Orthology detection combining clustering and synteny for very large datasets

OpenAIRE

Lechner, Marcus; Hernandez-Rosales, Maribel; Doerr, Daniel; Wieseke, Nicolas; Thévenin, Annelyse; Stoye, Jens; Hartmann, Roland K.; Prohaska, Sonja J.; Stadler, Peter F.

2014-01-01

The elucidation of orthology relationships is an important step both in gene function prediction as well as towards understanding patterns of sequence evolution. Orthology assignments are usually derived directly from sequence similarities for large data because more exact approaches exhibit too high computational costs. Here we present PoFF, an extension for the standalone tool Proteinortho, which enhances orthology detection by combining clustering, sequence similarity, and synteny. In the ...

QuartetS-DB: a large-scale orthology database for prokaryotes and eukaryotes inferred by evolutionary evidence

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Yu Chenggang

2012-06-01

Full Text Available Abstract Background The concept of orthology is key to decoding evolutionary relationships among genes across different species using comparative genomics. QuartetS is a recently reported algorithm for large-scale orthology detection. Based on the well-established evolutionary principle that gene duplication events discriminate paralogous from orthologous genes, QuartetS has been shown to improve orthology detection accuracy while maintaining computational efficiency. Description QuartetS-DB is a new orthology database constructed using the QuartetS algorithm. The database provides orthology predictions among 1621 complete genomes (1365 bacterial, 92 archaeal, and 164 eukaryotic, covering more than seven million proteins and four million pairwise orthologs. It is a major source of orthologous groups, containing more than 300,000 groups of orthologous proteins and 236,000 corresponding gene trees. The database also provides over 500,000 groups of inparalogs. In addition to its size, a distinguishing feature of QuartetS-DB is the ability to allow users to select a cutoff value that modulates the balance between prediction accuracy and coverage of the retrieved pairwise orthologs. The database is accessible at https://applications.bioanalysis.org/quartetsdb. Conclusions QuartetS-DB is one of the largest orthology resources available to date. Because its orthology predictions are underpinned by evolutionary evidence obtained from sequenced genomes, we expect its accuracy to continue to increase in future releases as the genomes of additional species are sequenced.

Assessment of orthologous splicing isoforms in human and mouse orthologous genes

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Horner David S

2010-10-01

Full Text Available Abstract Background Recent discoveries have highlighted the fact that alternative splicing and alternative transcripts are the rule, rather than the exception, in metazoan genes. Since multiple transcript and protein variants expressed by the same gene are, by definition, structurally distinct and need not to be functionally equivalent, the concept of gene orthology should be extended to the transcript level in order to describe evolutionary relationships between structurally similar transcript variants. In other words, the identification of true orthology relationships between gene products now should progress beyond primary sequence and "splicing orthology", consisting in ancestrally shared exon-intron structures, is required to define orthologous isoforms at transcript level. Results As a starting step in this direction, in this work we performed a large scale human- mouse gene comparison with a twofold goal: first, to assess if and to which extent traditional gene annotations such as RefSeq capture genuine splicing orthology; second, to provide a more detailed annotation and quantification of true human-mouse orthologous transcripts defined as transcripts of orthologous genes exhibiting the same splicing patterns. Conclusions We observed an identical exon/intron structure for 32% of human and mouse orthologous genes. This figure increases to 87% using less stringent criteria for gene structure similarity, thus implying that for about 13% of the human RefSeq annotated genes (and about 25% of the corresponding transcripts we could not identify any mouse transcript showing sufficient similarity to be confidently assigned as a splicing ortholog. Our data suggest that current gene and transcript data may still be rather incomplete - with several splicing variants still unknown. The observation that alternative splicing produces large numbers of alternative transcripts and proteins, some of them conserved across species and others truly species

Phylogenetic reconstruction of orthology, paralogy, and conserved synteny for dog and human.

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Goodstadt, Leo; Ponting, Chris P

2006-09-29

Accurate predictions of orthology and paralogy relationships are necessary to infer human molecular function from experiments in model organisms. Previous genome-scale approaches to predicting these relationships have been limited by their use of protein similarity and their failure to take into account multiple splicing events and gene prediction errors. We have developed PhyOP, a new phylogenetic orthology prediction pipeline based on synonymous rate estimates, which accurately predicts orthology and paralogy relationships for transcripts, genes, exons, or genomic segments between closely related genomes. We were able to identify orthologue relationships to human genes for 93% of all dog genes from Ensembl. Among 1:1 orthologues, the alignments covered a median of 97.4% of protein sequences, and 92% of orthologues shared essentially identical gene structures. PhyOP accurately recapitulated genomic maps of conserved synteny. Benchmarking against predictions from Ensembl and Inparanoid showed that PhyOP is more accurate, especially in its predictions of paralogy. Nearly half (46%) of PhyOP paralogy predictions are unique. Using PhyOP to investigate orthologues and paralogues in the human and dog genomes, we found that the human assembly contains 3-fold more gene duplications than the dog. Species-specific duplicate genes, or "in-paralogues," are generally shorter and have fewer exons than 1:1 orthologues, which is consistent with selective constraints and mutation biases based on the sizes of duplicated genes. In-paralogues have experienced elevated amino acid and synonymous nucleotide substitution rates. Duplicates possess similar biological functions for either the dog or human lineages. Having accounted for 2,954 likely pseudogenes and gene fragments, and after separating 346 erroneously merged genes, we estimated that the human genome encodes a minimum of 19,700 protein-coding genes, similar to the gene count of nematode worms. PhyOP is a fast and robust

Phylogenetic reconstruction of orthology, paralogy, and conserved synteny for dog and human.

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Leo Goodstadt

2006-09-01

Full Text Available Accurate predictions of orthology and paralogy relationships are necessary to infer human molecular function from experiments in model organisms. Previous genome-scale approaches to predicting these relationships have been limited by their use of protein similarity and their failure to take into account multiple splicing events and gene prediction errors. We have developed PhyOP, a new phylogenetic orthology prediction pipeline based on synonymous rate estimates, which accurately predicts orthology and paralogy relationships for transcripts, genes, exons, or genomic segments between closely related genomes. We were able to identify orthologue relationships to human genes for 93% of all dog genes from Ensembl. Among 1:1 orthologues, the alignments covered a median of 97.4% of protein sequences, and 92% of orthologues shared essentially identical gene structures. PhyOP accurately recapitulated genomic maps of conserved synteny. Benchmarking against predictions from Ensembl and Inparanoid showed that PhyOP is more accurate, especially in its predictions of paralogy. Nearly half (46% of PhyOP paralogy predictions are unique. Using PhyOP to investigate orthologues and paralogues in the human and dog genomes, we found that the human assembly contains 3-fold more gene duplications than the dog. Species-specific duplicate genes, or "in-paralogues," are generally shorter and have fewer exons than 1:1 orthologues, which is consistent with selective constraints and mutation biases based on the sizes of duplicated genes. In-paralogues have experienced elevated amino acid and synonymous nucleotide substitution rates. Duplicates possess similar biological functions for either the dog or human lineages. Having accounted for 2,954 likely pseudogenes and gene fragments, and after separating 346 erroneously merged genes, we estimated that the human genome encodes a minimum of 19,700 protein-coding genes, similar to the gene count of nematode worms. PhyOP is a

New Tools in Orthology Analysis: A Brief Review of Promising Perspectives.

