producing neurons, leading to dopamine deficiency and therefore striatal deficits, and they have difficulties with sequencing, including complex language comprehension and postural stability. Most research on implicit sequence learning in PD has used motor-based tasks. However, because PD presents with motor deficits, it is difficult to assess whether learning itself is impaired in these tasks. The present study used an implicit sequence learning task with a reduced motor component, the Triplets Learning Task (TLT. People with PD and age- and education-matched healthy older adults completed three sessions (each consisting of 10 blocks of 50 trials of the TLT. Results revealed that the PD group was able to learn the sequence, however, when learning was examined using a Half Blocks analysis (Nemeth et al., 2013, which compared learning in the 1st 25/50 trials of all blocks to that in the 2nd 25/50 trials, the PD group showed significantly less learning than Controls in the 2nd Half Blocks, but not in the 1st. Nemeth et al. hypothesized that the 1st Half Blocks involve recall and reactivation of the sequence learned, thus reflecting hippocampal-dependent learning, while the 2nd Half Blocks involve proceduralized behavior of learned sequences, reflecting striatal-based learning. The present results suggest that the PD group had intact hippocampal-dependent implicit sequence learning, but impaired striatal-dependent learning. Thus, sequencing deficits in PD are likely due to striatal impairments, but other brain systems, such as the hippocampus, may be able to partially compensate for striatal decline to improve
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Directory of Open Access Journals (Sweden)
Peek Andrew S
2007-06-01
Full Text Available Abstract Background RNA interference (RNAi is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathways. To dissect the factors that result in effective siRNA sequences a regression kernel Support Vector Machine (SVM approach was used to quantitatively model RNA interference activities. Results Eight overall feature mapping methods were compared in their abilities to build SVM regression models that predict published siRNA activities. The primary factors in predictive SVM models are position specific nucleotide compositions. The secondary factors are position independent sequence motifs (N-grams and guide strand to passenger strand sequence thermodynamics. Finally, the factors that are least contributory but are still predictive of efficacy are measures of intramolecular guide strand secondary structure and target strand secondary structure. Of these, the site of the 5' most base of the guide strand is the most informative. Conclusion The capacity of specific feature mapping methods and their ability to build predictive models of RNAi activity suggests a relative biological importance of these features. Some feature mapping methods are more informative in building predictive models and overall t-test filtering provides a method to remove some noisy features or make comparisons among datasets. Together, these features can yield predictive SVM regression models with increased predictive accuracy between predicted and observed activities both within datasets by cross validation, and between independently collected RNAi activity datasets. Feature filtering to remove features should be approached carefully in that it is possible to reduce feature set size without substantially reducing predictive models, but the features retained in the candidate models become increasingly distinct. Software to perform feature prediction and SVM training and testing on nucleic acid
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Taxonomic evaluation of selected Ganoderma species and database sequence validation
Directory of Open Access Journals (Sweden)
Suldbold Jargalmaa
2017-07-01
Full Text Available Species in the genus Ganoderma include several ecologically important and pathogenic fungal species whose medicinal and economic value is substantial. Due to the highly similar morphological features within the Ganoderma, identification of species has relied heavily on DNA sequencing using BLAST searches, which are only reliable if the GenBank submissions are accurately labeled. In this study, we examined 113 specimens collected from 1969 to 2016 from various regions in Korea using morphological features and multigene analysis (internal transcribed spacer, translation elongation factor 1-α, and the second largest subunit of RNA polymerase II. These specimens were identified as four Ganoderma species: G. sichuanense, G. cf. adspersum, G. cf. applanatum, and G. cf. gibbosum. With the exception of G. sichuanense, these species were difficult to distinguish based solely on morphological features. However, phylogenetic analysis at three different loci yielded concordant phylogenetic information, and supported the four species distinctions with high bootstrap support. A survey of over 600 Ganoderma sequences available on GenBank revealed that 65% of sequences were either misidentified or ambiguously labeled. Here, we suggest corrected annotations for GenBank sequences based on our phylogenetic validation and provide updated global distribution patterns for these Ganoderma species.
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Taxonomic evaluation of selected Ganoderma species and database sequence validation
Jargalmaa, Suldbold; Eimes, John A.; Park, Myung Soo; Park, Jae Young; Oh, Seung-Yoon
2017-01-01
Species in the genus Ganoderma include several ecologically important and pathogenic fungal species whose medicinal and economic value is substantial. Due to the highly similar morphological features within the Ganoderma, identification of species has relied heavily on DNA sequencing using BLAST searches, which are only reliable if the GenBank submissions are accurately labeled. In this study, we examined 113 specimens collected from 1969 to 2016 from various regions in Korea using morphological features and multigene analysis (internal transcribed spacer, translation elongation factor 1-α, and the second largest subunit of RNA polymerase II). These specimens were identified as four Ganoderma species: G. sichuanense, G. cf. adspersum, G. cf. applanatum, and G. cf. gibbosum. With the exception of G. sichuanense, these species were difficult to distinguish based solely on morphological features. However, phylogenetic analysis at three different loci yielded concordant phylogenetic information, and supported the four species distinctions with high bootstrap support. A survey of over 600 Ganoderma sequences available on GenBank revealed that 65% of sequences were either misidentified or ambiguously labeled. Here, we suggest corrected annotations for GenBank sequences based on our phylogenetic validation and provide updated global distribution patterns for these Ganoderma species. PMID:28761785
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DNA breaks and repair in interstitial telomere sequences: Influence of chromatin structure
International Nuclear Information System (INIS)
Revaud, D.
2009-06-01
Interstitial Telomeric Sequences (ITS) are over-involved in spontaneous and radiationinduced chromosome aberrations in chinese hamster cells. We have performed a study to investigate the origin of their instability, spontaneously or after low doses irradiation. Our results demonstrate that ITS have a particular chromatin structure: short nucleotide repeat length, less compaction of the 30 nm chromatin fiber, presence of G-quadruplex structures. These features would modulate breaks production and would favour the recruitment of alternative DNA repair mechanisms, which are prone to produce chromosome aberrations. These pathways could be at the origin of chromosome aberrations in ITS whereas NHEJ and HR Double Strand Break repair pathways are rather required for a correct repair in these regions. (author)
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Analyzing State Sequences with Probabilistic Suffix Trees: The PST R Package
Directory of Open Access Journals (Sweden)
Alexis Gabadinho
2016-08-01
Full Text Available This article presents the PST R package for categorical sequence analysis with probabilistic suffix trees (PSTs, i.e., structures that store variable-length Markov chains (VLMCs. VLMCs allow to model high-order dependencies in categorical sequences with parsimonious models based on simple estimation procedures. The package is specifically adapted to the field of social sciences, as it allows for VLMC models to be learned from sets of individual sequences possibly containing missing values; in addition, the package is extended to account for case weights. This article describes how a VLMC model is learned from one or more categorical sequences and stored in a PST. The PST can then be used for sequence prediction, i.e., to assign a probability to whole observed or artificial sequences. This feature supports data mining applications such as the extraction of typical patterns and outliers. This article also introduces original visualization tools for both the model and the outcomes of sequence prediction. Other features such as functions for pattern mining and artificial sequence generation are described as well. The PST package also allows for the computation of probabilistic divergence between two models and the fitting of segmented VLMCs, where sub-models fitted to distinct strata of the learning sample are stored in a single PST.
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Identification of sequence motifs significantly associated with antisense activity
Directory of Open Access Journals (Sweden)
Peek Andrew S
2007-06-01
Full Text Available Abstract Background Predicting the suppression activity of antisense oligonucleotide sequences is the main goal of the rational design of nucleic acids. To create an effective predictive model, it is important to know what properties of an oligonucleotide sequence associate significantly with antisense activity. Also, for the model to be efficient we must know what properties do not associate significantly and can be omitted from the model. This paper will discuss the results of a randomization procedure to find motifs that associate significantly with either high or low antisense suppression activity, analysis of their properties, as well as the results of support vector machine modelling using these significant motifs as features. Results We discovered 155 motifs that associate significantly with high antisense suppression activity and 202 motifs that associate significantly with low suppression activity. The motifs range in length from 2 to 5 bases, contain several motifs that have been previously discovered as associating highly with antisense activity, and have thermodynamic properties consistent with previous work associating thermodynamic properties of sequences with their antisense activity. Statistical analysis revealed no correlation between a motif's position within an antisense sequence and that sequences antisense activity. Also, many significant motifs existed as subwords of other significant motifs. Support vector regression experiments indicated that the feature set of significant motifs increased correlation compared to all possible motifs as well as several subsets of the significant motifs. Conclusion The thermodynamic properties of the significantly associated motifs support existing data correlating the thermodynamic properties of the antisense oligonucleotide with antisense efficiency, reinforcing our hypothesis that antisense suppression is strongly associated with probe/target thermodynamics, as there are no enzymatic
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Supervised Learning for Detection of Duplicates in Genomic Sequence Databases.
Directory of Open Access Journals (Sweden)
Qingyu Chen
Full Text Available First identified as an issue in 1996, duplication in biological databases introduces redundancy and even leads to inconsistency when contradictory information appears. The amount of data makes purely manual de-duplication impractical, and existing automatic systems cannot detect duplicates as precisely as can experts. Supervised learning has the potential to address such problems by building automatic systems that learn from expert curation to detect duplicates precisely and efficiently. While machine learning is a mature approach in other duplicate detection contexts, it has seen only preliminary application in genomic sequence databases.We developed and evaluated a supervised duplicate detection method based on an expert curated dataset of duplicates, containing over one million pairs across five organisms derived from genomic sequence databases. We selected 22 features to represent distinct attributes of the database records, and developed a binary model and a multi-class model. Both models achieve promising performance; under cross-validation, the binary model had over 90% accuracy in each of the five organisms, while the multi-class model maintains high accuracy and is more robust in generalisation. We performed an ablation study to quantify the impact of different sequence record features, finding that features derived from meta-data, sequence identity, and alignment quality impact performance most strongly. The study demonstrates machine learning can be an effective additional tool for de-duplication of genomic sequence databases. All Data are available as described in the supplementary material.
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Supervised Learning for Detection of Duplicates in Genomic Sequence Databases.
Chen, Qingyu; Zobel, Justin; Zhang, Xiuzhen; Verspoor, Karin
2016-01-01
First identified as an issue in 1996, duplication in biological databases introduces redundancy and even leads to inconsistency when contradictory information appears. The amount of data makes purely manual de-duplication impractical, and existing automatic systems cannot detect duplicates as precisely as can experts. Supervised learning has the potential to address such problems by building automatic systems that learn from expert curation to detect duplicates precisely and efficiently. While machine learning is a mature approach in other duplicate detection contexts, it has seen only preliminary application in genomic sequence databases. We developed and evaluated a supervised duplicate detection method based on an expert curated dataset of duplicates, containing over one million pairs across five organisms derived from genomic sequence databases. We selected 22 features to represent distinct attributes of the database records, and developed a binary model and a multi-class model. Both models achieve promising performance; under cross-validation, the binary model had over 90% accuracy in each of the five organisms, while the multi-class model maintains high accuracy and is more robust in generalisation. We performed an ablation study to quantify the impact of different sequence record features, finding that features derived from meta-data, sequence identity, and alignment quality impact performance most strongly. The study demonstrates machine learning can be an effective additional tool for de-duplication of genomic sequence databases. All Data are available as described in the supplementary material.
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A DNA Structure-Based Bionic Wavelet Transform and Its Application to DNA Sequence Analysis
Directory of Open Access Journals (Sweden)
Fei Chen
2003-01-01
Full Text Available DNA sequence analysis is of great significance for increasing our understanding of genomic functions. An important task facing us is the exploration of hidden structural information stored in the DNA sequence. This paper introduces a DNA structure-based adaptive wavelet transform (WT – the bionic wavelet transform (BWT – for DNA sequence analysis. The symbolic DNA sequence can be separated into four channels of indicator sequences. An adaptive symbol-to-number mapping, determined from the structural feature of the DNA sequence, was introduced into WT. It can adjust the weight value of each channel to maximise the useful energy distribution of the whole BWT output. The performance of the proposed BWT was examined by analysing synthetic and real DNA sequences. Results show that BWT performs better than traditional WT in presenting greater energy distribution. This new BWT method should be useful for the detection of the latent structural features in future DNA sequence analysis.
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Directory of Open Access Journals (Sweden)
Lunbiao Cui
2010-01-01
Full Text Available Role of microRNA (miRNA has been highlighted in pathogen-host interactions recently. To identify cellular miRNAs involved in the host response to enterovirus 71 (EV71 infection, we performed a comprehensive miRNA profiling in EV71-infected Hep2 cells through deep sequencing. 64 miRNAs were found whose expression levels changed for more than 2-fold in response to EV71 infection. Gene ontology analysis revealed that many of these mRNAs play roles in neurological process, immune response, and cell death pathways, which are known to be associated with the extreme virulence of EV71. To our knowledge, this is the first study on host miRNAs expression alteration response to EV71 infection. Our findings supported the hypothesis that certain miRNAs might be essential in the host-pathogen interactions.
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International Nuclear Information System (INIS)
Baloch, M.J.; Jatoi, W.A.
2012-01-01
Physiological and yield traits such as stomatal conductance (mmol m-/sup 2/s/sup -1/), Leaf relative water content (RWC %) and grain yield per plant were studied in a separate experiment. Results revealed that five out of sixteen cultivars viz. Anmol, Moomal, Sarsabz, Bhitai and Pavan, appeared to be relatively more drought tolerant. Based on morphophysiological results, studies were continued to look at these cultivars for drought tolerance at molecular level. Initially, four well recognized primers for dehydrin genes (DHNs) responsible for drought induction in T. durum L., T. aestivum L. and O. sativa L. were used for profiling gene sequence of sixteen wheat cultivars. The primers amplified the DHN genes variably like Primer WDHN13 (T. aestivum L.) amplified the DHN gene in only seven cultivars whereas primer TdDHN15 ( T. durum L.) amplified all the sixteen cultivars with even different DNA banding patterns some showing second weaker DNA bands. Third primer TdDHN16 (T. durum L.) has shown entirely different PCR amplification prototype, specially showing two strong DNA bands while fourth primer RAB16C (O. sativa L.) failed to amplify DHN gene in any of the cultivars. Examination of DNA sequences revealed several interesting features. First, it identified the two exon/one intron structure of this gene (complete sequences were not shown), a feature not previously described in the two database cDNA sequences available from T. aestivum L. (gi|21850). Secondly, the analysis identified several single nucleotide polymorphisms (SNPs), positions in gene sequence. Although complete gene sequence was not obtained for all the cultivars, yet there were a total of 38 variable positions in exonic (coding region) sequence, from a total gene length of 453 nucleotides. Matrix of SNP shows these 37 positions with individual sequence at positions given for each of the 14 cultivars (sequence of two cultivars was not obtained) included in this analysis. It demonstrated a considerab le
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Prediction of human protein function from post-translational modifications and localization features
DEFF Research Database (Denmark)
Jensen, Lars Juhl; Gupta, Ramneek; Blom, Nikolaj
2002-01-01
a number of functional attributes that are more directly related to the linear sequence of amino acids, and hence easier to predict, than protein structure. These attributes include features associated with post-translational modifications and protein sorting, but also much simpler aspects......We have developed an entirely sequence-based method that identifies and integrates relevant features that can be used to assign proteins of unknown function to functional classes, and enzyme categories for enzymes. We show that strategies for the elucidation of protein function may benefit from...
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Directory of Open Access Journals (Sweden)
Guziolowski Carito
2007-09-01
Full Text Available Abstract Background: We present the N-map method, a pairwise and asymmetrical approach which allows us to compare sequences by taking into account evolutionary events that produce shuffled, reversed or repeated elements. Basically, the optimal N-map of a sequence s over a sequence t is the best way of partitioning the first sequence into N parts and placing them, possibly complementary reversed, over the second sequence in order to maximize the sum of their gapless alignment scores. Results: We introduce an algorithm computing an optimal N-map with time complexity O (|s| × |t| × N using O (|s| × |t| × N memory space. Among all the numbers of parts taken in a reasonable range, we select the value N for which the optimal N-map has the most significant score. To evaluate this significance, we study the empirical distributions of the scores of optimal N-maps and show that they can be approximated by normal distributions with a reasonable accuracy. We test the functionality of the approach over random sequences on which we apply artificial evolutionary events. Practical Application: The method is illustrated with four case studies of pairs of sequences involving non-standard evolutionary events.
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Functionality of system components: Conservation of protein function in protein feature space
DEFF Research Database (Denmark)
Jensen, Lars Juhl; Ussery, David; Brunak, Søren
2003-01-01
well on organisms other than the one on which it was trained. We evaluate the performance of such a method, ProtFun, which relies on protein features as its sole input, and show that the method gives similar performance for most eukaryotes and performs much better than anticipated on archaea......Many protein features useful for prediction of protein function can be predicted from sequence, including posttranslational modifications, subcellular localization, and physical/chemical properties. We show here that such protein features are more conserved among orthologs than paralogs, indicating...... they are crucial for protein function and thus subject to selective pressure. This means that a function prediction method based on sequence-derived features may be able to discriminate between proteins with different function even when they have highly similar structure. Also, such a method is likely to perform...
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Invariant properties between stroke features in handwriting
Teulings, H L; Schomaker, L R
A handwriting pattern is considered as a sequence of ballistic strokes. Replications of a pattern may be generated from a single, higher-level memory representation, acting as a motor program. Therefore, those stroke features which show the most invariant pattern are probably related to the
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Directory of Open Access Journals (Sweden)
Hee Jeong Yoo
2015-03-01
Full Text Available Rubinstein-Taybi syndrome (RSTS is a rare condition with a prevalence of 1 in 125,000–720,000 births and characterized by clinical features that include facial, dental, and limb dysmorphology and growth retardation. Most cases of RSTS occur sporadically and are caused by de novo mutations. Cytogenetic or molecular abnormalities are detected in only 55% of RSTS cases. Previous genetic studies have yielded inconsistent results due to the variety of methods used for genetic analysis. The purpose of this study was to use whole exome sequencing (WES to evaluate the genetic causes of RSTS in a young girl presenting with an Autism phenotype. We used the Autism diagnostic observation schedule (ADOS and Autism diagnostic interview revised (ADI-R to confirm her diagnosis of Autism. In addition, various questionnaires were used to evaluate other psychiatric features. We used WES to analyze the DNA sequences of the patient and her parents and to search for de novo variants. The patient showed all the typical features of Autism, WES revealed a de novo frameshift mutation in CREBBP and de novo sequence variants in TNC and IGFALS genes. Mutations in the CREBBP gene have been extensively reported in RSTS patients, while potential missense mutations in TNC and IGFALS genes have not previously been associated with RSTS. The TNC and IGFALS genes are involved in central nervous system development and growth. It is possible for patients with RSTS to have additional de novo variants that could account for previously unexplained phenotypes.
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Results of the event sequence reliability benchmark exercise
International Nuclear Information System (INIS)
Silvestri, E.
1990-01-01
The Event Sequence Reliability Benchmark Exercise is the fourth of a series of benchmark exercises on reliability and risk assessment, with specific reference to nuclear power plant applications, and is the logical continuation of the previous benchmark exercises on System Analysis Common Cause Failure and Human Factors. The reference plant is the Nuclear Power Plant at Grohnde Federal Republic of Germany a 1300 MW PWR plant of KWU design. The specific objective of the Exercise is to model, to quantify and to analyze such event sequences initiated by the occurrence of a loss of offsite power that involve the steam generator feed. The general aim is to develop a segment of a risk assessment, which ought to include all the specific aspects and models of quantification, such as common canal failure, Human Factors and System Analysis, developed in the previous reliability benchmark exercises, with the addition of the specific topics of dependences between homologous components belonging to different systems featuring in a given event sequence and of uncertainty quantification, to end up with an overall assessment of: - the state of the art in risk assessment and the relative influences of quantification problems in a general risk assessment framework. The Exercise has been carried out in two phases, both requiring modelling and quantification, with the second phase adopting more restrictive rules and fixing certain common data, as emerged necessary from the first phase. Fourteen teams have participated in the Exercise mostly from EEC countries, with one from Sweden and one from the USA. (author)
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Plann: A command-line application for annotating plastome sequences.
Huang, Daisie I; Cronk, Quentin C B
2015-08-01
Plann automates the process of annotating a plastome sequence in GenBank format for either downstream processing or for GenBank submission by annotating a new plastome based on a similar, well-annotated plastome. Plann is a Perl script to be executed on the command line. Plann compares a new plastome sequence to the features annotated in a reference plastome and then shifts the intervals of any matching features to the locations in the new plastome. Plann's output can be used in the National Center for Biotechnology Information's tbl2asn to create a Sequin file for GenBank submission. Unlike Web-based annotation packages, Plann is a locally executable script that will accurately annotate a plastome sequence to a locally specified reference plastome. Because it executes from the command line, it is ready to use in other software pipelines and can be easily rerun as a draft plastome is improved.
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Context-dependent motor skill: perceptual processing in memory-based sequence production
Ruitenberg, M.F.L.; Abrahamse, E.L.; de Kleine, Elian; Verwey, Willem B.
2012-01-01
Previous studies have shown that motor sequencing skill can benefit from the reinstatement of the learning context—even with respect to features that are formally not required for appropriate task performance. The present study explored whether such context-dependence develops when sequence
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Occupational Sequences: Auto Engines 1. AT 121.
Korb, A. W.; And Others
In an attempt to individualize an automotive course, the Vocational-Technical Division of Northern Montana College has developed Occupational Sequences for an engine rebuilding course. Occupational Sequences, a learning or teaching aid, is an analysis of numbered operations involved in engine rebuilding. Job sheets, included in the book, provide a…
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Meningeal involvement in Behcet's disease: MRI
International Nuclear Information System (INIS)
Guma, A.; Aguilera, C.; Pons, L.; Acebes, J.; Arruga, J.
1998-01-01
Behcet's disease is a multisystem disease that involves the central nervous system up to half of cases. Presentation with neurologic symptoms occurs in 5 % of cases and cerebral venous thrombosis is one of its major manifestations. A feature not previously reported is progressive meningeal thickening with involvement of both optic nerves. We report a patient with cerebral venous thrombosis, meningeal thickening and contrast enhancement on MRI. This patient had two other unusual features: positive antineutrophil cytoplasmic antibodies and later development of central diabetes insipidus. (orig.)
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Interplay of a multiplicity of security features
Moser, Jean-Frederic
2000-04-01
The great variety of existing security features can cause difficulty in choosing the adequate set for a particular security document. Considering the cost/benefit aspects with respect to the overall protection performance requested, a choice has to be made, for example, between either few features of high-security value or numerous many, less- resistant features. Another choice is the high versus low complexity of one particular features. A study aimed at providing a decision basis is a challenging matter because it involves human factors. Attention, perception, physiology of seeing and habits - to name some of the factors - are intangibles and are subject to evaluations involving normally a great number of experiments, if they are to be representative. The opportunity was given for a case study with the introduction of new Swiss banknotes between 1995 and 1998, because the new banknotes represent a novelty in the sense of the multiplicity and interplay of its optical security features. We have analyzed 652 articles which appeared in the press media concerning the new banknotes, seeking especially for peoples' reaction towards the security features.
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Multiple Repair Sequences in Everyday Conversations Involving People with Parkinson's Disease
Griffiths, Sarah; Barnes, Rebecca; Britten, Nicky; Wilkinson, Ray
2015-01-01
Background: Features of dysarthria associated with Parkinson's disease (PD), such as low volume, variable rate of speech and increased pauses, impact speaker intelligibility. Those affected report restricted interactional participation, although this area is under explored. Aims: To examine naturally occurring instances of problems with…
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Decrease in gamma-band activity tracks sequence learning
Madhavan, Radhika; Millman, Daniel; Tang, Hanlin; Crone, Nathan E.; Lenz, Fredrick A.; Tierney, Travis S.; Madsen, Joseph R.; Kreiman, Gabriel; Anderson, William S.
2015-01-01
Learning novel sequences constitutes an example of declarative memory formation, involving conscious recall of temporal events. Performance in sequence learning tasks improves with repetition and involves forming temporal associations over scales of seconds to minutes. To further understand the neural circuits underlying declarative sequence learning over trials, we tracked changes in intracranial field potentials (IFPs) recorded from 1142 electrodes implanted throughout temporal and frontal cortical areas in 14 human subjects, while they learned the temporal-order of multiple sequences of images over trials through repeated recall. We observed an increase in power in the gamma frequency band (30–100 Hz) in the recall phase, particularly in areas within the temporal lobe including the parahippocampal gyrus. The degree of this gamma power enhancement decreased over trials with improved sequence recall. Modulation of gamma power was directly correlated with the improvement in recall performance. When presenting new sequences, gamma power was reset to high values and decreased again after learning. These observations suggest that signals in the gamma frequency band may play a more prominent role during the early steps of the learning process rather than during the maintenance of memory traces. PMID:25653598
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Application of eigen value expansion to feature extraction from MRI images
International Nuclear Information System (INIS)
Kinosada, Yasutomi; Takeda, Kan; Nakagawa, Tsuyoshi
1991-01-01
The eigen value expansion technique was utilized for feature extraction of magnetic resonance (MR) images. The eigen value expansion is an orthonormal transformation method which decomposes a set of images into some statistically uncorrelated images. The technique was applied to MR images obtained with various imaging parameters at the same anatomical site. It generated one mean image and another set of images called bases for the images. Each basis corresponds to a feature in the images. A basis is, therefore, utilized for the feature extraction from MR images and a weighted sum of bases is also used for the feature enhancement. Furthermore, any MR image with specific feature can be obtained from a linear combination of the mean image and all of the bases. Images of hemorrhaged brain with a spin echo sequence and a series of cinematic cerebro spinal fluid flow images with ECG gated gradient refocused echo sequence were employed to estimate the ability of the feature extraction and the contrast enhancement. Results showed us that proposed application of an eigen value expansion technique to the feature extraction of MR images is good enough to clinical use and superior to other feature extraction methods such as producing a calculated MR image with a given TR and TE or the matched-filter method in processing speed and reproducibility of results. (author)
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Kandaswamy, Krishna Kumar
2011-08-17
Background: Bioluminescence is a process in which light is emitted by a living organism. Most creatures that emit light are sea creatures, but some insects, plants, fungi etc, also emit light. The biotechnological application of bioluminescence has become routine and is considered essential for many medical and general technological advances. Identification of bioluminescent proteins is more challenging due to their poor similarity in sequence. So far, no specific method has been reported to identify bioluminescent proteins from primary sequence.Results: In this paper, we propose a novel predictive method that uses a Support Vector Machine (SVM) and physicochemical properties to predict bioluminescent proteins. BLProt was trained using a dataset consisting of 300 bioluminescent proteins and 300 non-bioluminescent proteins, and evaluated by an independent set of 141 bioluminescent proteins and 18202 non-bioluminescent proteins. To identify the most prominent features, we carried out feature selection with three different filter approaches, ReliefF, infogain, and mRMR. We selected five different feature subsets by decreasing the number of features, and the performance of each feature subset was evaluated.Conclusion: BLProt achieves 80% accuracy from training (5 fold cross-validations) and 80.06% accuracy from testing. The performance of BLProt was compared with BLAST and HMM. High prediction accuracy and successful prediction of hypothetical proteins suggests that BLProt can be a useful approach to identify bioluminescent proteins from sequence information, irrespective of their sequence similarity. 2011 Kandaswamy et al; licensee BioMed Central Ltd.
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Kandaswamy, Krishna Kumar; Pugalenthi, Ganesan; Hazrati, Mehrnaz Khodam; Kalies, Kai-Uwe; Martinetz, Thomas
2011-01-01
Background: Bioluminescence is a process in which light is emitted by a living organism. Most creatures that emit light are sea creatures, but some insects, plants, fungi etc, also emit light. The biotechnological application of bioluminescence has become routine and is considered essential for many medical and general technological advances. Identification of bioluminescent proteins is more challenging due to their poor similarity in sequence. So far, no specific method has been reported to identify bioluminescent proteins from primary sequence.Results: In this paper, we propose a novel predictive method that uses a Support Vector Machine (SVM) and physicochemical properties to predict bioluminescent proteins. BLProt was trained using a dataset consisting of 300 bioluminescent proteins and 300 non-bioluminescent proteins, and evaluated by an independent set of 141 bioluminescent proteins and 18202 non-bioluminescent proteins. To identify the most prominent features, we carried out feature selection with three different filter approaches, ReliefF, infogain, and mRMR. We selected five different feature subsets by decreasing the number of features, and the performance of each feature subset was evaluated.Conclusion: BLProt achieves 80% accuracy from training (5 fold cross-validations) and 80.06% accuracy from testing. The performance of BLProt was compared with BLAST and HMM. High prediction accuracy and successful prediction of hypothetical proteins suggests that BLProt can be a useful approach to identify bioluminescent proteins from sequence information, irrespective of their sequence similarity. 2011 Kandaswamy et al; licensee BioMed Central Ltd.
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Ruiz-Blanco, Yasser B; Paz, Waldo; Green, James; Marrero-Ponce, Yovani
2015-05-16
The exponential growth of protein structural and sequence databases is enabling multifaceted approaches to understanding the long sought sequence-structure-function relationship. Advances in computation now make it possible to apply well-established data mining and pattern recognition techniques to these data to learn models that effectively relate structure and function. However, extracting meaningful numerical descriptors of protein sequence and structure is a key issue that requires an efficient and widely available solution. We here introduce ProtDCal, a new computational software suite capable of generating tens of thousands of features considering both sequence-based and 3D-structural descriptors. We demonstrate, by means of principle component analysis and Shannon entropy tests, how ProtDCal's sequence-based descriptors provide new and more relevant information not encoded by currently available servers for sequence-based protein feature generation. The wide diversity of the 3D-structure-based features generated by ProtDCal is shown to provide additional complementary information and effectively completes its general protein encoding capability. As demonstration of the utility of ProtDCal's features, prediction models of N-linked glycosylation sites are trained and evaluated. Classification performance compares favourably with that of contemporary predictors of N-linked glycosylation sites, in spite of not using domain-specific features as input information. ProtDCal provides a friendly and cross-platform graphical user interface, developed in the Java programming language and is freely available at: http://bioinf.sce.carleton.ca/ProtDCal/ . ProtDCal introduces local and group-based encoding which enhances the diversity of the information captured by the computed features. Furthermore, we have shown that adding structure-based descriptors contributes non-redundant additional information to the features-based characterization of polypeptide systems. This
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Jiang, Yi; Liu, Haican; Wang, Xuezhi; Li, Guilian; Qiu, Yan; Dou, Xiangfeng; Wan, Kanglin
2015-01-01
Host immune pressure and associated parasite immune evasion are key features of host-pathogen co-evolution. A previous study showed that human T cell epitopes of Mycobacterium tuberculosis are evolutionarily hyperconserved and thus it was deduced that M. tuberculosis lacks antigenic variation and immune evasion. Here, we selected 151 clinical Mycobacterium tuberculosis isolates from China, amplified gene encoding Rv1977 and compared the sequences. The results showed that Rv1977, a conserved hypothetical protein, is not conserved in M. tuberculosis strains and there are polymorphisms existed in the protein. Some mutations, especially one frameshift mutation, occurred in the antigen Rv1977, which is uncommon in M.tb strains and may lead to the protein function altering. Mutations and deletion in the gene all affect one of three T cell epitopes and the changed T cell epitope contained more than one variable position, which may suggest ongoing immune evasion.
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Biophysical and structural considerations for protein sequence evolution
Directory of Open Access Journals (Sweden)
Grahnen Johan A
2011-12-01
Full Text Available Abstract Background Protein sequence evolution is constrained by the biophysics of folding and function, causing interdependence between interacting sites in the sequence. However, current site-independent models of sequence evolutions do not take this into account. Recent attempts to integrate the influence of structure and biophysics into phylogenetic models via statistical/informational approaches have not resulted in expected improvements in model performance. This suggests that further innovations are needed for progress in this field. Results Here we develop a coarse-grained physics-based model of protein folding and binding function, and compare it to a popular informational model. We find that both models violate the assumption of the native sequence being close to a thermodynamic optimum, causing directional selection away from the native state. Sampling and simulation show that the physics-based model is more specific for fold-defining interactions that vary less among residue type. The informational model diffuses further in sequence space with fewer barriers and tends to provide less support for an invariant sites model, although amino acid substitutions are generally conservative. Both approaches produce sequences with natural features like dN/dS Conclusions Simple coarse-grained models of protein folding can describe some natural features of evolving proteins but are currently not accurate enough to use in evolutionary inference. This is partly due to improper packing of the hydrophobic core. We suggest possible improvements on the representation of structure, folding energy, and binding function, as regards both native and non-native conformations, and describe a large number of possible applications for such a model.
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Schinagl, Carina; Melum, Guro Reinholt; Rødningen, Olaug Kristin; Bjørgo, Kathrine; Andresen, Jannicke Hanne
2017-08-17
Persistent pulmonary hypertension is a well-known disease of the newborn that in most cases responds well to treatment with nitric oxide and treatment of any underlying causes. Genetic causes of persistent pulmonary hypertension of the newborn are rare. The TWIST1 gene is involved in morphogenetics, and deletions are known to cause Saethre-Chotzen syndrome. Deletions of PHF14 have never been reported in neonates, but animal studies have shown a link between severe defects in lung development and deletions of this gene. There have not, to the best of our knowledge, been any publications of a link between the genes TWIST1 and PHF14 and persistent pulmonary hypertension of the newborn, making this a novel finding. We describe a white male neonate born at term to non-consanguineous white parents; he presented with dysmorphic features and a therapy-refractory persistent pulmonary hypertension. Array-based comparative genomic hybridization revealed the presence of a 14.7 Mb interstitial deletion on chromosome 7, encompassing the genes TWIST1 and PHF14. The TWIST1 gene can explain our patient's dysmorphic features. His severe persistent pulmonary hypertension has, however, not been described before in conjunction with the TWIST1 gene, but could be explained by involvement of PHF14, consistent with findings in animal experiments showing lethal respiratory failure with depletion of PHF14. These findings are novel and of importance for the clinical management and diagnostic workup of neonates with severe persistent pulmonary hypertension of the newborn and dysmorphic features.
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Face recognition based on matching of local features on 3D dynamic range sequences
Echeagaray-Patrón, B. A.; Kober, Vitaly
2016-09-01
3D face recognition has attracted attention in the last decade due to improvement of technology of 3D image acquisition and its wide range of applications such as access control, surveillance, human-computer interaction and biometric identification systems. Most research on 3D face recognition has focused on analysis of 3D still data. In this work, a new method for face recognition using dynamic 3D range sequences is proposed. Experimental results are presented and discussed using 3D sequences in the presence of pose variation. The performance of the proposed method is compared with that of conventional face recognition algorithms based on descriptors.
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Massouras, Andreas; Decouttere, Frederik; Hens, Korneel; Deplancke, Bart
2010-07-01
High-throughput sequencing (HTS) is revolutionizing our ability to obtain cheap, fast and reliable sequence information. Many experimental approaches are expected to benefit from the incorporation of such sequencing features in their pipeline. Consequently, software tools that facilitate such an incorporation should be of great interest. In this context, we developed WebPrInSeS, a web server tool allowing automated full-length clone sequence identification and verification using HTS data. WebPrInSeS encompasses two separate software applications. The first is WebPrInSeS-C which performs automated sequence verification of user-defined open-reading frame (ORF) clone libraries. The second is WebPrInSeS-E, which identifies positive hits in cDNA or ORF-based library screening experiments such as yeast one- or two-hybrid assays. Both tools perform de novo assembly using HTS data from any of the three major sequencing platforms. Thus, WebPrInSeS provides a highly integrated, cost-effective and efficient way to sequence-verify or identify clones of interest. WebPrInSeS is available at http://webprinses.epfl.ch/ and is open to all users.
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Massively Parallel Interrogation of Aptamer Sequence, Structure and Function
Energy Technology Data Exchange (ETDEWEB)
Fischer, N O; Tok, J B; Tarasow, T M
2008-02-08
Optimization of high affinity reagents is a significant bottleneck in medicine and the life sciences. The ability to synthetically create thousands of permutations of a lead high-affinity reagent and survey the properties of individual permutations in parallel could potentially relieve this bottleneck. Aptamers are single stranded oligonucleotides affinity reagents isolated by in vitro selection processes and as a class have been shown to bind a wide variety of target molecules. Methodology/Principal Findings. High density DNA microarray technology was used to synthesize, in situ, arrays of approximately 3,900 aptamer sequence permutations in triplicate. These sequences were interrogated on-chip for their ability to bind the fluorescently-labeled cognate target, immunoglobulin E, resulting in the parallel execution of thousands of experiments. Fluorescence intensity at each array feature was well resolved and shown to be a function of the sequence present. The data demonstrated high intra- and interchip correlation between the same features as well as among the sequence triplicates within a single array. Consistent with aptamer mediated IgE binding, fluorescence intensity correlated strongly with specific aptamer sequences and the concentration of IgE applied to the array. The massively parallel sequence-function analyses provided by this approach confirmed the importance of a consensus sequence found in all 21 of the original IgE aptamer sequences and support a common stem:loop structure as being the secondary structure underlying IgE binding. The microarray application, data and results presented illustrate an efficient, high information content approach to optimizing aptamer function. It also provides a foundation from which to better understand and manipulate this important class of high affinity biomolecules.
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Massively parallel interrogation of aptamer sequence, structure and function.