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Nichio, Bruno T L; Marchaukoski, Jeroniza Nunes; Raittz, Roberto Tadeu

2017-01-01

Nowadays defying homology relationships among sequences is essential for biological research. Within homology the analysis of orthologs sequences is of great importance for computational biology, annotation of genomes and for phylogenetic inference. Since 2007, with the increase in the number of new sequences being deposited in large biological databases, researchers have begun to analyse computerized methodologies and tools aimed at selecting the most promising ones in the prediction of orthologous groups. Literature in this field of research describes the problems that the majority of available tools show, such as those encountered in accuracy, time required for analysis (especially in light of the increasing volume of data being submitted, which require faster techniques) and the automatization of the process without requiring manual intervention. Conducting our search through BMC, Google Scholar, NCBI PubMed, and Expasy, we examined more than 600 articles pursuing the most recent techniques and tools developed to solve most the problems still existing in orthology detection. We listed the main computational tools created and developed between 2011 and 2017, taking into consideration the differences in the type of orthology analysis, outlining the main features of each tool and pointing to the problems that each one tries to address. We also observed that several tools still use as their main algorithm the BLAST "all-against-all" methodology, which entails some limitations, such as limited number of queries, computational cost, and high processing time to complete the analysis. However, new promising tools are being developed, like OrthoVenn (which uses the Venn diagram to show the relationship of ortholog groups generated by its algorithm); or proteinOrtho (which improves the accuracy of ortholog groups); or ReMark (tackling the integration of the pipeline to turn the entry process automatic); or OrthAgogue (using algorithms developed to minimize processing

New Tools in Orthology Analysis: A Brief Review of Promising Perspectives

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Bruno T. L. Nichio

2017-10-01

Full Text Available Nowadays defying homology relationships among sequences is essential for biological research. Within homology the analysis of orthologs sequences is of great importance for computational biology, annotation of genomes and for phylogenetic inference. Since 2007, with the increase in the number of new sequences being deposited in large biological databases, researchers have begun to analyse computerized methodologies and tools aimed at selecting the most promising ones in the prediction of orthologous groups. Literature in this field of research describes the problems that the majority of available tools show, such as those encountered in accuracy, time required for analysis (especially in light of the increasing volume of data being submitted, which require faster techniques and the automatization of the process without requiring manual intervention. Conducting our search through BMC, Google Scholar, NCBI PubMed, and Expasy, we examined more than 600 articles pursuing the most recent techniques and tools developed to solve most the problems still existing in orthology detection. We listed the main computational tools created and developed between 2011 and 2017, taking into consideration the differences in the type of orthology analysis, outlining the main features of each tool and pointing to the problems that each one tries to address. We also observed that several tools still use as their main algorithm the BLAST “all-against-all” methodology, which entails some limitations, such as limited number of queries, computational cost, and high processing time to complete the analysis. However, new promising tools are being developed, like OrthoVenn (which uses the Venn diagram to show the relationship of ortholog groups generated by its algorithm; or proteinOrtho (which improves the accuracy of ortholog groups; or ReMark (tackling the integration of the pipeline to turn the entry process automatic; or OrthAgogue (using algorithms developed to

Orthology detection combining clustering and synteny for very large datasets.

Science.gov (United States)

Lechner, Marcus; Hernandez-Rosales, Maribel; Doerr, Daniel; Wieseke, Nicolas; Thévenin, Annelyse; Stoye, Jens; Hartmann, Roland K; Prohaska, Sonja J; Stadler, Peter F

2014-01-01

The elucidation of orthology relationships is an important step both in gene function prediction as well as towards understanding patterns of sequence evolution. Orthology assignments are usually derived directly from sequence similarities for large data because more exact approaches exhibit too high computational costs. Here we present PoFF, an extension for the standalone tool Proteinortho, which enhances orthology detection by combining clustering, sequence similarity, and synteny. In the course of this work, FFAdj-MCS, a heuristic that assesses pairwise gene order using adjacencies (a similarity measure related to the breakpoint distance) was adapted to support multiple linear chromosomes and extended to detect duplicated regions. PoFF largely reduces the number of false positives and enables more fine-grained predictions than purely similarity-based approaches. The extension maintains the low memory requirements and the efficient concurrency options of its basis Proteinortho, making the software applicable to very large datasets.

Orthology detection combining clustering and synteny for very large datasets.

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Marcus Lechner

Full Text Available The elucidation of orthology relationships is an important step both in gene function prediction as well as towards understanding patterns of sequence evolution. Orthology assignments are usually derived directly from sequence similarities for large data because more exact approaches exhibit too high computational costs. Here we present PoFF, an extension for the standalone tool Proteinortho, which enhances orthology detection by combining clustering, sequence similarity, and synteny. In the course of this work, FFAdj-MCS, a heuristic that assesses pairwise gene order using adjacencies (a similarity measure related to the breakpoint distance was adapted to support multiple linear chromosomes and extended to detect duplicated regions. PoFF largely reduces the number of false positives and enables more fine-grained predictions than purely similarity-based approaches. The extension maintains the low memory requirements and the efficient concurrency options of its basis Proteinortho, making the software applicable to very large datasets.

Domain architecture conservation in orthologs

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2011-01-01

Background As orthologous proteins are expected to retain function more often than other homologs, they are often used for functional annotation transfer between species. However, ortholog identification methods do not take into account changes in domain architecture, which are likely to modify a protein's function. By domain architecture we refer to the sequential arrangement of domains along a protein sequence. To assess the level of domain architecture conservation among orthologs, we carried out a large-scale study of such events between human and 40 other species spanning the entire evolutionary range. We designed a score to measure domain architecture similarity and used it to analyze differences in domain architecture conservation between orthologs and paralogs relative to the conservation of primary sequence. We also statistically characterized the extents of different types of domain swapping events across pairs of orthologs and paralogs. Results The analysis shows that orthologs exhibit greater domain architecture conservation than paralogous homologs, even when differences in average sequence divergence are compensated for, for homologs that have diverged beyond a certain threshold. We interpret this as an indication of a stronger selective pressure on orthologs than paralogs to retain the domain architecture required for the proteins to perform a specific function. In general, orthologs as well as the closest paralogous homologs have very similar domain architectures, even at large evolutionary separation. The most common domain architecture changes observed in both ortholog and paralog pairs involved insertion/deletion of new domains, while domain shuffling and segment duplication/deletion were very infrequent. Conclusions On the whole, our results support the hypothesis that function conservation between orthologs demands higher domain architecture conservation than other types of homologs, relative to primary sequence conservation. This supports the

Enhancing the prediction of protein pairings between interacting families using orthology information

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Pazos Florencio

2008-01-01

Full Text Available Abstract Background It has repeatedly been shown that interacting protein families tend to have similar phylogenetic trees. These similarities can be used to predicting the mapping between two families of interacting proteins (i.e. which proteins from one family interact with which members of the other. The correct mapping will be that which maximizes the similarity between the trees. The two families may eventually comprise orthologs and paralogs, if members of the two families are present in more than one organism. This fact can be exploited to restrict the possible mappings, simply by impeding links between proteins of different organisms. We present here an algorithm to predict the mapping between families of interacting proteins which is able to incorporate information regarding orthologues, or any other assignment of proteins to "classes" that may restrict possible mappings. Results For the first time in methods for predicting mappings, we have tested this new approach on a large number of interacting protein domains in order to statistically assess its performance. The method accurately predicts around 80% in the most favourable cases. We also analysed in detail the results of the method for a well defined case of interacting families, the sensor and kinase components of the Ntr-type two-component system, for which up to 98% of the pairings predicted by the method were correct. Conclusion Based on the well established relationship between tree similarity and interactions we developed a method for predicting the mapping between two interacting families using genomic information alone. The program is available through a web interface.

A database of annotated tentative orthologs from crop abiotic stress transcripts.

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Balaji, Jayashree; Crouch, Jonathan H; Petite, Prasad V N S; Hoisington, David A

2006-10-07

A minimal requirement to initiate a comparative genomics study on plant responses to abiotic stresses is a dataset of orthologous sequences. The availability of a large amount of sequence information, including those derived from stress cDNA libraries allow for the identification of stress related genes and orthologs associated with the stress response. Orthologous sequences serve as tools to explore genes and their relationships across species. For this purpose, ESTs from stress cDNA libraries across 16 crop species including 6 important cereal crops and 10 dicots were systematically collated and subjected to bioinformatics analysis such as clustering, grouping of tentative orthologous sets, identification of protein motifs/patterns in the predicted protein sequence, and annotation with stress conditions, tissue/library source and putative function. All data are available to the scientific community at http://intranet.icrisat.org/gt1/tog/homepage.htm. We believe that the availability of annotated plant abiotic stress ortholog sets will be a valuable resource for researchers studying the biology of environmental stresses in plant systems, molecular evolution and genomics.

The other side of comparative genomics: genes with no orthologs between the cow and other mammalian species

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Ajmone-Marsan Paolo

2009-12-01

Full Text Available Abstract Background With the rapid growth in the availability of genome sequence data, the automated identification of orthologous genes between species (orthologs is of fundamental importance to facilitate functional annotation and studies on comparative and evolutionary genomics. Genes with no apparent orthologs between the bovine and human genome may be responsible for major differences between the species, however, such genes are often neglected in functional genomics studies. Results A BLAST-based method was exploited to explore the current annotation and orthology predictions in Ensembl. Genes with no orthologs between the two genomes were classified into groups based on alignments, ontology, manual curation and publicly available information. Starting from a high quality and specific set of orthology predictions, as provided by Ensembl, hidden relationship between genes and genomes of different mammalian species were unveiled using a highly sensitive approach, based on sequence similarity and genomic comparison. Conclusions The analysis identified 3,801 bovine genes with no orthologs in human and 1010 human genes with no orthologs in cow, among which 411 and 43 genes, respectively, had no match at all in the other species. Most of the apparently non-orthologous genes may potentially have orthologs which were missed in the annotation process, despite having a high percentage of identity, because of differences in gene length and structure. The comparative analysis reported here identified gene variants, new genes and species-specific features and gave an overview of the other side of orthology which may help to improve the annotation of the bovine genome and the knowledge of structural differences between species.

ORCAN-a web-based meta-server for real-time detection and functional annotation of orthologs.

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Zielezinski, Andrzej; Dziubek, Michal; Sliski, Jan; Karlowski, Wojciech M

2017-04-15

ORCAN (ORtholog sCANner) is a web-based meta-server for one-click evolutionary and functional annotation of protein sequences. The server combines information from the most popular orthology-prediction resources, including four tools and four online databases. Functional annotation utilizes five additional comparisons between the query and identified homologs, including: sequence similarity, protein domain architectures, functional motifs, Gene Ontology term assignments and a list of associated articles. Furthermore, the server uses a plurality-based rating system to evaluate the orthology relationships and to rank the reference proteins by their evolutionary and functional relevance to the query. Using a dataset of ∼1 million true yeast orthologs as a sample reference set, we show that combining multiple orthology-prediction tools in ORCAN increases the sensitivity and precision by 1-2 percent points. The service is available for free at http://www.combio.pl/orcan/ . wmk@amu.edu.pl. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

An integrative and applicable phylogenetic footprinting framework for cis-regulatory motifs identification in prokaryotic genomes.

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Liu, Bingqiang; Zhang, Hanyuan; Zhou, Chuan; Li, Guojun; Fennell, Anne; Wang, Guanghui; Kang, Yu; Liu, Qi; Ma, Qin

2016-08-09

Phylogenetic footprinting is an important computational technique for identifying cis-regulatory motifs in orthologous regulatory regions from multiple genomes, as motifs tend to evolve slower than their surrounding non-functional sequences. Its application, however, has several difficulties for optimizing the selection of orthologous data and reducing the false positives in motif prediction. Here we present an integrative phylogenetic footprinting framework for accurate motif predictions in prokaryotic genomes (MP(3)). The framework includes a new orthologous data preparation procedure, an additional promoter scoring and pruning method and an integration of six existing motif finding algorithms as basic motif search engines. Specifically, we collected orthologous genes from available prokaryotic genomes and built the orthologous regulatory regions based on sequence similarity of promoter regions. This procedure made full use of the large-scale genomic data and taxonomy information and filtered out the promoters with limited contribution to produce a high quality orthologous promoter set. The promoter scoring and pruning is implemented through motif voting by a set of complementary predicting tools that mine as many motif candidates as possible and simultaneously eliminate the effect of random noise. We have applied the framework to Escherichia coli k12 genome and evaluated the prediction performance through comparison with seven existing programs. This evaluation was systematically carried out at the nucleotide and binding site level, and the results showed that MP(3) consistently outperformed other popular motif finding tools. We have integrated MP(3) into our motif identification and analysis server DMINDA, allowing users to efficiently identify and analyze motifs in 2,072 completely sequenced prokaryotic genomes. The performance evaluation indicated that MP(3) is effective for predicting regulatory motifs in prokaryotic genomes. Its application may enhance

PhosphOrtholog: a web-based tool for cross-species mapping of orthologous protein post-translational modifications.