Directory of Open Access Journals (Sweden)
Nicholas O Fischer
Full Text Available BACKGROUND: Optimization of high affinity reagents is a significant bottleneck in medicine and the life sciences. The ability to synthetically create thousands of permutations of a lead high-affinity reagent and survey the properties of individual permutations in parallel could potentially relieve this bottleneck. Aptamers are single stranded oligonucleotides affinity reagents isolated by in vitro selection processes and as a class have been shown to bind a wide variety of target molecules. METHODOLOGY/PRINCIPAL FINDINGS: High density DNA microarray technology was used to synthesize, in situ, arrays of approximately 3,900 aptamer sequence permutations in triplicate. These sequences were interrogated on-chip for their ability to bind the fluorescently-labeled cognate target, immunoglobulin E, resulting in the parallel execution of thousands of experiments. Fluorescence intensity at each array feature was well resolved and shown to be a function of the sequence present. The data demonstrated high intra- and inter-chip correlation between the same features as well as among the sequence triplicates within a single array. Consistent with aptamer mediated IgE binding, fluorescence intensity correlated strongly with specific aptamer sequences and the concentration of IgE applied to the array. CONCLUSION AND SIGNIFICANCE: The massively parallel sequence-function analyses provided by this approach confirmed the importance of a consensus sequence found in all 21 of the original IgE aptamer sequences and support a common stem:loop structure as being the secondary structure underlying IgE binding. The microarray application, data and results presented illustrate an efficient, high information content approach to optimizing aptamer function. It also provides a foundation from which to better understand and manipulate this important class of high affinity biomolecules.
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Sequence and features of the tryptophan operon of Vibrio parahemolyticus.
Crawford, I P; Han, C Y; Silverman, M
1991-01-01
The nucleotide sequence of the trp operon of the marine enteric bacterium Vibrio parahemolyticus is presented. The gene order E, G, D, C(F), B, A is identical to that of other enterics. The structural genes of the operon are preceded by a long leader region encoding a 41-residue peptide containing five tryptophan residues. The organization of the leader region suggests that transcription of the operon is subject to attenuation control. The promoter-operator region of the V. parahemolyticus trp operon is almost identical to the corresponding promoter-operator of E. coli. The similarities suggest that promoter strength and operator function are identical in the two species, and that transcription initiation is regulated by repression. The operon appears to lack the internal promoter within trpD that is common in terrestrial enteric species.
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DEFF Research Database (Denmark)
Petersen, Bent; Lundegaard, Claus; Petersen, Thomas Nordahl
2010-01-01
is the highest reported performance on a two-class prediction of β-turn and not-β-turn. Furthermore NetTurnP shows improved performance on some of the specific β-turn types. In the present work, neural network methods have been trained to predict β-turn or not and individual β-turn types from the primary amino......β-turns are the most common type of non-repetitive structures, and constitute on average 25% of the amino acids in proteins. The formation of β-turns plays an important role in protein folding, protein stability and molecular recognition processes. In this work we present the neural network method...... NetTurnP, for prediction of two-class β-turns and prediction of the individual β-turn types, by use of evolutionary information and predicted protein sequence features. It has been evaluated against a commonly used dataset BT426, and achieves a Matthews correlation coefficient of 0.50, which...
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Directory of Open Access Journals (Sweden)
Jia Wang
2016-10-01
Full Text Available Seed development has a critical role during the spermatophyte life cycle. In Brassica napus, a major oil crop, fatty acids are synthesized and stored in specific tissues during embryogenesis, and understanding the molecular mechanism underlying fatty acid biosynthesis during seed development is an important research goal. In this study, we constructed three small RNA libraries from early seeds at 14, 21 and 28 days after flowering (DAF and used high-throughput sequencing to examine microRNA (miRNA expression. A total of 85 known miRNAs from 30 families and 1,160 novel miRNAs were identified, of which 24, including 5 known and 19 novel miRNAs, were found to be involved in fatty acid biosynthesis. bna-miR156b, bna-miR156c, bna-miR156g, novel_mir_1706, novel_mir_1407, novel_mir_173, and novel_mir_104 were significantly down-regulated at 21 DAF and 28 DAF, whereas bna-miR159, novel_mir_1081, novel_mir_19 and novel_mir_555 were significantly up-regulated. In addition, we found that some miRNAs regulate functional genes that are directly involved in fatty acid biosynthesis and that other miRNAs regulate the process of fatty acid biosynthesis by acting on a large number of transcription factors. The miRNAs and their corresponding predicted targets were partially validated by quantitative RT-PCR. Our data suggest that diverse and complex miRNAs are involved in the seed development process and that miRNAs play important roles in fatty acid biosynthesis during seed development.
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1981-01-01
The processing of image sequences has a broad spectrum of important applica tions including target tracking, robot navigation, bandwidth compression of TV conferencing video signals, studying the motion of biological cells using microcinematography, cloud tracking, and highway traffic monitoring. Image sequence processing involves a large amount of data. However, because of the progress in computer, LSI, and VLSI technologies, we have now reached a stage when many useful processing tasks can be done in a reasonable amount of time. As a result, research and development activities in image sequence analysis have recently been growing at a rapid pace. An IEEE Computer Society Workshop on Computer Analysis of Time-Varying Imagery was held in Philadelphia, April 5-6, 1979. A related special issue of the IEEE Transactions on Pattern Anal ysis and Machine Intelligence was published in November 1980. The IEEE Com puter magazine has also published a special issue on the subject in 1981. The purpose of this book ...
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Dai, Hanjun
2017-07-26
Motivation: An accurate characterization of transcription factor (TF)-DNA affinity landscape is crucial to a quantitative understanding of the molecular mechanisms underpinning endogenous gene regulation. While recent advances in biotechnology have brought the opportunity for building binding affinity prediction methods, the accurate characterization of TF-DNA binding affinity landscape still remains a challenging problem. Results: Here we propose a novel sequence embedding approach for modeling the transcription factor binding affinity landscape. Our method represents DNA binding sequences as a hidden Markov model (HMM) which captures both position specific information and long-range dependency in the sequence. A cornerstone of our method is a novel message passing-like embedding algorithm, called Sequence2Vec, which maps these HMMs into a common nonlinear feature space and uses these embedded features to build a predictive model. Our method is a novel combination of the strength of probabilistic graphical models, feature space embedding and deep learning. We conducted comprehensive experiments on over 90 large-scale TF-DNA data sets which were measured by different high-throughput experimental technologies. Sequence2Vec outperforms alternative machine learning methods as well as the state-of-the-art binding affinity prediction methods.
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Analysis of xylem formation in pine by cDNA sequencing
Allona, I.; Quinn, M.; Shoop, E.; Swope, K.; St Cyr, S.; Carlis, J.; Riedl, J.; Retzel, E.; Campbell, M. M.; Sederoff, R.;
1998-01-01
Secondary xylem (wood) formation is likely to involve some genes expressed rarely or not at all in herbaceous plants. Moreover, environmental and developmental stimuli influence secondary xylem differentiation, producing morphological and chemical changes in wood. To increase our understanding of xylem formation, and to provide material for comparative analysis of gymnosperm and angiosperm sequences, ESTs were obtained from immature xylem of loblolly pine (Pinus taeda L.). A total of 1,097 single-pass sequences were obtained from 5' ends of cDNAs made from gravistimulated tissue from bent trees. Cluster analysis detected 107 groups of similar sequences, ranging in size from 2 to 20 sequences. A total of 361 sequences fell into these groups, whereas 736 sequences were unique. About 55% of the pine EST sequences show similarity to previously described sequences in public databases. About 10% of the recognized genes encode factors involved in cell wall formation. Sequences similar to cell wall proteins, most known lignin biosynthetic enzymes, and several enzymes of carbohydrate metabolism were found. A number of putative regulatory proteins also are represented. Expression patterns of several of these genes were studied in various tissues and organs of pine. Sequencing novel genes expressed during xylem formation will provide a powerful means of identifying mechanisms controlling this important differentiation pathway.
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Computed tomographic feature of regional lymph nodes involvement in primary hepatocellular carcinoma
International Nuclear Information System (INIS)
Kim, Ki Whang; Kim, Hyung Sik; Lee, Jong Tae; Chung, Tae Sub; Sub, Jung Ho; Auh, Yong Ho
1987-01-01
The resectability of hepatocellular carcinoma is determined by the extent of hepatic involvement, the presence or absence of venous invasion and the presence or absence of extrahepatic metastasis. Extrahepatic spread to regional lymph node represent contraindication to surgical resection. Despite the importance of regional node metastasis, their CT appearance is poorly understood. 19 cases of hepatoma collected during Oct, 1982 to May, 1985 at New York Hospital-Cornell Medical center and 73 cases of hepatoma collected during Mar, 1985 to Sept, 1986 at Yonsei University Medical College were reviewed and analysed. Regional lymph node involvement were divided into four main groups with subgrouping according to the location and lymphatic pathway. 1.lymph nodes in lesser omentum: hepatic, portocaval, left gastric and celiac nodes. 2.lymph nodes around pancrease head: subpyloric, superior mesenteric, preaortic retropancreatic, and precaval retropancreatic lymph nodes. 3.paraaortic nodes: left paraaortic, interaorticocaval, retrocaval and preaortic below 3rd duodenum. 4.phrenic nodes: lower parasternal, middle phrenic and retrocrural nodes. The results were as follows: 1.The frequency of regional node involvement, cases collected at New York Hospital-Cornell Medical center, is hepatic node in 5 (26.3%), portocaval node in 8 (42.1%), left gastric in 4 (21.1%), celiac in 7 (36.8%), precaval retropancreatic in 5 (26.3%) preaortic retropancreatic in 4 (21.1%) interaorticocaval in 7 (36.8%) retrocaval in 4 (21.4%) and lower parasternal in (5.3%). 2.The frequency of regional node involvement, cases collected at Yonsei University college of Medicine, is hepatic in 20.5%, portocaval in 24.7% left gastric in 19.2% celiac in 19.2%, precaval retropancreatic in 8.2%, preaortic retropancreatic in 5.5%, left paraaortic in 12.3%, interaorticocaval in 12.3%, retrocaval in 11.0% low parasternal in 0.8%, superior mesenteric in 4.1% subpyloric 1.4% and preaortic below 3rd duodenum in 1
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Computed tomographic feature of regional lymph nodes involvement in primary hepatocellular carcinoma
Energy Technology Data Exchange (ETDEWEB)
Kim, Ki Whang; Kim, Hyung Sik; Lee, Jong Tae; Chung, Tae Sub; Sub, Jung Ho [Yonsei University College of Medicine, Seoul (Korea, Republic of); Auh, Yong Ho [New York Hospital-Cornell Medical Center, (United States)
1987-04-15
The resectability of hepatocellular carcinoma is determined by the extent of hepatic involvement, the presence or absence of venous invasion and the presence or absence of extrahepatic metastasis. Extrahepatic spread to regional lymph node represent contraindication to surgical resection. Despite the importance of regional node metastasis, their CT appearance is poorly understood. 19 cases of hepatoma collected during Oct, 1982 to May, 1985 at New York Hospital-Cornell Medical center and 73 cases of hepatoma collected during Mar, 1985 to Sept, 1986 at Yonsei University Medical College were reviewed and analysed. Regional lymph node involvement were divided into four main groups with subgrouping according to the location and lymphatic pathway. 1.lymph nodes in lesser omentum: hepatic, portocaval, left gastric and celiac nodes. 2.lymph nodes around pancrease head: subpyloric, superior mesenteric, preaortic retropancreatic, and precaval retropancreatic lymph nodes. 3.paraaortic nodes: left paraaortic, interaorticocaval, retrocaval and preaortic below 3rd duodenum. 4.phrenic nodes: lower parasternal, middle phrenic and retrocrural nodes. The results were as follows: 1.The frequency of regional node involvement, cases collected at New York Hospital-Cornell Medical center, is hepatic node in 5 (26.3%), portocaval node in 8 (42.1%), left gastric in 4 (21.1%), celiac in 7 (36.8%), precaval retropancreatic in 5 (26.3%) preaortic retropancreatic in 4 (21.1%) interaorticocaval in 7 (36.8%) retrocaval in 4 (21.4%) and lower parasternal in (5.3%). 2.The frequency of regional node involvement, cases collected at Yonsei University college of Medicine, is hepatic in 20.5%, portocaval in 24.7% left gastric in 19.2% celiac in 19.2%, precaval retropancreatic in 8.2%, preaortic retropancreatic in 5.5%, left paraaortic in 12.3%, interaorticocaval in 12.3%, retrocaval in 11.0% low parasternal in 0.8%, superior mesenteric in 4.1% subpyloric 1.4% and preaortic below 3rd duodenum in 1
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Dynamics and inherent safety features of small modular high temperature gas-cooled reactors
International Nuclear Information System (INIS)
Harrington, R.M.; Ball, S.J.; Cleveland, J.C.
1986-01-01
Investigations were made at Oak Ridge National Laboratory to characterize the dynamics and inherent safety features of various modular high temperature gas-cooled reactor (HTGR) designs. This work was sponsored by the US Nuclear Regulatory Commission's HTGR Safety Research program. The US Department of Energy (DOE) and the Gas Cooled Reactor Associates (GCRA) have sponsored studies of several modular HTGR concepts, each having it own unique advantageous economic and inherent safety features. The DOE design team has recently choses a 350-MW(t) annular core with prismatic, graphite matrix fuel for its reference plant. The various safety features of this plant and of the pebble-bed core designs similar to those currently being developed and operated in the Federal Republic of Germany (FRG) are described. A varity of postulated accident sequences involving combinations of loss of forced circulation of the helium primary coolant, loss of primary coolant pressurization, and loss of normal and backup heat sinks were studied and are discussed. Results demonstrate that each concept can withstand an uncontrolled heatup accident without reaching excessive peak fuel temperatures. Comparisons of calculated and measured response for a loss of forced circulation test on the FRG reactor, AVR, are also presented. 10 refs
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Parental Involvement and Public Schools: Disappearing Mothers in Labor and Politics
Shuffelton, Amy
2017-01-01
In this article, I argue that the material and rhetorical connection between "parental involvement" and motherhood has the effect of making two important features of parental involvement disappear. Both of these features need to be taken into account to think through the positive and negative effects of parental involvement in public…
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Hypothesis testing for differentially correlated features.
Sheng, Elisa; Witten, Daniela; Zhou, Xiao-Hua
2016-10-01
In a multivariate setting, we consider the task of identifying features whose correlations with the other features differ across conditions. Such correlation shifts may occur independently of mean shifts, or differences in the means of the individual features across conditions. Previous approaches for detecting correlation shifts consider features simultaneously, by computing a correlation-based test statistic for each feature. However, since correlations involve two features, such approaches do not lend themselves to identifying which feature is the culprit. In this article, we instead consider a serial testing approach, by comparing columns of the sample correlation matrix across two conditions, and removing one feature at a time. Our method provides a novel perspective and favorable empirical results compared with competing approaches. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention.
Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei
2016-01-13
An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features.
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Hypothesis testing in students: Sequences, stages, and instructional strategies
Moshman, David; Thompson, Pat A.
Six sequences in the development of hypothesis-testing conceptions are proposed, involving (a) interpretation of the hypothesis; (b) the distinction between using theories and testing theories; (c) the consideration of multiple possibilities; (d) the relation of theory and data; (e) the nature of verification and falsification; and (f) the relation of truth and falsity. An alternative account is then provided involving three global stages: concrete operations, formal operations, and a postformal metaconstructivestage. Relative advantages and difficulties of the stage and sequence conceptualizations are discussed. Finally, three families of teaching strategy are distinguished, which emphasize, respectively: (a) social transmission of knowledge; (b) carefully sequenced empirical experience by the student; and (c) self-regulated cognitive activity of the student. It is argued on the basis of Piaget's theory that the last of these plays a crucial role in the construction of such logical reasoning strategies as those involved in testing hypotheses.
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Triangular fibrocartilage lesions: comparison STIR sequence versus arthroscopy findings
International Nuclear Information System (INIS)
Wang Zhi; Meng; Xianghong; Wang Linsen; Suo Yongmei
2013-01-01
Objective: To explore the diagnostic value of short TI inversion recovery (STIR) sequence in evaluating triangular fibrocartilage (TFC) lesions, and to compare the findings with the arthroscopy findings. Materials and Methods: Wrist joint MR examination using STIR sequence and arthroscopy were performed in 56 patients with TFC lesions. The parameters of STIR sequence were: TR: 1164 ms, TE: 16 ms, and TI: 90 ms. The sensibility, specificity, positive predictive value, negative predictive value, and accuracy in the diagnosis of TFC lesions with STIR sequence were calculated, using arthroscopy as the standard. Results: (1) STIR manifested 10 patients with normal TFC; 6 with small edema or mucous degeneration in the body portion but not involving joint surface edge; 6 with horizontal avulsion in the body portion, but not involving joint surface edge; 6 with avulsion involving joint surface edge; 11 with perforation in central portion; 6 with avulsion in radial attached end; 5 with avulsion in ulnar attached end; 3 with avulsion in both radial and ulnar attached ends; 3 with irregular shape and thin on the whole TFC. (2) Arthroscopy manifested 21 patients with normal TFC; 8 with avulsion involving joint surface edge; 10 with perforation in central portion; 7 with avulsion in radial attached end; 5 with avulsion in ulnar attached end; 2 with avulsion in both radial and ulnar attached ends; 3 with irregular shape on the whole TFC. Using STIR sequence, the sensibility, specificity, positive predictive value, negative predictive value. and accuracy were 85.7%, 23.8%, 65.2%, 50%, and 62.5%, respectively, in detection of TFC lesions, with arthroscopy as the standard. Conclusion: STIR sequence has high diagnostic value in detection of TFC lesions. (authors)
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Directory of Open Access Journals (Sweden)
Jun Yang
2017-06-01
Full Text Available Tooth development depends on multiple molecular interactions between the dental epithelium and mesenchyme, which are derived from ectodermal and ectomesenchymal cells, respectively. We report on a systematic RNA sequencing analysis of transcriptional expression levels from the bud to hard tissue formation stages of rat tooth germ development. We found that GNAO1, ENO1, EFNB1, CALM1, SIAH2, ATP6V0A1, KDELR2, GTPBP1, POLR2C, SORT1, and members of the canonical transient receptor potential (TRPC channel family are involved in tooth germ development. Furthermore, Cell Counting Kit 8 (CCK8 and Transwell migration assays were performed to explore the effects of these differentially expressed genes (DEGs on the proliferation and migration of dental pulp stem cells. Immunostaining revealed that TRPC channels are expressed at varying levels during odontogenesis. The identified genes represent novel candidates that are likely to be vital for rat tooth germ development. Together, the results provide a valuable resource to elucidate the gene regulatory mechanisms underlying mammalian tooth germ development.
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Liang, Chun; Wang, Gang; Liu, Lin; Ji, Guoli; Fang, Lin; Liu, Yuansheng; Carter, Kikia; Webb, Jason S; Dean, Jeffrey F D
2007-05-29
With the advent of low-cost, high-throughput sequencing, the amount of public domain Expressed Sequence Tag (EST) sequence data available for both model and non-model organism is growing exponentially. While these data are widely used for characterizing various genomes, they also present a serious challenge for data quality control and validation due to their inherent deficiencies, particularly for species without genome sequences. ConiferEST is an integrated system for data reprocessing, visualization and mining of conifer ESTs. In its current release, Build 1.0, it houses 172,229 loblolly pine EST sequence reads, which were obtained from reprocessing raw DNA sequencer traces using our software--WebTraceMiner. The trace files were downloaded from NCBI Trace Archive. ConiferEST provides biologists unique, easy-to-use data visualization and mining tools for a variety of putative sequence features including cloning vector segments, adapter sequences, restriction endonuclease recognition sites, polyA and polyT runs, and their corresponding Phred quality values. Based on these putative features, verified sequence features such as 3' and/or 5' termini of cDNA inserts in either sense or non-sense strand have been identified in-silico. Interestingly, only 30.03% of the designated 3' ESTs were found to have an authenticated 5' terminus in the non-sense strand (i.e., polyT tails), while fewer than 5.34% of the designated 5' ESTs had a verified 5' terminus in the sense strand. Such previously ignored features provide valuable insight for data quality control and validation of error-prone ESTs, as well as the ability to identify novel functional motifs embedded in large EST datasets. We found that "double-termini adapters" were effective indicators of potential EST chimeras. For all sequences with in-silico verified termini/terminus, we used InterProScan to assign protein domain signatures, results of which are available for in-depth exploration using our biologist
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Directory of Open Access Journals (Sweden)
Carter Kikia
2007-05-01
Full Text Available Abstract Background With the advent of low-cost, high-throughput sequencing, the amount of public domain Expressed Sequence Tag (EST sequence data available for both model and non-model organism is growing exponentially. While these data are widely used for characterizing various genomes, they also present a serious challenge for data quality control and validation due to their inherent deficiencies, particularly for species without genome sequences. Description ConiferEST is an integrated system for data reprocessing, visualization and mining of conifer ESTs. In its current release, Build 1.0, it houses 172,229 loblolly pine EST sequence reads, which were obtained from reprocessing raw DNA sequencer traces using our software – WebTraceMiner. The trace files were downloaded from NCBI Trace Archive. ConiferEST provides biologists unique, easy-to-use data visualization and mining tools for a variety of putative sequence features including cloning vector segments, adapter sequences, restriction endonuclease recognition sites, polyA and polyT runs, and their corresponding Phred quality values. Based on these putative features, verified sequence features such as 3' and/or 5' termini of cDNA inserts in either sense or non-sense strand have been identified in-silico. Interestingly, only 30.03% of the designated 3' ESTs were found to have an authenticated 5' terminus in the non-sense strand (i.e., polyT tails, while fewer than 5.34% of the designated 5' ESTs had a verified 5' terminus in the sense strand. Such previously ignored features provide valuable insight for data quality control and validation of error-prone ESTs, as well as the ability to identify novel functional motifs embedded in large EST datasets. We found that "double-termini adapters" were effective indicators of potential EST chimeras. For all sequences with in-silico verified termini/terminus, we used InterProScan to assign protein domain signatures, results of which are available
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Directory of Open Access Journals (Sweden)
Hu Jianjun
2011-05-01
Full Text Available Abstract Background Accurate prediction of binding residues involved in the interactions between proteins and small ligands is one of the major challenges in structural bioinformatics. Heme is an essential and commonly used ligand that plays critical roles in electron transfer, catalysis, signal transduction and gene expression. Although much effort has been devoted to the development of various generic algorithms for ligand binding site prediction over the last decade, no algorithm has been specifically designed to complement experimental techniques for identification of heme binding residues. Consequently, an urgent need is to develop a computational method for recognizing these important residues. Results Here we introduced an efficient algorithm HemeBIND for predicting heme binding residues by integrating structural and sequence information. We systematically investigated the characteristics of binding interfaces based on a non-redundant dataset of heme-protein complexes. It was found that several sequence and structural attributes such as evolutionary conservation, solvent accessibility, depth and protrusion clearly illustrate the differences between heme binding and non-binding residues. These features can then be separately used or combined to build the structure-based classifiers using support vector machine (SVM. The results showed that the information contained in these features is largely complementary and their combination achieved the best performance. To further improve the performance, an attempt has been made to develop a post-processing procedure to reduce the number of false positives. In addition, we built a sequence-based classifier based on SVM and sequence profile as an alternative when only sequence information can be used. Finally, we employed a voting method to combine the outputs of structure-based and sequence-based classifiers, which demonstrated remarkably better performance than the individual classifier alone
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Invariant Handwriting Features Useful in Cursive-Script Recognition
Teulings, Hans-leo L; Schomaker, L R; Impedovo, S.
1994-01-01
A handwriting pattern is considered as a sequence of ballistic strokes. Replications of a pattern may be generated from a single, higher-level memory representation, acting as a motor program. Therefore, those stroke features which show the most invariant pattern are probably related to the
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Sirius PSB: a generic system for analysis of biological sequences.
Koh, Chuan Hock; Lin, Sharene; Jedd, Gregory; Wong, Limsoon
2009-12-01
Computational tools are essential components of modern biological research. For example, BLAST searches can be used to identify related proteins based on sequence homology, or when a new genome is sequenced, prediction models can be used to annotate functional sites such as transcription start sites, translation initiation sites and polyadenylation sites and to predict protein localization. Here we present Sirius Prediction Systems Builder (PSB), a new computational tool for sequence analysis, classification and searching. Sirius PSB has four main operations: (1) Building a classifier, (2) Deploying a classifier, (3) Search for proteins similar to query proteins, (4) Preliminary and post-prediction analysis. Sirius PSB supports all these operations via a simple and interactive graphical user interface. Besides being a convenient tool, Sirius PSB has also introduced two novelties in sequence analysis. Firstly, genetic algorithm is used to identify interesting features in the feature space. Secondly, instead of the conventional method of searching for similar proteins via sequence similarity, we introduced searching via features' similarity. To demonstrate the capabilities of Sirius PSB, we have built two prediction models - one for the recognition of Arabidopsis polyadenylation sites and another for the subcellular localization of proteins. Both systems are competitive against current state-of-the-art models based on evaluation of public datasets. More notably, the time and effort required to build each model is greatly reduced with the assistance of Sirius PSB. Furthermore, we show that under certain conditions when BLAST is unable to find related proteins, Sirius PSB can identify functionally related proteins based on their biophysical similarities. Sirius PSB and its related supplements are available at: http://compbio.ddns.comp.nus.edu.sg/~sirius.
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Historical Feature Pattern Extraction Based Network Attack Situation Sensing Algorithm
Zeng, Yong; Liu, Dacheng; Lei, Zhou
2014-01-01
The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE). First, HFPE algorithm seeks similar indications from the history si...
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Correlated mutations in protein sequences: Phylogenetic and structural effects
Energy Technology Data Exchange (ETDEWEB)
Lapedes, A.S. [Los Alamos National Lab., NM (United States). Theoretical Div.]|[Santa Fe Inst., NM (United States); Giraud, B.G. [C.E.N. Saclay, Gif/Yvette (France). Service Physique Theorique; Liu, L.C. [Los Alamos National Lab., NM (United States). Theoretical Div.; Stormo, G.D. [Univ. of Colorado, Boulder, CO (United States). Dept. of Molecular, Cellular and Developmental Biology
1998-12-01
Covariation analysis of sets of aligned sequences for RNA molecules is relatively successful in elucidating RNA secondary structure, as well as some aspects of tertiary structure. Covariation analysis of sets of aligned sequences for protein molecules is successful in certain instances in elucidating certain structural and functional links, but in general, pairs of sites displaying highly covarying mutations in protein sequences do not necessarily correspond to sites that are spatially close in the protein structure. In this paper the authors identify two reasons why naive use of covariation analysis for protein sequences fails to reliably indicate sequence positions that are spatially proximate. The first reason involves the bias introduced in calculation of covariation measures due to the fact that biological sequences are generally related by a non-trivial phylogenetic tree. The authors present a null-model approach to solve this problem. The second reason involves linked chains of covariation which can result in pairs of sites displaying significant covariation even though they are not spatially proximate. They present a maximum entropy solution to this classic problem of causation versus correlation. The methodologies are validated in simulation.
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Olson, Nathan D.; Lund, Steven P.; Zook, Justin M.; Rojas-Cornejo, Fabiola; Beck, Brian; Foy, Carole; Huggett, Jim; Whale, Alexandra S.; Sui, Zhiwei; Baoutina, Anna; Dobeson, Michael; Partis, Lina; Morrow, Jayne B.
2015-01-01
This study presents the results from an interlaboratory sequencing study for which we developed a novel high-resolution method for comparing data from different sequencing platforms for a multi-copy, paralogous gene. The combination of PCR amplification and 16S ribosomal RNA gene (16S rRNA) sequencing has revolutionized bacteriology by enabling rapid identification, frequently without the need for culture. To assess variability between laboratories in sequencing 16S rRNA, six laboratories sequenced the gene encoding the 16S rRNA from Escherichia coli O157:H7 strain EDL933 and Listeria monocytogenes serovar 4b strain NCTC11994. Participants performed sequencing methods and protocols available in their laboratories: Sanger sequencing, Roche 454 pyrosequencing®, or Ion Torrent PGM®. The sequencing data were evaluated on three levels: (1) identity of biologically conserved position, (2) ratio of 16S rRNA gene copies featuring identified variants, and (3) the collection of variant combinations in a set of 16S rRNA gene copies. The same set of biologically conserved positions was identified for each sequencing method. Analytical methods using Bayesian and maximum likelihood statistics were developed to estimate variant copy ratios, which describe the ratio of nucleotides at each identified biologically variable position, as well as the likely set of variant combinations present in 16S rRNA gene copies. Our results indicate that estimated variant copy ratios at biologically variable positions were only reproducible for high throughput sequencing methods. Furthermore, the likely variant combination set was only reproducible with increased sequencing depth and longer read lengths. We also demonstrate novel methods for evaluating variable positions when comparing multi-copy gene sequence data from multiple laboratories generated using multiple sequencing technologies. PMID:27077030
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Directory of Open Access Journals (Sweden)
Nathan D. Olson
2015-03-01
Full Text Available This study presents the results from an interlaboratory sequencing study for which we developed a novel high-resolution method for comparing data from different sequencing platforms for a multi-copy, paralogous gene. The combination of PCR amplification and 16S ribosomal RNA gene (16S rRNA sequencing has revolutionized bacteriology by enabling rapid identification, frequently without the need for culture. To assess variability between laboratories in sequencing 16S rRNA, six laboratories sequenced the gene encoding the 16S rRNA from Escherichia coli O157:H7 strain EDL933 and Listeria monocytogenes serovar 4b strain NCTC11994. Participants performed sequencing methods and protocols available in their laboratories: Sanger sequencing, Roche 454 pyrosequencing®, or Ion Torrent PGM®. The sequencing data were evaluated on three levels: (1 identity of biologically conserved position, (2 ratio of 16S rRNA gene copies featuring identified variants, and (3 the collection of variant combinations in a set of 16S rRNA gene copies. The same set of biologically conserved positions was identified for each sequencing method. Analytical methods using Bayesian and maximum likelihood statistics were developed to estimate variant copy ratios, which describe the ratio of nucleotides at each identified biologically variable position, as well as the likely set of variant combinations present in 16S rRNA gene copies. Our results indicate that estimated variant copy ratios at biologically variable positions were only reproducible for high throughput sequencing methods. Furthermore, the likely variant combination set was only reproducible with increased sequencing depth and longer read lengths. We also demonstrate novel methods for evaluating variable positions when comparing multi-copy gene sequence data from multiple laboratories generated using multiple sequencing technologies.
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Li, Yushuang; Song, Tian; Yang, Jiasheng; Zhang, Yi; Yang, Jialiang
2016-01-01
In this paper, we have proposed a novel alignment-free method for comparing the similarity of protein sequences. We first encode a protein sequence into a 440 dimensional feature vector consisting of a 400 dimensional Pseudo-Markov transition probability vector among the 20 amino acids, a 20 dimensional content ratio vector, and a 20 dimensional position ratio vector of the amino acids in the sequence. By evaluating the Euclidean distances among the representing vectors, we compare the similarity of protein sequences. We then apply this method into the ND5 dataset consisting of the ND5 protein sequences of 9 species, and the F10 and G11 datasets representing two of the xylanases containing glycoside hydrolase families, i.e., families 10 and 11. As a result, our method achieves a correlation coefficient of 0.962 with the canonical protein sequence aligner ClustalW in the ND5 dataset, much higher than those of other 5 popular alignment-free methods. In addition, we successfully separate the xylanases sequences in the F10 family and the G11 family and illustrate that the F10 family is more heat stable than the G11 family, consistent with a few previous studies. Moreover, we prove mathematically an identity equation involving the Pseudo-Markov transition probability vector and the amino acids content ratio vector.
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GeneViTo: Visualizing gene-product functional and structural features in genomic datasets
Directory of Open Access Journals (Sweden)
Promponas Vasilis J
2003-10-01
Full Text Available Abstract Background The availability of increasing amounts of sequence data from completely sequenced genomes boosts the development of new computational methods for automated genome annotation and comparative genomics. Therefore, there is a need for tools that facilitate the visualization of raw data and results produced by bioinformatics analysis, providing new means for interactive genome exploration. Visual inspection can be used as a basis to assess the quality of various analysis algorithms and to aid in-depth genomic studies. Results GeneViTo is a JAVA-based computer application that serves as a workbench for genome-wide analysis through visual interaction. The application deals with various experimental information concerning both DNA and protein sequences (derived from public sequence databases or proprietary data sources and meta-data obtained by various prediction algorithms, classification schemes or user-defined features. Interaction with a Graphical User Interface (GUI allows easy extraction of genomic and proteomic data referring to the sequence itself, sequence features, or general structural and functional features. Emphasis is laid on the potential comparison between annotation and prediction data in order to offer a supplement to the provided information, especially in cases of "poor" annotation, or an evaluation of available predictions. Moreover, desired information can be output in high quality JPEG image files for further elaboration and scientific use. A compilation of properly formatted GeneViTo input data for demonstration is available to interested readers for two completely sequenced prokaryotes, Chlamydia trachomatis and Methanococcus jannaschii. Conclusions GeneViTo offers an inspectional view of genomic functional elements, concerning data stemming both from database annotation and analysis tools for an overall analysis of existing genomes. The application is compatible with Linux or Windows ME-2000-XP operating
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The nucleotide sequence of 5S ribosomal RNA from Micrococcus lysodeikticus.
Hori, H; Osawa, S; Murao, K; Ishikura, H
1980-01-01
The nucleotide sequence of ribosomal 5S RNA from Micrococcus lysodeikticus is pGUUACGGCGGCUAUAGCGUGGGGGAAACGCCCGGCCGUAUAUCGAACCCGGAAGCUAAGCCCCAUAGCGCCGAUGGUUACUGUAACCGGGAGGUUGUGGGAGAGUAGGUCGCCGCCGUGAOH. When compared to other 5S RNAs, the sequence homology is greatest with Thermus aquaticus, and these two 5S RNAs reveal several features intermediate between those of typical gram-positive bacteria and gram-negative bacteria. PMID:6780979
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Direct, rapid RNA sequence analysis
International Nuclear Information System (INIS)
Peattie, D.A.
1987-01-01
The original methods of RNA sequence analysis were based on enzymatic production and chromatographic separation of overlapping oligonucleotide fragments from within an RNA molecule followed by identification of the mononucleotides comprising the oligomer. Over the past decade the field of nucleic acid sequencing has changed dramatically, however, and RNA molecules now can be sequenced in a variety of more streamlined fashions. Most of the more recent advances in RNA sequencing have involved one-dimensional electrophoretic separation of 32 P-end-labeled oligoribonucleotides on polyacrylamide gels. In this chapter the author discusses two of these methods for determining the nucleotide sequences of RNA molecules rapidly: the chemical method and the enzymatic method. Both methods are direct and degradative, i.e., they rely on fragmatic and chemical approaches should be utilized. The single-strand-specific ribonucleases (A, T 1 , T 2 , and S 1 ) provide an efficient means to locate double-helical regions rapidly, and the chemical reactions provide a means to determine the RNA sequence within these regions. In addition, the chemical reactions allow one to assign interactions to specific atoms and to distinguish secondary interactions from tertiary ones. If the RNA molecule is small enough to be sequenced directly by the enzymatic or chemical method, the probing reactions can be done easily at the same time as sequencing reactions
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Application of Next-generation Sequencing in Clinical Molecular Diagnostics
Directory of Open Access Journals (Sweden)
Morteza Seifi
2017-05-01
Full Text Available ABSTRACT Next-generation sequencing (NGS is the catch all terms that used to explain several different modern sequencing technologies which let us to sequence nucleic acids much more rapidly and cheaply than the formerly used Sanger sequencing, and as such have revolutionized the study of molecular biology and genomics with excellent resolution and accuracy. Over the past years, many academic companies and institutions have continued technological advances to expand NGS applications from research to the clinic. In this review, the performance and technical features of current NGS platforms were described. Furthermore, advances in the applying of NGS technologies towards the progress of clinical molecular diagnostics were emphasized. General advantages and disadvantages of each sequencing system are summarized and compared to guide the selection of NGS platforms for specific research aims.
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Management of High-Throughput DNA Sequencing Projects: Alpheus.
Miller, Neil A; Kingsmore, Stephen F; Farmer, Andrew; Langley, Raymond J; Mudge, Joann; Crow, John A; Gonzalez, Alvaro J; Schilkey, Faye D; Kim, Ryan J; van Velkinburgh, Jennifer; May, Gregory D; Black, C Forrest; Myers, M Kathy; Utsey, John P; Frost, Nicholas S; Sugarbaker, David J; Bueno, Raphael; Gullans, Stephen R; Baxter, Susan M; Day, Steve W; Retzel, Ernest F
2008-12-26
High-throughput DNA sequencing has enabled systems biology to begin to address areas in health, agricultural and basic biological research. Concomitant with the opportunities is an absolute necessity to manage significant volumes of high-dimensional and inter-related data and analysis. Alpheus is an analysis pipeline, database and visualization software for use with massively parallel DNA sequencing technologies that feature multi-gigabase throughput characterized by relatively short reads, such as Illumina-Solexa (sequencing-by-synthesis), Roche-454 (pyrosequencing) and Applied Biosystem's SOLiD (sequencing-by-ligation). Alpheus enables alignment to reference sequence(s), detection of variants and enumeration of sequence abundance, including expression levels in transcriptome sequence. Alpheus is able to detect several types of variants, including non-synonymous and synonymous single nucleotide polymorphisms (SNPs), insertions/deletions (indels), premature stop codons, and splice isoforms. Variant detection is aided by the ability to filter variant calls based on consistency, expected allele frequency, sequence quality, coverage, and variant type in order to minimize false positives while maximizing the identification of true positives. Alpheus also enables comparisons of genes with variants between cases and controls or bulk segregant pools. Sequence-based differential expression comparisons can be developed, with data export to SAS JMP Genomics for statistical analysis.
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Klenkova, N A; Kapustin, S I; Saltykova, N B; Shmeleva, V M; Blinov, M N
2009-01-01
Under study were features of allele polymorphism of genes of methylenetetrahydrofolate reductase (MTHFR C677T and A1298C), methionine synthase (MS A 2756G), methionine synthase reductase (MTRR A66G) and methylenetetrahydrofolate dehydrogenase (MTHFD G1958A) in patients with atherosclerosis of the lower extremity arteries (ALEA). Patients with hyperhomocysteinemia (HHcy) had statistically significant increase of allele MTHFR 677T and MTRR 66GG as compared both with the control group and with the group of patients without HHcy. It suggests that polymorphism of genes involved in homocystein and folate metabolism might affect the risk of HHcy in patients with ALEA.
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DNA Nucleotide Sequence Restricted by the RI Endonuclease
Hedgpeth, Joe; Goodman, Howard M.; Boyer, Herbert W.
1972-01-01
The sequence of DNA base pairs adjacent to the phosphodiester bonds cleaved by the RI restriction endonuclease in unmodified DNA from coliphage λ has been determined. The 5′-terminal nucleotide labeled with 32P and oligonucleotides up to the heptamer were analyzed from a pancreatic DNase digest. The following sequence of nucleotides adjacent to the RI break made in λ DNA was deduced from these data and from the 3′-dinucleotide sequence and nearest-neighbor analysis obtained from repair synthesis with the DNA polymerase of Rous sarcoma virus [Formula: see text] The RI endonuclease cleavage of the phosphodiester bonds (indicated by arrows) generates 5′-phosphoryls and short cohesive termini of four nucleotides, pApApTpT. The most striking feature of the sequence is its symmetry. PMID:4343974
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Feature Selection using Multi-objective Genetic Algorith m: A Hybrid Approach
Ahuja, Jyoti; GJUST - Guru Jambheshwar University of Sciecne and Technology; Ratnoo, Saroj Dahiya; GJUST - Guru Jambheshwar University of Sciecne and Technology
2015-01-01
Feature selection is an important pre-processing task for building accurate and comprehensible classification models. Several researchers have applied filter, wrapper or hybrid approaches using genetic algorithms which are good candidates for optimization problems that involve large search spaces like in the case of feature selection. Moreover, feature selection is an inherently multi-objective problem with many competing objectives involving size, predictive power and redundancy of the featu...
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Insights into the sequence parameters for halophilic adaptation.
Nath, Abhigyan
2016-03-01
The sequence parameters for halophilic adaptation are still not fully understood. To understand the molecular basis of protein hypersaline adaptation, a detailed analysis is carried out, and investigated the likely association of protein sequence attributes to halophilic adaptation. A two-stage strategy is implemented, where in the first stage a supervised machine learning classifier is build, giving an overall accuracy of 86 % on stratified tenfold cross validation and 90 % on blind testing set, which are better than the previously reported results. The second stage consists of statistical analysis of sequence features and possible extraction of halophilic molecular signatures. The results of this study showed that, halophilic proteins are characterized by lower average charge, lower K content, and lower S content. A statistically significant preference/avoidance list of sequence parameters is also reported giving insights into the molecular basis of halophilic adaptation. D, Q, E, H, P, T, V are significantly preferred while N, C, I, K, M, F, S are significantly avoided. Among amino acid physicochemical groups, small, polar, charged, acidic and hydrophilic groups are preferred over other groups. The halophilic proteins also showed a preference for higher average flexibility, higher average polarity and avoidance for higher average positive charge, average bulkiness and average hydrophobicity. Some interesting trends observed in dipeptide counts are also reported. Further a systematic statistical comparison is undertaken for gaining insights into the sequence feature distribution in different residue structural states. The current analysis may facilitate the understanding of the mechanism of halophilic adaptation clearer, which can be further used for rational design of halophilic proteins.
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The impact of feature selection on one and two-class classification performance for plant microRNAs.
Khalifa, Waleed; Yousef, Malik; Saçar Demirci, Müşerref Duygu; Allmer, Jens
2016-01-01
MicroRNAs (miRNAs) are short nucleotide sequences that form a typical hairpin structure which is recognized by a complex enzyme machinery. It ultimately leads to the incorporation of 18-24 nt long mature miRNAs into RISC where they act as recognition keys to aid in regulation of target mRNAs. It is involved to determine miRNAs experimentally and, therefore, machine learning is used to complement such endeavors. The success of machine learning mostly depends on proper input data and appropriate features for parameterization of the data. Although, in general, two-class classification (TCC) is used in the field; because negative examples are hard to come by, one-class classification (OCC) has been tried for pre-miRNA detection. Since both positive and negative examples are currently somewhat limited, feature selection can prove to be vital for furthering the field of pre-miRNA detection. In this study, we compare the performance of OCC and TCC using eight feature selection methods and seven different plant species providing positive pre-miRNA examples. Feature selection was very successful for OCC where the best feature selection method achieved an average accuracy of 95.6%, thereby being ∼29% better than the worst method which achieved 66.9% accuracy. While the performance is comparable to TCC, which performs up to 3% better than OCC, TCC is much less affected by feature selection and its largest performance gap is ∼13% which only occurs for two of the feature selection methodologies. We conclude that feature selection is crucially important for OCC and that it can perform on par with TCC given the proper set of features.
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The impact of feature selection on one and two-class classification performance for plant microRNAs
Directory of Open Access Journals (Sweden)
Waleed Khalifa
2016-06-01
Full Text Available MicroRNAs (miRNAs are short nucleotide sequences that form a typical hairpin structure which is recognized by a complex enzyme machinery. It ultimately leads to the incorporation of 18–24 nt long mature miRNAs into RISC where they act as recognition keys to aid in regulation of target mRNAs. It is involved to determine miRNAs experimentally and, therefore, machine learning is used to complement such endeavors. The success of machine learning mostly depends on proper input data and appropriate features for parameterization of the data. Although, in general, two-class classification (TCC is used in the field; because negative examples are hard to come by, one-class classification (OCC has been tried for pre-miRNA detection. Since both positive and negative examples are currently somewhat limited, feature selection can prove to be vital for furthering the field of pre-miRNA detection. In this study, we compare the performance of OCC and TCC using eight feature selection methods and seven different plant species providing positive pre-miRNA examples. Feature selection was very successful for OCC where the best feature selection method achieved an average accuracy of 95.6%, thereby being ∼29% better than the worst method which achieved 66.9% accuracy. While the performance is comparable to TCC, which performs up to 3% better than OCC, TCC is much less affected by feature selection and its largest performance gap is ∼13% which only occurs for two of the feature selection methodologies. We conclude that feature selection is crucially important for OCC and that it can perform on par with TCC given the proper set of features.
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International Nuclear Information System (INIS)
Corti, Marcelo; Villafañe, Maria; Minue, Gonzalo; Campitelli, Ana; Narbaitz, Marina; Gilardi, Leonardo
2015-01-01
To study the main clinical and histopathological features of 12 patients with Hodgkin’s lymphoma (HL) diagnosed primarily from bone marrow (BM) involvement. We included 12 acquired immunodeficiency syndrome (AIDS) patients with HL assisted in the F. J. Muñiz Infectious Diseases Hospital since January 2002 to December 2013. The diagnosis of HL with primary BM involvement in patients was confirmed by clinical, histopathological, and immunohistochemical findings. All patients presented “B” symptoms and pancytopenia. All of them had stage IV neoplasm disease because of BM infiltration. The median of CD4 + T-cell counts was 114 cells/μL, and mixed cellularity (MC) was the most frequent histopathological subtype of 92% cases. When other causes are excluded, BM biopsy should be performed in AIDS patients with “B” symptoms and pancytopenia to evaluate BM infiltration by atypical lymphocytes
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Imaging features of foot osteoid osteoma
Energy Technology Data Exchange (ETDEWEB)
Shukla, Satyen; Clarke, Andrew W.; Saifuddin, Asif [Royal National Orthopaedic Hospital NHS Trust, Department of Radiology, Stanmore, Middlesex (United Kingdom)
2010-07-15
We performed a retrospective review of the imaging of nine patients with a diagnosis of foot osteoid osteoma (OO). Radiographs, computed tomography (CT) and magnetic resonance imaging (MRI) had been performed in all patients. Radiographic features evaluated were the identification of a nidus and cortical thickening. CT features noted were nidus location (affected bone - intramedullary, intracortical, subarticular) and nidus calcification. MRI features noted were the presence of an identifiable nidus, presence and grade of bone oedema and whether a joint effusion was identified. Of the nine patients, three were female and six male, with a mean age of 21 years (range 11-39 years). Classical symptoms of OO (night pain, relief with aspirin) were identified in five of eight (62.5%) cases (in one case, the medical records could not be retrieved). In five patients the lesion was located in the hindfoot (four calcaneus, one talus), while four were in the mid- or forefoot (two metatarsal and two phalangeal). Radiographs were normal in all patients with hindfoot OO. CT identified the nidus in all cases (89%) except one terminal phalanx lesion, while MRI demonstrated a nidus in six of nine cases (67%). The nidus was of predominantly intermediate signal intensity on T1-weighted (T1W) sequences, with intermediate to high signal intensity on T2-weighted (T2W) sequences. High-grade bone marrow oedema, limited to the affected bone and adjacent soft tissue oedema was identified in all cases. In a young patient with chronic hindfoot pain and a normal radiograph, MRI features suggestive of possible OO include extensive bone marrow oedema limited to one bone, with a possible nidus demonstrated in two-thirds of cases. The presence or absence of a nidus should be confirmed with high-resolution CT. (orig.)
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Plann: A command-line application for annotating plastome sequences1
Huang, Daisie I.; Cronk, Quentin C. B.
2015-01-01
Premise of the study: Plann automates the process of annotating a plastome sequence in GenBank format for either downstream processing or for GenBank submission by annotating a new plastome based on a similar, well-annotated plastome. Methods and Results: Plann is a Perl script to be executed on the command line. Plann compares a new plastome sequence to the features annotated in a reference plastome and then shifts the intervals of any matching features to the locations in the new plastome. Plann’s output can be used in the National Center for Biotechnology Information’s tbl2asn to create a Sequin file for GenBank submission. Conclusions: Unlike Web-based annotation packages, Plann is a locally executable script that will accurately annotate a plastome sequence to a locally specified reference plastome. Because it executes from the command line, it is ready to use in other software pipelines and can be easily rerun as a draft plastome is improved. PMID:26312193
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Detection of distorted frames in retinal video-sequences via machine learning
Kolar, Radim; Liberdova, Ivana; Odstrcilik, Jan; Hracho, Michal; Tornow, Ralf P.
2017-07-01
This paper describes detection of distorted frames in retinal sequences based on set of global features extracted from each frame. The feature vector is consequently used in classification step, in which three types of classifiers are tested. The best classification accuracy 96% has been achieved with support vector machine approach.
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Parry, David A D; Fraser, R D Bruce; Squire, John M
2008-09-01
alpha-Helical coiled coils are remarkable for the diversity of related conformations that they adopt in both fibrous and globular proteins, and for the range of functions that they exhibit. The coiled coils are based on a heptad (7-residue), hendecad (11-residue) or a related quasi-repeat of apolar residues in the sequences of the alpha-helical regions involved. Most of these, however, display one or more sequence discontinuities known as stutters or stammers. The resulting coiled coils vary in length, in the number of chains participating, in the relative polarity of the contributing alpha-helical regions (parallel or antiparallel), and in the pitch length and handedness of the supercoil (left- or right-handed). Functionally, the concept that a coiled coil can act only as a static rod is no longer valid, and the range of roles that these structures have now been shown to exhibit has expanded rapidly in recent years. An important development has been the recognition that the delightful simplicity that exists between sequence and structure, and between structure and function, allows coiled coils with specialized features to be designed de novo.
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Energy Technology Data Exchange (ETDEWEB)
Revaud, D.
2009-06-15
Interstitial Telomeric Sequences (ITS) are over-involved in spontaneous and radiationinduced chromosome aberrations in chinese hamster cells. We have performed a study to investigate the origin of their instability, spontaneously or after low doses irradiation. Our results demonstrate that ITS have a particular chromatin structure: short nucleotide repeat length, less compaction of the 30 nm chromatin fiber, presence of G-quadruplex structures. These features would modulate breaks production and would favour the recruitment of alternative DNA repair mechanisms, which are prone to produce chromosome aberrations. These pathways could be at the origin of chromosome aberrations in ITS whereas NHEJ and HR Double Strand Break repair pathways are rather required for a correct repair in these regions. (author)
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Putaminal involvement in Rasmussen encephalitis
Energy Technology Data Exchange (ETDEWEB)
Rajesh, Bhagavatheeswaran; Ashalatha, Radhakrishnan [Sree Chitra Tirunal Institute for Medical Sciences and Technology, Department of Neurology, Trivandrum, Kerala (India); Kesavadas, Chandrasekharan; Thomas, Bejoy [Sree Chitra Tirunal Institute for Medical Sciences and Technology, Department of Imaging Sciences and Interventional Radiology, Trivandrum, Kerala (India)
2006-08-15
Rasmussen encephalitis (RE) is a rare devastating disease of childhood causing progressive neurological deficits and intractable seizures, typically affecting one hemisphere. Characteristic MRI features include progressive unihemispheric focal cortical atrophy and grey- or white-matter high-signal changes and basal ganglion involvement, particularly of the caudate nucleus. To analyse the pattern of involvement of different brain structures in a series of patients with RE and to attempt clinical correlation. We reviewed the medical records and neuroimaging data of 12 patients diagnosed with RE satisfying the European Consensus Statement diagnostic criteria. The disease manifested as seizures in all patients and was refractory; epilepsia partialis continua was a notable feature (nine patients). Hemiparesis of varying grades was noted in all but one patient; none had extrapyramidal signs. Neuroimaging showed cortical involvement in the insular/periinsular regions in 11 patients. Caudate atrophy was noted in ten patients. Putaminal atrophy was seen in nine patients, six of whom had additional hyperintense signal changes. Our study highlights frequent putaminal atrophy and signal changes in RE, which suggests a more extensive basal ganglion involvement than emphasized previously. Recognition of putaminal changes may be a useful additional tool in the radiological diagnosis of RE. (orig.)
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Putaminal involvement in Rasmussen encephalitis
International Nuclear Information System (INIS)
Rajesh, Bhagavatheeswaran; Ashalatha, Radhakrishnan; Kesavadas, Chandrasekharan; Thomas, Bejoy
2006-01-01
Rasmussen encephalitis (RE) is a rare devastating disease of childhood causing progressive neurological deficits and intractable seizures, typically affecting one hemisphere. Characteristic MRI features include progressive unihemispheric focal cortical atrophy and grey- or white-matter high-signal changes and basal ganglion involvement, particularly of the caudate nucleus. To analyse the pattern of involvement of different brain structures in a series of patients with RE and to attempt clinical correlation. We reviewed the medical records and neuroimaging data of 12 patients diagnosed with RE satisfying the European Consensus Statement diagnostic criteria. The disease manifested as seizures in all patients and was refractory; epilepsia partialis continua was a notable feature (nine patients). Hemiparesis of varying grades was noted in all but one patient; none had extrapyramidal signs. Neuroimaging showed cortical involvement in the insular/periinsular regions in 11 patients. Caudate atrophy was noted in ten patients. Putaminal atrophy was seen in nine patients, six of whom had additional hyperintense signal changes. Our study highlights frequent putaminal atrophy and signal changes in RE, which suggests a more extensive basal ganglion involvement than emphasized previously. Recognition of putaminal changes may be a useful additional tool in the radiological diagnosis of RE. (orig.)
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The interacting role of media sequence and product involvement in cross-media campaigns
Voorveld, H.A.M.; Neijens, P.C.; Smit, E.G.
2012-01-01
The aim of the study is to investigate the role of media sequence on consumers' responses to cross-media campaigns. To do so, we conducted an experiment in which we studied the effects of a combination of TV commercials and websites (TV commercial-website vs. website-TV commercial) for two different
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Directory of Open Access Journals (Sweden)
ZHANG Zhengpeng
2015-10-01
Full Text Available Panoramic image matching method with the constraint condition of local structure from motion similarity feature is an important method, the process requires multivariable kernel density estimations for the structure from motion feature used nonparametric mean shift. Proper selection of the kernel bandwidth is a critical step for convergence speed and accuracy of matching method. Variable bandwidth with adaptive structure from motion feature for panoramic image matching method has been proposed in this work. First the bandwidth matrix is defined using the locally adaptive spatial structure of the sampling point in spatial domain and optical flow domain. The relaxation diffusion process of structure from motion similarity feature is described by distance weighting method of local optical flow feature vector. Then the expression form of adaptive multivariate kernel density function is given out, and discusses the solution of the mean shift vector, termination conditions, and the seed point selection method. The final fusions of multi-scale SIFT the features and structure features to establish a unified panoramic image matching framework. The sphere panoramic images from vehicle-borne mobile measurement system are chosen such that a comparison analysis between fixed bandwidth and adaptive bandwidth is carried out in detail. The results show that adaptive bandwidth is good for case with the inlier ratio changes and the object space scale changes. The proposed method can realize the adaptive similarity measure of structure from motion feature, improves the correct matching points and matching rate, experimental results have shown our method to be robust.
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Chaos game representation (CGR)-walk model for DNA sequences
International Nuclear Information System (INIS)
Jie, Gao; Zhen-Yuan, Xu
2009-01-01
Chaos game representation (CGR) is an iterative mapping technique that processes sequences of units, such as nucleotides in a DNA sequence or amino acids in a protein, in order to determine the coordinates of their positions in a continuous space. This distribution of positions has two features: one is unique, and the other is source sequence that can be recovered from the coordinates so that the distance between positions may serve as a measure of similarity between the corresponding sequences. A CGR-walk model is proposed based on CGR coordinates for the DNA sequences. The CGR coordinates are converted into a time series, and a long-memory ARFIMA (p, d, q) model, where ARFIMA stands for autoregressive fractionally integrated moving average, is introduced into the DNA sequence analysis. This model is applied to simulating real CGR-walk sequence data of ten genomic sequences. Remarkably long-range correlations are uncovered in the data, and the results from these models are reasonably fitted with those from the ARFIMA (p, d, q) model. (cross-disciplinary physics and related areas of science and technology)
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Salutogenic service user involvement in nursing research: a case study.
Mjøsund, Nina Helen; Vinje, Hege Forbech; Eriksson, Monica; Haaland-Øverby, Mette; Jensen, Sven Liang; Kjus, Solveig; Norheim, Irene; Portaasen, Inger-Lill; Espnes, Geir Arild
2018-05-12
The aim was to explore the process of involving mental healthcare service users in a mental health promotion research project as research advisors and to articulate features of the collaboration which encouraged and empowered the advisors to make significant contributions to the research process and outcome. There is an increasing interest in evaluating aspects of service user involvement in nursing research. Few descriptions exist of features that enable meaningful service user involvement. We draw on experiences from conducting research which used the methodology interpretative phenomenological analysis to explore how persons with mental disorders perceived mental health. Aside from the participants in the project, five research advisors with service user experience were involved in the entire research process. We applied a case study design to explore the ongoing processes of service user involvement. Documents and texts produced while conducting the project (2012-2016), as well as transcripts from multistage focus group discussions with the research advisors, were analysed. The level of involvement was dynamic and varied throughout the different stages of the research process. Six features: leadership, meeting structure, role clarification, being members of a team, a focus on possibilities and being seen and treated as holistic individuals, were guiding principles for a salutogenic service user involvement. These features strengthened the advisors' perception of themselves as valuable and competent contributors. Significant contributions from research advisors were promoted by facilitating the process of involvement. A supporting structure and atmosphere were consistent with a salutogenic service user involvement. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
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Transitions in Lava Emplacement Recorded in the Deccan Traps Sequence (India)
Vanderkluysen, L.; Self, S.; Jay, A. E.; Sheth, H. C.; Clarke, A. B.
2015-12-01
Transitions in the style of lava flow emplacement are recognized in the stratigraphic sequence of several mafic large igneous provinces (LIPs), including the Etendeka (Namibia), the Faeroe Islands (North Atlantic LIP), the Ethiopian Traps, and the Deccan Traps (India). These transitions, from units dominated by meter-sized pāhoehoe toes and lobes to those dominated by inflated sheet lobes tens to hundreds of meters in width and meters to tens of meters in height, seems to be a fundamental feature of LIP emplacement. In the Deccan, this volcanological transition is thought to coincide with deeper changes to the volcano-magmatic system expressed, notably, in the trace element and isotopic signature of erupted flows. We investigated this transition in the Deccan Traps by logging eight sequences along the Western Ghats, an escarpment in western India where the Deccan province is thickest and best exposed. The Deccan province, which once covered ~1 million km2 of west-central India, is subdivided in eleven chemo-stratigraphic formations in the type sections of the Western Ghats. Where the lower Deccan formations are exposed, we found that as much as 65% of the exposed thickness (below the Khandala Formation) is made up of sheet lobes, from 40% in the Bhimashankar Formation to 75% in the Thakurvadi Formation. Near the bottom of the sequence, 25% of the Neral Formation is composed of sheet lobes ≥15 m in thickness. On this basis, the traditional view that inflated sheet lobes are an exclusive feature of the upper part of the stratigraphy must be challenged. Several mechanisms have been proposed to explain the development of compound flows and inflated sheet lobes, involving one or more of the following factors: underlying slope, varying effusion rate, and source geometry. Analogue experiments are currently under way to test the relative influence of each of these factors in the development of different lava flow morphologies in LIPs.
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Godkin, A; Friede, T; Davenport, M; Stevanovic, S; Willis, A; Jewell, D; Hill, A; Rammensee, H G
1997-06-01
HLA-DQ8 (A1*0301, B1*0302) and -DQ2 (A1*0501, B1*0201) are both associated with diseases such as insulin-dependent diabetes mellitus and coeliac disease. We used the technique of pool sequencing to look at the requirements of peptides binding to HLA-DQ8, and combined these data with naturally sequenced ligands and in vitro binding assays to describe a novel motif for HLA-DQ8. The motif, which has the same basic format as many HLA-DR molecules, consists of four or five anchor regions, in the positions from the N-terminus of the binding core of n, n + 3, n + 5/6 and n + 8, i.e. P1, P4, P6/7 and P9. P1 and P9 require negative or polar residues, with mainly aliphatic residues at P4 and P6/7. The features of the HLA-DQ8 motif were then compared to a pool sequence of peptides eluted from HLA-DQ2. A consensus motif for the binding of a common peptide which may be involved in disease pathogenesis is described. Neither of the disease-associated alleles HLA-DQ2 and -DQ8 have Asp at position 57 of the beta-chain. This Asp, if present, may form a salt bridge with an Arg at position 79 of the alpha-chain and so alter the binding specificity of P9. HLA-DQ2 and -DQ8 both appear to prefer negatively charged amino acids at P9. In contrast, HLA-DQ7 (A1*0301, B1*0301), which is not associated with diabetes, has Asp at beta 57, allowing positively charged amino acids at P9. This analysis of the sequence features of DQ-binding peptides suggests molecular characteristics which may be useful to predict epitopes involved in disease pathogenesis.
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Intra-species sequence comparisons for annotating genomes
Energy Technology Data Exchange (ETDEWEB)
Boffelli, Dario; Weer, Claire V.; Weng, Li; Lewis, Keith D.; Shoukry, Malak I.; Pachter, Lior; Keys, David N.; Rubin, Edward M.
2004-07-15
Analysis of sequence variation among members of a single species offers a potential approach to identify functional DNA elements responsible for biological features unique to that species. Due to its high rate of allelic polymorphism and ease of genetic manipulability, we chose the sea squirt, Ciona intestinalis, to explore intra-species sequence comparisons for genome annotation. A large number of C. intestinalis specimens were collected from four continents and a set of genomic intervals amplified, resequenced and analyzed to determine the mutation rates at each nucleotide in the sequence. We found that regions with low mutation rates efficiently demarcated functionally constrained sequences: these include a set of noncoding elements, which we showed in C intestinalis transgenic assays to act as tissue-specific enhancers, as well as the location of coding sequences. This illustrates that comparisons of multiple members of a species can be used for genome annotation, suggesting a path for the annotation of the sequenced genomes of organisms occupying uncharacterized phylogenetic branches of the animal kingdom and raises the possibility that the resequencing of a large number of Homo sapiens individuals might be used to annotate the human genome and identify sequences defining traits unique to our species. The sequence data from this study has been submitted to GenBank under accession nos. AY667278-AY667407.
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Investigation of a steam generator tube rupture sequence using VICTORIA
International Nuclear Information System (INIS)
Bixler, N.E.; Erickson, C.M.; Schaperow, J.H.
1995-01-01
VICTORIA-92 is a mechanistic computer code for analyzing fission product behavior within the reactor coolant system (RCS) during a severe reactor accident. It provides detailed predictions of the release of radionuclides and nonradioactive materials from the core and transport of these materials within the RCS. The modeling accounts for the chemical and aerosol processes that affect radionuclide behavior. Coupling of detailed chemistry and aerosol packages is a unique feature of VICTORIA; it allows exploration of phenomena involving deposition, revaporization, and re-entrainment that cannot be resolved with other codes. The purpose of this work is to determine the attenuation of fission products in the RCS and on the secondary side of the steam generator in an accident initiated by a steam generator tube rupture (SGTR). As a class, bypass sequences have been identified in NUREG-1150 as being risk dominant for the Surry and Sequoyah pressurized water reactor (PWR) plants
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da Fonseca, Néli José; Lima Afonso, Marcelo Querino; Pedersolli, Natan Gonçalves; de Oliveira, Lucas Carrijo; Andrade, Dhiego Souto; Bleicher, Lucas
2017-10-28
Flaviviruses are responsible for serious diseases such as dengue, yellow fever, and zika fever. Their genomes encode a polyprotein which, after cleavage, results in three structural and seven non-structural proteins. Homologous proteins can be studied by conservation and coevolution analysis as detected in multiple sequence alignments, usually reporting positions which are strictly necessary for the structure and/or function of all members in a protein family or which are involved in a specific sub-class feature requiring the coevolution of residue sets. This study provides a complete conservation and coevolution analysis on all flaviviruses non-structural proteins, with results mapped on all well-annotated available sequences. A literature review on the residues found in the analysis enabled us to compile available information on their roles and distribution among different flaviviruses. Also, we provide the mapping of conserved and coevolved residues for all sequences currently in SwissProt as a supplementary material, so that particularities in different viruses can be easily analyzed. Copyright © 2017 Elsevier Inc. All rights reserved.
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Imaging features of kaposiform lymphangiomatosis
International Nuclear Information System (INIS)
Goyal, Pradeep; Alomari, Ahmad I.; Shaikh, Raja; Chaudry, Gulraiz; Kozakewich, Harry P.; Perez-Atayde, Antonio R.; Trenor, Cameron C.; Fishman, Steven J.; Greene, Arin K.
2016-01-01
Kaposiform lymphangiomatosis is a rare, aggressive lymphatic disorder. The imaging and presenting features of kaposiform lymphangiomatosis can overlap with those of central conducting lymphatic anomaly and generalized lymphatic anomaly. To analyze the imaging findings of kaposiform lymphangiomatosis disorder and highlight features most suggestive of this diagnosis. We retrospectively identified and characterized 20 children and young adults with histopathological diagnosis of kaposiform lymphangiomatosis and radiologic imaging referred to the vascular anomalies center between 1995 and 2015. The median age at onset was 6.5 years (range 3 months to 27 years). The most common presenting features were respiratory compromise (dyspnea, cough, chest pain; 55.5%), swelling/mass (25%), bleeding (15%) and fracture (5%). The thoracic cavity was involved in all patients; all patients had mediastinal involvement followed by lung parenchymal disease (90%) and pleural (85%) and pericardial (50%) effusions. The most common extra-thoracic sites of disease were the retroperitoneum (80%), bone (60%), abdominal viscera (55%) and muscles (45%). There was characteristic enhancing and infiltrative soft-tissue thickening in the mediastinum and retroperitoneum extending along the lymphatic distribution. Kaposiform lymphangiomatosis has overlapping imaging features with central conducting lymphatic anomaly and generalized lymphatic anomaly. Presence of mediastinal or retroperitoneal enhancing and infiltrative soft-tissue disease along the lymphatic distribution, hemorrhagic effusions and moderate thrombocytopenia (50-100,000/μl) should favor diagnosis of kaposiform lymphangiomatosis. (orig.)
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Protein functional features are reflected in the patterns of mRNA translation speed.
López, Daniel; Pazos, Florencio
2015-07-09
The degeneracy of the genetic code makes it possible for the same amino acid string to be coded by different messenger RNA (mRNA) sequences. These "synonymous mRNAs" may differ largely in a number of aspects related to their overall translational efficiency, such as secondary structure content and availability of the encoded transfer RNAs (tRNAs). Consequently, they may render different yields of the translated polypeptides. These mRNA features related to translation efficiency are also playing a role locally, resulting in a non-uniform translation speed along the mRNA, which has been previously related to some protein structural features and also used to explain some dramatic effects of "silent" single-nucleotide-polymorphisms (SNPs). In this work we perform the first large scale analysis of the relationship between three experimental proxies of mRNA local translation efficiency and the local features of the corresponding encoded proteins. We found that a number of protein functional and structural features are reflected in the patterns of ribosome occupancy, secondary structure and tRNA availability along the mRNA. One or more of these proxies of translation speed have distinctive patterns around the mRNA regions coding for certain protein local features. In some cases the three patterns follow a similar trend. We also show specific examples where these patterns of translation speed point to the protein's important structural and functional features. This support the idea that the genome not only codes the protein functional features as sequences of amino acids, but also as subtle patterns of mRNA properties which, probably through local effects on the translation speed, have some consequence on the final polypeptide. These results open the possibility of predicting a protein's functional regions based on a single genomic sequence, and have implications for heterologous protein expression and fine-tuning protein function.
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Image Recommendation Algorithm Using Feature-Based Collaborative Filtering
Kim, Deok-Hwan
As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.
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Spatial Narrative As Feature Of Singularity In Sacral Architecture
Directory of Open Access Journals (Sweden)
Gytis Oržikauskas
2014-05-01
Full Text Available The paper analyses architectural compositions of various religious complexes – historical and contemporary – apart from their stylistic features. The most prominent ensembles under analysis have one noticeably common feature – spatial narrative. The foreseen sequence of forms of experience and spatial structure tell different religious narratives depending on which different aspects of faith were actualized in a given period. The analyzed examples stand in proof that suggestibility of religious aspects in sacral architecture are inseparable from their artistic suggestibility aspects. In some cases, these aspects are less related to architectural stylistic means, but have a direct connection to such components of architectural compositions as foreseen sequence of a visitor’s experience and semantics of particular forms, i.e. architectural narrative, which is achieved not only through the means of perception of space, but also by the relationship to social and cultural meanings and subtext of architecture.
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cDNA sequences of two inducible T-cell genes
Energy Technology Data Exchange (ETDEWEB)
Kwon, B.S. (Indiana Univ. School of Medicine, Indianapolis (USA) Guthrie Research Institute, Sayre, PA (USA)); Weissman, S.M. (Yale Univ., New Haven, CT (USA))
1989-03-01
The authors have previously described a set of human T-lymphocyte-specific cDNA clones isolated by a modified differential screening procedure. Apparent full-length cDNAs containing the sequences of 14 of the 16 initial isolates were sequenced and were found to represent five different species of mRNA; three of the five species were identical to previously reported cDNA sequences of preproenkephalin, T-cell-replacing factor, and a serine esterase, respectively. The other two species, 4-1BB and L2G25B, were inducible sequences found in mRNA from both a cytolytic T-lymphocyte and a helper T-lymphocyte clone and were not previously described in T-cell mRNA; these mRNA sequences encode peptides of 256 and 92 amino acids, respectively. Both peptides contain putative leader sequences. The protein encoded by 4-1BB also has a potential membrane anchor segment and other features also seen in known receptor proteins.
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Human gait recognition by pyramid of HOG feature on silhouette images
Yang, Guang; Yin, Yafeng; Park, Jeanrok; Man, Hong
2013-03-01
As a uncommon biometric modality, human gait recognition has a great advantage of identify people at a distance without high resolution images. It has attracted much attention in recent years, especially in the fields of computer vision and remote sensing. In this paper, we propose a human gait recognition framework that consists of a reliable background subtraction method followed by the pyramid of Histogram of Gradient (pHOG) feature extraction on the silhouette image, and a Hidden Markov Model (HMM) based classifier. Through background subtraction, the silhouette of human gait in each frame is extracted and normalized from the raw video sequence. After removing the shadow and noise in each region of interest (ROI), pHOG feature is computed on the silhouettes images. Then the pHOG features of each gait class will be used to train a corresponding HMM. In the test stage, pHOG feature will be extracted from each test sequence and used to calculate the posterior probability toward each trained HMM model. Experimental results on the CASIA Gait Dataset B1 demonstrate that with our proposed method can achieve very competitive recognition rate.
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Statistical analyses of conserved features of genomic islands in bacteria.
Guo, F-B; Xia, Z-K; Wei, W; Zhao, H-L
2014-03-17
We performed statistical analyses of five conserved features of genomic islands of bacteria. Analyses were made based on 104 known genomic islands, which were identified by comparative methods. Four of these features include sequence size, abnormal G+C content, flanking tRNA gene, and embedded mobility gene, which are frequently investigated. One relatively new feature, G+C homogeneity, was also investigated. Among the 104 known genomic islands, 88.5% were found to fall in the typical length of 10-200 kb and 80.8% had G+C deviations with absolute values larger than 2%. For the 88 genomic islands whose hosts have been sequenced and annotated, 52.3% of them were found to have flanking tRNA genes and 64.7% had embedded mobility genes. For the homogeneity feature, 85% had an h homogeneity index less than 0.1, indicating that their G+C content is relatively uniform. Taking all the five features into account, 87.5% of 88 genomic islands had three of them. Only one genomic island had only one conserved feature and none of the genomic islands had zero features. These statistical results should help to understand the general structure of known genomic islands. We found that larger genomic islands tend to have relatively small G+C deviations relative to absolute values. For example, the absolute G+C deviations of 9 genomic islands longer than 100,000 bp were all less than 5%. This is a novel but reasonable result given that larger genomic islands should have greater restrictions in their G+C contents, in order to maintain the stable G+C content of the recipient genome.
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Sequence determinants of human microsatellite variability
Directory of Open Access Journals (Sweden)
Jakobsson Mattias
2009-12-01
Full Text Available Abstract Background Microsatellite loci are frequently used in genomic studies of DNA sequence repeats and in population studies of genetic variability. To investigate the effect of sequence properties of microsatellites on their level of variability we have analyzed genotypes at 627 microsatellite loci in 1,048 worldwide individuals from the HGDP-CEPH cell line panel together with the DNA sequences of these microsatellites in the human RefSeq database. Results Calibrating PCR fragment lengths in individual genotypes by using the RefSeq sequence enabled us to infer repeat number in the HGDP-CEPH dataset and to calculate the mean number of repeats (as opposed to the mean PCR fragment length, under the assumption that differences in PCR fragment length reflect differences in the numbers of repeats in the embedded repeat sequences. We find the mean and maximum numbers of repeats across individuals to be positively correlated with heterozygosity. The size and composition of the repeat unit of a microsatellite are also important factors in predicting heterozygosity, with tetra-nucleotide repeat units high in G/C content leading to higher heterozygosity. Finally, we find that microsatellites containing more separate sets of repeated motifs generally have higher heterozygosity. Conclusions These results suggest that sequence properties of microsatellites have a significant impact in determining the features of human microsatellite variability.
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Crowding with conjunctions of simple features.
Põder, Endel; Wagemans, Johan
2007-11-20
Several recent studies have related crowding with the feature integration stage in visual processing. In order to understand the mechanisms involved in this stage, it is important to use stimuli that have several features to integrate, and these features should be clearly defined and measurable. In this study, Gabor patches were used as target and distractor stimuli. The stimuli differed in three dimensions: spatial frequency, orientation, and color. A group of 3, 5, or 7 objects was presented briefly at 4 deg eccentricity of the visual field. The observers' task was to identify the object located in the center of the group. A strong effect of the number of distractors was observed, consistent with various spatial pooling models. The analysis of incorrect responses revealed that these were a mix of feature errors and mislocalizations of the target object. Feature errors were not purely random, but biased by the features of distractors. We propose a simple feature integration model that predicts most of the observed regularities.
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Gubser, Caroline; Smith, Geoffrey L
2002-04-01
Camelpox virus (CMPV) and variola virus (VAR) are orthopoxviruses (OPVs) that share several biological features and cause high mortality and morbidity in their single host species. The sequence of a virulent CMPV strain was determined; it is 202182 bp long, with inverted terminal repeats (ITRs) of 6045 bp and has 206 predicted open reading frames (ORFs). As for other poxviruses, the genes are tightly packed with little non-coding sequence. Most genes within 25 kb of each terminus are transcribed outwards towards the terminus, whereas genes within the centre of the genome are transcribed from either DNA strand. The central region of the genome contains genes that are highly conserved in other OPVs and 87 of these are conserved in all sequenced chordopoxviruses. In contrast, genes towards either terminus are more variable and encode proteins involved in host range, virulence or immunomodulation. In some cases, these are broken versions of genes found in other OPVs. The relationship of CMPV to other OPVs was analysed by comparisons of DNA and predicted protein sequences, repeats within the ITRs and arrangement of ORFs within the terminal regions. Each comparison gave the same conclusion: CMPV is the closest known virus to variola virus, the cause of smallpox.