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Chaudhuri, Rima; Sadrieh, Arash; Hoffman, Nolan J; Parker, Benjamin L; Humphrey, Sean J; Stöckli, Jacqueline; Hill, Adam P; James, David E; Yang, Jean Yee Hwa

2015-08-19

Most biological processes are influenced by protein post-translational modifications (PTMs). Identifying novel PTM sites in different organisms, including humans and model organisms, has expedited our understanding of key signal transduction mechanisms. However, with increasing availability of deep, quantitative datasets in diverse species, there is a growing need for tools to facilitate cross-species comparison of PTM data. This is particularly important because functionally important modification sites are more likely to be evolutionarily conserved; yet cross-species comparison of PTMs is difficult since they often lie in structurally disordered protein domains. Current tools that address this can only map known PTMs between species based on known orthologous phosphosites, and do not enable the cross-species mapping of newly identified modification sites. Here, we addressed this by developing a web-based software tool, PhosphOrtholog ( www.phosphortholog.com ) that accurately maps protein modification sites between different species. This facilitates the comparison of datasets derived from multiple species, and should be a valuable tool for the proteomics community. Here we describe PhosphOrtholog, a web-based application for mapping known and novel orthologous PTM sites from experimental data obtained from different species. PhosphOrtholog is the only generic and automated tool that enables cross-species comparison of large-scale PTM datasets without relying on existing PTM databases. This is achieved through pairwise sequence alignment of orthologous protein residues. To demonstrate its utility we apply it to two sets of human and rat muscle phosphoproteomes generated following insulin and exercise stimulation, respectively, and one publicly available mouse phosphoproteome following cellular stress revealing high mapping and coverage efficiency. Although coverage statistics are dataset dependent, PhosphOrtholog increased the number of cross-species mapped sites

On calculating the probability of a set of orthologous sequences

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Junfeng Liu

2009-02-01

Full Text Available Junfeng Liu1,2, Liang Chen3, Hongyu Zhao4, Dirk F Moore1,2, Yong Lin1,2, Weichung Joe Shih1,21Biometrics Division, The Cancer, Institute of New Jersey, New Brunswick, NJ, USA; 2Department of Biostatistics, School of Public Health, University of Medicine and Dentistry of New Jersey, Piscataway, NJ, USA; 3Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA; 4Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT, USAAbstract: Probabilistic DNA sequence models have been intensively applied to genome research. Within the evolutionary biology framework, this article investigates the feasibility for rigorously estimating the probability of a set of orthologous DNA sequences which evolve from a common progenitor. We propose Monte Carlo integration algorithms to sample the unknown ancestral and/or root sequences a posteriori conditional on a reference sequence and apply pairwise Needleman–Wunsch alignment between the sampled and nonreference species sequences to estimate the probability. We test our algorithms on both simulated and real sequences and compare calculated probabilities from Monte Carlo integration to those induced by single multiple alignment.Keywords: evolution, Jukes–Cantor model, Monte Carlo integration, Needleman–Wunsch alignment, orthologous

Domain similarity based orthology detection

OpenAIRE

Bitard-Feildel, Tristan; Kemena, Carsten; Greenwood, Jenny M; Bornberg-Bauer, Erich

2015-01-01

Background Orthologous protein detection software mostly uses pairwise comparisons of amino-acid sequences to assert whether two proteins are orthologous or not. Accordingly, when the number of sequences for comparison increases, the number of comparisons to compute grows in a quadratic order. A current challenge of bioinformatic research, especially when taking into account the increasing number of sequenced organisms available, is to make this ever-growing number of comparisons computationa...

OrthoDB v8: update of the hierarchical catalog of orthologs and the underlying free software.

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Kriventseva, Evgenia V; Tegenfeldt, Fredrik; Petty, Tom J; Waterhouse, Robert M; Simão, Felipe A; Pozdnyakov, Igor A; Ioannidis, Panagiotis; Zdobnov, Evgeny M

2015-01-01

Orthology, refining the concept of homology, is the cornerstone of evolutionary comparative studies. With the ever-increasing availability of genomic data, inference of orthology has become instrumental for generating hypotheses about gene functions crucial to many studies. This update of the OrthoDB hierarchical catalog of orthologs (http://www.orthodb.org) covers 3027 complete genomes, including the most comprehensive set of 87 arthropods, 61 vertebrates, 227 fungi and 2627 bacteria (sampling the most complete and representative genomes from over 11,000 available). In addition to the most extensive integration of functional annotations from UniProt, InterPro, GO, OMIM, model organism phenotypes and COG functional categories, OrthoDB uniquely provides evolutionary annotations including rates of ortholog sequence divergence, copy-number profiles, sibling groups and gene architectures. We re-designed the entirety of the OrthoDB website from the underlying technology to the user interface, enabling the user to specify species of interest and to select the relevant orthology level by the NCBI taxonomy. The text searches allow use of complex logic with various identifiers of genes, proteins, domains, ontologies or annotation keywords and phrases. Gene copy-number profiles can also be queried. This release comes with the freely available underlying ortholog clustering pipeline (http://www.orthodb.org/software). © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Domain similarity based orthology detection.

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Bitard-Feildel, Tristan; Kemena, Carsten; Greenwood, Jenny M; Bornberg-Bauer, Erich

2015-05-13

Orthologous protein detection software mostly uses pairwise comparisons of amino-acid sequences to assert whether two proteins are orthologous or not. Accordingly, when the number of sequences for comparison increases, the number of comparisons to compute grows in a quadratic order. A current challenge of bioinformatic research, especially when taking into account the increasing number of sequenced organisms available, is to make this ever-growing number of comparisons computationally feasible in a reasonable amount of time. We propose to speed up the detection of orthologous proteins by using strings of domains to characterize the proteins. We present two new protein similarity measures, a cosine and a maximal weight matching score based on domain content similarity, and new software, named porthoDom. The qualities of the cosine and the maximal weight matching similarity measures are compared against curated datasets. The measures show that domain content similarities are able to correctly group proteins into their families. Accordingly, the cosine similarity measure is used inside porthoDom, the wrapper developed for proteinortho. porthoDom makes use of domain content similarity measures to group proteins together before searching for orthologs. By using domains instead of amino acid sequences, the reduction of the search space decreases the computational complexity of an all-against-all sequence comparison. We demonstrate that representing and comparing proteins as strings of discrete domains, i.e. as a concatenation of their unique identifiers, allows a drastic simplification of search space. porthoDom has the advantage of speeding up orthology detection while maintaining a degree of accuracy similar to proteinortho. The implementation of porthoDom is released using python and C++ languages and is available under the GNU GPL licence 3 at http://www.bornberglab.org/pages/porthoda .

Standardized benchmarking in the quest for orthologs

DEFF Research Database (Denmark)

Altenhoff, Adrian M; Boeckmann, Brigitte; Capella-Gutierrez, Salvador

2016-01-01

Achieving high accuracy in orthology inference is essential for many comparative, evolutionary and functional genomic analyses, yet the true evolutionary history of genes is generally unknown and orthologs are used for very different applications across phyla, requiring different precision-recall...

Orthology and paralogy constraints: satisfiability and consistency.