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Image sequence analysis workstation for multipoint motion analysis
Mostafavi, Hassan
1990-08-01
This paper describes an application-specific engineering workstation designed and developed to analyze motion of objects from video sequences. The system combines the software and hardware environment of a modem graphic-oriented workstation with the digital image acquisition, processing and display techniques. In addition to automation and Increase In throughput of data reduction tasks, the objective of the system Is to provide less invasive methods of measurement by offering the ability to track objects that are more complex than reflective markers. Grey level Image processing and spatial/temporal adaptation of the processing parameters is used for location and tracking of more complex features of objects under uncontrolled lighting and background conditions. The applications of such an automated and noninvasive measurement tool include analysis of the trajectory and attitude of rigid bodies such as human limbs, robots, aircraft in flight, etc. The system's key features are: 1) Acquisition and storage of Image sequences by digitizing and storing real-time video; 2) computer-controlled movie loop playback, freeze frame display, and digital Image enhancement; 3) multiple leading edge tracking in addition to object centroids at up to 60 fields per second from both live input video or a stored Image sequence; 4) model-based estimation and tracking of the six degrees of freedom of a rigid body: 5) field-of-view and spatial calibration: 6) Image sequence and measurement data base management; and 7) offline analysis software for trajectory plotting and statistical analysis.
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Directory of Open Access Journals (Sweden)
Sutapa Datta
Full Text Available An important step in understanding gene regulation is to identify the promoter regions where the transcription factor binding takes place. Predicting a promoter region de novo has been a theoretical goal for many researchers for a long time. There exists a number of in silico methods to predict the promoter region de novo but most of these methods are still suffering from various shortcomings, a major one being the selection of appropriate features of promoter region distinguishing them from non-promoters. In this communication, we have proposed a new composite method that predicts promoter sequences based on the interrelationship between structural profiles of DNA and primary sequence elements of the promoter regions. We have shown that a Context Free Grammar (CFG can formalize the relationships between different primary sequence features and by utilizing the CFG, we demonstrate that an efficient parser can be constructed for extracting these relationships from DNA sequences to distinguish the true promoter sequences from non-promoter sequences. Along with CFG, we have extracted the structural features of the promoter region to improve upon the efficiency of our prediction system. Extensive experiments performed on different datasets reveals that our method is effective in predicting promoter sequences on a genome-wide scale and performs satisfactorily as compared to other promoter prediction techniques.
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Datta, Sutapa; Mukhopadhyay, Subhasis
2013-01-01
An important step in understanding gene regulation is to identify the promoter regions where the transcription factor binding takes place. Predicting a promoter region de novo has been a theoretical goal for many researchers for a long time. There exists a number of in silico methods to predict the promoter region de novo but most of these methods are still suffering from various shortcomings, a major one being the selection of appropriate features of promoter region distinguishing them from non-promoters. In this communication, we have proposed a new composite method that predicts promoter sequences based on the interrelationship between structural profiles of DNA and primary sequence elements of the promoter regions. We have shown that a Context Free Grammar (CFG) can formalize the relationships between different primary sequence features and by utilizing the CFG, we demonstrate that an efficient parser can be constructed for extracting these relationships from DNA sequences to distinguish the true promoter sequences from non-promoter sequences. Along with CFG, we have extracted the structural features of the promoter region to improve upon the efficiency of our prediction system. Extensive experiments performed on different datasets reveals that our method is effective in predicting promoter sequences on a genome-wide scale and performs satisfactorily as compared to other promoter prediction techniques. PMID:23437045
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Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics.
Directory of Open Access Journals (Sweden)
Ehsaneddin Asgari
Full Text Available We introduce a new representation and feature extraction method for biological sequences. Named bio-vectors (BioVec to refer to biological sequences in general with protein-vectors (ProtVec for proteins (amino-acid sequences and gene-vectors (GeneVec for gene sequences, this representation can be widely used in applications of deep learning in proteomics and genomics. In the present paper, we focus on protein-vectors that can be utilized in a wide array of bioinformatics investigations such as family classification, protein visualization, structure prediction, disordered protein identification, and protein-protein interaction prediction. In this method, we adopt artificial neural network approaches and represent a protein sequence with a single dense n-dimensional vector. To evaluate this method, we apply it in classification of 324,018 protein sequences obtained from Swiss-Prot belonging to 7,027 protein families, where an average family classification accuracy of 93%±0.06% is obtained, outperforming existing family classification methods. In addition, we use ProtVec representation to predict disordered proteins from structured proteins. Two databases of disordered sequences are used: the DisProt database as well as a database featuring the disordered regions of nucleoporins rich with phenylalanine-glycine repeats (FG-Nups. Using support vector machine classifiers, FG-Nup sequences are distinguished from structured protein sequences found in Protein Data Bank (PDB with a 99.8% accuracy, and unstructured DisProt sequences are differentiated from structured DisProt sequences with 100.0% accuracy. These results indicate that by only providing sequence data for various proteins into this model, accurate information about protein structure can be determined. Importantly, this model needs to be trained only once and can then be applied to extract a comprehensive set of information regarding proteins of interest. Moreover, this representation can be
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Order and correlations in genomic DNA sequences. The spectral approach
International Nuclear Information System (INIS)
Lobzin, Vasilii V; Chechetkin, Vladimir R
2000-01-01
The structural analysis of genomic DNA sequences is discussed in the framework of the spectral approach, which is sufficiently universal due to the reciprocal correspondence and mutual complementarity of Fourier transform length scales. The spectral characteristics of random sequences of the same nucleotide composition possess the property of self-averaging for relatively short sequences of length M≥100-300. Comparison with the characteristics of random sequences determines the statistical significance of the structural features observed. Apart from traditional applications to the search for hidden periodicities, spectral methods are also efficient in studying mutual correlations in DNA sequences. By combining spectra for structure factors and correlation functions, not only integral correlations can be estimated but also their origin identified. Using the structural spectral entropy approach, the regularity of a sequence can be quantitatively assessed. A brief introduction to the problem is also presented and other major methods of DNA sequence analysis described. (reviews of topical problems)
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Endoscopic Findings of Upper Gastrointestinal Involvement in Primary Vasculitis.
Gong, Eun Jeong; Kim, Do Hoon; Chun, Joo Hyun; Ahn, Ji Yong; Choi, Kwi-Sook; Jung, Kee Wook; Lee, Jeong Hoon; Choi, Kee Don; Song, Ho June; Lee, Gin Hyug; Jung, Hwoon-Yong; Kim, Jin Ho; Song, In Hye; Kim, Yong-Gil
2016-07-15
Gastrointestinal involvement in vasculitis may result in life-threatening complications. However, its variable clinical presentations and endoscopic features, and the rarity of the disease, often result in delayed diagnosis. Clinical characteristics, endoscopic features, and histopathological findings were reviewed from medical records. Of 6,477 patients with vasculitis, 148 were diagnosed as primary vasculitis with upper gastrointestinal involvement. Of these, 21 cases (14.2%) were classified as large-vessel vasculitis, 17 cases (11.5%) as medium-vessel vasculitis, and 110 cases (74.3%) as small-vessel vasculitis. According to the specific diagnosis, IgA vasculitis (Henoch-Schönlein purpura) was the most common diagnosis (56.8%), followed by Takayasu arteritis (14.1%), microscopic polyangiitis (10.1%), and polyarteritis nodosa (6.8%). Gastrointestinal symptoms were present in 113 subjects (76.4%), with abdominal pain (78.8%) the most common symptom. Erosion and ulcers were striking endoscopic features, and the second portion of the duodenum was the most frequently involved site. Biopsy specimens were obtained from 124 patients, and only eight (5.4%) presented histopathological signs of vasculitis. Diagnosis of vasculitis involving the upper gastrointestinal tract is difficult. Because of the widespread use of endoscopy, combining clinical features with endoscopic findings may facilitate making appropriate diagnoses; however, the diagnostic yield of endoscopic biopsy is low.
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Predicting DNA binding proteins using support vector machine with hybrid fractal features.
Niu, Xiao-Hui; Hu, Xue-Hai; Shi, Feng; Xia, Jing-Bo
2014-02-21
DNA-binding proteins play a vitally important role in many biological processes. Prediction of DNA-binding proteins from amino acid sequence is a significant but not fairly resolved scientific problem. Chaos game representation (CGR) investigates the patterns hidden in protein sequences, and visually reveals previously unknown structure. Fractal dimensions (FD) are good tools to measure sizes of complex, highly irregular geometric objects. In order to extract the intrinsic correlation with DNA-binding property from protein sequences, CGR algorithm, fractal dimension and amino acid composition are applied to formulate the numerical features of protein samples in this paper. Seven groups of features are extracted, which can be computed directly from the primary sequence, and each group is evaluated by the 10-fold cross-validation test and Jackknife test. Comparing the results of numerical experiments, the group of amino acid composition and fractal dimension (21-dimension vector) gets the best result, the average accuracy is 81.82% and average Matthew's correlation coefficient (MCC) is 0.6017. This resulting predictor is also compared with existing method DNA-Prot and shows better performances. © 2013 The Authors. Published by Elsevier Ltd All rights reserved.
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Crash sequence based risk matrix for motorcycle crashes.
Wu, Kun-Feng; Sasidharan, Lekshmi; Thor, Craig P; Chen, Sheng-Yin
2018-04-05
Considerable research has been conducted related to motorcycle and other powered-two-wheeler (PTW) crashes; however, it always has been controversial among practitioners concerning with types of crashes should be first targeted and how to prioritize resources for the implementation of mitigating actions. Therefore, there is a need to identify types of motorcycle crashes that constitute the greatest safety risk to riders - most frequent and most severe crashes. This pilot study seeks exhibit the efficacy of a new approach for prioritizing PTW crash causation sequences as they relate to injury severity to better inform the application of mitigating countermeasures. To accomplish this, the present study constructed a crash sequence-based risk matrix to identify most frequent and most severe motorcycle crashes in an attempt to better connect causes and countermeasures of PTW crashes. Although the frequency of each crash sequence can be computed from crash data, a crash severity model is needed to compare the levels of crash severity among different crash sequences, while controlling for other factors that also have effects on crash severity such drivers' age, use of helmet, etc. The construction of risk matrix based on crash sequences involve two tasks: formulation of crash sequence and the estimation of a mixed-effects (ME) model to adjust the levels of severities for each crash sequence to account for other crash contributing factors that would have an effect on the maximum level of crash severity in a crash. Three data elements from the National Automotive Sampling System - General Estimating System (NASS-GES) data were utilized to form a crash sequence: critical event, crash types, and sequence of events. A mixed-effects model was constructed to model the severity levels for each crash sequence while accounting for the effects of those crash contributing factors on crash severity. A total of 8039 crashes involving 8208 motorcycles occurred during 2011 and 2013 were
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Directory of Open Access Journals (Sweden)
Jingjing Li
2017-07-01
Full Text Available ObjectivePrimary amyloidosis is a disease with a poor prognosis and multi-organ involvement. Here, we report the clinical and pathological features of a patient with primary amyloidosis featuring autonomic neuropathy as the initial symptom and albuminocytologic dissociation in the cerebrospinal fluid (CSF.MethodsThe patient was a 60-year-old Chinese male with numbness, orthostatic hypotension, and gastrointestinal symptoms. For diagnosis, we performed an electromyogram (EMG, lumbar puncture, Bence Jones protein urine test, serum electrophoresis blood test, sural nerve and rectal membrane biopsies, transthyretin (TTR gene sequencing, and bone marrow puncture.ResultsCongo red staining of sural nerve and rectal membrane biopsies showed amyloid deposition and apple-green birefringence was visualized under polarized light microscopy. TTR gene sequencing showed no causative mutation. Following lumbar puncture, normal CSF cell counts and elevated CSF protein concentration (1,680 mg/L were detected. Bone marrow puncture showed that out of the total number of whole blood cells, 0.56% were abnormal plasma cells and that 87.4% of the total number of plasma cells were abnormal. EMG results showed mixed peripheral nerve damage predominately in the sensory nerve fibers.ConclusionObvious symptoms of neuropathy, particularly autonomic neuropathy, albuminocytologic dissociation, and organ function damage suggested a diagnosis of amyloidosis. In such patients, neurologists should use caution to differentiate between chronic inflammatory demyelinating polyneuropathy, primary amyloidosis, and familial amyloid neuropathy.
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Directory of Open Access Journals (Sweden)
Xiaoxia Yang
Full Text Available Protein-nucleic acid interactions are central to various fundamental biological processes. Automated methods capable of reliably identifying DNA- and RNA-binding residues in protein sequence are assuming ever-increasing importance. The majority of current algorithms rely on feature-based prediction, but their accuracy remains to be further improved. Here we propose a sequence-based hybrid algorithm SNBRFinder (Sequence-based Nucleic acid-Binding Residue Finder by merging a feature predictor SNBRFinderF and a template predictor SNBRFinderT. SNBRFinderF was established using the support vector machine whose inputs include sequence profile and other complementary sequence descriptors, while SNBRFinderT was implemented with the sequence alignment algorithm based on profile hidden Markov models to capture the weakly homologous template of query sequence. Experimental results show that SNBRFinderF was clearly superior to the commonly used sequence profile-based predictor and SNBRFinderT can achieve comparable performance to the structure-based template methods. Leveraging the complementary relationship between these two predictors, SNBRFinder reasonably improved the performance of both DNA- and RNA-binding residue predictions. More importantly, the sequence-based hybrid prediction reached competitive performance relative to our previous structure-based counterpart. Our extensive and stringent comparisons show that SNBRFinder has obvious advantages over the existing sequence-based prediction algorithms. The value of our algorithm is highlighted by establishing an easy-to-use web server that is freely accessible at http://ibi.hzau.edu.cn/SNBRFinder.
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Yang, Xiaoxia; Wang, Jia; Sun, Jun; Liu, Rong
2015-01-01
Protein-nucleic acid interactions are central to various fundamental biological processes. Automated methods capable of reliably identifying DNA- and RNA-binding residues in protein sequence are assuming ever-increasing importance. The majority of current algorithms rely on feature-based prediction, but their accuracy remains to be further improved. Here we propose a sequence-based hybrid algorithm SNBRFinder (Sequence-based Nucleic acid-Binding Residue Finder) by merging a feature predictor SNBRFinderF and a template predictor SNBRFinderT. SNBRFinderF was established using the support vector machine whose inputs include sequence profile and other complementary sequence descriptors, while SNBRFinderT was implemented with the sequence alignment algorithm based on profile hidden Markov models to capture the weakly homologous template of query sequence. Experimental results show that SNBRFinderF was clearly superior to the commonly used sequence profile-based predictor and SNBRFinderT can achieve comparable performance to the structure-based template methods. Leveraging the complementary relationship between these two predictors, SNBRFinder reasonably improved the performance of both DNA- and RNA-binding residue predictions. More importantly, the sequence-based hybrid prediction reached competitive performance relative to our previous structure-based counterpart. Our extensive and stringent comparisons show that SNBRFinder has obvious advantages over the existing sequence-based prediction algorithms. The value of our algorithm is highlighted by establishing an easy-to-use web server that is freely accessible at http://ibi.hzau.edu.cn/SNBRFinder.
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Kinnebrew, John S.; Biswas, Gautam
2012-01-01
Our learning-by-teaching environment, Betty's Brain, captures a wealth of data on students' learning interactions as they teach a virtual agent. This paper extends an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs sequence mining techniques to…
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Naito, Mariko; Ogura, Yoshitoshi; Itoh, Takehiko; Shoji, Mikio; Okamoto, Masaaki; Hayashi, Tetsuya; Nakayama, Koji
2016-02-01
Prevotella intermedia is a pathogenic bacterium involved in periodontal diseases. Here, we present the complete genome sequence of a clinical strain, OMA14, of this bacterium along with the results of comparative genome analysis with strain 17 of the same species whose genome has also been sequenced, but not fully analysed yet. The genomes of both strains consist of two circular chromosomes: the larger chromosomes are similar in size and exhibit a high overall linearity of gene organizations, whereas the smaller chromosomes show a significant size variation and have undergone remarkable genome rearrangements. Unique features of the Pre. intermedia genomes are the presence of a remarkable number of essential genes on the second chromosomes and the abundance of conjugative and mobilizable transposons (CTns and MTns). The CTns/MTns are particularly abundant in the second chromosomes, involved in its extensive genome rearrangement, and have introduced a number of strain-specific genes into each strain. We also found a novel 188-bp repeat sequence that has been highly amplified in Pre. intermedia and are specifically distributed among the Pre. intermedia-related species. These findings expand our understanding of the genetic features of Pre. intermedia and the roles of CTns and MTns in the evolution of bacteria. © The Author 2015. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.
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Increasing the reach of forensic genetics with massively parallel sequencing.
Budowle, Bruce; Schmedes, Sarah E; Wendt, Frank R
2017-09-01
The field of forensic genetics has made great strides in the analysis of biological evidence related to criminal and civil matters. More so, the discipline has set a standard of performance and quality in the forensic sciences. The advent of massively parallel sequencing will allow the field to expand its capabilities substantially. This review describes the salient features of massively parallel sequencing and how it can impact forensic genetics. The features of this technology offer increased number and types of genetic markers that can be analyzed, higher throughput of samples, and the capability of targeting different organisms, all by one unifying methodology. While there are many applications, three are described where massively parallel sequencing will have immediate impact: molecular autopsy, microbial forensics and differentiation of monozygotic twins. The intent of this review is to expose the forensic science community to the potential enhancements that have or are soon to arrive and demonstrate the continued expansion the field of forensic genetics and its service in the investigation of legal matters.
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Accident sequence precursor events with age-related contributors
Energy Technology Data Exchange (ETDEWEB)
Murphy, G.A.; Kohn, W.E.
1995-12-31
The Accident Sequence Precursor (ASP) Program at ORNL analyzed about 14.000 Licensee Event Reports (LERs) filed by US nuclear power plants 1987--1993. There were 193 events identified as precursors to potential severe core accident sequences. These are reported in G/CR-4674. Volumes 7 through 20. Under the NRC Nuclear Plant Aging Research program, the authors evaluated these events to determine the extent to which component aging played a role. Events were selected that involved age-related equipment degradation that initiated an event or contributed to an event sequence. For the 7-year period, ORNL identified 36 events that involved aging degradation as a contributor to an ASP event. Except for 1992, the percentage of age-related events within the total number of ASP events over the 7-year period ({approximately}19%) appears fairly consistent up to 1991. No correlation between plant ape and number of precursor events was found. A summary list of the age-related events is presented in the report.
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Van den Berg, B.A.; Reinders, M.J.T.; Hulsman, M.; Wu, L.; Pel, H.J.; Roubos, J.A.; De Ridder, D.
2012-01-01
Protein sequence features are explored in relation to the production of over-expressed extracellular proteins by fungi. Knowledge on features influencing protein production and secretion could be employed to improve enzyme production levels in industrial bioprocesses via protein engineering. A large
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Directory of Open Access Journals (Sweden)
Alexander M Sevy
2015-07-01
Full Text Available Computational protein design has found great success in engineering proteins for thermodynamic stability, binding specificity, or enzymatic activity in a 'single state' design (SSD paradigm. Multi-specificity design (MSD, on the other hand, involves considering the stability of multiple protein states simultaneously. We have developed a novel MSD algorithm, which we refer to as REstrained CONvergence in multi-specificity design (RECON. The algorithm allows each state to adopt its own sequence throughout the design process rather than enforcing a single sequence on all states. Convergence to a single sequence is encouraged through an incrementally increasing convergence restraint for corresponding positions. Compared to MSD algorithms that enforce (constrain an identical sequence on all states the energy landscape is simplified, which accelerates the search drastically. As a result, RECON can readily be used in simulations with a flexible protein backbone. We have benchmarked RECON on two design tasks. First, we designed antibodies derived from a common germline gene against their diverse targets to assess recovery of the germline, polyspecific sequence. Second, we design "promiscuous", polyspecific proteins against all binding partners and measure recovery of the native sequence. We show that RECON is able to efficiently recover native-like, biologically relevant sequences in this diverse set of protein complexes.
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Ma, Xin; Guo, Jing; Sun, Xiao
2016-01-01
DNA-binding proteins are fundamentally important in cellular processes. Several computational-based methods have been developed to improve the prediction of DNA-binding proteins in previous years. However, insufficient work has been done on the prediction of DNA-binding proteins from protein sequence information. In this paper, a novel predictor, DNABP (DNA-binding proteins), was designed to predict DNA-binding proteins using the random forest (RF) classifier with a hybrid feature. The hybrid feature contains two types of novel sequence features, which reflect information about the conservation of physicochemical properties of the amino acids, and the binding propensity of DNA-binding residues and non-binding propensities of non-binding residues. The comparisons with each feature demonstrated that these two novel features contributed most to the improvement in predictive ability. Furthermore, to improve the prediction performance of the DNABP model, feature selection using the minimum redundancy maximum relevance (mRMR) method combined with incremental feature selection (IFS) was carried out during the model construction. The results showed that the DNABP model could achieve 86.90% accuracy, 83.76% sensitivity, 90.03% specificity and a Matthews correlation coefficient of 0.727. High prediction accuracy and performance comparisons with previous research suggested that DNABP could be a useful approach to identify DNA-binding proteins from sequence information. The DNABP web server system is freely available at http://www.cbi.seu.edu.cn/DNABP/.
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Is the binding of visual features in working memory resource-demanding?
Allen, Richard J; Baddeley, Alan D; Hitch, Graham J
2006-05-01
The episodic buffer component of working memory is assumed to play a role in the binding of features into chunks. A series of experiments compared memory for arrays of colors or shapes with memory for bound combinations of these features. Demanding concurrent verbal tasks were used to investigate the role of general attentional processes, producing load effects that were no greater on memory for feature combinations than for the features themselves. However, the binding condition was significantly less accurate with sequential rather than simultaneous presentation, especially for items earlier in the sequence. The findings are interpreted as evidence of a relatively automatic but fragile visual feature binding mechanism in working memory. Implications for the concept of an episodic buffer are discussed. 2006 APA, all rights reserved
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Historical feature pattern extraction based network attack situation sensing algorithm.
Zeng, Yong; Liu, Dacheng; Lei, Zhou
2014-01-01
The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE). First, HFPE algorithm seeks similar indications from the history situation sequence recorded and weighs the link intensity between occurred indication and subsequent effect. Then it calculates the probability that a certain effect reappears according to the current indication and makes a prediction after weighting. Meanwhile, HFPE method gives an evolution algorithm to derive the prediction deviation from the views of pattern and accuracy. This algorithm can continuously promote the adaptability of HFPE through gradual fine-tuning. The method preserves the rules in sequence at its best, does not need data preprocessing, and can track and adapt to the variation of situation sequence continuously.
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Historical Feature Pattern Extraction Based Network Attack Situation Sensing Algorithm
Directory of Open Access Journals (Sweden)
Yong Zeng
2014-01-01
Full Text Available The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE. First, HFPE algorithm seeks similar indications from the history situation sequence recorded and weighs the link intensity between occurred indication and subsequent effect. Then it calculates the probability that a certain effect reappears according to the current indication and makes a prediction after weighting. Meanwhile, HFPE method gives an evolution algorithm to derive the prediction deviation from the views of pattern and accuracy. This algorithm can continuously promote the adaptability of HFPE through gradual fine-tuning. The method preserves the rules in sequence at its best, does not need data preprocessing, and can track and adapt to the variation of situation sequence continuously.
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The Sequence and Analysis of Duplication Rich Human Chromosome 16
Martin, Joel; Han, Cliff; Gordon, Laurie A.; Terry, Astrid; Prabhakar, Shyam; She, Xinwei; Xie, Gary; Hellsten, Uffe; Man Chan, Yee; Altherr, Michael; Couronne, Olivier; Aerts, Andrea; Bajorek, Eva; Black, Stacey; Blumer, Heather; Branscomb, Elbert; Brown, Nancy C.; Bruno, William J.; Buckingham, Judith M.; Callen, David F.; Campbell, Connie S.; Campbell, Mary L.; Campbell, Evelyn W.; Caoile, Chenier; Challacombe, Jean F.; Chasteen, Leslie A.; Chertkov, Olga; Chi, Han C.; Christensen, Mari; Clark, Lynn M.; Cohn, Judith D.; Denys, Mirian; Detter, John C.; Dickson, Mark; Dimitrijevic-Bussod, Mira; Escobar, Julio; Fawcett, Joseph J.; Flowers, Dave; Fotopulos, Dea; Glavina, Tijana; Gomez, Maria; Gonzales, Eidelyn; Goodstein, David; Goodwin, Lynne A.; Grady, Deborah L.; Grigoriev, Igor; Groza, Matthew; Hammon, Nancy; Hawkins, Trevor; Haydu, Lauren; Hildebrand, Carl E.; Huang, Wayne; Israni, Sanjay; Jett, Jamie; Jewett, Phillip E.; Kadner, Kristen; Kimball, Heather; Kobayashi, Arthur; Krawczyk, Marie-Claude; Leyba, Tina; Longmire, Jonathan L.; Lopez, Frederick; Lou, Yunian; Lowry, Steve; Ludeman, Thom; Mark, Graham A.; Mcmurray, Kimberly L.; Meincke, Linda J.; Morgan, Jenna; Moyzis, Robert K.; Mundt, Mark O.; Munk, A. Christine; Nandkeshwar, Richard D.; Pitluck, Sam; Pollard, Martin; Predki, Paul; Parson-Quintana, Beverly; Ramirez, Lucia; Rash, Sam; Retterer, James; Ricke, Darryl O.; Robinson, Donna L.; Rodriguez, Alex; Salamov, Asaf; Saunders, Elizabeth H.; Scott, Duncan; Shough, Timothy; Stallings, Raymond L.; Stalvey, Malinda; Sutherland, Robert D.; Tapia, Roxanne; Tesmer, Judith G.; Thayer, Nina; Thompson, Linda S.; Tice, Hope; Torney, David C.; Tran-Gyamfi, Mary; Tsai, Ming; Ulanovsky, Levy E.; Ustaszewska, Anna; Vo, Nu; White, P. Scott; Williams, Albert L.; Wills, Patricia L.; Wu, Jung-Rung; Wu, Kevin; Yang, Joan; DeJong, Pieter; Bruce, David; Doggett, Norman; Deaven, Larry; Schmutz, Jeremy; Grimwood, Jane; Richardson, Paul; et al.
2004-01-01
We report here the 78,884,754 base pairs of finished human chromosome 16 sequence, representing over 99.9 percent of its euchromatin. Manual annotation revealed 880 protein coding genes confirmed by 1,637 aligned transcripts, 19 tRNA genes, 341 pseudogenes and 3 RNA pseudogenes. These genes include metallothionein, cadherin and iroquois gene families, as well as the disease genes for polycystic kidney disease and acute myelomonocytic leukemia. Several large-scale structural polymorphisms spanning hundreds of kilobasepairs were identified and result in gene content differences across humans. One of the unique features of chromosome 16 is its high level of segmental duplication, ranked among the highest of the human autosomes. While the segmental duplications are enriched in the relatively gene poor pericentromere of the p-arm, some are involved in recent gene duplication and conversion events which are likely to have had an impact on the evolution of primates and human disease susceptibility.
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The sequence and analysis of duplication rich human chromosome 16
Energy Technology Data Exchange (ETDEWEB)
Martin, Joel; Han, Cliff; Gordon, Laurie A.; Terry, Astrid; Prabhakar, Shyam; She, Xinwei; Xie, Gary; Hellsten, Uffe; Man Chan, Yee; Altherr, Michael; Couronne, Olivier; Aerts, Andrea; Bajorek, Eva; Black, Stacey; Blumer, Heather; Branscomb, Elbert; Brown, Nancy C.; Bruno, William J.; Buckingham, Judith M.; Callen, David F.; Campbell, Connie S.; Campbell, Mary L.; Campbell, Evelyn W.; Caoile, Chenier; Challacombe, Jean F.; Chasteen, Leslie A.; Chertkov, Olga; Chi, Han C.; Christensen, Mari; Clark, Lynn M.; Cohn, Judith D.; Denys, Mirian; Detter, John C.; Dickson, Mark; Dimitrijevic-Bussod, Mira; Escobar, Julio; Fawcett, Joseph J.; Flowers, Dave; Fotopulos, Dea; Glavina, Tijana; Gomez, Maria; Gonzales, Eidelyn; Goodstein, David; Goodwin, Lynne A.; Grady, Deborah L.; Grigoriev, Igor; Groza, Matthew; Hammon, Nancy; Hawkins, Trevor; Haydu, Lauren; Hildebrand, Carl E.; Huang, Wayne; Israni, Sanjay; Jett, Jamie; Jewett, Phillip E.; Kadner, Kristen; Kimball, Heather; Kobayashi, Arthur; Krawczyk, Marie-Claude; Leyba, Tina; Longmire, Jonathan L.; Lopez, Frederick; Lou, Yunian; Lowry, Steve; Ludeman, Thom; Mark, Graham A.; Mcmurray, Kimberly L.; Meincke, Linda J.; Morgan, Jenna; Moyzis, Robert K.; Mundt, Mark O.; Munk, A. Christine; Nandkeshwar, Richard D.; Pitluck, Sam; Pollard, Martin; Predki, Paul; Parson-Quintana, Beverly; Ramirez, Lucia; Rash, Sam; Retterer, James; Ricke, Darryl O.; Robinson, Donna L.; Rodriguez, Alex; Salamov, Asaf; Saunders, Elizabeth H.; Scott, Duncan; Shough, Timothy; Stallings, Raymond L.; Stalvey, Malinda; Sutherland, Robert D.; Tapia, Roxanne; Tesmer, Judith G.; Thayer, Nina; Thompson, Linda S.; Tice, Hope; Torney, David C.; Tran-Gyamfi, Mary; Tsai, Ming; Ulanovsky, Levy E.; Ustaszewska, Anna; Vo, Nu; White, P. Scott; Williams, Albert L.; Wills, Patricia L.; Wu, Jung-Rung; Wu, Kevin; Yang, Joan; DeJong, Pieter; Bruce, David; Doggett, Norman; Deaven, Larry; Schmutz, Jeremy; Grimwood, Jane; Richardson, Paul; et al.
2004-08-01
We report here the 78,884,754 base pairs of finished human chromosome 16 sequence, representing over 99.9 percent of its euchromatin. Manual annotation revealed 880 protein coding genes confirmed by 1,637 aligned transcripts, 19 tRNA genes, 341 pseudogenes and 3 RNA pseudogenes. These genes include metallothionein, cadherin and iroquois gene families, as well as the disease genes for polycystic kidney disease and acute myelomonocytic leukemia. Several large-scale structural polymorphisms spanning hundreds of kilobasepairs were identified and result in gene content differences across humans. One of the unique features of chromosome 16 is its high level of segmental duplication, ranked among the highest of the human autosomes. While the segmental duplications are enriched in the relatively gene poor pericentromere of the p-arm, some are involved in recent gene duplication and conversion events which are likely to have had an impact on the evolution of primates and human disease susceptibility.
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Biometric feature extraction using local fractal auto-correlation
International Nuclear Information System (INIS)
Chen Xi; Zhang Jia-Shu
2014-01-01
Image texture feature extraction is a classical means for biometric recognition. To extract effective texture feature for matching, we utilize local fractal auto-correlation to construct an effective image texture descriptor. Three main steps are involved in the proposed scheme: (i) using two-dimensional Gabor filter to extract the texture features of biometric images; (ii) calculating the local fractal dimension of Gabor feature under different orientations and scales using fractal auto-correlation algorithm; and (iii) linking the local fractal dimension of Gabor feature under different orientations and scales into a big vector for matching. Experiments and analyses show our proposed scheme is an efficient biometric feature extraction approach. (condensed matter: structural, mechanical, and thermal properties)
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Modeling crash injury severity by road feature to improve safety.
Penmetsa, Praveena; Pulugurtha, Srinivas S
2018-01-02
The objective of this research is 2-fold: to (a) model and identify critical road features (or locations) based on crash injury severity and compare it with crash frequency and (b) model and identify drivers who are more likely to contribute to crashes by road feature. Crash data from 2011 to 2013 were obtained from the Highway Safety Information System (HSIS) for the state of North Carolina. Twenty-three different road features were considered, analyzed, and compared with each other as well as no road feature. A multinomial logit (MNL) model was developed and odds ratios were estimated to investigate the effect of road features on crash injury severity. Among the many road features, underpass, end or beginning of a divided highway, and on-ramp terminal on crossroad are the top 3 critical road features. Intersection crashes are frequent but are not highly likely to result in severe injuries compared to critical road features. Roundabouts are least likely to result in both severe and moderate injuries. Female drivers are more likely to be involved in crashes at intersections (4-way and T) compared to male drivers. Adult drivers are more likely to be involved in crashes at underpasses. Older drivers are 1.6 times more likely to be involved in a crash at the end or beginning of a divided highway. The findings from this research help to identify critical road features that need to be given priority. As an example, additional advanced warning signs and providing enlarged or highly retroreflective signs that grab the attention of older drivers may help in making locations such as end or beginning of a divided highway much safer. Educating drivers about the necessary skill sets required at critical road features in addition to engineering solutions may further help them adopt safe driving behaviors on the road.
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The Complete Sequence of a Human Parainfluenzavirus 4 Genome
Yea, Carmen; Cheung, Rose; Collins, Carol; Adachi, Dena; Nishikawa, John; Tellier, Raymond
2009-01-01
Although the human parainfluenza virus 4 (HPIV4) has been known for a long time, its genome, alone among the human paramyxoviruses, has not been completely sequenced to date. In this study we obtained the first complete genomic sequence of HPIV4 from a clinical isolate named SKPIV4 obtained at the Hospital for Sick Children in Toronto (Ontario, Canada). The coding regions for the N, P/V, M, F and HN proteins show very high identities (95% to 97%) with previously available partial sequences for HPIV4B. The sequence for the L protein and the non-coding regions represent new information. A surprising feature of the genome is its length, more than 17 kb, making it the longest genome within the genus Rubulavirus, although the length is well within the known range of 15 kb to 19 kb for the subfamily Paramyxovirinae. The availability of a complete genomic sequence will facilitate investigations on a respiratory virus that is still not completely characterized. PMID:21994536
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The Complete Sequence of a Human Parainfluenzavirus 4 Genome
Directory of Open Access Journals (Sweden)
Carmen Yea
2009-06-01
Full Text Available Although the human parainfluenza virus 4 (HPIV4 has been known for a long time, its genome, alone among the human paramyxoviruses, has not been completely sequenced to date. In this study we obtained the first complete genomic sequence of HPIV4 from a clinical isolate named SKPIV4 obtained at the Hospital for Sick Children in Toronto (Ontario, Canada. The coding regions for the N, P/V, M, F and HN proteins show very high identities (95% to 97% with previously available partial sequences for HPIV4B. The sequence for the L protein and the non-coding regions represent new information. A surprising feature of the genome is its length, more than 17 kb, making it the longest genome within the genus Rubulavirus, although the length is well within the known range of 15 kb to 19 kb for the subfamily Paramyxovirinae. The availability of a complete genomic sequence will facilitate investigations on a respiratory virus that is still not completely characterized.
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Durack, Juliana; Lynch, Susan V; Nariya, Snehal; Bhakta, Nirav R; Beigelman, Avraham; Castro, Mario; Dyer, Anne-Marie; Israel, Elliot; Kraft, Monica; Martin, Richard J; Mauger, David T; Rosenberg, Sharon R; Sharp-King, Tonya; White, Steven R; Woodruff, Prescott G; Avila, Pedro C; Denlinger, Loren C; Holguin, Fernando; Lazarus, Stephen C; Lugogo, Njira; Moore, Wendy C; Peters, Stephen P; Que, Loretta; Smith, Lewis J; Sorkness, Christine A; Wechsler, Michael E; Wenzel, Sally E; Boushey, Homer A; Huang, Yvonne J
2017-07-01
Compositional differences in the bronchial bacterial microbiota have been associated with asthma, but it remains unclear whether the findings are attributable to asthma, to aeroallergen sensitization, or to inhaled corticosteroid treatment. We sought to compare the bronchial bacterial microbiota in adults with steroid-naive atopic asthma, subjects with atopy but no asthma, and nonatopic healthy control subjects and to determine relationships of the bronchial microbiota to phenotypic features of asthma. Bacterial communities in protected bronchial brushings from 42 atopic asthmatic subjects, 21 subjects with atopy but no asthma, and 21 healthy control subjects were profiled by using 16S rRNA gene sequencing. Bacterial composition and community-level functions inferred from sequence profiles were analyzed for between-group differences. Associations with clinical and inflammatory variables were examined, including markers of type 2-related inflammation and change in airway hyperresponsiveness after 6 weeks of fluticasone treatment. The bronchial microbiome differed significantly among the 3 groups. Asthmatic subjects were uniquely enriched in members of the Haemophilus, Neisseria, Fusobacterium, and Porphyromonas species and the Sphingomonodaceae family and depleted in members of the Mogibacteriaceae family and Lactobacillales order. Asthma-associated differences in predicted bacterial functions included involvement of amino acid and short-chain fatty acid metabolism pathways. Subjects with type 2-high asthma harbored significantly lower bronchial bacterial burden. Distinct changes in specific microbiota members were seen after fluticasone treatment. Steroid responsiveness was linked to differences in baseline compositional and functional features of the bacterial microbiome. Even in subjects with mild steroid-naive asthma, differences in the bronchial microbiome are associated with immunologic and clinical features of the disease. The specific differences identified
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Directory of Open Access Journals (Sweden)
Sara Imari Walker
Full Text Available Many models for the origin of life have focused on understanding how evolution can drive the refinement of a preexisting enzyme, such as the evolution of efficient replicase activity. Here we present a model for what was, arguably, an even earlier stage of chemical evolution, when polymer sequence diversity was generated and sustained before, and during, the onset of functional selection. The model includes regular environmental cycles (e.g. hydration-dehydration cycles that drive polymers between times of replication and functional activity, which coincide with times of different monomer and polymer diffusivity. Template-directed replication of informational polymers, which takes place during the dehydration stage of each cycle, is considered to be sequence-independent. New sequences are generated by spontaneous polymer formation, and all sequences compete for a finite monomer resource that is recycled via reversible polymerization. Kinetic Monte Carlo simulations demonstrate that this proposed prebiotic scenario provides a robust mechanism for the exploration of sequence space. Introduction of a polymer sequence with monomer synthetase activity illustrates that functional sequences can become established in a preexisting pool of otherwise non-functional sequences. Functional selection does not dominate system dynamics and sequence diversity remains high, permitting the emergence and spread of more than one functional sequence. It is also observed that polymers spontaneously form clusters in simulations where polymers diffuse more slowly than monomers, a feature that is reminiscent of a previous proposal that the earliest stages of life could have been defined by the collective evolution of a system-wide cooperation of polymer aggregates. Overall, the results presented demonstrate the merits of considering plausible prebiotic polymer chemistries and environments that would have allowed for the rapid turnover of monomer resources and for
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Adaptive compressive learning for prediction of protein-protein interactions from primary sequence.
Zhang, Ya-Nan; Pan, Xiao-Yong; Huang, Yan; Shen, Hong-Bin
2011-08-21
Protein-protein interactions (PPIs) play an important role in biological processes. Although much effort has been devoted to the identification of novel PPIs by integrating experimental biological knowledge, there are still many difficulties because of lacking enough protein structural and functional information. It is highly desired to develop methods based only on amino acid sequences for predicting PPIs. However, sequence-based predictors are often struggling with the high-dimensionality causing over-fitting and high computational complexity problems, as well as the redundancy of sequential feature vectors. In this paper, a novel computational approach based on compressed sensing theory is proposed to predict yeast Saccharomyces cerevisiae PPIs from primary sequence and has achieved promising results. The key advantage of the proposed compressed sensing algorithm is that it can compress the original high-dimensional protein sequential feature vector into a much lower but more condensed space taking the sparsity property of the original signal into account. What makes compressed sensing much more attractive in protein sequence analysis is its compressed signal can be reconstructed from far fewer measurements than what is usually considered necessary in traditional Nyquist sampling theory. Experimental results demonstrate that proposed compressed sensing method is powerful for analyzing noisy biological data and reducing redundancy in feature vectors. The proposed method represents a new strategy of dealing with high-dimensional protein discrete model and has great potentiality to be extended to deal with many other complicated biological systems. Copyright © 2011 Elsevier Ltd. All rights reserved.
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Energy Technology Data Exchange (ETDEWEB)
White, Richard A.; Panyala, Ajay R.; Glass, Kevin A.; Colby, Sean M.; Glaesemann, Kurt R.; Jansson, Georg C.; Jansson, Janet K.
2017-02-21
MerCat is a parallel, highly scalable and modular property software package for robust analysis of features in next-generation sequencing data. MerCat inputs include assembled contigs and raw sequence reads from any platform resulting in feature abundance counts tables. MerCat allows for direct analysis of data properties without reference sequence database dependency commonly used by search tools such as BLAST and/or DIAMOND for compositional analysis of whole community shotgun sequencing (e.g. metagenomes and metatranscriptomes).
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GIF Video Sentiment Detection Using Semantic Sequence
Directory of Open Access Journals (Sweden)
Dazhen Lin
2017-01-01
Full Text Available With the development of social media, an increasing number of people use short videos in social media applications to express their opinions and sentiments. However, sentiment detection of short videos is a very challenging task because of the semantic gap problem and sequence based sentiment understanding problem. In this context, we propose a SentiPair Sequence based GIF video sentiment detection approach with two contributions. First, we propose a Synset Forest method to extract sentiment related semantic concepts from WordNet to build a robust SentiPair label set. This approach considers the semantic gap between label words and selects a robust label subset which is related to sentiment. Secondly, we propose a SentiPair Sequence based GIF video sentiment detection approach that learns the semantic sequence to understand the sentiment from GIF videos. Our experiment results on GSO-2016 (GIF Sentiment Ontology data show that our approach not only outperforms four state-of-the-art classification methods but also shows better performance than the state-of-the-art middle level sentiment ontology features, Adjective Noun Pairs (ANPs.
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Sequence alignment visualization in HTML5 without Java.
Gille, Christoph; Birgit, Weyand; Gille, Andreas
2014-01-01
Java has been extensively used for the visualization of biological data in the web. However, the Java runtime environment is an additional layer of software with an own set of technical problems and security risks. HTML in its new version 5 provides features that for some tasks may render Java unnecessary. Alignment-To-HTML is the first HTML-based interactive visualization for annotated multiple sequence alignments. The server side script interpreter can perform all tasks like (i) sequence retrieval, (ii) alignment computation, (iii) rendering, (iv) identification of a homologous structural models and (v) communication with BioDAS-servers. The rendered alignment can be included in web pages and is displayed in all browsers on all platforms including touch screen tablets. The functionality of the user interface is similar to legacy Java applets and includes color schemes, highlighting of conserved and variable alignment positions, row reordering by drag and drop, interlinked 3D visualization and sequence groups. Novel features are (i) support for multiple overlapping residue annotations, such as chemical modifications, single nucleotide polymorphisms and mutations, (ii) mechanisms to quickly hide residue annotations, (iii) export to MS-Word and (iv) sequence icons. Alignment-To-HTML, the first interactive alignment visualization that runs in web browsers without additional software, confirms that to some extend HTML5 is already sufficient to display complex biological data. The low speed at which programs are executed in browsers is still the main obstacle. Nevertheless, we envision an increased use of HTML and JavaScript for interactive biological software. Under GPL at: http://www.bioinformatics.org/strap/toHTML/.
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Bakhtiarizadeh, Mohammad Reza; Moradi-Shahrbabak, Mohammad; Ebrahimi, Mansour; Ebrahimie, Esmaeil
2014-09-07
Due to the central roles of lipid binding proteins (LBPs) in many biological processes, sequence based identification of LBPs is of great interest. The major challenge is that LBPs are diverse in sequence, structure, and function which results in low accuracy of sequence homology based methods. Therefore, there is a need for developing alternative functional prediction methods irrespective of sequence similarity. To identify LBPs from non-LBPs, the performances of support vector machine (SVM) and neural network were compared in this study. Comprehensive protein features and various techniques were employed to create datasets. Five-fold cross-validation (CV) and independent evaluation (IE) tests were used to assess the validity of the two methods. The results indicated that SVM outperforms neural network. SVM achieved 89.28% (CV) and 89.55% (IE) overall accuracy in identification of LBPs from non-LBPs and 92.06% (CV) and 92.90% (IE) (in average) for classification of different LBPs classes. Increasing the number and the range of extracted protein features as well as optimization of the SVM parameters significantly increased the efficiency of LBPs class prediction in comparison to the only previous report in this field. Altogether, the results showed that the SVM algorithm can be run on broad, computationally calculated protein features and offers a promising tool in detection of LBPs classes. The proposed approach has the potential to integrate and improve the common sequence alignment based methods. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Discrete Feature Model (DFM) User Documentation
Energy Technology Data Exchange (ETDEWEB)
Geier, Joel (Clearwater Hardrock Consulting, Corvallis, OR (United States))
2008-06-15
software, the geometry of discrete features and their hydrologic properties are defined as a mesh composed of triangular, finite elements. Hydrologic boundary conditions arc prescribed as a simulation sequence, which permits specification of conditions ranging from simple, steady-state flow to complex situations where both the magnitude and type of boundary conditions may vary over time
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Discrete Feature Model (DFM) User Documentation
International Nuclear Information System (INIS)
Geier, Joel
2008-06-01
geometry of discrete features and their hydrologic properties are defined as a mesh composed of triangular, finite elements. Hydrologic boundary conditions arc prescribed as a simulation sequence, which permits specification of conditions ranging from simple, steady-state flow to complex situations where both the magnitude and type of boundary conditions may vary over time
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Wang, Yongkang; Song, Xiaodan; Li, Xiaorong; Yang, Sang-tian; Zou, Xiang
2017-01-04
To explore the genome sequence of Aureobasidium pullulans CCTCC M2012223, analyze the key genes related to the biosynthesis of important metabolites, and provide genetic background for metabolic engineering. Complete genome of A. pullulans CCTCC M2012223 was sequenced by Illumina HiSeq high throughput sequencing platform. Then, fragment assembly, gene prediction, functional annotation, and GO/COG cluster were analyzed in comparison with those of other five A. pullulans varieties. The complete genome sequence of A. pullulans CCTCC M2012223 was 30756831 bp with an average GC content of 47.49%, and 9452 genes were successfully predicted. Genome-wide analysis showed that A. pullulans CCTCC M2012223 had the biggest genome assembly size. Protein sequences involved in the pullulan and polymalic acid pathway were highly conservative in all of six A. pullulans varieties. Although both A. pullulans CCTCC M2012223 and A. pullulans var. melanogenum have a close affinity, some point mutation and inserts were occurred in protein sequences involved in melanin biosynthesis. Genome information of A. pullulans CCTCC M2012223 was annotated and genes involved in melanin, pullulan and polymalic acid pathway were compared, which would provide a theoretical basis for genetic modification of metabolic pathway in A. pullulans.
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DEEPre: sequence-based enzyme EC number prediction by deep learning
Li, Yu
2017-10-20
Annotation of enzyme function has a broad range of applications, such as metagenomics, industrial biotechnology, and diagnosis of enzyme deficiency-caused diseases. However, the time and resource required make it prohibitively expensive to experimentally determine the function of every enzyme. Therefore, computational enzyme function prediction has become increasingly important. In this paper, we develop such an approach, determining the enzyme function by predicting the Enzyme Commission number.We propose an end-to-end feature selection and classification model training approach, as well as an automatic and robust feature dimensionality uniformization method, DEEPre, in the field of enzyme function prediction. Instead of extracting manuallycrafted features from enzyme sequences, our model takes the raw sequence encoding as inputs, extracting convolutional and sequential features from the raw encoding based on the classification result to directly improve the prediction performance. The thorough cross-fold validation experiments conducted on two large-scale datasets show that DEEPre improves the prediction performance over the previous state-of-the-art methods. In addition, our server outperforms five other servers in determining the main class of enzymes on a separate low-homology dataset. Two case studies demonstrate DEEPre\\'s ability to capture the functional difference of enzyme isoforms.The server could be accessed freely at http://www.cbrc.kaust.edu.sa/DEEPre.
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DEEPre: sequence-based enzyme EC number prediction by deep learning
Li, Yu; Wang, Sheng; Umarov, Ramzan; Xie, Bingqing; Fan, Ming; Li, Lihua; Gao, Xin
2017-01-01
Annotation of enzyme function has a broad range of applications, such as metagenomics, industrial biotechnology, and diagnosis of enzyme deficiency-caused diseases. However, the time and resource required make it prohibitively expensive to experimentally determine the function of every enzyme. Therefore, computational enzyme function prediction has become increasingly important. In this paper, we develop such an approach, determining the enzyme function by predicting the Enzyme Commission number.We propose an end-to-end feature selection and classification model training approach, as well as an automatic and robust feature dimensionality uniformization method, DEEPre, in the field of enzyme function prediction. Instead of extracting manuallycrafted features from enzyme sequences, our model takes the raw sequence encoding as inputs, extracting convolutional and sequential features from the raw encoding based on the classification result to directly improve the prediction performance. The thorough cross-fold validation experiments conducted on two large-scale datasets show that DEEPre improves the prediction performance over the previous state-of-the-art methods. In addition, our server outperforms five other servers in determining the main class of enzymes on a separate low-homology dataset. Two case studies demonstrate DEEPre's ability to capture the functional difference of enzyme isoforms.The server could be accessed freely at http://www.cbrc.kaust.edu.sa/DEEPre.
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MRI features of epidural extramedullary hematopoiesis
Energy Technology Data Exchange (ETDEWEB)
Alorainy, Ibrahim A. E-mail: alorainy@ksu.edu.sa; Al-Asmi, Abdullah R.; Carpio, Raquel del
2000-07-01
A case of {beta}-thalassemia intermedia with spinal cord compression due to extramedullary hematopoiesis, which was successfully treated by blood transfusion, is presented. Emphasis was made on the MRI appearance of extramedullary hematopoiesis on different pulse sequences. The theories that aimed to explain the involvement of the epidural space by extramedullary hematopoiesis are discussed.
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MRI features of epidural extramedullary hematopoiesis
International Nuclear Information System (INIS)
Alorainy, Ibrahim A.; Al-Asmi, Abdullah R.; Carpio, Raquel del
2000-01-01
A case of β-thalassemia intermedia with spinal cord compression due to extramedullary hematopoiesis, which was successfully treated by blood transfusion, is presented. Emphasis was made on the MRI appearance of extramedullary hematopoiesis on different pulse sequences. The theories that aimed to explain the involvement of the epidural space by extramedullary hematopoiesis are discussed
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Effects of Normal Aging on Memory for Multiple Contextual Features
Gagnon, Sylvain; Soulard, Kathleen; Brasgold, Melissa; Kreller, Joshua
2007-01-01
Twenty-four younger (18-35 years) and 24 older adult participants (65 or older) were exposed to three experimental conditions involving the memorization words and their associated contextual features, with contextual feature complexity increasing from Conditions 1 to 3. In Condition 1, words presented varied only on one binary feature (color,…
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Directory of Open Access Journals (Sweden)
Dikshit Rajesh
2008-09-01
Full Text Available Abstract The distinction between metastasis from a colorectal adenocarcinoma into the ovary and an ovarian adenocarcinoma is vital, but challenging at times, due to overlapping morphological features. Similarly, a distinction between an ovarian metastasis into the colorectum and a colorectal adenocarcinoma, although rare; is important and can be daunting. We report an analysis of 20 cases of ovarian involvement by metastatic colorectal adenocarcinomas and colorectal involvement by metastatic ovarian adenocarcinomas, including the value of differential expression of cytokeratins 7 & 20 by immunohistochemistry (IHC, in these cases. Nine cases (45% were identified as colorectal adenocarcinomas metastatic to the ovary. On biopsy, all these cases showed a 'garland-like' tumor necrosis, with desmoplasia and predominantly exhibited a tubuloalveolar pattern (67% cases. On IHC, all 8 of 9 such cases, where staining for cytokeratin 20 was performed, displayed strong positivity and 7 cases, where staining for carcinoembryogenic antigen (CEA was performed, revealed positivity for this marker (100%. Other 11 cases (55% were ovarian adenocarcinomas, metastatic to the colorectum. These showed metachronous presentations, with the ovarian tumor preceding the colorectal tumor deposits. Morphologically, psammomatous calcification was noted in 73% of these cases, whereas 'garland-like' necrosis was absent in all. The chief morphological subtype was serous papillary cystadenocarcinoma (55% cases. On IHC, CK7 and CA 125 were positive in all 6 of 11 such cases, whereas CK 20 was negative in all these cases. In cases of complex presentations like an ovarian involvement by a metastatic colorectal adenocarcinoma and vice-versa, certain clinicopathological features are useful. Differential expression of CK 7 and CK20 is vital in resolving these dilemmas. CK20 positivity and CK7 negativity is associated with a colorectal adenocarcinoma. Markers like CEA and CA-125 have an
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Automatic processing of unattended object features by functional connectivity
Directory of Open Access Journals (Sweden)
Katja Martina Mayer
2013-05-01
Full Text Available Observers can selectively attend to object features that are relevant for a task. However, unattended task-irrelevant features may still be processed and possibly integrated with the attended features. This study investigated the neural mechanisms for processing both task-relevant (attended and task-irrelevant (unattended object features. The Garner paradigm was adapted for functional magnetic resonance imaging (fMRI to test whether specific brain areas process the conjunction of features or whether multiple interacting areas are involved in this form of feature integration. Observers attended to shape, colour, or non-rigid motion of novel objects while unattended features changed from trial to trial (change blocks or remained constant (no-change blocks during a given block. This block manipulation allowed us to measure the extent to which unattended features affected neural responses which would reflect the extent to which multiple object features are automatically processed. We did not find Garner interference at the behavioural level. However, we designed the experiment to equate performance across block types so that any fMRI results could not be due solely to differences in task difficulty between change and no-change blocks. Attention to specific features localised several areas known to be involved in object processing. No area showed larger responses on change blocks compared to no-change blocks. However, psychophysiological interaction analyses revealed that several functionally-localised areas showed significant positive interactions with areas in occipito-temporal and frontal areas that depended on block type. Overall, these findings suggest that both regional responses and functional connectivity are crucial for processing multi-featured objects.
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Uncommon nucleotide excision repair phenotypes revealed by targeted high-throughput sequencing.
Calmels, Nadège; Greff, Géraldine; Obringer, Cathy; Kempf, Nadine; Gasnier, Claire; Tarabeux, Julien; Miguet, Marguerite; Baujat, Geneviève; Bessis, Didier; Bretones, Patricia; Cavau, Anne; Digeon, Béatrice; Doco-Fenzy, Martine; Doray, Bérénice; Feillet, François; Gardeazabal, Jesus; Gener, Blanca; Julia, Sophie; Llano-Rivas, Isabel; Mazur, Artur; Michot, Caroline; Renaldo-Robin, Florence; Rossi, Massimiliano; Sabouraud, Pascal; Keren, Boris; Depienne, Christel; Muller, Jean; Mandel, Jean-Louis; Laugel, Vincent
2016-03-22
Deficient nucleotide excision repair (NER) activity causes a variety of autosomal recessive diseases including xeroderma pigmentosum (XP) a disorder which pre-disposes to skin cancer, and the severe multisystem condition known as Cockayne syndrome (CS). In view of the clinical overlap between NER-related disorders, as well as the existence of multiple phenotypes and the numerous genes involved, we developed a new diagnostic approach based on the enrichment of 16 NER-related genes by multiplex amplification coupled with next-generation sequencing (NGS). Our test cohort consisted of 11 DNA samples, all with known mutations and/or non pathogenic SNPs in two of the tested genes. We then used the same technique to analyse samples from a prospective cohort of 40 patients. Multiplex amplification and sequencing were performed using AmpliSeq protocol on the Ion Torrent PGM (Life Technologies). We identified causative mutations in 17 out of the 40 patients (43%). Four patients showed biallelic mutations in the ERCC6(CSB) gene, five in the ERCC8(CSA) gene: most of them had classical CS features but some had very mild and incomplete phenotypes. A small cohort of 4 unrelated classic XP patients from the Basque country (Northern Spain) revealed a common splicing mutation in POLH (XP-variant), demonstrating a new founder effect in this population. Interestingly, our results also found ERCC2(XPD), ERCC3(XPB) or ERCC5(XPG) mutations in two cases of UV-sensitive syndrome and in two cases with mixed XP/CS phenotypes. Our study confirms that NGS is an efficient technique for the analysis of NER-related disorders on a molecular level. It is particularly useful for phenotypes with combined features or unusually mild symptoms. Targeted NGS used in conjunction with DNA repair functional tests and precise clinical evaluation permits rapid and cost-effective diagnosis in patients with NER-defects.
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The First Symbiont-Free Genome Sequence of Marine Red Alga, Susabi-nori (Pyropia yezoensis)
Nakamura, Yoji; Sasaki, Naobumi; Kobayashi, Masahiro; Ojima, Nobuhiko; Yasuike, Motoshige; Shigenobu, Yuya; Satomi, Masataka; Fukuma, Yoshiya; Shiwaku, Koji; Tsujimoto, Atsumi; Kobayashi, Takanori; Nakayama, Ichiro; Ito, Fuminari; Nakajima, Kazuhiro; Sano, Motohiko; Wada, Tokio; Kuhara, Satoru; Inouye, Kiyoshi; Gojobori, Takashi; Ikeo, Kazuho
2013-01-01
Nori, a marine red alga, is one of the most profitable mariculture crops in the world. However, the biological properties of this macroalga are poorly understood at the molecular level. In this study, we determined the draft genome sequence of susabi-nori (Pyropia yezoensis) using next-generation sequencing platforms. For sequencing, thalli of P. yezoensis were washed to remove bacteria attached on the cell surface and enzymatically prepared as purified protoplasts. The assembled contig size of the P. yezoensis nuclear genome was approximately 43 megabases (Mb), which is an order of magnitude smaller than the previously estimated genome size. A total of 10,327 gene models were predicted and about 60% of the genes validated lack introns and the other genes have shorter introns compared to large-genome algae, which is consistent with the compact size of the P. yezoensis genome. A sequence homology search showed that 3,611 genes (35%) are functionally unknown and only 2,069 gene groups are in common with those of the unicellular red alga, Cyanidioschyzon merolae. As color trait determinants of red algae, light-harvesting genes involved in the phycobilisome were predicted from the P. yezoensis nuclear genome. In particular, we found a second homolog of phycobilisome-degradation gene, which is usually chloroplast-encoded, possibly providing a novel target for color fading of susabi-nori in aquaculture. These findings shed light on unexplained features of macroalgal genes and genomes, and suggest that the genome of P. yezoensis is a promising model genome of marine red algae. PMID:23536760
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The first symbiont-free genome sequence of marine red alga, Susabi-nori (Pyropia yezoensis.
Directory of Open Access Journals (Sweden)
Yoji Nakamura
Full Text Available Nori, a marine red alga, is one of the most profitable mariculture crops in the world. However, the biological properties of this macroalga are poorly understood at the molecular level. In this study, we determined the draft genome sequence of susabi-nori (Pyropia yezoensis using next-generation sequencing platforms. For sequencing, thalli of P. yezoensis were washed to remove bacteria attached on the cell surface and enzymatically prepared as purified protoplasts. The assembled contig size of the P. yezoensis nuclear genome was approximately 43 megabases (Mb, which is an order of magnitude smaller than the previously estimated genome size. A total of 10,327 gene models were predicted and about 60% of the genes validated lack introns and the other genes have shorter introns compared to large-genome algae, which is consistent with the compact size of the P. yezoensis genome. A sequence homology search showed that 3,611 genes (35% are functionally unknown and only 2,069 gene groups are in common with those of the unicellular red alga, Cyanidioschyzon merolae. As color trait determinants of red algae, light-harvesting genes involved in the phycobilisome were predicted from the P. yezoensis nuclear genome. In particular, we found a second homolog of phycobilisome-degradation gene, which is usually chloroplast-encoded, possibly providing a novel target for color fading of susabi-nori in aquaculture. These findings shed light on unexplained features of macroalgal genes and genomes, and suggest that the genome of P. yezoensis is a promising model genome of marine red algae.
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Vakili Azghandi, Masoume; Nasiri, Mohammadreza; Shamsa, Ali; Jalali, Mohsen; Shariati, Mohammad Mahdi
2016-04-01
The SRY gene (SRY) provides instructions for making a transcription factor called the sex-determining region Y protein. The sex-determining region Y protein causes a fetus to develop as a male. In this study, SRY of 15 spices included of human, chimpanzee, dog, pig, rat, cattle, buffalo, goat, sheep, horse, zebra, frog, urial, dolphin and killer whale were used for determine of bioinformatic differences. Nucleotide sequences of SRY were retrieved from the NCBI databank. Bioinformatic analysis of SRY is done by CLC Main Workbench version 5.5 and ClustalW (http:/www.ebi.ac.uk/clustalw/) and MEGA6 softwares. The multiple sequence alignment results indicated that SRY protein sequences from Orcinus orca (killer whale) and Tursiopsaduncus (dolphin) have least genetic distance of 0.33 in these 15 species and are 99.67% identical at the amino acid level. Homosapiens and Pantroglodytes (chimpanzee) have the next lowest genetic distance of 1.35 and are 98.65% identical at the amino acid level. These findings indicate that the SRY proteins are conserved in the 15 species, and their evolutionary relationships are similar.
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Directory of Open Access Journals (Sweden)
Linchuan Fang
Full Text Available Rhododendron spp. is an important ornamental species that is widely cultivated for landscape worldwide. Heat stress is a major obstacle for its cultivation in south China. Previous studies on rhododendron principally focused on its physiological and biochemical processes, which are involved in a series of stress tolerance. However, molecular or genetic properties of rhododendron's response to heat stress are still poorly understood. The phenotype and chlorophyll fluorescence kinetics parameters of four rhododendron cultivars were compared under normal or heat stress conditions, and a cultivar with highest heat tolerance, "Yanzhimi" (R. obtusum was selected for transcriptome sequencing. A total of 325,429,240 high quality reads were obtained and assembled into 395,561 transcripts and 92,463 unigenes. Functional annotation showed that 38,724 unigenes had sequence similarity to known genes in at least one of the proteins or nucleotide databases used in this study. These 38,724 unigenes were categorized into 51 functional groups based on Gene Ontology classification and were blasted to 24 known cluster of orthologous groups. A total of 973 identified unigenes belonged to 57 transcription factor families, including the stress-related HSF, DREB, ZNF, and NAC genes. Photosynthesis was significantly enriched in the Kyoto Encyclopedia of Genes and Genomes pathway, and the changed expression pattern was illustrated. The key pathways and signaling components that contribute to heat tolerance in rhododendron were revealed. These results provide a potentially valuable resource that can be used for heat-tolerance breeding.
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Tong, Jun; Dong, Yanfang; Xu, Dongyun; Mao, Jing; Zhou, Yuan
2017-01-01
Rhododendron spp. is an important ornamental species that is widely cultivated for landscape worldwide. Heat stress is a major obstacle for its cultivation in south China. Previous studies on rhododendron principally focused on its physiological and biochemical processes, which are involved in a series of stress tolerance. However, molecular or genetic properties of rhododendron’s response to heat stress are still poorly understood. The phenotype and chlorophyll fluorescence kinetics parameters of four rhododendron cultivars were compared under normal or heat stress conditions, and a cultivar with highest heat tolerance, “Yanzhimi” (R. obtusum) was selected for transcriptome sequencing. A total of 325,429,240 high quality reads were obtained and assembled into 395,561 transcripts and 92,463 unigenes. Functional annotation showed that 38,724 unigenes had sequence similarity to known genes in at least one of the proteins or nucleotide databases used in this study. These 38,724 unigenes were categorized into 51 functional groups based on Gene Ontology classification and were blasted to 24 known cluster of orthologous groups. A total of 973 identified unigenes belonged to 57 transcription factor families, including the stress-related HSF, DREB, ZNF, and NAC genes. Photosynthesis was significantly enriched in the Kyoto Encyclopedia of Genes and Genomes pathway, and the changed expression pattern was illustrated. The key pathways and signaling components that contribute to heat tolerance in rhododendron were revealed. These results provide a potentially valuable resource that can be used for heat-tolerance breeding. PMID:29059200
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Hammond, R W
2003-06-01
Isolates of Prunus necrotic ringspot virus (PNRSV) were examined to establish the level of naturally occurring sequence variation in the coat protein (CP) gene and to identify group-specific genome features that may prove valuable for the generation of diagnostic reagents. Phylogenetic analysis of a 452 bp sequence of 68 virus isolates, 20 obtained from the European Union Ilarvirus Ringtest held in October 1998, confirmed the clustering of the isolates into three distinct groups. Although no correlation was found between the sequence and host or geographic origin, there was a general trend for severe isolates to cluster into one group. Group-specific features have been identified for discrimination between virus strains.
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Assessment of severe accident prevention and mitigation features: PWR, large dry containment design
International Nuclear Information System (INIS)
Perkins, K.R.; Hsu, C.J.; Lehner, J.R.; Luckas, W.J.; Cho, N.; Fitzpatrick, R.G.; Pratt, W.T.; Eltawila, F.; Maly, J.A.
1988-07-01
Plant features and operator actions which have been found to be important in either preventing or mitigating severe accidents in PWRs with large dry containments have been identified. These features and actions were developed from insights derived from reviews of risk assessments performed specifically for the Zion plant and from assessments of other relevant studies. Accident sequences that dominate the core-damage frequency and those accident sequences that are of potentially high consequence were identified. Vulnerabilities of the large dry containment to severe accident containment loads were also identified. In addition, those features of a PWR with a large dry containment, which are important for preventing core damage and are available for mitigating fission-product release to the environment were identified. The report is issued to provide focus to the analyst examining an individual plant. The report calls attention to plant features and operator actions and provides a list of deterministic tributes for assessing those features and actions found to be helpful in reducing the overall risk for Zion and other PWRs with large dry containments. Thus, the guidance is offered as a resource in examining the subject plant to determine if the same, or similar, plant features and operator actions will be of value in reducing overall plant risk. This report is intended to serve solely as guidance
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International Nuclear Information System (INIS)
Hsu, C.J.; Perkins, K.R.; Luckas, W.J.; Fitzpatrick, R.G.; Cho, N.; Lehner, J.R.; Pratt, W.T.; Eltawila, F.; Maly, J.A.
1988-07-01
Plant features and operator actions which have been found to be important in either preventing and mitigating severe accidents in PWRs with ice-condenser containments have been identified. Thus features and actions were developed from insights derived from reviews of risk assessments performed specifically for the Sequoyah plant and from assessments of other relevant studies. Accident sequences that dominate the core-damage frequency and those accident sequences that are of potentially high consequence were identified. Vulnerabilities of the ice-condenser containment to sever accident containment loads were also identified. In addition, those features of a PWR with an ice-condenser containment, which are important for preventing core damage and are available for mitigating fission-product release to the environment were identified. This report is issued to provide focus to an analyst examining an individual plant. The report calls attention to plant features and operator actions and provides a list of deterministic attributes for assessing those features and actions found to be helpful in reducing the overall risk for Sequoyah and other PWRs with ice-condenser containments. Thus, the guidance is offered as a resource in examining the subject plant to determine if the same, or similar, plant features and operator actions will be of value in reducing overall plant risk. This report is intended to serve solely as guidance. 14 tabs
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Assessment of severe accident prevention and mitigation features: BWR, Mark II containment design
International Nuclear Information System (INIS)
Lehner, J.R.; Hsu, C.J.; Eltawila, F.; Perkins, K.R.; Luckas, W.J.; Fitzpatrick, R.G.; Pratt, W.T.
1988-07-01
Plant features and operator actions, which have been found to be important in either preventing or mitigating severe accidents in BWRs with Mark II containments (BWR Mark II's) have been identified. These features and actions were developed from insights derived from reviews of in-depth risk assessments performed specifically for the Limerick and Shoreham plants and from other relevant studies. Accident sequences that dominate the core-damage frequency and those accident sequences that are of potentially high consequence were identified. Vulnerabilities of the BWR Mark II to severe-accident containment loads were also noted. In addition, those features of a BWR Mark II, which are important for preventing core damage and are available for mitigating fission-product release to the environment were also identified. This report is issued to provide focus to an analyst examining an individual plant. This report calls attention to plant features and operator actions and provides a list of deterministic attributes for assessing those features and actions found to be helpful in reducing the overall risk for Mark II plants. Thus, the guidance is offered as a resource in examining the subject plant to determine if the same, or similar, plant features and operator actions will be of value in reducing overall plant risk. This report is intended to serve solely as guidance
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Learning models of activities involving interacting objects
DEFF Research Database (Denmark)
Manfredotti, Cristina; Pedersen, Kim Steenstrup; Hamilton, Howard J.
2013-01-01
We propose the LEMAIO multi-layer framework, which makes use of hierarchical abstraction to learn models for activities involving multiple interacting objects from time sequences of data concerning the individual objects. Experiments in the sea navigation domain yielded learned models that were t...
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Lyu, Yuqiang; Huang, Jing; Zhang, Kaihui; Liu, Guohua; Gao, Min; Gai, Zhongtao; Liu, Yi
2017-02-10
To explore the clinical and genetic features of a Chinese boy with oculocutaneous albinism. The clinical features of the patient were analyzed. The DNA of the patient and his parents was extracted and sequenced by next generation exome capture sequencing. The nature and impact of detected mutation were predicted and validated. The child has displayed strabismus, poor vision, nystagmus and brown hair. DNA sequencing showed that the patient has carried compound heterozygous mutations of the TYRP1 gene, namely c.1214C>A (p.T405N) and c.1333dupG, which were inherited from his mother and father, respectively. Neither mutation was reported previously. The child has suffered from oculocutaneous albinism type Ⅲ caused by mutations of the TYRP1 gene.
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Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods.
Qu, Kaiyang; Han, Ke; Wu, Song; Wang, Guohua; Wei, Leyi
2017-09-22
DNA-binding proteins play vital roles in cellular processes, such as DNA packaging, replication, transcription, regulation, and other DNA-associated activities. The current main prediction method is based on machine learning, and its accuracy mainly depends on the features extraction method. Therefore, using an efficient feature representation method is important to enhance the classification accuracy. However, existing feature representation methods cannot efficiently distinguish DNA-binding proteins from non-DNA-binding proteins. In this paper, a multi-feature representation method, which combines three feature representation methods, namely, K-Skip-N-Grams, Information theory, and Sequential and structural features (SSF), is used to represent the protein sequences and improve feature representation ability. In addition, the classifier is a support vector machine. The mixed-feature representation method is evaluated using 10-fold cross-validation and a test set. Feature vectors, which are obtained from a combination of three feature extractions, show the best performance in 10-fold cross-validation both under non-dimensional reduction and dimensional reduction by max-relevance-max-distance. Moreover, the reduced mixed feature method performs better than the non-reduced mixed feature technique. The feature vectors, which are a combination of SSF and K-Skip-N-Grams, show the best performance in the test set. Among these methods, mixed features exhibit superiority over the single features.
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Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods
Directory of Open Access Journals (Sweden)
Kaiyang Qu
2017-09-01
Full Text Available DNA-binding proteins play vital roles in cellular processes, such as DNA packaging, replication, transcription, regulation, and other DNA-associated activities. The current main prediction method is based on machine learning, and its accuracy mainly depends on the features extraction method. Therefore, using an efficient feature representation method is important to enhance the classification accuracy. However, existing feature representation methods cannot efficiently distinguish DNA-binding proteins from non-DNA-binding proteins. In this paper, a multi-feature representation method, which combines three feature representation methods, namely, K-Skip-N-Grams, Information theory, and Sequential and structural features (SSF, is used to represent the protein sequences and improve feature representation ability. In addition, the classifier is a support vector machine. The mixed-feature representation method is evaluated using 10-fold cross-validation and a test set. Feature vectors, which are obtained from a combination of three feature extractions, show the best performance in 10-fold cross-validation both under non-dimensional reduction and dimensional reduction by max-relevance-max-distance. Moreover, the reduced mixed feature method performs better than the non-reduced mixed feature technique. The feature vectors, which are a combination of SSF and K-Skip-N-Grams, show the best performance in the test set. Among these methods, mixed features exhibit superiority over the single features.
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Yu, Yue; Kushnir, Tamar
2016-01-01
This study explores the role of a particular social cue--the "sequence" of demonstrated actions and events--in preschooler's categorization. A demonstrator sorted objects that varied on both a surface feature (color) and a nonobvious property (sound made when shaken). Children saw a sequence of actions in which the nonobvious property…
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Directory of Open Access Journals (Sweden)
Pelletier Eric
2010-10-01
Full Text Available Abstract Background Clostridium sticklandii belongs to a cluster of non-pathogenic proteolytic clostridia which utilize amino acids as carbon and energy sources. Isolated by T.C. Stadtman in 1954, it has been generally regarded as a "gold mine" for novel biochemical reactions and is used as a model organism for studying metabolic aspects such as the Stickland reaction, coenzyme-B12- and selenium-dependent reactions of amino acids. With the goal of revisiting its carbon, nitrogen, and energy metabolism, and comparing studies with other clostridia, its genome has been sequenced and analyzed. Results C. sticklandii is one of the best biochemically studied proteolytic clostridial species. Useful additional information has been obtained from the sequencing and annotation of its genome, which is presented in this paper. Besides, experimental procedures reveal that C. sticklandii degrades amino acids in a preferential and sequential way. The organism prefers threonine, arginine, serine, cysteine, proline, and glycine, whereas glutamate, aspartate and alanine are excreted. Energy conservation is primarily obtained by substrate-level phosphorylation in fermentative pathways. The reactions catalyzed by different ferredoxin oxidoreductases and the exergonic NADH-dependent reduction of crotonyl-CoA point to a possible chemiosmotic energy conservation via the Rnf complex. C. sticklandii possesses both the F-type and V-type ATPases. The discovery of an as yet unrecognized selenoprotein in the D-proline reductase operon suggests a more detailed mechanism for NADH-dependent D-proline reduction. A rather unusual metabolic feature is the presence of genes for all the enzymes involved in two different CO2-fixation pathways: C. sticklandii harbours both the glycine synthase/glycine reductase and the Wood-Ljungdahl pathways. This unusual pathway combination has retrospectively been observed in only four other sequenced microorganisms. Conclusions Analysis of the C
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Space moving target detection using time domain feature
Wang, Min; Chen, Jin-yong; Gao, Feng; Zhao, Jin-yu
2018-01-01
The traditional space target detection methods mainly use the spatial characteristics of the star map to detect the targets, which can not make full use of the time domain information. This paper presents a new space moving target detection method based on time domain features. We firstly construct the time spectral data of star map, then analyze the time domain features of the main objects (target, stars and the background) in star maps, finally detect the moving targets using single pulse feature of the time domain signal. The real star map target detection experimental results show that the proposed method can effectively detect the trajectory of moving targets in the star map sequence, and the detection probability achieves 99% when the false alarm rate is about 8×10-5, which outperforms those of compared algorithms.
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Comparison of clustering methods for tracking features in RGB-D images
CSIR Research Space (South Africa)
Pancham, Ardhisha
2016-10-01
Full Text Available difficult to track individually over an image sequence. Clustering techniques have been recommended and used to cluster image features to improve tracking results. New and affordable RGB-D cameras, provide both color and depth information. This paper...
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Draft genome sequence of the Coccolithovirus Emiliania huxleyi virus 203.
Nissimov, Jozef I; Worthy, Charlotte A; Rooks, Paul; Napier, Johnathan A; Kimmance, Susan A; Henn, Matthew R; Ogata, Hiroyuki; Allen, Michael J
2011-12-01
The Coccolithoviridae are a recently discovered group of viruses that infect the marine coccolithophorid Emiliania huxleyi. Emiliania huxleyi virus 203 (EhV-203) has a 160- to 180-nm-diameter icosahedral structure and a genome of approximately 400 kbp, consisting of 464 coding sequences (CDSs). Here we describe the genomic features of EhV-203 together with a draft genome sequence and its annotation, highlighting the homology and heterogeneity of this genome in comparison with the EhV-86 reference genome.