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Lafond, Manuel; El-Mabrouk, Nadia

2014-01-01

A variety of methods based on sequence similarity, reconciliation, synteny or functional characteristics, can be used to infer orthology and paralogy relations between genes of a given gene family  G. But is a given set  C of orthology/paralogy constraints possible, i.e., can they simultaneously co-exist in an evolutionary history for  G? While previous studies have focused on full sets of constraints, here we consider the general case where  C does not necessarily involve a constraint for each pair of genes. The problem is subdivided in two parts: (1) Is  C satisfiable, i.e. can we find an event-labeled gene tree G inducing  C? (2) Is there such a G which is consistent, i.e., such that all displayed triplet phylogenies are included in a species tree? Previous results on the Graph sandwich problem can be used to answer to (1), and we provide polynomial-time algorithms for satisfiability and consistency with a given species tree. We also describe a new polynomial-time algorithm for the case of consistency with an unknown species tree and full knowledge of pairwise orthology/paralogy relationships, as well as a branch-and-bound algorithm in the case when unknown relations are present. We show that our algorithms can be used in combination with ProteinOrtho, a sequence similarity-based orthology detection tool, to extract a set of robust orthology/paralogy relationships.

Conserved repertoire of orthologous vomeronasal type 1 receptor genes in ruminant species

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Okamura Hiroaki

2009-09-01

Full Text Available Abstract Background In mammals, pheromones play an important role in social and innate reproductive behavior within species. In rodents, vomeronasal receptor type 1 (V1R, which is specifically expressed in the vomeronasal organ, is thought to detect pheromones. The V1R gene repertoire differs dramatically between mammalian species, and the presence of species-specific V1R subfamilies in mouse and rat suggests that V1R plays a profound role in species-specific recognition of pheromones. In ruminants, however, the molecular mechanism(s for pheromone perception is not well understood. Interestingly, goat male pheromone, which can induce out-of-season ovulation in anestrous females, causes the same pheromone response in sheep, and vice versa, suggesting that there may be mechanisms for detecting "inter-species" pheromones among ruminant species. Results We isolated 23 goat and 21 sheep intact V1R genes based on sequence similarity with 32 cow V1R genes in the cow genome database. We found that all of the goat and sheep V1R genes have orthologs in their cross-species counterparts among these three ruminant species and that the sequence identity of V1R orthologous pairs among these ruminants is much higher than that of mouse-rat V1R orthologous pairs. Furthermore, all goat V1Rs examined thus far are expressed not only in the vomeronasal organ but also in the main olfactory epithelium. Conclusion Our results suggest that, compared with rodents, the repertoire of orthologous V1R genes is remarkably conserved among the ruminants cow, sheep and goat. We predict that these orthologous V1Rs can detect the same or closely related chemical compound(s within each orthologous set/pair. Furthermore, all identified goat V1Rs are expressed in the vomeronasal organ and the main olfactory epithelium, suggesting that V1R-mediated ligand information can be detected and processed by both the main and accessory olfactory systems. The fact that ruminant and rodent V1Rs

Increased taxon sampling reveals thousands of hidden orthologs in flatworms

Science.gov (United States)

2017-01-01

Gains and losses shape the gene complement of animal lineages and are a fundamental aspect of genomic evolution. Acquiring a comprehensive view of the evolution of gene repertoires is limited by the intrinsic limitations of common sequence similarity searches and available databases. Thus, a subset of the gene complement of an organism consists of hidden orthologs, i.e., those with no apparent homology to sequenced animal lineages—mistakenly considered new genes—but actually representing rapidly evolving orthologs or undetected paralogs. Here, we describe Leapfrog, a simple automated BLAST pipeline that leverages increased taxon sampling to overcome long evolutionary distances and identify putative hidden orthologs in large transcriptomic databases by transitive homology. As a case study, we used 35 transcriptomes of 29 flatworm lineages to recover 3427 putative hidden orthologs, some unidentified by OrthoFinder and HaMStR, two common orthogroup inference algorithms. Unexpectedly, we do not observe a correlation between the number of putative hidden orthologs in a lineage and its “average” evolutionary rate. Hidden orthologs do not show unusual sequence composition biases that might account for systematic errors in sequence similarity searches. Instead, gene duplication with divergence of one paralog and weak positive selection appear to underlie hidden orthology in Platyhelminthes. By using Leapfrog, we identify key centrosome-related genes and homeodomain classes previously reported as absent in free-living flatworms, e.g., planarians. Altogether, our findings demonstrate that hidden orthologs comprise a significant proportion of the gene repertoire in flatworms, qualifying the impact of gene losses and gains in gene complement evolution. PMID:28400424

New Tools in Orthology Analysis: A Brief Review of Promising Perspectives

OpenAIRE

Bruno T. L. Nichio; Jeroniza Nunes Marchaukoski; Roberto Tadeu Raittz

2017-01-01

Nowadays defying homology relationships among sequences is essential for biological research. Within homology the analysis of orthologs sequences is of great importance for computational biology, annotation of genomes and for phylogenetic inference. Since 2007, with the increase in the number of new sequences being deposited in large biological databases, researchers have begun to analyse computerized methodologies and tools aimed at selecting the most promising ones in the prediction of orth...

IONS: Identification of Orthologs by Neighborhood and Similarity-an Automated Method to Identify Orthologs in Chromosomal Regions of Common Evolutionary Ancestry and its Application to Hemiascomycetous Yeasts.

Science.gov (United States)

Seret, Marie-Line; Baret, Philippe V

2011-01-01

Comparative sequence analysis is widely used to infer gene function and study genome evolution and requires proper ortholog identification across different genomes. We have developed a program for the Identification of Orthologs in one-to-one relationship by Neighborhood and Similarity (IONS) between closely related species. The algorithm combines two levels of evidence to determine co-ancestrality at the genome scale: sequence similarity and shared neighborhood. The method was initially designed to provide anchor points for syntenic blocks within the Génolevures project concerning nine hemiascomycetous yeasts (about 50,000 genes) and is applicable to different input databases. Comparison based on use of a Rand index shows that the results are highly consistent with the pillars of the Yeast Gene Order Browser, a manually curated database. Compared with SYNERGY, another algorithm reporting homology relationships, our method's main advantages are its automation and the absence of dataset-dependent parameters, facilitating consistent integration of newly released genomes.

IONS: Identification of Orthologs by Neighborhood and Similarity—an Automated Method to Identify Orthologs in Chromosomal Regions of Common Evolutionary Ancestry and its Application to Hemiascomycetous Yeasts

Science.gov (United States)

Seret, Marie-Line; Baret, Philippe V.