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Directory of Open Access Journals (Sweden)
Konstantin Okonechnikov
Full Text Available Analysis of fusion transcripts has become increasingly important due to their link with cancer development. Since high-throughput sequencing approaches survey fusion events exhaustively, several computational methods for the detection of gene fusions from RNA-seq data have been developed. This kind of analysis, however, is complicated by native trans-splicing events, the splicing-induced complexity of the transcriptome and biases and artefacts introduced in experiments and data analysis. There are a number of tools available for the detection of fusions from RNA-seq data; however, certain differences in specificity and sensitivity between commonly used approaches have been found. The ability to detect gene fusions of different types, including isoform fusions and fusions involving non-coding regions, has not been thoroughly studied yet. Here, we propose a novel computational toolkit called InFusion for fusion gene detection from RNA-seq data. InFusion introduces several unique features, such as discovery of fusions involving intergenic regions, and detection of anti-sense transcription in chimeric RNAs based on strand-specificity. Our approach demonstrates superior detection accuracy on simulated data and several public RNA-seq datasets. This improved performance was also evident when evaluating data from RNA deep-sequencing of two well-established prostate cancer cell lines. InFusion identified 26 novel fusion events that were validated in vitro, including alternatively spliced gene fusion isoforms and chimeric transcripts that include intergenic regions. The toolkit is freely available to download from http:/bitbucket.org/kokonech/infusion.
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T.A. Knoch (Tobias); M. Göcker; R. Lohner (Rudolf); A. Abuseiris (Anis); F.G. Grosveld (Frank)
2009-01-01
textabstractThe sequential organization of genomes, i.e. the relations between distant base pairs and regions within sequences, and its connection to the three-dimensional organization of genomes is still a largely unresolved problem. Long-range power-law correlations were found using correlation
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Designing a placebo device: involving service users in clinical trial design.
Gooberman-Hill, Rachael; Jinks, Clare; Bouças, Sofia Barbosa; Hislop, Kelly; Dziedzic, Krysia S; Rhodes, Carol; Burston, Amanda; Adams, Jo
2013-12-01
Service users are increasingly involved in the design of clinical trials and in product and device development. Service user involvement in placebo development is crucial to a credible and acceptable placebo for clinical trials, but such involvement has not yet been reported. To enhance the design of a future clinical trial of hand splints for thumb-base osteoarthritis (OA), service users were involved in splint selection and design of a placebo splint. This article describes and reflects on this process. Two fora of service users were convened in 2011. Service users who had been prescribed a thumb splint for thumb-base OA were approached about involvement by Occupational Therapy (OT) practitioners. A total of eight service users took part in the fora. Service users discussed their experience of OA and their own splints and then tried a variety of alternative splints. Through this they identified the active features of splints alongside acceptable and unacceptable design features. Service users focused on wearability and support with or without immobilization. Fora discussed whether a placebo group ('arm') was an acceptable feature of a future trial, and service users developed a potential design for a placebo splint. This is the first project that to involve service users in placebo design. Service users are increasingly involved in product and device design and are ideally placed to identify features to make a placebo credible yet lacking key active ingredients. The future trial will include research into its acceptability. © 2013 John Wiley & Sons Ltd.
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Jo, Yeong Deuk; Choi, Yoomi; Kim, Dong-Hwan; Kim, Byung-Dong; Kang, Byoung-Cheorl
2014-07-04
Cytoplasmic male sterility (CMS) is an inability to produce functional pollen that is caused by mutation of the mitochondrial genome. Comparative analyses of mitochondrial genomes of lines with and without CMS in several species have revealed structural differences between genomes, including extensive rearrangements caused by recombination. However, the mitochondrial genome structure and the DNA rearrangements that may be related to CMS have not been characterized in Capsicum spp. We obtained the complete mitochondrial genome sequences of the pepper CMS line FS4401 (507,452 bp) and the fertile line Jeju (511,530 bp). Comparative analysis between mitochondrial genomes of peppers and tobacco that are included in Solanaceae revealed extensive DNA rearrangements and poor conservation in non-coding DNA. In comparison between pepper lines, FS4401 and Jeju mitochondrial DNAs contained the same complement of protein coding genes except for one additional copy of an atp6 gene (ψatp6-2) in FS4401. In terms of genome structure, we found eighteen syntenic blocks in the two mitochondrial genomes, which have been rearranged in each genome. By contrast, sequences between syntenic blocks, which were specific to each line, accounted for 30,380 and 17,847 bp in FS4401 and Jeju, respectively. The previously-reported CMS candidate genes, orf507 and ψatp6-2, were located on the edges of the largest sequence segments that were specific to FS4401. In this region, large number of small sequence segments which were absent or found on different locations in Jeju mitochondrial genome were combined together. The incorporation of repeats and overlapping of connected sequence segments by a few nucleotides implied that extensive rearrangements by homologous recombination might be involved in evolution of this region. Further analysis using mtDNA pairs from other plant species revealed common features of DNA regions around CMS-associated genes. Although large portion of sequence context was
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Expression profiling and comparative sequence derived insights into lipid metabolism
Energy Technology Data Exchange (ETDEWEB)
Callow, Matthew J.; Rubin, Edward M.
2001-12-19
Expression profiling and genomic DNA sequence comparisons are increasingly being applied to the identification and analysis of the genes involved in lipid metabolism. Not only has genome-wide expression profiling aided in the identification of novel genes involved in important processes in lipid metabolism such as sterol efflux, but the utilization of information from these studies has added to our understanding of the regulation of pathways participating in the process. Coupled with these gene expression studies, cross species comparison, searching for sequences conserved through evolution, has proven to be a powerful tool to identify important non-coding regulatory sequences as well as the discovery of novel genes relevant to lipid biology. An example of the value of this approach was the recent chance discovery of a new apolipoprotein gene (apo AV) that has dramatic effects upon triglyceride metabolism in mice and humans.
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High quality draft genome sequence of Staphylococcus cohnii subsp. cohnii strain hu-01.
Hu, XinJun; Li, Ang; Lv, LongXian; Yuan, Chunhui; Guo, Lihua; Jiang, Xiawei; Jiang, Haiyin; Qian, GuiRong; Zheng, BeiWen; Guo, Jing; Li, LanJuan
2014-06-15
Staphylococcus cohnii subsp. cohnii belongs to the family Staphylococcaceae in the order Bacillales, class Bacilli and phylum Firmicutes. The increasing relevance of S. cohnii to human health prompted us to determine the genomic sequence of Staphylococcus cohnii subsp. cohnii strain hu-01, a multidrug-resistant isolate from a hospital in China. Here we describe the features of S. cohnii subsp. cohnii strain hu-01, together with the genome sequence and its annotation. This is the first genome sequence of the species Staphylococcus cohnii.
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Directory of Open Access Journals (Sweden)
Masoume Vakili Azghandi
2016-05-01
Full Text Available Background: The SRY gene (SRY provides instructions for making a transcription factor called the sex-determining region Y protein. The sex-determining region Y protein causes a fetus to develop as a male. In this study, SRY of 15 spices included of human, chimpanzee, dog, pig, rat, cattle, buffalo, goat, sheep, horse, zebra, frog, urial, dolphin and killer whale were used for determine of bioinformatic differences. Methods: Nucleotide sequences of SRY were retrieved from the NCBI databank. Bioinformatic analysis of SRY is done by CLC Main Workbench version 5.5 and ClustalW (http:/www.ebi.ac.uk/clustalw/ and MEGA6 softwares. Results: The multiple sequence alignment results indicated that SRY protein sequences from Orcinus orca (killer whale and Tursiopsaduncus (dolphin have least genetic distance of 0.33 in these 15 species and are 99.67% identical at the amino acid level. Homosapiens and Pantroglodytes (chimpanzee have the next lowest genetic distance of 1.35 and are 98.65% identical at the amino acid level. Conclusion: These findings indicate that the SRY proteins are conserved in the 15 species, and their evolutionary relationships are similar.
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A computational genomics pipeline for prokaryotic sequencing projects.
Kislyuk, Andrey O; Katz, Lee S; Agrawal, Sonia; Hagen, Matthew S; Conley, Andrew B; Jayaraman, Pushkala; Nelakuditi, Viswateja; Humphrey, Jay C; Sammons, Scott A; Govil, Dhwani; Mair, Raydel D; Tatti, Kathleen M; Tondella, Maria L; Harcourt, Brian H; Mayer, Leonard W; Jordan, I King
2010-08-01
New sequencing technologies have accelerated research on prokaryotic genomes and have made genome sequencing operations outside major genome sequencing centers routine. However, no off-the-shelf solution exists for the combined assembly, gene prediction, genome annotation and data presentation necessary to interpret sequencing data. The resulting requirement to invest significant resources into custom informatics support for genome sequencing projects remains a major impediment to the accessibility of high-throughput sequence data. We present a self-contained, automated high-throughput open source genome sequencing and computational genomics pipeline suitable for prokaryotic sequencing projects. The pipeline has been used at the Georgia Institute of Technology and the Centers for Disease Control and Prevention for the analysis of Neisseria meningitidis and Bordetella bronchiseptica genomes. The pipeline is capable of enhanced or manually assisted reference-based assembly using multiple assemblers and modes; gene predictor combining; and functional annotation of genes and gene products. Because every component of the pipeline is executed on a local machine with no need to access resources over the Internet, the pipeline is suitable for projects of a sensitive nature. Annotation of virulence-related features makes the pipeline particularly useful for projects working with pathogenic prokaryotes. The pipeline is licensed under the open-source GNU General Public License and available at the Georgia Tech Neisseria Base (http://nbase.biology.gatech.edu/). The pipeline is implemented with a combination of Perl, Bourne Shell and MySQL and is compatible with Linux and other Unix systems.
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Feature selection gait-based gender classification under different circumstances
Sabir, Azhin; Al-Jawad, Naseer; Jassim, Sabah
2014-05-01
This paper proposes a gender classification based on human gait features and investigates the problem of two variations: clothing (wearing coats) and carrying bag condition as addition to the normal gait sequence. The feature vectors in the proposed system are constructed after applying wavelet transform. Three different sets of feature are proposed in this method. First, Spatio-temporal distance that is dealing with the distance of different parts of the human body (like feet, knees, hand, Human Height and shoulder) during one gait cycle. The second and third feature sets are constructed from approximation and non-approximation coefficient of human body respectively. To extract these two sets of feature we divided the human body into two parts, upper and lower body part, based on the golden ratio proportion. In this paper, we have adopted a statistical method for constructing the feature vector from the above sets. The dimension of the constructed feature vector is reduced based on the Fisher score as a feature selection method to optimize their discriminating significance. Finally k-Nearest Neighbor is applied as a classification method. Experimental results demonstrate that our approach is providing more realistic scenario and relatively better performance compared with the existing approaches.
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FAST: FAST Analysis of Sequences Toolbox
Directory of Open Access Journals (Sweden)
Travis J. Lawrence
2015-05-01
Full Text Available FAST (FAST Analysis of Sequences Toolbox provides simple, powerful open source command-line tools to filter, transform, annotate and analyze biological sequence data. Modeled after the GNU (GNU’s Not Unix Textutils such as grep, cut, and tr, FAST tools such as fasgrep, fascut, and fastr make it easy to rapidly prototype expressive bioinformatic workflows in a compact and generic command vocabulary. Compact combinatorial encoding of data workflows with FAST commands can simplify the documentation and reproducibility of bioinformatic protocols, supporting better transparency in biological data science. Interface self-consistency and conformity with conventions of GNU, Matlab, Perl, BioPerl, R and GenBank help make FAST easy and rewarding to learn. FAST automates numerical, taxonomic, and text-based sorting, selection and transformation of sequence records and alignment sites based on content, index ranges, descriptive tags, annotated features, and in-line calculated analytics, including composition and codon usage. Automated content- and feature-based extraction of sites and support for molecular population genetic statistics makes FAST useful for molecular evolutionary analysis. FAST is portable, easy to install and secure thanks to the relative maturity of its Perl and BioPerl foundations, with stable releases posted to CPAN. Development as well as a publicly accessible Cookbook and Wiki are available on the FAST GitHub repository at https://github.com/tlawrence3/FAST. The default data exchange format in FAST is Multi-FastA (specifically, a restriction of BioPerl FastA format. Sanger and Illumina 1.8+ FastQ formatted files are also supported. FAST makes it easier for non-programmer biologists to interactively investigate and control biological data at the speed of thought.
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A novel, privacy-preserving cryptographic approach for sharing sequencing data
Cassa, Christopher A; Miller, Rachel A; Mandl, Kenneth D
2013-01-01
Objective DNA samples are often processed and sequenced in facilities external to the point of collection. These samples are routinely labeled with patient identifiers or pseudonyms, allowing for potential linkage to identity and private clinical information if intercepted during transmission. We present a cryptographic scheme to securely transmit externally generated sequence data which does not require any patient identifiers, public key infrastructure, or the transmission of passwords. Materials and methods This novel encryption scheme cryptographically protects participant sequence data using a shared secret key that is derived from a unique subset of an individual’s genetic sequence. This scheme requires access to a subset of an individual’s genetic sequence to acquire full access to the transmitted sequence data, which helps to prevent sample mismatch. Results We validate that the proposed encryption scheme is robust to sequencing errors, population uniqueness, and sibling disambiguation, and provides sufficient cryptographic key space. Discussion Access to a set of an individual’s genotypes and a mutually agreed cryptographic seed is needed to unlock the full sequence, which provides additional sample authentication and authorization security. We present modest fixed and marginal costs to implement this transmission architecture. Conclusions It is possible for genomics researchers who sequence participant samples externally to protect the transmission of sequence data using unique features of an individual’s genetic sequence. PMID:23125421
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Neural mechanisms of sequence generation in songbirds
Langford, Bruce
Animal models in research are useful for studying more complex behavior. For example, motor sequence generation of actions requiring good muscle coordination such as writing with a pen, playing an instrument, or speaking, may involve the interaction of many areas in the brain, each a complex system in itself; thus it can be difficult to determine causal relationships between neural behavior and the behavior being studied. Birdsong, however, provides an excellent model behavior for motor sequence learning, memory, and generation. The song consists of learned sequences of notes that are spectrographically stereotyped over multiple renditions of the song, similar to syllables in human speech. The main areas of the songbird brain involve in singing are known, however, the mechanisms by which these systems store and produce song are not well understood. We used a custom built, head-mounted, miniature motorized microdrive to chronically record the neural firing patterns of identified neurons in HVC, a pre-motor cortical nucleus which has been shown to be important in song timing. These were done in Bengalese finch which generate a song made up of stereotyped notes but variable note sequences. We observed song related bursting in neurons projecting to Area X, a homologue to basal ganglia, and tonic firing in HVC interneurons. Interneuron had firing rate patterns that were consistent over multiple renditions of the same note sequence. We also designed and built a light-weight, low-powered wireless programmable neural stimulator using Bluetooth Low Energy Protocol. It was able to generate perturbations in the song when current pulses were administered to RA, which projects to the brainstem nucleus responsible for syringeal muscle control.
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Mission Management Computer and Sequencing Hardware for RLV-TD HEX-01 Mission
Gupta, Sukrat; Raj, Remya; Mathew, Asha Mary; Koshy, Anna Priya; Paramasivam, R.; Mookiah, T.
2017-12-01
Reusable Launch Vehicle-Technology Demonstrator Hypersonic Experiment (RLV-TD HEX-01) mission posed some unique challenges in the design and development of avionics hardware. This work presents the details of mission critical avionics hardware mainly Mission Management Computer (MMC) and sequencing hardware. The Navigation, Guidance and Control (NGC) chain for RLV-TD is dual redundant with cross-strapped Remote Terminals (RTs) interfaced through MIL-STD-1553B bus. MMC is Bus Controller on the 1553 bus, which does the function of GPS aided navigation, guidance, digital autopilot and sequencing for the RLV-TD launch vehicle in different periodicities (10, 20, 500 ms). Digital autopilot execution in MMC with a periodicity of 10 ms (in ascent phase) is introduced for the first time and successfully demonstrated in the flight. MMC is built around Intel i960 processor and has inbuilt fault tolerance features like ECC for memories. Fault Detection and Isolation schemes are implemented to isolate the failed MMC. The sequencing hardware comprises Stage Processing System (SPS) and Command Execution Module (CEM). SPS is `RT' on the 1553 bus which receives the sequencing and control related commands from MMCs and posts to downstream modules after proper error handling for final execution. SPS is designed as a high reliability system by incorporating various fault tolerance and fault detection features. CEM is a relay based module for sequence command execution.
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Dean, Kimberly M; Grayhack, Elizabeth J
2012-12-01
We have developed a robust and sensitive method, called RNA-ID, to screen for cis-regulatory sequences in RNA using fluorescence-activated cell sorting (FACS) of yeast cells bearing a reporter in which expression of both superfolder green fluorescent protein (GFP) and yeast codon-optimized mCherry red fluorescent protein (RFP) is driven by the bidirectional GAL1,10 promoter. This method recapitulates previously reported progressive inhibition of translation mediated by increasing numbers of CGA codon pairs, and restoration of expression by introduction of a tRNA with an anticodon that base pairs exactly with the CGA codon. This method also reproduces effects of paromomycin and context on stop codon read-through. Five key features of this method contribute to its effectiveness as a selection for regulatory sequences: The system exhibits greater than a 250-fold dynamic range, a quantitative and dose-dependent response to known inhibitory sequences, exquisite resolution that allows nearly complete physical separation of distinct populations, and a reproducible signal between different cells transformed with the identical reporter, all of which are coupled with simple methods involving ligation-independent cloning, to create large libraries. Moreover, we provide evidence that there are sequences within a 9-nt library that cause reduced GFP fluorescence, suggesting that there are novel cis-regulatory sequences to be found even in this short sequence space. This method is widely applicable to the study of both RNA-mediated and codon-mediated effects on expression.
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nRC: non-coding RNA Classifier based on structural features.
Fiannaca, Antonino; La Rosa, Massimo; La Paglia, Laura; Rizzo, Riccardo; Urso, Alfonso
2017-01-01
Non-coding RNA (ncRNA) are small non-coding sequences involved in gene expression regulation of many biological processes and diseases. The recent discovery of a large set of different ncRNAs with biologically relevant roles has opened the way to develop methods able to discriminate between the different ncRNA classes. Moreover, the lack of knowledge about the complete mechanisms in regulative processes, together with the development of high-throughput technologies, has required the help of bioinformatics tools in addressing biologists and clinicians with a deeper comprehension of the functional roles of ncRNAs. In this work, we introduce a new ncRNA classification tool, nRC (non-coding RNA Classifier). Our approach is based on features extraction from the ncRNA secondary structure together with a supervised classification algorithm implementing a deep learning architecture based on convolutional neural networks. We tested our approach for the classification of 13 different ncRNA classes. We obtained classification scores, using the most common statistical measures. In particular, we reach an accuracy and sensitivity score of about 74%. The proposed method outperforms other similar classification methods based on secondary structure features and machine learning algorithms, including the RNAcon tool that, to date, is the reference classifier. nRC tool is freely available as a docker image at https://hub.docker.com/r/tblab/nrc/. The source code of nRC tool is also available at https://github.com/IcarPA-TBlab/nrc.
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Poincaré recurrences of DNA sequences
Frahm, K. M.; Shepelyansky, D. L.
2012-01-01
We analyze the statistical properties of Poincaré recurrences of Homo sapiens, mammalian, and other DNA sequences taken from the Ensembl Genome data base with up to 15 billion base pairs. We show that the probability of Poincaré recurrences decays in an algebraic way with the Poincaré exponent β≈4 even if the oscillatory dependence is well pronounced. The correlations between recurrences decay with an exponent ν≈0.6 that leads to an anomalous superdiffusive walk. However, for Homo sapiens sequences, with the largest available statistics, the diffusion coefficient converges to a finite value on distances larger than one million base pairs. We argue that the approach based on Poncaré recurrences determines new proximity features between different species and sheds a new light on their evolution history.
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Upadia, Jariya; Gonzales, Patrick R; Robin, Nathaniel H
2018-04-16
The NR2F2 gene plays an important role in angiogenesis and heart development. Moreover, this gene is involved in organogenesis in many other organs in mouse models. Variants in this gene have been reported in a number of patients with nonsyndromic atrioventricular septal defect, and in one patient with congenital heart defect and dysmorphic features. Here we report an 11-month-old Caucasian male with global developmental delay, dysmorphic features, coarctation of the aorta, and ventricular septal defect. He was later found to have a pathogenic mutation in the NR2F2 gene by whole exome sequencing. This is the second instance in which an NR2F2 mutation has been identified in a child with a congenital heart defect and other anomalies. This case suggests that some variants in NR2F2 may cause syndromic forms of congenital heart defect. © 2018 Wiley Periodicals, Inc.
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Optimized Feature Extraction for Temperature-Modulated Gas Sensors
Directory of Open Access Journals (Sweden)
Alexander Vergara
2009-01-01
Full Text Available One of the most serious limitations to the practical utilization of solid-state gas sensors is the drift of their signal. Even if drift is rooted in the chemical and physical processes occurring in the sensor, improved signal processing is generally considered as a methodology to increase sensors stability. Several studies evidenced the augmented stability of time variable signals elicited by the modulation of either the gas concentration or the operating temperature. Furthermore, when time-variable signals are used, the extraction of features can be accomplished in shorter time with respect to the time necessary to calculate the usual features defined in steady-state conditions. In this paper, we discuss the stability properties of distinct dynamic features using an array of metal oxide semiconductors gas sensors whose working temperature is modulated with optimized multisinusoidal signals. Experiments were aimed at measuring the dispersion of sensors features in repeated sequences of a limited number of experimental conditions. Results evidenced that the features extracted during the temperature modulation reduce the multidimensional data dispersion among repeated measurements. In particular, the Energy Signal Vector provided an almost constant classification rate along the time with respect to the temperature modulation.
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Progressive multiple sequence alignments from triplets
Directory of Open Access Journals (Sweden)
Stadler Peter F
2007-07-01
Full Text Available Abstract Background The quality of progressive sequence alignments strongly depends on the accuracy of the individual pairwise alignment steps since gaps that are introduced at one step cannot be removed at later aggregation steps. Adjacent insertions and deletions necessarily appear in arbitrary order in pairwise alignments and hence form an unavoidable source of errors. Research Here we present a modified variant of progressive sequence alignments that addresses both issues. Instead of pairwise alignments we use exact dynamic programming to align sequence or profile triples. This avoids a large fractions of the ambiguities arising in pairwise alignments. In the subsequent aggregation steps we follow the logic of the Neighbor-Net algorithm, which constructs a phylogenetic network by step-wisely replacing triples by pairs instead of combining pairs to singletons. To this end the three-way alignments are subdivided into two partial alignments, at which stage all-gap columns are naturally removed. This alleviates the "once a gap, always a gap" problem of progressive alignment procedures. Conclusion The three-way Neighbor-Net based alignment program aln3nn is shown to compare favorably on both protein sequences and nucleic acids sequences to other progressive alignment tools. In the latter case one easily can include scoring terms that consider secondary structure features. Overall, the quality of resulting alignments in general exceeds that of clustalw or other multiple alignments tools even though our software does not included heuristics for context dependent (mismatch scores.
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Extended sequence diagram for human system interaction
International Nuclear Information System (INIS)
Hwang, Jong Rok; Choi, Sun Woo; Ko, Hee Ran; Kim, Jong Hyun
2012-01-01
Unified Modeling Language (UML) is a modeling language in the field of object oriented software engineering. The sequence diagram is a kind of interaction diagram that shows how processes operate with one another and in what order. It is a construct of a message sequence chart. It depicts the objects and classes involved in the scenario and the sequence of messages exchanged between the objects needed to carry out the functionality of the scenario. This paper proposes the Extended Sequence Diagram (ESD), which is capable of depicting human system interaction for nuclear power plants, as well as cognitive process of operators analysis. In the conventional sequence diagram, there is a limit to only identify the activities of human and systems interactions. The ESD is extended to describe operators' cognitive process in more detail. The ESD is expected to be used as a task analysis method for describing human system interaction. The ESD can also present key steps causing abnormal operations or failures and diverse human errors based on cognitive condition
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CISAPS: Complex Informational Spectrum for the Analysis of Protein Sequences
Directory of Open Access Journals (Sweden)
Charalambos Chrysostomou
2015-01-01
Full Text Available Complex informational spectrum analysis for protein sequences (CISAPS and its web-based server are developed and presented. As recent studies show, only the use of the absolute spectrum in the analysis of protein sequences using the informational spectrum analysis is proven to be insufficient. Therefore, CISAPS is developed to consider and provide results in three forms including absolute, real, and imaginary spectrum. Biologically related features to the analysis of influenza A subtypes as presented as a case study in this study can also appear individually either in the real or imaginary spectrum. As the results presented, protein classes can present similarities or differences according to the features extracted from CISAPS web server. These associations are probable to be related with the protein feature that the specific amino acid index represents. In addition, various technical issues such as zero-padding and windowing that may affect the analysis are also addressed. CISAPS uses an expanded list of 611 unique amino acid indices where each one represents a different property to perform the analysis. This web-based server enables researchers with little knowledge of signal processing methods to apply and include complex informational spectrum analysis to their work.
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Predicting tissue-specific expressions based on sequence characteristics
Paik, Hyojung; Ryu, Tae Woo; Heo, Hyoungsam; Seo, Seungwon; Lee, Doheon; Hur, Cheolgoo
2011-01-01
In multicellular organisms, including humans, understanding expression specificity at the tissue level is essential for interpreting protein function, such as tissue differentiation. We developed a prediction approach via generated sequence features from overrepresented patterns in housekeeping (HK) and tissue-specific (TS) genes to classify TS expression in humans. Using TS domains and transcriptional factor binding sites (TFBSs), sequence characteristics were used as indices of expressed tissues in a Random Forest algorithm by scoring exclusive patterns considering the biological intuition; TFBSs regulate gene expression, and the domains reflect the functional specificity of a TS gene. Our proposed approach displayed better performance than previous attempts and was validated using computational and experimental methods.
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Predicting tissue-specific expressions based on sequence characteristics
Paik, Hyojung
2011-04-30
In multicellular organisms, including humans, understanding expression specificity at the tissue level is essential for interpreting protein function, such as tissue differentiation. We developed a prediction approach via generated sequence features from overrepresented patterns in housekeeping (HK) and tissue-specific (TS) genes to classify TS expression in humans. Using TS domains and transcriptional factor binding sites (TFBSs), sequence characteristics were used as indices of expressed tissues in a Random Forest algorithm by scoring exclusive patterns considering the biological intuition; TFBSs regulate gene expression, and the domains reflect the functional specificity of a TS gene. Our proposed approach displayed better performance than previous attempts and was validated using computational and experimental methods.
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Directory of Open Access Journals (Sweden)
Elena A. Borovikova
2016-09-01
Full Text Available Background. Recently was revealed that cisco from Lake Sobachye (Putorana Plateau is more similar to Coregonus albula Linnaeuas than C. sardinella Valenciennes according to number of vertebrae [13]. The aim of this work was to investigate molecular genetic features of this population. Materials and methods. For morphological analysis were used 60 specimens of cisco from Lake Sobachye. For nine specimens molecular genetic analysis was performed. The sequences of two fragments of the mitochondrial DNA (ND1 and COI were defined. Results. The cisco of the Lake Sobachye significantly differed from riverine cisco of this region by meristic features (namely from cisco of the River Pyasina. Sequencing results showed the minimal divergence of the ND1 and COI sequences of the cisco from Lake Sobachye and vendace. Conclusion. Morphological analysis and analysis of the mitochondrial DNA polymorphism of cisco from Lake Sobachye revealed close relationship of this population to C. albula.
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International Nuclear Information System (INIS)
Lee, Sang Kwon; Choe, Mi Sun
2013-01-01
We report a case of mucosa-associated lymphoid tissue (MALT) lymphoma involving the medial rectus muscle in a 47-year-old man along with CT, MRI, 18 F-fluorodeoxy-glucose positron emission tomography/CT ( 18 F-FDG PET/CT), and pathologic features. The lesion was manifested as a fusiform enlargement isolated to the right medial rectus muscle with involvement of its tendinous insertion. The lesion was isoattenuating to the brain on non-enhanced CT images, showing as isointense to gray matter on fast spin echo T1- and T2-weighted images with fat saturation, and showed homogeneous enhancement on contrast-enhanced CT and MR images. The maximum stan- dardized uptake value on 18 F-FDG PET/CT was 4.9 g/mL. The results of histological and immunohistochemical examinations of the specimen obtained by biopsy of the right medial rectus muscle were consistent with MALT lymphoma. It should be noted that the extraocular muscle (EOM) is a rare location for the involvement of MALT lympho- ma, and MALT lymphoma of the EOM may mimic thyroid orbitopathy.
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Draft genome sequence of the coccolithovirus Emiliania huxleyi virus 202.
Nissimov, Jozef I; Worthy, Charlotte A; Rooks, Paul; Napier, Johnathan A; Kimmance, Susan A; Henn, Matthew R; Ogata, Hiroyuki; Allen, Michael J
2012-02-01
Emiliania huxleyi virus 202 (EhV-202) is a member of the Coccolithoviridae, a group of viruses that infect the marine coccolithophorid Emiliania huxleyi. EhV-202 has a 160- to 180-nm-diameter icosahedral structure and a genome of approximately 407 kbp, consisting of 485 coding sequences (CDSs). Here we describe the genomic features of EhV-202, together with a draft genome sequence and its annotation, highlighting the homology and heterogeneity of this genome in comparison with the EhV-86 reference genome.
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Complete genome sequence of Gordonia bronchialis type strain (3410T)
Energy Technology Data Exchange (ETDEWEB)
Ivanova, N [U.S. Department of Energy, Joint Genome Institute; Sikorski, Johannes [DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany; Jando, Marlen [DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany; Lapidus, Alla L. [U.S. Department of Energy, Joint Genome Institute; Nolan, Matt [U.S. Department of Energy, Joint Genome Institute; Glavina Del Rio, Tijana [U.S. Department of Energy, Joint Genome Institute; Tice, Hope [U.S. Department of Energy, Joint Genome Institute; Copeland, A [U.S. Department of Energy, Joint Genome Institute; Cheng, Jan-Fang [U.S. Department of Energy, Joint Genome Institute; Chen, Feng [U.S. Department of Energy, Joint Genome Institute; Bruce, David [Los Alamos National Laboratory (LANL); Goodwin, Lynne A. [Los Alamos National Laboratory (LANL); Pitluck, Sam [U.S. Department of Energy, Joint Genome Institute; Mavromatis, K [U.S. Department of Energy, Joint Genome Institute; Ovchinnikova, Galina [U.S. Department of Energy, Joint Genome Institute; Pati, Amrita [U.S. Department of Energy, Joint Genome Institute; Chen, Amy [U.S. Department of Energy, Joint Genome Institute; Palaniappan, Krishna [U.S. Department of Energy, Joint Genome Institute; Land, Miriam L [ORNL; Hauser, Loren John [ORNL; Chang, Yun-Juan [ORNL; Jeffries, Cynthia [Oak Ridge National Laboratory (ORNL); Chain, Patrick S. G. [Lawrence Livermore National Laboratory (LLNL); Saunders, Elizabeth H [Los Alamos National Laboratory (LANL); Han, Cliff [Los Alamos National Laboratory (LANL); Detter, J C [U.S. Department of Energy, Joint Genome Institute; Brettin, Thomas S [ORNL; Rohde, Manfred [HZI - Helmholtz Centre for Infection Research, Braunschweig, Germany; Goker, Markus [DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany; Bristow, James [U.S. Department of Energy, Joint Genome Institute; Eisen, Jonathan [U.S. Department of Energy, Joint Genome Institute; Markowitz, Victor [U.S. Department of Energy, Joint Genome Institute; Hugenholtz, Philip [U.S. Department of Energy, Joint Genome Institute; Klenk, Hans-Peter [DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany; Kyrpides, Nikos C [U.S. Department of Energy, Joint Genome Institute
2010-01-01
Gordonia bronchialis Tsukamura 1971 is the type species of the genus. G. bronchialis is a human-pathogenic organism that has been isolated from a large variety of human tissues. Here we describe the features of this organism, together with the complete genome sequence and annotation. This is the first completed genome sequence of the family Gordoniaceae. The 5,290,012 bp long genome with its 4,944 protein-coding and 55 RNA genes is part of the Genomic Encyclopedia of Bacteria and Archaea project.
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Biased distribution of DNA uptake sequences towards genome maintenance genes
DEFF Research Database (Denmark)
Davidsen, T.; Rodland, E.A.; Lagesen, K.
2004-01-01
Repeated sequence signatures are characteristic features of all genomic DNA. We have made a rigorous search for repeat genomic sequences in the human pathogens Neisseria meningitidis, Neisseria gonorrhoeae and Haemophilus influenzae and found that by far the most frequent 9-10mers residing within...... in these organisms. Pasteurella multocida also displayed high frequencies of a putative DUS identical to that previously identified in H. influenzae and with a skewed distribution towards genome maintenance genes, indicating that this bacterium might be transformation competent under certain conditions....
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POST-MERGER SIGNATURES OF RED-SEQUENCE GALAXIES IN RICH ABELL CLUSTERS AT z ∼< 0.1
International Nuclear Information System (INIS)
Sheen, Yun-Kyeong; Yi, Sukyoung K.; Lee, Jaehyun; Ree, Chang H.
2012-01-01
We have investigated the post-merger signatures of red-sequence galaxies in rich Abell clusters at z ∼ r < –20) cluster red-sequence galaxies show post-merger signatures in four clusters consistently. Most (∼71%) of the featured galaxies were found to be bulge dominated, and for the subsample of bulge-dominated red-sequence galaxies, the post-merger fraction rises to ∼38%. We also found that roughly 4% of bulge-dominated red-sequence galaxies interact (ongoing merger). A total of 42% (38% post-merger, 4% ongoing merger) of galaxies show merger-related features. Compared to a field galaxy study with a similar limiting magnitude by van Dokkum in 2005, our cluster study presents a similar post-merger fraction but a markedly lower ongoing merger fraction. The merger fraction derived is surprisingly high for the high density of our clusters, where the fast internal motions of galaxies are thought to play a negative role in galaxy mergers. The fraction of post-merger and ongoing merger galaxies can be explained as follows. Most of the post-merger galaxies may have carried over their merger features from their previous halo environment, whereas interacting galaxies interact in the current cluster in situ. According to our semi-analytic calculation, massive cluster halos may very well have experienced tens of halo mergers over the last 4-5 Gyr; post-merger features last that long, allowing these features to be detected in our clusters today. The apparent lack of dependence of the merger fraction on the clustocentric distance is naturally explained this way. In this scenario, the galaxy morphology and properties can be properly interpreted only when the halo evolution characteristics are understood first.
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Alertness modulates conflict adaptation and feature integration in an opposite way.
Directory of Open Access Journals (Sweden)
Peiduo Liu
Full Text Available Previous studies show that the congruency sequence effect can result from both the conflict adaptation effect (CAE and feature integration effect which can be observed as the repetition priming effect (RPE and feature overlap effect (FOE depending on different experimental conditions. Evidence from neuroimaging studies suggests that a close correlation exists between the neural mechanisms of alertness-related modulations and the congruency sequence effect. However, little is known about whether and how alertness mediates the congruency sequence effect. In Experiment 1, the Attentional Networks Test (ANT and a modified flanker task were used to evaluate whether the alertness of the attentional functions had a correlation with the CAE and RPE. In Experimental 2, the ANT and another modified flanker task were used to investigate whether alertness of the attentional functions correlate with the CAE and FOE. In Experiment 1, through the correlative analysis, we found a significant positive correlation between alertness and the CAE, and a negative correlation between the alertness and the RPE. Moreover, a significant negative correlation existed between CAE and RPE. In Experiment 2, we found a marginally significant negative correlation between the CAE and the RPE, but the correlation between alertness and FOE, CAE and FOE was not significant. These results suggest that alertness can modulate conflict adaptation and feature integration in an opposite way. Participants at the high alerting level group may tend to use the top-down cognitive processing strategy, whereas participants at the low alerting level group tend to use the bottom-up processing strategy.
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Alertness Modulates Conflict Adaptation and Feature Integration in an Opposite Way
Chen, Jia; Huang, Xiting; Chen, Antao
2013-01-01
Previous studies show that the congruency sequence effect can result from both the conflict adaptation effect (CAE) and feature integration effect which can be observed as the repetition priming effect (RPE) and feature overlap effect (FOE) depending on different experimental conditions. Evidence from neuroimaging studies suggests that a close correlation exists between the neural mechanisms of alertness-related modulations and the congruency sequence effect. However, little is known about whether and how alertness mediates the congruency sequence effect. In Experiment 1, the Attentional Networks Test (ANT) and a modified flanker task were used to evaluate whether the alertness of the attentional functions had a correlation with the CAE and RPE. In Experimental 2, the ANT and another modified flanker task were used to investigate whether alertness of the attentional functions correlate with the CAE and FOE. In Experiment 1, through the correlative analysis, we found a significant positive correlation between alertness and the CAE, and a negative correlation between the alertness and the RPE. Moreover, a significant negative correlation existed between CAE and RPE. In Experiment 2, we found a marginally significant negative correlation between the CAE and the RPE, but the correlation between alertness and FOE, CAE and FOE was not significant. These results suggest that alertness can modulate conflict adaptation and feature integration in an opposite way. Participants at the high alerting level group may tend to use the top-down cognitive processing strategy, whereas participants at the low alerting level group tend to use the bottom-up processing strategy. PMID:24250824
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Directory of Open Access Journals (Sweden)
Bingjun eDang
2016-02-01
Full Text Available Plasmid pGA45 was isolated from the sediment of Haihe River using E. coli CV601 (gfp-tagged as recipients and indigenous bacteria from sediment as donors. This plasmid confers reduced susceptibility to imipenem which belongs to carbapenem group. Plasmid pGA45 was fully sequenced on an Illumina HiSeq 2000 sequencing system. The complete sequence of plasmid pGA45 was 140,698 bp in length with an average G+C content of 52.03%. Sequence analysis shows that pGA45 belongs to incFIIY group and harbors a backbone region shares high homology and gene synteny to several other incF plasmids including pNDM1_EC14653, pYDC644, pNDM-Ec1GN574, pRJF866, pKOX_NDM1 and pP10164-NDM. In addition to the backbone region, plasmid pGA45 harbors two notable features including one blaIMI-3-containing region and one type VI secretion system region. The blaIMI-3-containing region is responsible for bacteria carbapenem resistance and the type VI secretion system region is probably involved in bacteria virulence, respectively. Plasmid pGA45 represents the first complete nucleotide sequence of the blaIMI-harboring plasmid from environment sample and the sequencing of this plasmid provided insight into the architecture used for the dissemination of blaIMI carbapenemase genes.
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MicroRNA categorization using sequence motifs and k-mers.
Yousef, Malik; Khalifa, Waleed; Acar, İlhan Erkin; Allmer, Jens
2017-03-14
Post-transcriptional gene dysregulation can be a hallmark of diseases like cancer and microRNAs (miRNAs) play a key role in the modulation of translation efficiency. Known pre-miRNAs are listed in miRBase, and they have been discovered in a variety of organisms ranging from viruses and microbes to eukaryotic organisms. The computational detection of pre-miRNAs is of great interest, and such approaches usually employ machine learning to discriminate between miRNAs and other sequences. Many features have been proposed describing pre-miRNAs, and we have previously introduced the use of sequence motifs and k-mers as useful ones. There have been reports of xeno-miRNAs detected via next generation sequencing. However, they may be contaminations and to aid that important decision-making process, we aimed to establish a means to differentiate pre-miRNAs from different species. To achieve distinction into species, we used one species' pre-miRNAs as the positive and another species' pre-miRNAs as the negative training and test data for the establishment of machine learned models based on sequence motifs and k-mers as features. This approach resulted in higher accuracy values between distantly related species while species with closer relation produced lower accuracy values. We were able to differentiate among species with increasing success when the evolutionary distance increases. This conclusion is supported by previous reports of fast evolutionary changes in miRNAs since even in relatively closely related species a fairly good discrimination was possible.
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Patient involvement in Danish health care
DEFF Research Database (Denmark)
Vrangbaek, Karsten
2015-01-01
PURPOSE: The purpose of this paper is to investigate different types of patient involvement in Denmark, and to discuss the potential implications of pursuing several strategies for patient involvement simultaneously. DESIGN/METHODOLOGY/APPROACH: The paper presents a preliminary framework for anal......PURPOSE: The purpose of this paper is to investigate different types of patient involvement in Denmark, and to discuss the potential implications of pursuing several strategies for patient involvement simultaneously. DESIGN/METHODOLOGY/APPROACH: The paper presents a preliminary framework...... for analysis of patient involvement in health care. This framework is used to analyze key governance features of patient involvement in Denmark based on previous research papers and reports describing patient involvement in Danish health care. FINDINGS: Patient involvement is important in Denmark...... be identified when pursuing the strategies at the same time. RESEARCH LIMITATIONS/IMPLICATIONS: Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed framework further. PRACTICAL IMPLICATIONS: The paper includes...
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Multisystem involvement in neuromyelitis optica
Directory of Open Access Journals (Sweden)
Megan M Langille
2015-01-01
Full Text Available We describe a case of pediatric neuromyelitis optica (NMO with muscle and lung involvement in addition to central nervous system disease. Our patient initially presented with features of area postrema syndrome, then subsequently with optic neuritis. The patient also had recurrent hyperCKemia that responded to corticosteroids. Finally, axillary and hilar adenopathy with pulmonary consolidation were noted as well and responded to immunomodulation. Our case highlights multisystem involvement in NMO including non-infectious pulmonary findings which have not been described in the pediatric population previously.
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System-level hazard analysis using the sequence-tree method
International Nuclear Information System (INIS)
Huang, H.-W.; Shih Chunkuan; Yih Swu; Chen, M.-H.
2008-01-01
A system-level PHA using the sequence-tree method is presented to perform safety-related digital I and C system SSA. The conventional PHA involves brainstorming among experts on various portions of the system to identify hazards through discussions. However, since the conventional PHA is not a systematic technique, the analysis results depend strongly on the experts' subjective opinions. The quality of analysis cannot be appropriately controlled. Therefore, this study presents a system-level sequence tree based PHA, which can clarify the relationship among the major digital I and C systems. This sequence-tree-based technique has two major phases. The first phase adopts a table to analyze each event in SAR Chapter 15 for a specific safety-related I and C system, such as RPS. The second phase adopts a sequence tree to recognize the I and C systems involved in the event, the working of the safety-related systems and how the backup systems can be activated to mitigate the consequence if the primary safety systems fail. The defense-in-depth echelons, namely the Control echelon, Reactor trip echelon, ESFAS echelon and Monitoring and indicator echelon, are arranged to build the sequence-tree structure. All the related I and C systems, including the digital systems and the analog back-up systems, are allocated in their specific echelons. This system-centric sequence-tree analysis not only systematically identifies preliminary hazards, but also vulnerabilities in a nuclear power plant. Hence, an effective simplified D3 evaluation can also be conducted
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Structural and sequence analysis of imelysin-like proteins implicated in bacterial iron uptake.
Directory of Open Access Journals (Sweden)
Qingping Xu
Full Text Available Imelysin-like proteins define a superfamily of bacterial proteins that are likely involved in iron uptake. Members of this superfamily were previously thought to be peptidases and were included in the MEROPS family M75. We determined the first crystal structures of two remotely related, imelysin-like proteins. The Psychrobacter arcticus structure was determined at 2.15 Å resolution and contains the canonical imelysin fold, while higher resolution structures from the gut bacteria Bacteroides ovatus, in two crystal forms (at 1.25 Å and 1.44 Å resolution, have a circularly permuted topology. Both structures are highly similar to each other despite low sequence similarity and circular permutation. The all-helical structure can be divided into two similar four-helix bundle domains. The overall structure and the GxHxxE motif region differ from known HxxE metallopeptidases, suggesting that imelysin-like proteins are not peptidases. A putative functional site is located at the domain interface. We have now organized the known homologous proteins into a superfamily, which can be separated into four families. These families share a similar functional site, but each has family-specific structural and sequence features. These results indicate that imelysin-like proteins have evolved from a common ancestor, and likely have a conserved function.
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Survey of the transcriptome of Aspergillus oryzae via massively parallel mRNA sequencing.
Wang, Bin; Guo, Guangwu; Wang, Chao; Lin, Ying; Wang, Xiaoning; Zhao, Mouming; Guo, Yong; He, Minghui; Zhang, Yong; Pan, Li
2010-08-01
Aspergillus oryzae, an important filamentous fungus used in food fermentation and the enzyme industry, has been shown through genome sequencing and various other tools to have prominent features in its genomic composition. However, the functional complexity of the A. oryzae transcriptome has not yet been fully elucidated. Here, we applied direct high-throughput paired-end RNA-sequencing (RNA-Seq) to the transcriptome of A. oryzae under four different culture conditions. With the high resolution and sensitivity afforded by RNA-Seq, we were able to identify a substantial number of novel transcripts, new exons, untranslated regions, alternative upstream initiation codons and upstream open reading frames, which provide remarkable insight into the A. oryzae transcriptome. We were also able to assess the alternative mRNA isoforms in A. oryzae and found a large number of genes undergoing alternative splicing. Many genes and pathways that might be involved in higher levels of protein production in solid-state culture than in liquid culture were identified by comparing gene expression levels between different cultures. Our analysis indicated that the transcriptome of A. oryzae is much more complex than previously anticipated, and these results may provide a blueprint for further study of the A. oryzae transcriptome.
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Complete genome sequence of Parvibaculum lavamentivorans type strain (DS-1(T)).
Schleheck, David; Weiss, Michael; Pitluck, Sam; Bruce, David; Land, Miriam L; Han, Shunsheng; Saunders, Elizabeth; Tapia, Roxanne; Detter, Chris; Brettin, Thomas; Han, James; Woyke, Tanja; Goodwin, Lynne; Pennacchio, Len; Nolan, Matt; Cook, Alasdair M; Kjelleberg, Staffan; Thomas, Torsten
2011-12-31
Parvibaculum lavamentivorans DS-1(T) is the type species of the novel genus Parvibaculum in the novel family Rhodobiaceae (formerly Phyllobacteriaceae) of the order Rhizobiales of Alphaproteobacteria. Strain DS-1(T) is a non-pigmented, aerobic, heterotrophic bacterium and represents the first tier member of environmentally important bacterial communities that catalyze the complete degradation of synthetic laundry surfactants. Here we describe the features of this organism, together with the complete genome sequence and annotation. The 3,914,745 bp long genome with its predicted 3,654 protein coding genes is the first completed genome sequence of the genus Parvibaculum, and the first genome sequence of a representative of the family Rhodobiaceae.
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Lu, Emily; Elizondo-Riojas, Miguel-Angel; Chang, Jeffrey T; Volk, David E
2014-06-10
Next-generation sequencing results from bead-based aptamer libraries have demonstrated that traditional DNA/RNA alignment software is insufficient. This is particularly true for X-aptamers containing specialty bases (W, X, Y, Z, ...) that are identified by special encoding. Thus, we sought an automated program that uses the inherent design scheme of bead-based X-aptamers to create a hypothetical reference library and Markov modeling techniques to provide improved alignments. Aptaligner provides this feature as well as length error and noise level cutoff features, is parallelized to run on multiple central processing units (cores), and sorts sequences from a single chip into projects and subprojects.
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HIV protein sequence hotspots for crosstalk with host hub proteins.
Directory of Open Access Journals (Sweden)
Mahdi Sarmady
Full Text Available HIV proteins target host hub proteins for transient binding interactions. The presence of viral proteins in the infected cell results in out-competition of host proteins in their interaction with hub proteins, drastically affecting cell physiology. Functional genomics and interactome datasets can be used to quantify the sequence hotspots on the HIV proteome mediating interactions with host hub proteins. In this study, we used the HIV and human interactome databases to identify HIV targeted host hub proteins and their host binding partners (H2. We developed a high throughput computational procedure utilizing motif discovery algorithms on sets of protein sequences, including sequences of HIV and H2 proteins. We identified as HIV sequence hotspots those linear motifs that are highly conserved on HIV sequences and at the same time have a statistically enriched presence on the sequences of H2 proteins. The HIV protein motifs discovered in this study are expressed by subsets of H2 host proteins potentially outcompeted by HIV proteins. A large subset of these motifs is involved in cleavage, nuclear localization, phosphorylation, and transcription factor binding events. Many such motifs are clustered on an HIV sequence in the form of hotspots. The sequential positions of these hotspots are consistent with the curated literature on phenotype altering residue mutations, as well as with existing binding site data. The hotspot map produced in this study is the first global portrayal of HIV motifs involved in altering the host protein network at highly connected hub nodes.
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Thermodynamics-based models of transcriptional regulation with gene sequence.
Wang, Shuqiang; Shen, Yanyan; Hu, Jinxing
2015-12-01
Quantitative models of gene regulatory activity have the potential to improve our mechanistic understanding of transcriptional regulation. However, the few models available today have been based on simplistic assumptions about the sequences being modeled or heuristic approximations of the underlying regulatory mechanisms. In this work, we have developed a thermodynamics-based model to predict gene expression driven by any DNA sequence. The proposed model relies on a continuous time, differential equation description of transcriptional dynamics. The sequence features of the promoter are exploited to derive the binding affinity which is derived based on statistical molecular thermodynamics. Experimental results show that the proposed model can effectively identify the activity levels of transcription factors and the regulatory parameters. Comparing with the previous models, the proposed model can reveal more biological sense.
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Zhang, Shijun; Jing, Zhongliang; Li, Jianxun
2005-01-01
The rotation invariant feature of the target is obtained using the multi-direction feature extraction property of the steerable filter. Combining the morphological operation top-hat transform with the self-organizing feature map neural network, the adaptive topological region is selected. Using the erosion operation, the topological region shrinkage is achieved. The steerable filter based morphological self-organizing feature map neural network is applied to automatic target recognition of binary standard patterns and real-world infrared sequence images. Compared with Hamming network and morphological shared-weight networks respectively, the higher recognition correct rate, robust adaptability, quick training, and better generalization of the proposed method are achieved.
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Emission features in the spectrum of NGC 7027 near 3. 3 microns at very high resolution
Energy Technology Data Exchange (ETDEWEB)
Lowe, R.P.; Moorhead, J.M.; Wehlau, W.H.; Maillard, J.P. (Western Ontario Univ., London (Canada) CNRS, Institut d' Astrophysique, Paris (France))
1991-02-01
A very high resolution spectrum is presented of the planetary nebula NGC 7027 over a 200/cm interval centered at 2950/cm, and the features found are described: (1) nebular continuum, (2) atomic recombination lines of H and He II, and (3) three broader emission features of uncertain origin. For the latter the first evidence is presented that the 3.46 micron feature and possibly the 3.40 micron feature are resolvable into a sequence of narrower features. The interpretation of the broader features is discussed in terms of the hypothesis of identification with emission by polycyclic aromatic hydrocarbons. 18 refs.
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Emission features in the spectrum of NGC 7027 near 3.3 microns at very high resolution
International Nuclear Information System (INIS)
Lowe, R.P.; Moorhead, J.M.; Wehlau, W.H.; Maillard, J.P.
1991-01-01
A very high resolution spectrum is presented of the planetary nebula NGC 7027 over a 200/cm interval centered at 2950/cm, and the features found are described: (1) nebular continuum, (2) atomic recombination lines of H and He II, and (3) three broader emission features of uncertain origin. For the latter the first evidence is presented that the 3.46 micron feature and possibly the 3.40 micron feature are resolvable into a sequence of narrower features. The interpretation of the broader features is discussed in terms of the hypothesis of identification with emission by polycyclic aromatic hydrocarbons. 18 refs
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Shafiee, Mohammad Javad; Chung, Audrey G; Khalvati, Farzad; Haider, Masoom A; Wong, Alexander
2017-10-01
While lung cancer is the second most diagnosed form of cancer in men and women, a sufficiently early diagnosis can be pivotal in patient survival rates. Imaging-based, or radiomics-driven, detection methods have been developed to aid diagnosticians, but largely rely on hand-crafted features that may not fully encapsulate the differences between cancerous and healthy tissue. Recently, the concept of discovery radiomics was introduced, where custom abstract features are discovered from readily available imaging data. We propose an evolutionary deep radiomic sequencer discovery approach based on evolutionary deep intelligence. Motivated by patient privacy concerns and the idea of operational artificial intelligence, the evolutionary deep radiomic sequencer discovery approach organically evolves increasingly more efficient deep radiomic sequencers that produce significantly more compact yet similarly descriptive radiomic sequences over multiple generations. As a result, this framework improves operational efficiency and enables diagnosis to be run locally at the radiologist's computer while maintaining detection accuracy. We evaluated the evolved deep radiomic sequencer (EDRS) discovered via the proposed evolutionary deep radiomic sequencer discovery framework against state-of-the-art radiomics-driven and discovery radiomics methods using clinical lung CT data with pathologically proven diagnostic data from the LIDC-IDRI dataset. The EDRS shows improved sensitivity (93.42%), specificity (82.39%), and diagnostic accuracy (88.78%) relative to previous radiomics approaches.
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Comparison of 61 Sequenced Escherichia coli Genomes
DEFF Research Database (Denmark)
Lukjancenko, Oksana; Wassenaar, T. M.; Ussery, David
2010-01-01
Escherichia coli is an important component of the biosphere and is an ideal model for studies of processes involved in bacterial genome evolution. Sixty-one publically available E. coli and Shigella spp. sequenced genomes are compared, using basic methods to produce phylogenetic and proteomics...
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Fat suppression in MR imaging with binomial pulse sequences
International Nuclear Information System (INIS)
Baudovin, C.J.; Bryant, D.J.; Bydder, G.M.; Young, I.R.
1989-01-01
This paper reports on a study to develop pulse sequences allowing suppression of fat signal on MR images without eliminating signal from other tissues with short T1. They have developed such a technique involving selective excitation of protons in water, based on a binomial pulse sequence. Imaging is performed at 0.15 T. Careful shimming is performed to maximize separation of fat and water peaks. A spin-echo 1,500/80 sequence is used, employing 90 degrees pulse with transit frequency optimized for water with null excitation of 20 H offset, followed by a section-selective 180 degrees pulse. With use of the binomial sequence for imagining, reduction in fat signal is seen on images of the pelvis and legs of volunteers. Patient studies show dramatic improvement in visualization of prostatic carcinoma compared with standard sequences
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Motif discovery in ranked lists of sequences
DEFF Research Database (Denmark)
Nielsen, Morten Muhlig; Tataru, Paula; Madsen, Tobias
2016-01-01
Motif analysis has long been an important method to characterize biological functionality and the current growth of sequencing-based genomics experiments further extends its potential. These diverse experiments often generate sequence lists ranked by some functional property. There is therefore...... advantage of the regular expression feature, including enrichments for combinations of different microRNA seed sites. The method is implemented and made publicly available as an R package and supports high parallelization on multi-core machinery....... a growing need for motif analysis methods that can exploit this coupled data structure and be tailored for specific biological questions. Here, we present an exploratory motif analysis tool, Regmex (REGular expression Motif EXplorer), which offers several methods to evaluate the correlation of motifs...
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Zhao, Kaixi; Margaria, Paolo; Rosa, Cristina
2018-05-10
Impatiens necrotic spot orthotospovirus (INSV) can impact economically important ornamental plants and vegetables worldwide. Characterization studies on INSV are limited. For most INSV isolates, there are no complete genome sequences available. This lack of genomic information has a negative impact on the understanding of the INSV genetic diversity and evolution. Here we report the first complete nucleotide sequence of a US INSV isolate. INSV-UP01 was isolated from an impatiens in Pennsylvania, US. RT-PCR was used to clone its full-length genome and Vector NTI to assemble overlapping sequences. Phylogenetic trees were constructed by using MEGA7 software to show the phylogenetic relationships with other available INSV sequences worldwide. This US isolate has genome and biological features classical of INSV species and clusters in the Western Hemisphere clade, but its origin appears to be recent. Furthermore, INSV-UP01 might have been involved in a recombination event with an Italian isolate belonging to the Asian clade. Our analyses support that INSV isolates infect a broad plant-host range they group by geographic origin and not by host, and are subjected to frequent recombination events. These results justify the need to generate and analyze complete genome sequences of orthotospoviruses in general and INSV in particular.
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Directory of Open Access Journals (Sweden)
Zhongyi Yu
2016-11-01
Full Text Available Blown pack spoilage (BPS is a major issue for the beef industry. Aetiological agents of BPS involve members of a group of Clostridium species, including Clostridium estertheticum which has the ability to produce gas, mostly carbon dioxide, under anaerobic psychotrophic growth conditions. This spore-forming bacterium grows slowly under laboratory conditions, and it can take up to 3 months to produce a workable culture. These characteristics have limited the study of this commercially challenging bacterium. Consequently information on this bacterium is limited and no effective controls are currently available to confidently detect and manage this production risk. In this study the complete genome of Clostridium estertheticum DSM 8809 was determined by SMRT® sequencing. The genome consists of a circular chromosome of 4.7 Mbp along with a single plasmid carrying a potential tellurite resistance gene tehB and a Tn3-like resolvase-encoding gene tnpR. The genome sequence was searched for central metabolic pathways that would support its biochemical profile and several enzymes contributing to this phenotype were identified. Several putative antibiotic/biocide/metal resistance-encoding genes and virulence factors were also identified in the genome, a feature that requires further research. The availability of the genome sequence will provide a basic blueprint from which to develop valuable biomarkers that could support and improve the detection and control of this bacterium along the beef production chain.
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MIPS: a database for protein sequences and complete genomes.
Mewes, H W; Hani, J; Pfeiffer, F; Frishman, D
1998-01-01
The MIPS group [Munich Information Center for Protein Sequences of the German National Center for Environment and Health (GSF)] at the Max-Planck-Institute for Biochemistry, Martinsried near Munich, Germany, is involved in a number of data collection activities, including a comprehensive database of the yeast genome, a database reflecting the progress in sequencing the Arabidopsis thaliana genome, the systematic analysis of other small genomes and the collection of protein sequence data within the framework of the PIR-International Protein Sequence Database (described elsewhere in this volume). Through its WWW server (http://www.mips.biochem.mpg.de ) MIPS provides access to a variety of generic databases, including a database of protein families as well as automatically generated data by the systematic application of sequence analysis algorithms. The yeast genome sequence and its related information was also compiled on CD-ROM to provide dynamic interactive access to the 16 chromosomes of the first eukaryotic genome unraveled. PMID:9399795
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Second generation sequencing of the mesothelioma tumor genome.
Directory of Open Access Journals (Sweden)
Raphael Bueno
2010-05-01
Full Text Available The current paradigm for elucidating the molecular etiology of cancers relies on the interrogation of small numbers of genes, which limits the scope of investigation. Emerging second-generation massively parallel DNA sequencing technologies have enabled more precise definition of the cancer genome on a global scale. We examined the genome of a human primary malignant pleural mesothelioma (MPM tumor and matched normal tissue by using a combination of sequencing-by-synthesis and pyrosequencing methodologies to a 9.6X depth of coverage. Read density analysis uncovered significant aneuploidy and numerous rearrangements. Method-dependent informatics rules, which combined the results of different sequencing platforms, were developed to identify and validate candidate mutations of multiple types. Many more tumor-specific rearrangements than point mutations were uncovered at this depth of sequencing, resulting in novel, large-scale, inter- and intra-chromosomal deletions, inversions, and translocations. Nearly all candidate point mutations appeared to be previously unknown SNPs. Thirty tumor-specific fusions/translocations were independently validated with PCR and Sanger sequencing. Of these, 15 represented disrupted gene-encoding regions, including kinases, transcription factors, and growth factors. One large deletion in DPP10 resulted in altered transcription and expression of DPP10 transcripts in a set of 53 additional MPM tumors correlated with survival. Additionally, three point mutations were observed in the coding regions of NKX6-2, a transcription regulator, and NFRKB, a DNA-binding protein involved in modulating NFKB1. Several regions containing genes such as PCBD2 and DHFR, which are involved in growth factor signaling and nucleotide synthesis, respectively, were selectively amplified in the tumor. Second-generation sequencing uncovered all types of mutations in this MPM tumor, with DNA rearrangements representing the dominant type.
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Evaluation of a target region capture sequencing platform using monogenic diabetes as a study-model
DEFF Research Database (Denmark)
Gao, Rui; Liu, Yanxia; Gjesing, Anette Marianne Prior
2014-01-01
Monogenic diabetes is a genetic disease often caused by mutations in genes involved in beta-cell function. Correct sub-categorization of the disease is a prerequisite for appropriate treatment and genetic counseling. Target-region capture sequencing is a combination of genomic region enrichment...... and next generation sequencing which might be used as an efficient way to diagnose various genetic disorders. We aimed to develop a target-region capture sequencing platform to screen 117 selected candidate genes involved in metabolism for mutations and to evaluate its performance using monogenic diabetes...
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Long-read sequencing data analysis for yeasts.
Yue, Jia-Xing; Liti, Gianni
2018-06-01
Long-read sequencing technologies have become increasingly popular due to their strengths in resolving complex genomic regions. As a leading model organism with small genome size and great biotechnological importance, the budding yeast Saccharomyces cerevisiae has many isolates currently being sequenced with long reads. However, analyzing long-read sequencing data to produce high-quality genome assembly and annotation remains challenging. Here, we present a modular computational framework named long-read sequencing data analysis for yeasts (LRSDAY), the first one-stop solution that streamlines this process. Starting from the raw sequencing reads, LRSDAY can produce chromosome-level genome assembly and comprehensive genome annotation in a highly automated manner with minimal manual intervention, which is not possible using any alternative tool available to date. The annotated genomic features include centromeres, protein-coding genes, tRNAs, transposable elements (TEs), and telomere-associated elements. Although tailored for S. cerevisiae, we designed LRSDAY to be highly modular and customizable, making it adaptable to virtually any eukaryotic organism. When applying LRSDAY to an S. cerevisiae strain, it takes ∼41 h to generate a complete and well-annotated genome from ∼100× Pacific Biosciences (PacBio) running the basic workflow with four threads. Basic experience working within the Linux command-line environment is recommended for carrying out the analysis using LRSDAY.
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Caudate nucleus reactivity predicts perceptual learning rate for visual feature conjunctions.
Reavis, Eric A; Frank, Sebastian M; Tse, Peter U
2015-04-15
Useful information in the visual environment is often contained in specific conjunctions of visual features (e.g., color and shape). The ability to quickly and accurately process such conjunctions can be learned. However, the neural mechanisms responsible for such learning remain largely unknown. It has been suggested that some forms of visual learning might involve the dopaminergic neuromodulatory system (Roelfsema et al., 2010; Seitz and Watanabe, 2005), but this hypothesis has not yet been directly tested. Here we test the hypothesis that learning visual feature conjunctions involves the dopaminergic system, using functional neuroimaging, genetic assays, and behavioral testing techniques. We use a correlative approach to evaluate potential associations between individual differences in visual feature conjunction learning rate and individual differences in dopaminergic function as indexed by neuroimaging and genetic markers. We find a significant correlation between activity in the caudate nucleus (a component of the dopaminergic system connected to visual areas of the brain) and visual feature conjunction learning rate. Specifically, individuals who showed a larger difference in activity between positive and negative feedback on an unrelated cognitive task, indicative of a more reactive dopaminergic system, learned visual feature conjunctions more quickly than those who showed a smaller activity difference. This finding supports the hypothesis that the dopaminergic system is involved in visual learning, and suggests that visual feature conjunction learning could be closely related to associative learning. However, no significant, reliable correlations were found between feature conjunction learning and genotype or dopaminergic activity in any other regions of interest. Copyright © 2015 Elsevier Inc. All rights reserved.
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HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features.
Zaman, Rianon; Chowdhury, Shahana Yasmin; Rashid, Mahmood A; Sharma, Alok; Dehzangi, Abdollah; Shatabda, Swakkhar
2017-01-01
DNA-binding proteins often play important role in various processes within the cell. Over the last decade, a wide range of classification algorithms and feature extraction techniques have been used to solve this problem. In this paper, we propose a novel DNA-binding protein prediction method called HMMBinder. HMMBinder uses monogram and bigram features extracted from the HMM profiles of the protein sequences. To the best of our knowledge, this is the first application of HMM profile based features for the DNA-binding protein prediction problem. We applied Support Vector Machines (SVM) as a classification technique in HMMBinder. Our method was tested on standard benchmark datasets. We experimentally show that our method outperforms the state-of-the-art methods found in the literature.
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HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features
Directory of Open Access Journals (Sweden)
Rianon Zaman
2017-01-01
Full Text Available DNA-binding proteins often play important role in various processes within the cell. Over the last decade, a wide range of classification algorithms and feature extraction techniques have been used to solve this problem. In this paper, we propose a novel DNA-binding protein prediction method called HMMBinder. HMMBinder uses monogram and bigram features extracted from the HMM profiles of the protein sequences. To the best of our knowledge, this is the first application of HMM profile based features for the DNA-binding protein prediction problem. We applied Support Vector Machines (SVM as a classification technique in HMMBinder. Our method was tested on standard benchmark datasets. We experimentally show that our method outperforms the state-of-the-art methods found in the literature.
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Do Carmo, A P; da Silva, D F; De Oliveira, M N V; Borges, A C; De Carvalho, A F; De Moraes, C A
2011-09-01
A basic requirement for the prediction of the potential use of lactic acid bacteria (LAB) in the dairy industry is the identification of specific genes involved in flavour-forming pathways. The probiotic Lactobacillus delbrueckii UFV H2b20 was submitted to a genetic characterisation and phylogenetic analysis of genes involved in protein catabolism. Eight genes belonging to this system were identified, which possess a closely phylogenetic relationship to NCFM strains representative, as it was demonstrated for oppC and oppBII, encoding oligopeptide transport system components. PepC, PepN, and PepX might be essential for growth of LAB, probiotic or not, since the correspondent genes are always present, including in L. delbrueckii UFV H2b20 genome. For pepX gene, a probable link between carbohydrate catabolism and PepX expression may exists, where it is regulated by PepR1/CcpA-like, a common feature between Lactobacillus strains and also in L. delbrueckii UFV H2b20. The well conserved evolutionary history of the ilvE gene is evidence that the pathways leading to branched-chain amino acid degradation, such as isoleucine and valine, are similar among L. delbrueckii subsp. bulgaricus strains and L. delbrueckii UFV H2b20. Thus, the involvement of succinate in flavour formation can be attributed to IlvE activity. The presence of aminopeptidase G in L. delbrueckii UFV H2b20 genome, which is absent in several strains, might improve the proteolytic activity and effectiveness. The nucleotide sequence encoding PepG revealed that it is a cysteine endopeptidase, belonging to Peptidase C1 superfamily; sequence analysis showed 99% identity with L. delbrueckii subsp. bulgaricus ATCC 11842 pepG, whereas protein sequence analysis revealed 100% similarity with PepG from the same organism. The present study proposes a schematic model to explain how the proteolytic system of the probiotic L. delbrueckii UFV H2b20 works, based on the components identified so far.
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Student Involvement in Learning and School Achievement.
Anderson, Lorin W.
The purpose of the study was to investigate the relationship between selected student characteristics, student involvement in learning, and achievement. Both naturalistic (n = 28, 27) and experimental studies were conducted. In the experimental study, two classes (n = 29, 26) learned a sequence of matrix arithmetic by mastery learning strategies.…
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A Case Study into Microbial Genome Assembly Gap Sequences and Finishing Strategies.
Utturkar, Sagar M; Klingeman, Dawn M; Hurt, Richard A; Brown, Steven D
2017-01-01
This study characterized regions of DNA which remained unassembled by either PacBio and Illumina sequencing technologies for seven bacterial genomes. Two genomes were manually finished using bioinformatics and PCR/Sanger sequencing approaches and regions not assembled by automated software were analyzed. Gaps present within Illumina assemblies mostly correspond to repetitive DNA regions such as multiple rRNA operon sequences. PacBio gap sequences were evaluated for several properties such as GC content, read coverage, gap length, ability to form strong secondary structures, and corresponding annotations. Our hypothesis that strong secondary DNA structures blocked DNA polymerases and contributed to gap sequences was not accepted. PacBio assemblies had few limitations overall and gaps were explained as cumulative effect of lower than average sequence coverage and repetitive sequences at contig termini. An important aspect of the present study is the compilation of biological features that interfered with assembly and included active transposons, multiple plasmid sequences, phage DNA integration, and large sequence duplication. Our targeted genome finishing approach and systematic evaluation of the unassembled DNA will be useful for others looking to close, finish, and polish microbial genome sequences.
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Outflow of chromospheric emission features from the rim of a sunspot
Liu, S.-Y.
1973-01-01
In viewing a 16 mm movie made from a time sequence of spectroheliograms, some of these emission features are found to move outward from the rim of the sunspot until they are eventually lost in the small plage. There are two interpretations for the streaming of the magnetic features. It is possible that kinks in the line of force propagate along a horizontal extension of the penumbral magnetic field. Alternatively, fragments of the sunspot magnetic field are carried away by the photospheric velocity field.
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Facial expression recognition in the wild based on multimodal texture features
Sun, Bo; Li, Liandong; Zhou, Guoyan; He, Jun
2016-11-01
Facial expression recognition in the wild is a very challenging task. We describe our work in static and continuous facial expression recognition in the wild. We evaluate the recognition results of gray deep features and color deep features, and explore the fusion of multimodal texture features. For the continuous facial expression recognition, we design two temporal-spatial dense scale-invariant feature transform (SIFT) features and combine multimodal features to recognize expression from image sequences. For the static facial expression recognition based on video frames, we extract dense SIFT and some deep convolutional neural network (CNN) features, including our proposed CNN architecture. We train linear support vector machine and partial least squares classifiers for those kinds of features on the static facial expression in the wild (SFEW) and acted facial expression in the wild (AFEW) dataset, and we propose a fusion network to combine all the extracted features at decision level. The final achievement we gained is 56.32% on the SFEW testing set and 50.67% on the AFEW validation set, which are much better than the baseline recognition rates of 35.96% and 36.08%.
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Huckabee, Maggie-Lee; Lamvik, Kristin; Jones, Richard
2014-08-15
Clinical data are submitted as documentation of a pathophysiologic feature of dysphagia termed pharyngeal mis-sequencing and to encourage clinicians and researchers to adopt more critical approaches to diagnosis and treatment planning. Recent clinical experience has identified a cohort of patients who present with an atypical dysphagia not specifically described in the literature: mis-sequenced constriction of the pharynx when swallowing. As a result, they are unable to coordinate streamlined bolus transfer from the pharynx into the esophagus. This mis-sequencing contributes to nasal redirection, aspiration, and, for some, the inability to safely tolerate an oral diet. Sixteen patients (8 females, 8 males), with a mean age of 44 years (range=25-78), had an average time post-onset of 23 months (range=2-72) at initiation of intensive rehabilitation. A 3-channel manometric catheter was used to measure pharyngeal pressure. The average peak-to-peak latency between nadir pressures at sensor-1 and sensor-2 was 15 ms (95% CI, -2 to 33 ms), compared to normative mean latency of 239 ms (95% CI, 215 to 263 ms). Rehabilitative responses are summarized, along with a single detailed case report. It is unclear from these data if pharyngeal mis-sequencing is (i) a pathological feature of impaired motor planning from brainstem damage or (ii) a maladaptive compensation developed in response to chronic dysphagia. Future investigation is needed to provide a full report of pharyngeal mis-sequencing, and the implications on our understanding of underlying neural control of swallowing. Copyright © 2014 Elsevier B.V. All rights reserved.
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Nucleation phenomena in protein folding: the modulating role of protein sequence
International Nuclear Information System (INIS)
Travasso, Rui D M; FaIsca, Patricia F N; Gama, Margarida M Telo da
2007-01-01
For the vast majority of naturally occurring, small, single-domain proteins, folding is often described as a two-state process that lacks detectable intermediates. This observation has often been rationalized on the basis of a nucleation mechanism for protein folding whose basic premise is the idea that, after completion of a specific set of contacts forming the so-called folding nucleus, the native state is achieved promptly. Here we propose a methodology to identify folding nuclei in small lattice polymers and apply it to the study of protein molecules with a chain length of N = 48. To investigate the extent to which protein topology is a robust determinant of the nucleation mechanism, we compare the nucleation scenario of a native-centric model with that of a sequence-specific model sharing the same native fold. To evaluate the impact of the sequence's finer details in the nucleation mechanism, we consider the folding of two non-homologous sequences. We conclude that, in a sequence-specific model, the folding nucleus is, to some extent, formed by the most stable contacts in the protein and that the less stable linkages in the folding nucleus are solely determined by the fold's topology. We have also found that, independently of the protein sequence, the folding nucleus performs the same 'topological' function. This unifying feature of the nucleation mechanism results from the residues forming the folding nucleus being distributed along the protein chain in a similar and well-defined manner that is determined by the fold's topological features
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Chan, Chon-Kit Kenneth; Hsu, Arthur L.; Tang, Sen-Lin; Halgamuge, Saman K.
2008-01-01
Metagenomic projects using whole-genome shotgun (WGS) sequencing produces many unassembled DNA sequences and small contigs. The step of clustering these sequences, based on biological and molecular features, is called binning. A reported strategy for binning that combines oligonucleotide frequency and self-organising maps (SOM) shows high potential. We improve this strategy by identifying suitable training features, implementing a better clustering algorithm, and defining quantitative measures for assessing results. We investigated the suitability of each of di-, tri-, tetra-, and pentanucleotide frequencies. The results show that dinucleotide frequency is not a sufficiently strong signature for binning 10 kb long DNA sequences, compared to the other three. Furthermore, we observed that increased order of oligonucleotide frequency may deteriorate the assignment result in some cases, which indicates the possible existence of optimal species-specific oligonucleotide frequency. We replaced SOM with growing self-organising map (GSOM) where comparable results are obtained while gaining 7%–15% speed improvement. PMID:18288261
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Medulloblastoma with Excessive Nodularity: Radiographic Features and Pathologic Correlate
Directory of Open Access Journals (Sweden)
L. A. Yeh-Nayre
2012-01-01
Full Text Available Medulloblastoma with extensive nodularity is a rare subtype of the most common malignant childhood brain tumor and has been associated with more favorable prognosis. The authors report the case of a 10-month-old girl with a posterior fossa tumor of excessive nodularity with decreased diffusivity on diffusion-weighted magnetic resonance imaging sequences and robust grape-like postgadolinium contrast enhancing features. The unique neuroradiographic features were confirmed by histopathology and a diagnosis of medulloblastoma with extensive nodularity was made. This case highlights the importance of recognizing this unique medulloblastoma subtype preoperatively, as the more favorable outcome may preclude less aggressive medical management.
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Directory of Open Access Journals (Sweden)
D. A. Starunskaya
2017-01-01
Full Text Available Importance. The study of psychological characteristics of patients is important for the creation and planning of psychological correction and improve the efficiency of the treatment of coronary heart disease.Тhe purpose. This research is devoted to the study of the psychological features in patients with coronary artery disease (CHD in the preoperative period, depending on their involvement in psycho-correction program.Material and methods. We observed 30 patients with coronary heart disease before coronary bypass surgery. Clinical-psychological method (observation, conversation and psychological testing were used.Results and conclusions. We found that patients who participated in psycho-correction program had lower values of «anxiety», «phobic anxiety» and «obsessive-compulsive» symptoms. In both groups of patients, on average, we identified the prevalence of the coping-strategies «self-control» and «planning solution». Furthermore, on average, the «self-awareness» and «extraversion» were more manifested features in the structure of the personality traits of the surveyed patients. The revealed features should be taken into account in planning the programs of psycho-correction for patients with CHD prior to CABG surgery.