2011-01-01

Comparative sequence analysis is widely used to infer gene function and study genome evolution and requires proper ortholog identification across different genomes. We have developed a program for the Identification of Orthologs in one-to-one relationship by Neighborhood and Similarity (IONS) between closely related species. The algorithm combines two levels of evidence to determine co-ancestrality at the genome scale: sequence similarity and shared neighborhood. The method was initially designed to provide anchor points for syntenic blocks within the Génolevures project concerning nine hemiascomycetous yeasts (about 50,000 genes) and is applicable to different input databases. Comparison based on use of a Rand index shows that the results are highly consistent with the pillars of the Yeast Gene Order Browser, a manually curated database. Compared with SYNERGY, another algorithm reporting homology relationships, our method’s main advantages are its automation and the absence of dataset-dependent parameters, facilitating consistent integration of newly released genomes. PMID:21918595

Ortholog - MicrobeDB.jp | LSDB Archive [Life Science Database Archive metadata

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Full Text Available List Contact us MicrobeDB.jp Ortholog Data detail Data name Ortholog DOI 10.18908/lsdba.nbdc01181-010.V002 V...814 triples - About This Database Database Description Download License Update History of This Database Site Policy | Contact Us Ortholog - MicrobeDB.jp | LSDB Archive ...

Orthology and paralogy constraints: satisfiability and consistency

OpenAIRE

Lafond, Manuel; El-Mabrouk, Nadia

2014-01-01

Background A variety of methods based on sequence similarity, reconciliation, synteny or functional characteristics, can be used to infer orthology and paralogy relations between genes of a given gene family   G . But is a given set   C of orthology/paralogy constraints possible, i.e., can they simultaneously co-exist in an evolutionary history for   G ? While previous studies have focused on full sets of constraints, here we consider the general case where   C does not necessarily involve a ...

Pleurochrysome: A Web Database of Pleurochrysis Transcripts and Orthologs Among Heterogeneous Algae

Science.gov (United States)

Fujiwara, Shoko; Takatsuka, Yukiko; Hirokawa, Yasutaka; Tsuzuki, Mikio; Takano, Tomoyuki; Kobayashi, Masaaki; Suda, Kunihiro; Asamizu, Erika; Yokoyama, Koji; Shibata, Daisuke; Tabata, Satoshi; Yano, Kentaro

2016-01-01

Pleurochrysis is a coccolithophorid genus, which belongs to the Coccolithales in the Haptophyta. The genus has been used extensively for biological research, together with Emiliania in the Isochrysidales, to understand distinctive features between the two coccolithophorid-including orders. However, molecular biological research on Pleurochrysis such as elucidation of the molecular mechanism behind coccolith formation has not made great progress at least in part because of lack of comprehensive gene information. To provide such information to the research community, we built an open web database, the Pleurochrysome (http://bioinf.mind.meiji.ac.jp/phapt/), which currently stores 9,023 unique gene sequences (designated as UNIGENEs) assembled from expressed sequence tag sequences of P. haptonemofera as core information. The UNIGENEs were annotated with gene sequences sharing significant homology, conserved domains, Gene Ontology, KEGG Orthology, predicted subcellular localization, open reading frames and orthologous relationship with genes of 10 other algal species, a cyanobacterium and the yeast Saccharomyces cerevisiae. This sequence and annotation information can be easily accessed via several search functions. Besides fundamental functions such as BLAST and keyword searches, this database also offers search functions to explore orthologous genes in the 12 organisms and to seek novel genes. The Pleurochrysome will promote molecular biological and phylogenetic research on coccolithophorids and other haptophytes by helping scientists mine data from the primary transcriptome of P. haptonemofera. PMID:26746174

Proteinortho: detection of (co-)orthologs in large-scale analysis.

Science.gov (United States)

Lechner, Marcus; Findeiss, Sven; Steiner, Lydia; Marz, Manja; Stadler, Peter F; Prohaska, Sonja J

2011-04-28

Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes it desirable to compute genome-wide orthology relations for a given dataset rather than relying on relations listed in databases. The program Proteinortho described here is a stand-alone tool that is geared towards large datasets and makes use of distributed computing techniques when run on multi-core hardware. It implements an extended version of the reciprocal best alignment heuristic. We apply Proteinortho to compute orthologous proteins in the complete set of all 717 eubacterial genomes available at NCBI at the beginning of 2009. We identified thirty proteins present in 99% of all bacterial proteomes. Proteinortho significantly reduces the required amount of memory for orthology analysis compared to existing tools, allowing such computations to be performed on off-the-shelf hardware.

Proteinortho: Detection of (Co-orthologs in large-scale analysis

Directory of Open Access Journals (Sweden)

Steiner Lydia

2011-04-01

Full Text Available Abstract Background Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes it desirable to compute genome-wide orthology relations for a given dataset rather than relying on relations listed in databases. Results The program Proteinortho described here is a stand-alone tool that is geared towards large datasets and makes use of distributed computing techniques when run on multi-core hardware. It implements an extended version of the reciprocal best alignment heuristic. We apply Proteinortho to compute orthologous proteins in the complete set of all 717 eubacterial genomes available at NCBI at the beginning of 2009. We identified thirty proteins present in 99% of all bacterial proteomes. Conclusions Proteinortho significantly reduces the required amount of memory for orthology analysis compared to existing tools, allowing such computations to be performed on off-the-shelf hardware.

Cluster (Viridiplantae) - PGDBj - Ortholog DB | LSDB Archive [Life Science Database Archive metadata

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Full Text Available 0”. This cluster ID is uniquely-assigned by the PGDBj Ortholog Database. Cluster size Number of proteins aff...r About This Database Database Description Download License Update History of This Database Site Policy | Contact Us Cluster (Viridiplantae) - PGDBj - Ortholog DB | LSDB Archive ... ...List Contact us PGDBj - Ortholog DB Cluster (Viridiplantae) Data detail Data name Cluster (Viridiplantae) DO...switchLanguage; BLAST Search Image Search Home About Archive Update History Data

Cluster (Cyanobacteria) - PGDBj - Ortholog DB | LSDB Archive [Life Science Database Archive metadata

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Full Text Available 3090”. This cluster ID is uniquely-assigned by the PGDBj Ortholog Database. Cluster size Number of proteins ...ster About This Database Database Description Download License Update History of This Database Site Policy | Contact Us Cluster (Cyanobacteria) - PGDBj - Ortholog DB | LSDB Archive ... ...List Contact us PGDBj - Ortholog DB Cluster (Cyanobacteria) Data detail Data name Cluster (Cyanobacteria) DO...switchLanguage; BLAST Search Image Search Home About Archive Update History Data

Download - PGDBj - Ortholog DB | LSDB Archive [Life Science Database Archive metadata

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Full Text Available e Description Download License Update History of This Database Site Policy | Contact Us Download - PGDBj - Ortholog DB | LSDB Archive ... ...List Contact us PGDBj - Ortholog DB Download First of all, please read the license of this database. Data na...switchLanguage; BLAST Search Image Search Home About Archive Update History Data

Ortholog-based screening and identification of genes related to intracellular survival.