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From Sequence and Forces to Structure, Function and Evolution of Intrinsically Disordered Proteins
Forman-Kay, Julie D.; Mittag, Tanja
2015-01-01
Intrinsically disordered proteins (IDPs), which lack persistent structure, are a challenge to structural biology due to the inapplicability of standard methods for characterization of folded proteins as well as their deviation from the dominant structure/function paradigm. Their widespread presence and involvement in biological function, however, has spurred the growing acceptance of the importance of IDPs and the development of new tools for studying their structure, dynamics and function. The interplay of folded and disordered domains or regions for function and the existence of a continuum of protein states with respect to conformational energetics, motional timescales and compactness is shaping a unified understanding of structure-dynamics-disorder/function relationships. On the 20th anniversary of this journal, Structure, we provide a historical perspective on the investigation of IDPs and summarize the sequence features and physical forces that underlie their unique structural, functional and evolutionary properties. PMID:24010708
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ASAP: Amplification, sequencing & annotation of plastomes
Directory of Open Access Journals (Sweden)
Folta Kevin M
2005-12-01
Full Text Available Abstract Background Availability of DNA sequence information is vital for pursuing structural, functional and comparative genomics studies in plastids. Traditionally, the first step in mining the valuable information within a chloroplast genome requires sequencing a chloroplast plasmid library or BAC clones. These activities involve complicated preparatory procedures like chloroplast DNA isolation or identification of the appropriate BAC clones to be sequenced. Rolling circle amplification (RCA is being used currently to amplify the chloroplast genome from purified chloroplast DNA and the resulting products are sheared and cloned prior to sequencing. Herein we present a universal high-throughput, rapid PCR-based technique to amplify, sequence and assemble plastid genome sequence from diverse species in a short time and at reasonable cost from total plant DNA, using the large inverted repeat region from strawberry and peach as proof of concept. The method exploits the highly conserved coding regions or intergenic regions of plastid genes. Using an informatics approach, chloroplast DNA sequence information from 5 available eudicot plastomes was aligned to identify the most conserved regions. Cognate primer pairs were then designed to generate ~1 – 1.2 kb overlapping amplicons from the inverted repeat region in 14 diverse genera. Results 100% coverage of the inverted repeat region was obtained from Arabidopsis, tobacco, orange, strawberry, peach, lettuce, tomato and Amaranthus. Over 80% coverage was obtained from distant species, including Ginkgo, loblolly pine and Equisetum. Sequence from the inverted repeat region of strawberry and peach plastome was obtained, annotated and analyzed. Additionally, a polymorphic region identified from gel electrophoresis was sequenced from tomato and Amaranthus. Sequence analysis revealed large deletions in these species relative to tobacco plastome thus exhibiting the utility of this method for structural and
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ASAP: an environment for automated preprocessing of sequencing data
Directory of Open Access Journals (Sweden)
Torstenson Eric S
2013-01-01
Full Text Available Abstract Background Next-generation sequencing (NGS has yielded an unprecedented amount of data for genetics research. It is a daunting task to process the data from raw sequence reads to variant calls and manually processing this data can significantly delay downstream analysis and increase the possibility for human error. The research community has produced tools to properly prepare sequence data for analysis and established guidelines on how to apply those tools to achieve the best results, however, existing pipeline programs to automate the process through its entirety are either inaccessible to investigators, or web-based and require a certain amount of administrative expertise to set up. Findings Advanced Sequence Automated Pipeline (ASAP was developed to provide a framework for automating the translation of sequencing data into annotated variant calls with the goal of minimizing user involvement without the need for dedicated hardware or administrative rights. ASAP works both on computer clusters and on standalone machines with minimal human involvement and maintains high data integrity, while allowing complete control over the configuration of its component programs. It offers an easy-to-use interface for submitting and tracking jobs as well as resuming failed jobs. It also provides tools for quality checking and for dividing jobs into pieces for maximum throughput. Conclusions ASAP provides an environment for building an automated pipeline for NGS data preprocessing. This environment is flexible for use and future development. It is freely available at http://biostat.mc.vanderbilt.edu/ASAP.
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ASAP: an environment for automated preprocessing of sequencing data.
Torstenson, Eric S; Li, Bingshan; Li, Chun
2013-01-04
Next-generation sequencing (NGS) has yielded an unprecedented amount of data for genetics research. It is a daunting task to process the data from raw sequence reads to variant calls and manually processing this data can significantly delay downstream analysis and increase the possibility for human error. The research community has produced tools to properly prepare sequence data for analysis and established guidelines on how to apply those tools to achieve the best results, however, existing pipeline programs to automate the process through its entirety are either inaccessible to investigators, or web-based and require a certain amount of administrative expertise to set up. Advanced Sequence Automated Pipeline (ASAP) was developed to provide a framework for automating the translation of sequencing data into annotated variant calls with the goal of minimizing user involvement without the need for dedicated hardware or administrative rights. ASAP works both on computer clusters and on standalone machines with minimal human involvement and maintains high data integrity, while allowing complete control over the configuration of its component programs. It offers an easy-to-use interface for submitting and tracking jobs as well as resuming failed jobs. It also provides tools for quality checking and for dividing jobs into pieces for maximum throughput. ASAP provides an environment for building an automated pipeline for NGS data preprocessing. This environment is flexible for use and future development. It is freely available at http://biostat.mc.vanderbilt.edu/ASAP.
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ASAP: an environment for automated preprocessing of sequencing data
2013-01-01
Background Next-generation sequencing (NGS) has yielded an unprecedented amount of data for genetics research. It is a daunting task to process the data from raw sequence reads to variant calls and manually processing this data can significantly delay downstream analysis and increase the possibility for human error. The research community has produced tools to properly prepare sequence data for analysis and established guidelines on how to apply those tools to achieve the best results, however, existing pipeline programs to automate the process through its entirety are either inaccessible to investigators, or web-based and require a certain amount of administrative expertise to set up. Findings Advanced Sequence Automated Pipeline (ASAP) was developed to provide a framework for automating the translation of sequencing data into annotated variant calls with the goal of minimizing user involvement without the need for dedicated hardware or administrative rights. ASAP works both on computer clusters and on standalone machines with minimal human involvement and maintains high data integrity, while allowing complete control over the configuration of its component programs. It offers an easy-to-use interface for submitting and tracking jobs as well as resuming failed jobs. It also provides tools for quality checking and for dividing jobs into pieces for maximum throughput. Conclusions ASAP provides an environment for building an automated pipeline for NGS data preprocessing. This environment is flexible for use and future development. It is freely available at http://biostat.mc.vanderbilt.edu/ASAP. PMID:23289815
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Behind every innovative solution lies an obscure feature
Directory of Open Access Journals (Sweden)
Lee Spector (Fellow ISGEC
2012-06-01
Full Text Available The Obscure Features Hypothesis (OFH for innovation states that a two-step process undergirds almost all innovative solutions: (1 notice an infrequently observed or new (i.e., obscure feature of the problem and (2 construct an interaction involving the obscure feature that produces the desired effects to solve the problem. The OFH leads to a systematic derivation of innovation-enhancing techniques by engaging in two tasks. First, we developed a 32-category system of the types of features possessable by a physical object or material. This Feature Type Taxonomy (FTT provides a panoramic view of the space of features and assists in searches for the obscure ones. Second, we are articulating the many cognitive reasons that obscure features are overlooked and are developing countering techniques for each known reason. We present the implications and techniques of the OFH, as well as indicate how software can assist innovators in the effective use of these innovation-enhancing techniques.
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Sequence features of E. coli mRNAs affect their degradation.
Directory of Open Access Journals (Sweden)
Gal Lenz
Full Text Available Degradation of mRNA in bacteria is a regulatory mechanism, providing an efficient way to fine-tune protein abundance in response to environmental changes. While the mechanisms responsible for initiation and subsequent propagation of mRNA degradation are well studied, the mRNA features that affect its stability are yet to be elucidated. We calculated three properties for each mRNA in the E. coli transcriptome: G+C content, tRNA adaptation index (tAI and folding energy. Each of these properties were then correlated with the experimental transcript half life measured for each transcript and detected significant correlations. A sliding window analysis identified the regions that displayed the maximal signal. The correlation between transcript half life and both G+C content and folding energy was strongest at the 5' termini of the mRNAs. Partial correlations showed that each of the parameters contributes separately to mRNA half life. Notably, mRNAs of recently-acquired genes in the E. coli genome, which have a distinct nucleotide composition, tend to be highly stable. This high stability may aid the evolutionary fixation of horizontally acquired genes.
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Determination of feature generation methods for PTZ camera object tracking
Doyle, Daniel D.; Black, Jonathan T.
2012-06-01
Object detection and tracking using computer vision (CV) techniques have been widely applied to sensor fusion applications. Many papers continue to be written that speed up performance and increase learning of artificially intelligent systems through improved algorithms, workload distribution, and information fusion. Military application of real-time tracking systems is becoming more and more complex with an ever increasing need of fusion and CV techniques to actively track and control dynamic systems. Examples include the use of metrology systems for tracking and measuring micro air vehicles (MAVs) and autonomous navigation systems for controlling MAVs. This paper seeks to contribute to the determination of select tracking algorithms that best track a moving object using a pan/tilt/zoom (PTZ) camera applicable to both of the examples presented. The select feature generation algorithms compared in this paper are the trained Scale-Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF), the Mixture of Gaussians (MoG) background subtraction method, the Lucas- Kanade optical flow method (2000) and the Farneback optical flow method (2003). The matching algorithm used in this paper for the trained feature generation algorithms is the Fast Library for Approximate Nearest Neighbors (FLANN). The BSD licensed OpenCV library is used extensively to demonstrate the viability of each algorithm and its performance. Initial testing is performed on a sequence of images using a stationary camera. Further testing is performed on a sequence of images such that the PTZ camera is moving in order to capture the moving object. Comparisons are made based upon accuracy, speed and memory.
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An EM based approach for motion segmentation of video sequence
Zhao, Wei; Roos, Nico; Pan, Zhigeng; Skala, Vaclav
2016-01-01
Motions are important features for robot vision as we live in a dynamic world. Detecting moving objects is crucial for mobile robots and computer vision systems. This paper investigates an architecture for the segmentation of moving objects from image sequences. Objects are represented as groups of
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Liu, Shu-Bin; Liu, Yao-Sheng; Li, Ding-Feng; Fan, Hai-Tao; Huai, Jian-Ye; Guo, Jun; Wang, Lei; Liu, Cheng; Zhang, Ping; Cui, Qiu; Jiang, Wei-Hao; Cao, Yun-Cen; Jiang, Ning; Sui, Jia-Hong; Zhang, Bin; Zhou, Jiu
2010-06-15
To explore the relationship of motor deficits of the lower extremities with the imaging features of malignant spinal cord compression (MESCCs). From July 2006 through December 2008, 56 successive MESCC patients were treated at our department. All were evaluated by magnetic resonance imaging and computed tomography and were scored according to motor deficits Frankel grading on admission. Imaging assessment factors of main involved vertebrae were level of vertebral metastatic location, epidural space involvement, vertebral body involvement, lamina involvement, posterior protrusion of posterior wall, pedicle involvement, continuity of main involved vertebrae, fracture of anterior column, fracture of posterior wall, location in upper thoracic spine and/or cervicothoracic junction. Occurrence was the same between paralytic state of MESCCs and epidural space involvement of imaging features. Multiple regression equation showed that paralytic state had a linear regression relationship with imaging factors of lamina involvement (X1), posterior protrusion of posterior wall (X2), location in upper thoracic spine and/or cervicothoracic junction (X7) of main involved vertebrae. The optimal regression equation of paralytic state (Y) and imaging feature (X) was Y = -0.009 +0.639X, + 0.149X, +0.282X. Lamina involvement of main involved vertebrae has a greatest influence upon paralytic state of MESCC patients. Imaging factors of lamina involvement, posterior protrusion of posterior wall, location in upper thoracic spine and/or cervicothoracic junction of main involved vertebrae can predict the paralytic state of MESCC patients. MESCC with lamina involvement is more easily encroached on epidural space.
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Learning multiple variable-speed sequences in striatum via cortical tutoring.
Murray, James M; Escola, G Sean
2017-05-08
Sparse, sequential patterns of neural activity have been observed in numerous brain areas during timekeeping and motor sequence tasks. Inspired by such observations, we construct a model of the striatum, an all-inhibitory circuit where sequential activity patterns are prominent, addressing the following key challenges: (i) obtaining control over temporal rescaling of the sequence speed, with the ability to generalize to new speeds; (ii) facilitating flexible expression of distinct sequences via selective activation, concatenation, and recycling of specific subsequences; and (iii) enabling the biologically plausible learning of sequences, consistent with the decoupling of learning and execution suggested by lesion studies showing that cortical circuits are necessary for learning, but that subcortical circuits are sufficient to drive learned behaviors. The same mechanisms that we describe can also be applied to circuits with both excitatory and inhibitory populations, and hence may underlie general features of sequential neural activity pattern generation in the brain.
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Clarke, Wayne E.; Parkin, Isobel A.; Gajardo, Humberto A.; Gerhardt, Daniel J.; Higgins, Erin; Sidebottom, Christine; Sharpe, Andrew G.; Snowdon, Rod J.; Federico, Maria L.; Iniguez-Luy, Federico L.
2013-01-01
Targeted genomic selection methodologies, or sequence capture, allow for DNA enrichment and large-scale resequencing and characterization of natural genetic variation in species with complex genomes, such as rapeseed canola (Brassica napus L., AACC, 2n=38). The main goal of this project was to combine sequence capture with next generation sequencing (NGS) to discover single nucleotide polymorphisms (SNPs) in specific areas of the B. napus genome historically associated (via quantitative trait loci –QTL– analysis) to traits of agronomical and nutritional importance. A 2.1 million feature sequence capture platform was designed to interrogate DNA sequence variation across 47 specific genomic regions, representing 51.2 Mb of the Brassica A and C genomes, in ten diverse rapeseed genotypes. All ten genotypes were sequenced using the 454 Life Sciences chemistry and to assess the effect of increased sequence depth, two genotypes were also sequenced using Illumina HiSeq chemistry. As a result, 589,367 potentially useful SNPs were identified. Analysis of sequence coverage indicated a four-fold increased representation of target regions, with 57% of the filtered SNPs falling within these regions. Sixty percent of discovered SNPs corresponded to transitions while 40% were transversions. Interestingly, fifty eight percent of the SNPs were found in genic regions while 42% were found in intergenic regions. Further, a high percentage of genic SNPs was found in exons (65% and 64% for the A and C genomes, respectively). Two different genotyping assays were used to validate the discovered SNPs. Validation rates ranged from 61.5% to 84% of tested SNPs, underpinning the effectiveness of this SNP discovery approach. Most importantly, the discovered SNPs were associated with agronomically important regions of the B. napus genome generating a novel data resource for research and breeding this crop species. PMID:24312619
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Robust Image Hashing Using Radon Transform and Invariant Features
Directory of Open Access Journals (Sweden)
Y.L. Liu
2016-09-01
Full Text Available A robust image hashing method based on radon transform and invariant features is proposed for image authentication, image retrieval, and image detection. Specifically, an input image is firstly converted into a counterpart with a normalized size. Then the invariant centroid algorithm is applied to obtain the invariant feature point and the surrounding circular area, and the radon transform is employed to acquire the mapping coefficient matrix of the area. Finally, the hashing sequence is generated by combining the feature vectors and the invariant moments calculated from the coefficient matrix. Experimental results show that this method not only can resist against the normal image processing operations, but also some geometric distortions. Comparisons of receiver operating characteristic (ROC curve indicate that the proposed method outperforms some existing methods in classification between perceptual robustness and discrimination.
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Adaptive Colour Feature Identification in Image for Object Tracking
Directory of Open Access Journals (Sweden)
Feng Su
2012-01-01
Full Text Available Identification and tracking of a moving object using computer vision techniques is important in robotic surveillance. In this paper, an adaptive colour filtering method is introduced for identifying and tracking a moving object appearing in image sequences. This filter is capable of automatically identifying the most salient colour feature of the moving object in the image and using this for a robot to track the object. The method enables the selected colour feature to adapt to surrounding condition when it is changed. A method of determining the region of interest of the moving target is also developed for the adaptive colour filter to extract colour information. Experimental results show that by using a camera mounted on a robot, the proposed methods can perform robustly in tracking a randomly moving object using adaptively selected colour features in a crowded environment.
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Demonstration of IGCC features - plant integration and syngas combustion
Energy Technology Data Exchange (ETDEWEB)
Hannemann, F.; Huth, M.; Karg, J.; Schiffers, U. [Siemens AG Power Generation (KWU), Erlanger/Muelheim (Germany)
2000-07-01
Siemens is involved in three IGCC plants in Europe that are currently in operation. Against the background of the Puertollano and Buggenum plants, some of the specific new features of fully integrated IGCC power plants are discussed, including: requirements and design features of the gas turbine syngas supply system; gas turbine operating experience with air extraction for the air separation unit from the gas turbine air compressor; and design requirements and operational features of the combustion system. 7 refs., 17 figs., 1 tab.
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Sequence-dependent DNA deformability studied using molecular dynamics simulations.
Fujii, Satoshi; Kono, Hidetoshi; Takenaka, Shigeori; Go, Nobuhiro; Sarai, Akinori
2007-01-01
Proteins recognize specific DNA sequences not only through direct contact between amino acids and bases, but also indirectly based on the sequence-dependent conformation and deformability of the DNA (indirect readout). We used molecular dynamics simulations to analyze the sequence-dependent DNA conformations of all 136 possible tetrameric sequences sandwiched between CGCG sequences. The deformability of dimeric steps obtained by the simulations is consistent with that by the crystal structures. The simulation results further showed that the conformation and deformability of the tetramers can highly depend on the flanking base pairs. The conformations of xATx tetramers show the most rigidity and are not affected by the flanking base pairs and the xYRx show by contrast the greatest flexibility and change their conformations depending on the base pairs at both ends, suggesting tetramers with the same central dimer can show different deformabilities. These results suggest that analysis of dimeric steps alone may overlook some conformational features of DNA and provide insight into the mechanism of indirect readout during protein-DNA recognition. Moreover, the sequence dependence of DNA conformation and deformability may be used to estimate the contribution of indirect readout to the specificity of protein-DNA recognition as well as nucleosome positioning and large-scale behavior of nucleic acids.
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Tourette Syndrome and Associated Features and the School Aged Child.
Willis, Christopher
Tourette Syndrome (TS) is described as a genetically based, chronic constellation of neurobehavioral symptoms and associated features involving repetitive, simple, and/or complex motor and phonic tics. Treatment generally involves neuroleptic medication. Symptoms of obsessive-compulsive disorder, attention deficit hyperactive disorder, learning…
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Including product features in process redesign
DEFF Research Database (Denmark)
Hvam, Lars; Hauksdóttir, Dagný; Mortensen, Niels Henrik
2017-01-01
do not take into account how the product features are applied throughout the process, which makes it difficult to obtain a comprehensive understanding of the activities in the processes and to generate significant improvements. The suggested approach models the product family using the so......This article suggests a visual modelling method for integrating models of product features with business process models for redesigning the business processes involving specifications of customer-tailored products and services. The current methods for redesigning these types of business processes......-called product variant master and the business process modelling notation for modelling the process flow. The product model is combined with the process map by identifying features used in each step of the process flow. Additionally, based on the information absorbed from the integrated model, the value stream...
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Feature Statistics Modulate the Activation of Meaning during Spoken Word Processing
Devereux, Barry J.; Taylor, Kirsten I.; Randall, Billi; Geertzen, Jeroen; Tyler, Lorraine K.
2016-01-01
Understanding spoken words involves a rapid mapping from speech to conceptual representations. One distributed feature-based conceptual account assumes that the statistical characteristics of concepts' features--the number of concepts they occur in ("distinctiveness/sharedness") and likelihood of co-occurrence ("correlational…
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Esser, Karlheinz; Tursun, Baris; Ingenhoven, Martin; Michaelis, Georg; Pratje, Elke
2002-11-08
The yeast protein cytochrome c peroxidase (Ccp1) is nuclearly encoded and imported into the mitochondrial intermembrane space, where it is involved in degradation of reactive oxygen species. It is known, that Ccp1 is synthesised as a precursor with a N-terminal pre-sequence, that is proteolytically removed during transport of the protein. Here we present evidence for a new processing pathway, involving novel signal peptidase activities. The mAAA protease subunits Yta10 (Afg3) and Yta12 (Rca1) were identified both to be essential for the first processing step. In addition, the Pcp1 (Ygr101w) gene product was found to be required for the second processing step, yielding the mature Ccp1 protein. The newly identified Pcp1 protein belongs to the rhomboid-GlpG superfamily of putative intramembrane peptidases. Inactivation of the protease motifs in mAAA and Pcp1 blocks the respective steps of proteolysis. A model of coupled Ccp1 transport and N-terminal processing by the mAAA complex and Pcp1 is discussed. Similar processing mechanisms may exist, because the mAAA subunits and the newly identified Pcp1 protein belong to ubiquitous protein families.
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Training Sequences and their Effects on Task Performance and User Outcomes
DEFF Research Database (Denmark)
Sanford, Clive Carlton
2007-01-01
This article introduces the concept of information technology (IT) training sequencesand examines how sequencing of conceptual and procedural training impact IT task performance, user satisfaction and users' self-efficacy. Using assimilation theory, we develop four hypotheses related to training...... sequences. These hypotheses were then tested in a database design context using a quasi-experimental study involving student subjects. Empirical results demonstrate improved far-transfer andnear-transfer task performance and higher self-efficacy for subjects trained in the conceptual-procedural sequence vs...
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Google matrix analysis of DNA sequences.
Kandiah, Vivek; Shepelyansky, Dima L
2013-01-01
For DNA sequences of various species we construct the Google matrix [Formula: see text] of Markov transitions between nearby words composed of several letters. The statistical distribution of matrix elements of this matrix is shown to be described by a power law with the exponent being close to those of outgoing links in such scale-free networks as the World Wide Web (WWW). At the same time the sum of ingoing matrix elements is characterized by the exponent being significantly larger than those typical for WWW networks. This results in a slow algebraic decay of the PageRank probability determined by the distribution of ingoing elements. The spectrum of [Formula: see text] is characterized by a large gap leading to a rapid relaxation process on the DNA sequence networks. We introduce the PageRank proximity correlator between different species which determines their statistical similarity from the view point of Markov chains. The properties of other eigenstates of the Google matrix are also discussed. Our results establish scale-free features of DNA sequence networks showing their similarities and distinctions with the WWW and linguistic networks.
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Google matrix analysis of DNA sequences.
Directory of Open Access Journals (Sweden)
Vivek Kandiah
Full Text Available For DNA sequences of various species we construct the Google matrix [Formula: see text] of Markov transitions between nearby words composed of several letters. The statistical distribution of matrix elements of this matrix is shown to be described by a power law with the exponent being close to those of outgoing links in such scale-free networks as the World Wide Web (WWW. At the same time the sum of ingoing matrix elements is characterized by the exponent being significantly larger than those typical for WWW networks. This results in a slow algebraic decay of the PageRank probability determined by the distribution of ingoing elements. The spectrum of [Formula: see text] is characterized by a large gap leading to a rapid relaxation process on the DNA sequence networks. We introduce the PageRank proximity correlator between different species which determines their statistical similarity from the view point of Markov chains. The properties of other eigenstates of the Google matrix are also discussed. Our results establish scale-free features of DNA sequence networks showing their similarities and distinctions with the WWW and linguistic networks.
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Directory of Open Access Journals (Sweden)
Evelyne Mann
2018-01-01
Full Text Available Microbiota of the rumen wall constitute an important niche of rumen microbial ecology and their composition has been elucidated in different ruminants during the last years. However, the knowledge about the function of rumen wall microbes is still limited. Rumen wall biopsies were taken from three fistulated dairy cows under a standard forage-based diet and after 4 weeks of high concentrate feeding inducing a subacute rumen acidosis (SARA. Extracted RNA was used for metatranscriptome sequencing using Illumina HiSeq sequencing technology. The gene expression of the rumen wall microbial community was analyzed by mapping 35 million sequences against the Kyoto Encyclopedia for Genes and Genomes (KEGG database and determining differentially expressed genes. A total of 1,607 functional features were assigned with high expression of genes involved in central metabolism, galactose, starch and sucrose metabolism. The glycogen phosphorylase (EC:2.4.1.1 which degrades (1->4-alpha-D-glucans was among the highest expressed genes being transcribed by 115 bacterial genera. Energy metabolism genes were also highly expressed, including the pyruvate orthophosphate dikinase (EC:2.7.9.1 involved in pyruvate metabolism, which was covered by 177 genera. Nitrogen metabolism genes, in particular glutamate dehydrogenase (EC:1.4.1.4, glutamine synthetase (EC:6.3.1.2 and glutamate synthase (EC:1.4.1.13, EC:1.4.1.14 were also found to be highly expressed and prove rumen wall microbiota to be actively involved in providing host-relevant metabolites for exchange across the rumen wall. In addition, we found all four urease subunits (EC:3.5.1.5 transcribed by members of the genera Flavobacterium, Corynebacterium, Helicobacter, Clostridium, and Bacillus, and the dissimilatory sulfate reductase (EC 1.8.99.5 dsrABC, which is responsible for the reduction of sulfite to sulfide. We also provide in situ evidence for cellulose and cellobiose degradation, a key step in fiber-rich feed
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Characterization of soybean genomic features by analysis of its expressed sequence tags
DEFF Research Database (Denmark)
Tian, Ai-Guo; Wang, Jun; Cui, Peng
2004-01-01
to be fast-evolving. Soybean unigenes with no match to genes within the Arabidopsis genome were identified as soybean-specific genes. These genes were mainly involved in nodule development and the synthesis of seed storage proteins. In addition, we also identified 61 genes regulated by salicylic acid, 1...
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Energy Technology Data Exchange (ETDEWEB)
Lee, Sang Kwon; Choe, Mi Sun [Dongsan Medical Center, Keimyung University School of Medicine, Daegu (Korea, Republic of)
2013-06-15
We report a case of mucosa-associated lymphoid tissue (MALT) lymphoma involving the medial rectus muscle in a 47-year-old man along with CT, MRI, 18 F-fluorodeoxy-glucose positron emission tomography/CT ( 18 F-FDG PET/CT), and pathologic features. The lesion was manifested as a fusiform enlargement isolated to the right medial rectus muscle with involvement of its tendinous insertion. The lesion was isoattenuating to the brain on non-enhanced CT images, showing as isointense to gray matter on fast spin echo T1- and T2-weighted images with fat saturation, and showed homogeneous enhancement on contrast-enhanced CT and MR images. The maximum stan- dardized uptake value on 18 F-FDG PET/CT was 4.9 g/mL. The results of histological and immunohistochemical examinations of the specimen obtained by biopsy of the right medial rectus muscle were consistent with MALT lymphoma. It should be noted that the extraocular muscle (EOM) is a rare location for the involvement of MALT lympho- ma, and MALT lymphoma of the EOM may mimic thyroid orbitopathy.
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Anderson, Nathaniel D; Dell, Gary S
2018-04-03
Speakers implicitly learn novel phonotactic patterns by producing strings of syllables. The learning is revealed in their speech errors. First-order patterns, such as "/f/ must be a syllable onset," can be distinguished from contingent, or second-order, patterns, such as "/f/ must be an onset if the vowel is /a/, but a coda if the vowel is /o/." A metaanalysis of 19 experiments clearly demonstrated that first-order patterns affect speech errors to a very great extent in a single experimental session, but second-order vowel-contingent patterns only affect errors on the second day of testing, suggesting the need for a consolidation period. Two experiments tested an analogue to these studies involving sequences of button pushes, with fingers as "consonants" and thumbs as "vowels." The button-push errors revealed two of the key speech-error findings: first-order patterns are learned quickly, but second-order thumb-contingent patterns are only strongly revealed in the errors on the second day of testing. The influence of computational complexity on the implicit learning of phonotactic patterns in speech production may be a general feature of sequence production.
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Directory of Open Access Journals (Sweden)
Chong Kang
2009-09-01
Full Text Available Abstract Background MicroRNAs (miRNAs are endogenous small RNAs having large-scale regulatory effects on plant development and stress responses. Extensive studies of miRNAs have only been performed in a few model plants. Although miRNAs are proved to be involved in plant cold stress responses, little is known for winter-habit monocots. Brachypodium distachyon, with close evolutionary relationship to cool-season cereals, has recently emerged as a novel model plant. There are few reports of Brachypodium miRNAs. Results High-throughput sequencing and whole-genome-wide data mining led to the identification of 27 conserved miRNAs, as well as 129 predicted miRNAs in Brachypodium. For multiple-member conserved miRNA families, their sizes in Brachypodium were much smaller than those in rice and Populus. The genome organization of miR395 family in Brachypodium was quite different from that in rice. The expression of 3 conserved miRNAs and 25 predicted miRNAs showed significant changes in response to cold stress. Among these miRNAs, some were cold-induced and some were cold-suppressed, but all the conserved miRNAs were up-regulated under cold stress condition. Conclusion Our results suggest that Brachypodium miRNAs are composed of a set of conserved miRNAs and a large proportion of non-conserved miRNAs with low expression levels. Both kinds of miRNAs were involved in cold stress response, but all the conserved miRNAs were up-regulated, implying an important role for cold-induced miRNAs. The different size and genome organization of miRNA families in Brachypodium and rice suggest that the frequency of duplication events or the selection pressure on duplicated miRNAs are different between these two closely related plant species.
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Vertebral osteomyelitis without disc involvement
Energy Technology Data Exchange (ETDEWEB)
Kamani, I.; Syed, I.; Saifuddin, A. E-mail: asaifuddin@aol.com; Green, R.; MacSweeney, F
2004-10-01
Vertebral osteomyelitis is most commonly due to pyogenic or granulomatous infection and typically results in the combined involvement of the intervertebral disc and adjacent vertebral bodies. Non-infective causes include the related conditions of chronic recurrent multifocal osteomyelitis (CRMO) and SAPHO (synovitis, acne, pustulosis, hyperostosis, and osteitis) syndrome. Occasionally, these conditions may present purely within the vertebral body, resulting in various combinations of vertebral marrow oedema and sclerosis, destructive lesions of the vertebral body and pathological vertebral collapse, thus mimicking neoplastic disease. This review illustrates the imaging features of vertebral osteomyelitis without disc involvement, with emphasis on magnetic resonance imaging (MRI) findings.
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Sequence-specific bias correction for RNA-seq data using recurrent neural networks.
Zhang, Yao-Zhong; Yamaguchi, Rui; Imoto, Seiya; Miyano, Satoru
2017-01-25
The recent success of deep learning techniques in machine learning and artificial intelligence has stimulated a great deal of interest among bioinformaticians, who now wish to bring the power of deep learning to bare on a host of bioinformatical problems. Deep learning is ideally suited for biological problems that require automatic or hierarchical feature representation for biological data when prior knowledge is limited. In this work, we address the sequence-specific bias correction problem for RNA-seq data redusing Recurrent Neural Networks (RNNs) to model nucleotide sequences without pre-determining sequence structures. The sequence-specific bias of a read is then calculated based on the sequence probabilities estimated by RNNs, and used in the estimation of gene abundance. We explore the application of two popular RNN recurrent units for this task and demonstrate that RNN-based approaches provide a flexible way to model nucleotide sequences without knowledge of predetermined sequence structures. Our experiments show that training a RNN-based nucleotide sequence model is efficient and RNN-based bias correction methods compare well with the-state-of-the-art sequence-specific bias correction method on the commonly used MAQC-III data set. RNNs provides an alternative and flexible way to calculate sequence-specific bias without explicitly pre-determining sequence structures.
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Directory of Open Access Journals (Sweden)
Pablo S.B. de Oliveira
Full Text Available ABSTRACT: Canine parvovirus type 2c (CPV-2c emerged in Europe in the early 2000’s and rapidly spread out worldwide. Clinical and molecular data have demonstrated its circulation in Brazilian dogs, yet detailed descriptions of cases are still lacking. This article describes the epidemiological, clinical and pathological features of 24 cases of CPV-2c-associated disease in dogs submitted to veterinary clinics and laboratory diagnosis in southern Brazil (2014-2016. Most affected dogs presented signs/lesions suggestive of parvovirus enteritis: diarrhea, vomiting, hyperemia and hemorrhage of the serous membrane of the small intestine, diffuse segmental granulation, atrophy of the villi, necrosis and fusion of crypts, squamous metaplasia and epithelial syncytia. A number of cases presented features divergent from the classical presentations, including a wide variation in the color of feces (reddish and/or yellowish, light-brownish, orange-brown and brownish, involvement of adults (4/24 and vaccinated dogs (12/24, extensive involvement of the small intestine (8/20 and the presence of pulmonary edema (7/24 and convulsions (3/24. Feces and intestinal fragments submitted to PCR for the CPV-2 VP2 gene and to virus isolation in cell culture yielded positive results in 100% and 58.3% (14/24 of the cases, respectively. Nucleotide sequencing revealed a high nucleotide identity in VP2 (99.4 to 100% and a consistent mutation at amino acid 426 (asparagine to glutamic acid, considered a signature of CPV-2c. These results confirm the involvement of CPV-2c in the described cases and demonstrate the importance of CPV-2c infection among Brazilian dogs, calling attention of veterinarians to correctly diagnose the disease, mainly considering the frequent atypical presentations.
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Directory of Open Access Journals (Sweden)
Devilee Peter
2005-11-01
Full Text Available Abstract Background The SDHA, SDHB, SDHC and SDHD genes encode the subunits of succinate dehydrogenase (succinate: ubiquinone oxidoreductase, a component of both the Krebs cycle and the mitochondrial respiratory chain. SDHA, a flavoprotein and SDHB, an iron-sulfur protein together constitute the catalytic domain, while SDHC and SDHD encode membrane anchors that allow the complex to participate in the respiratory chain as complex II. Germline mutations of SDHD and SDHB are a major cause of the hereditary forms of the tumors paraganglioma and pheochromocytoma. The largest subunit, SDHA, is mutated in patients with Leigh syndrome and late-onset optic atrophy, but has not as yet been identified as a factor in hereditary cancer. Description The SDH mutation database is based on the recently described Leiden Open (source Variation Database (LOVD system. The variants currently described in the database were extracted from the published literature and in some cases annotated to conform to current mutation nomenclature. Researchers can also directly submit new sequence variants online. Since the identification of SDHD, SDHC, and SDHB as classic tumor suppressor genes in 2000 and 2001, studies from research groups around the world have identified a total of 120 variants. Here we introduce all reported paraganglioma and pheochromocytoma related sequence variations in these genes, in addition to all reported mutations of SDHA. The database is now accessible online. Conclusion The SDH mutation database offers a valuable tool and resource for clinicians involved in the treatment of patients with paraganglioma-pheochromocytoma, clinical geneticists needing an overview of current knowledge, and geneticists and other researchers needing a solid foundation for further exploration of both these tumor syndromes and SDHA-related phenotypes.
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Consed: a graphical editor for next-generation sequencing.
Gordon, David; Green, Phil
2013-11-15
The rapid growth of DNA sequencing throughput in recent years implies that graphical interfaces for viewing and correcting errors must now handle large numbers of reads, efficiently pinpoint regions of interest and automate as many tasks as possible. We have adapted consed to reflect this. To allow full-feature editing of large datasets while keeping memory requirements low, we developed a viewer, bamScape, that reads billion-read BAM files, identifies and displays problem areas for user review and launches the consed graphical editor on user-selected regions, allowing, in addition to longstanding consed capabilities such as assembly editing, a variety of new features including direct editing of the reference sequence, variant and error detection, display of annotation tracks and the ability to simultaneously process a group of reads. Many batch processing capabilities have been added. The consed package is free to academic, government and non-profit users, and licensed to others for a fee by the University of Washington. The current version (26.0) is available for linux, macosx and solaris systems or as C++ source code. It includes a user's manual (with exercises) and example datasets. http://www.phrap.org/consed/consed.html dgordon@uw.edu .
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RNA-ID, a Powerful Tool for Identifying and Characterizing Regulatory Sequences.
Brule, C E; Dean, K M; Grayhack, E J
2016-01-01
The identification and analysis of sequences that regulate gene expression is critical because regulated gene expression underlies biology. RNA-ID is an efficient and sensitive method to discover and investigate regulatory sequences in the yeast Saccharomyces cerevisiae, using fluorescence-based assays to detect green fluorescent protein (GFP) relative to a red fluorescent protein (RFP) control in individual cells. Putative regulatory sequences can be inserted either in-frame or upstream of a superfolder GFP fusion protein whose expression, like that of RFP, is driven by the bidirectional GAL1,10 promoter. In this chapter, we describe the methodology to identify and study cis-regulatory sequences in the RNA-ID system, explaining features and variations of the RNA-ID reporter, as well as some applications of this system. We describe in detail the methods to analyze a single regulatory sequence, from construction of a single GFP variant to assay of variants by flow cytometry, as well as modifications required to screen libraries of different strains simultaneously. We also describe subsequent analyses of regulatory sequences. © 2016 Elsevier Inc. All rights reserved.
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Lymphangioleiomyomatosis and tuberous sclerosis with pulmonary involvement
International Nuclear Information System (INIS)
Pedrosa, I.; Saiz, A.; Bustos, A.; Hernando, F.
2000-01-01
We present two cases of pulmonary lumphangioleiomyomatosis and one case of tuberous sclerosis with pulmonary involvement describing the most characteristic features according to plain chest X-ray and high-resolution computed tomography (HRCT). (Author) 14 refs