Science.gov (United States)

Yang, Xiaowen; Wang, Jiawei; Bing, Guoxia; Bie, Pengfei; De, Yanyan; Lyu, Yanli; Wu, Qingmin

2018-04-20

Bioinformatics and comparative genomics analysis methods were used to predict unknown pathogen genes based on homology with identified or functionally clustered genes. In this study, the genes of common pathogens were analyzed to screen and identify genes associated with intracellular survival through sequence similarity, phylogenetic tree analysis and the λ-Red recombination system test method. The total 38,952 protein-coding genes of common pathogens were divided into 19,775 clusters. As demonstrated through a COG analysis, information storage and processing genes might play an important role intracellular survival. Only 19 clusters were present in facultative intracellular pathogens, and not all were present in extracellular pathogens. Construction of a phylogenetic tree selected 18 of these 19 clusters. Comparisons with the DEG database and previous research revealed that seven other clusters are considered essential gene clusters and that seven other clusters are associated with intracellular survival. Moreover, this study confirmed that clusters screened by orthologs with similar function could be replaced with an approved uvrY gene and its orthologs, and the results revealed that the usg gene is associated with intracellular survival. The study improves the current understanding of intracellular pathogens characteristics and allows further exploration of the intracellular survival-related gene modules in these pathogens. Copyright © 2018. Published by Elsevier B.V.

Computational prediction of protein-protein interactions in Leishmania predicted proteomes.

Directory of Open Access Journals (Sweden)

Antonio M Rezende

Full Text Available The Trypanosomatids parasites Leishmania braziliensis, Leishmania major and Leishmania infantum are important human pathogens. Despite of years of study and genome availability, effective vaccine has not been developed yet, and the chemotherapy is highly toxic. Therefore, it is clear just interdisciplinary integrated studies will have success in trying to search new targets for developing of vaccines and drugs. An essential part of this rationale is related to protein-protein interaction network (PPI study which can provide a better understanding of complex protein interactions in biological system. Thus, we modeled PPIs for Trypanosomatids through computational methods using sequence comparison against public database of protein or domain interaction for interaction prediction (Interolog Mapping and developed a dedicated combined system score to address the predictions robustness. The confidence evaluation of network prediction approach was addressed using gold standard positive and negative datasets and the AUC value obtained was 0.94. As result, 39,420, 43,531 and 45,235 interactions were predicted for L. braziliensis, L. major and L. infantum respectively. For each predicted network the top 20 proteins were ranked by MCC topological index. In addition, information related with immunological potential, degree of protein sequence conservation among orthologs and degree of identity compared to proteins of potential parasite hosts was integrated. This information integration provides a better understanding and usefulness of the predicted networks that can be valuable to select new potential biological targets for drug and vaccine development. Network modularity which is a key when one is interested in destabilizing the PPIs for drug or vaccine purposes along with multiple alignments of the predicted PPIs were performed revealing patterns associated with protein turnover. In addition, around 50% of hypothetical protein present in the networks

MSOAR 2.0: Incorporating tandem duplications into ortholog assignment based on genome rearrangement

Directory of Open Access Journals (Sweden)

Zhang Liqing

2010-01-01

Full Text Available Abstract Background Ortholog assignment is a critical and fundamental problem in comparative genomics, since orthologs are considered to be functional counterparts in different species and can be used to infer molecular functions of one species from those of other species. MSOAR is a recently developed high-throughput system for assigning one-to-one orthologs between closely related species on a genome scale. It attempts to reconstruct the evolutionary history of input genomes in terms of genome rearrangement and gene duplication events. It assumes that a gene duplication event inserts a duplicated gene into the genome of interest at a random location (i.e., the random duplication model. However, in practice, biologists believe that genes are often duplicated by tandem duplications, where a duplicated gene is located next to the original copy (i.e., the tandem duplication model. Results In this paper, we develop MSOAR 2.0, an improved system for one-to-one ortholog assignment. For a pair of input genomes, the system first focuses on the tandemly duplicated genes of each genome and tries to identify among them those that were duplicated after the speciation (i.e., the so-called inparalogs, using a simple phylogenetic tree reconciliation method. For each such set of tandemly duplicated inparalogs, all but one gene will be deleted from the concerned genome (because they cannot possibly appear in any one-to-one ortholog pairs, and MSOAR is invoked. Using both simulated and real data experiments, we show that MSOAR 2.0 is able to achieve a better sensitivity and specificity than MSOAR. In comparison with the well-known genome-scale ortholog assignment tool InParanoid, Ensembl ortholog database, and the orthology information extracted from the well-known whole-genome multiple alignment program MultiZ, MSOAR 2.0 shows the highest sensitivity. Although the specificity of MSOAR 2.0 is slightly worse than that of InParanoid in the real data experiments

Taxon (Viridiplantae) - PGDBj - Ortholog DB | LSDB Archive [Life Science Database Archive metadata

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Taxon (Cyanobacteria) - PGDBj - Ortholog DB | LSDB Archive [Life Science Database Archive metadata

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Protein (Viridiplantae) - PGDBj - Ortholog DB | LSDB Archive [Life Science Database Archive metadata

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Full Text Available ase Description Download License Update History of This Database Site Policy | Contact Us Protein (Viridiplantae) - PGDBj - Ortholog DB | LSDB Archive ... ...List Contact us PGDBj - Ortholog DB Protein (Viridiplantae) Data detail Data name Protein (Viridiplantae) DO...switchLanguage; BLAST Search Image Search Home About Archive Update History Data

Cis-regulatory signatures of orthologous stress-associated bZIP transcription factors from rice, sorghum and Arabidopsis based on phylogenetic footprints

Directory of Open Access Journals (Sweden)

Xu Fuyu

2012-09-01

Full Text Available Abstract Background The potential contribution of upstream sequence variation to the unique features of orthologous genes is just beginning to be unraveled. A core subset of stress-associated bZIP transcription factors from rice (Oryza sativa formed ten clusters of orthologous groups (COG with genes from the monocot sorghum (Sorghum bicolor and dicot Arabidopsis (Arabidopsis thaliana. The total cis-regulatory information content of each stress-associated COG was examined by phylogenetic footprinting to reveal ortholog-specific, lineage-specific and species-specific conservation patterns. Results The most apparent pattern observed was the occurrence of spatially conserved ‘core modules’ among the COGs but not among paralogs. These core modules are comprised of various combinations of two to four putative transcription factor binding site (TFBS classes associated with either developmental or stress-related functions. Outside the core modules are specific stress (ABA, oxidative, abiotic, biotic or organ-associated signals, which may be functioning as ‘regulatory fine-tuners’ and further define lineage-specific and species-specific cis-regulatory signatures. Orthologous monocot and dicot promoters have distinct TFBS classes involved in disease and oxidative-regulated expression, while the orthologous rice and sorghum promoters have distinct combinations of root-specific signals, a pattern that is not particularly conserved in Arabidopsis. Conclusions Patterns of cis-regulatory conservation imply that each ortholog has distinct signatures, further suggesting that they are potentially unique in a regulatory context despite the presumed conservation of broad biological function during speciation. Based on the observed patterns of conservation, we postulate that core modules are likely primary determinants of basal developmental programming, which may be integrated with and further elaborated by additional intrinsic or extrinsic signals in

Protein (Cyanobacteria) - PGDBj - Ortholog DB | LSDB Archive [Life Science Database Archive metadata

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Full Text Available ut This Database Database Description Download License Update History of This Database Site Policy | Contact Us Protein (Cyanobacteria) - PGDBj - Ortholog DB | LSDB Archive ... ...List Contact us PGDBj - Ortholog DB Protein (Cyanobacteria) Data detail Data name Protein (Cyanobacteria) DO...switchLanguage; BLAST Search Image Search Home About Archive Update History Data

Assessing the evolutionary rate of positional orthologous genes in prokaryotes using synteny data

Directory of Open Access Journals (Sweden)

Lespinet Olivier

2007-11-01

Full Text Available Abstract Background Comparison of completely sequenced microbial genomes has revealed how fluid these genomes are. Detecting synteny blocks requires reliable methods to determining the orthologs among the whole set of homologs detected by exhaustive comparisons between each pair of completely sequenced genomes. This is a complex and difficult problem in the field of comparative genomics but will help to better understand the way prokaryotic genomes are evolving. Results We have developed a suite of programs that automate three essential steps to study conservation of gene order, and validated them with a set of 107 bacteria and archaea that cover the majority of the prokaryotic taxonomic space. We identified the whole set of shared homologs between two or more species and computed the evolutionary distance separating each pair of homologs. We applied two strategies to extract from the set of homologs a collection of valid orthologs shared by at least two genomes. The first computes the Reciprocal Smallest Distance (RSD using the PAM distances separating pairs of homologs. The second method groups homologs in families and reconstructs each family's evolutionary tree, distinguishing bona fide orthologs as well as paralogs created after the last speciation event. Although the phylogenetic tree method often succeeds where RSD fails, the reverse could occasionally be true. Accordingly, we used the data obtained with either methods or their intersection to number the orthologs that are adjacent in for each pair of genomes, the Positional Orthologous Genes (POGs, and to further study their properties. Once all these synteny blocks have been detected, we showed that POGs are subject to more evolutionary constraints than orthologs outside synteny groups, whichever the taxonomic distance separating the compared organisms. Conclusion The suite of programs described in this paper allows a reliable detection of orthologs and is useful for evaluating gene

eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences

OpenAIRE

Huerta-Cepas, J.; Szklarczyk, D.; Forslund, K.; Cook, H.; Heller, D.; Walter, M.C.; Rattei, T.; Mende, D.R.; Sunagawa, S.; Kuhn, M.; Jensen, L.J.; von Mering, C.; Bork, P.

2016-01-01

eggNOG is a public resource that provides Orthologous Groups (OGs) of proteins at different taxonomic levels, each with integrated and summarized functional annotations. Developments since the latest public release include changes to the algorithm for creating OGs across taxonomic levels, making nested groups hierarchically consistent. This allows for a better propagation of functional terms across nested OGs and led to the novel annotation of 95 890 previously uncharacterized OGs, increasing...

wALADin benzimidazoles differentially modulate the function of porphobilinogen synthase orthologs.

Science.gov (United States)

Lentz, Christian S; Halls, Victoria S; Hannam, Jeffrey S; Strassel, Silke; Lawrence, Sarah H; Jaffe, Eileen K; Famulok, Michael; Hoerauf, Achim; Pfarr, Kenneth M

2014-03-27

The heme biosynthesis enzyme porphobilinogen synthase (PBGS) is a potential drug target in several human pathogens. wALADin1 benzimidazoles have emerged as species-selective PBGS inhibitors against Wolbachia endobacteria of filarial worms. In the present study, we have systematically tested wALADins against PBGS orthologs from bacteria, protozoa, metazoa, and plants to elucidate the inhibitory spectrum. However, the effect of wALADin1 on different PBGS orthologs was not limited to inhibition: several orthologs were stimulated by wALADin1; others remained unaffected. We demonstrate that wALADins allosterically modulate the PBGS homooligomeric equilibrium with inhibition mediated by favoring low-activity oligomers, while 5-aminolevulinic acid, Mg(2+), or K(+) stabilized high-activity oligomers. Pseudomonas aeruginosa PBGS could be inhibited or stimulated by wALADin1 depending on these factors and pH. We have defined the wALADin chemotypes responsible for either inhibition or stimulation, facilitating the design of tailored PBGS modulators for potential application as antimicrobial agents, herbicides, or drugs for porphyric disorders.

MBGD update 2015: microbial genome database for flexible ortholog analysis utilizing a diverse set of genomic data.

Science.gov (United States)

Uchiyama, Ikuo; Mihara, Motohiro; Nishide, Hiroyo; Chiba, Hirokazu

2015-01-01

The microbial genome database for comparative analysis (MBGD) (available at http://mbgd.genome.ad.jp/) is a comprehensive ortholog database for flexible comparative analysis of microbial genomes, where the users are allowed to create an ortholog table among any specified set of organisms. Because of the rapid increase in microbial genome data owing to the next-generation sequencing technology, it becomes increasingly challenging to maintain high-quality orthology relationships while allowing the users to incorporate the latest genomic data available into an analysis. Because many of the recently accumulating genomic data are draft genome sequences for which some complete genome sequences of the same or closely related species are available, MBGD now stores draft genome data and allows the users to incorporate them into a user-specific ortholog database using the MyMBGD functionality. In this function, draft genome data are incorporated into an existing ortholog table created only from the complete genome data in an incremental manner to prevent low-quality draft data from affecting clustering results. In addition, to provide high-quality orthology relationships, the standard ortholog table containing all the representative genomes, which is first created by the rapid classification program DomClust, is now refined using DomRefine, a recently developed program for improving domain-level clustering using multiple sequence alignment information. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Identification, developmental expression and regulation of the Xenopus ortholog of human FANCG/XRCC9.

Science.gov (United States)

Stone, Stacie; Sobeck, Alexandra; van Kogelenberg, Margriet; de Graaf, Bendert; Joenje, Hans; Christian, Jan; Hoatlin, Maureen E

2007-07-01

Fanconi anemia (FA) is associated with variable developmental abnormalities, bone marrow failure and cancer susceptibility. FANCG/XRCC9 is member of the FA core complex, a group of proteins that control the monoubiquitylation of FANCD2, an event that plays a critical role in maintaining genomic stability. Here we report the identification of the Xenopus laevis ortholog of human FANCG (xFANCG), its expression during development, and its molecular interactions with a partner protein, xFANCA. The xFANCG protein sequence is 47% similar to its human ortholog, with highest conservation in the two putative N-terminal leucine zippers and the tetratricopeptide repeat (TPR) motifs. xFANCG is maternally and zygotically transcribed. Prior to the midblastula stage, a single xFANCG transcript is observed but two additional alternatively spliced mRNAs are detected after the midblastula transition. One of the variants is predicted to encode a novel isoform of xFANCG lacking exon 2. The mutual association between FANCG and FANCA required for their nuclear import is conserved in Xenopus egg extracts. Our data demonstrate that interactions between FANCA and FANCG occur at the earliest stage of vertebrate development and raise the possibility that functionally different isoforms of xFANCG may play a role in early development.

An Effective Big Data Supervised Imbalanced Classification Approach for Ortholog Detection in Related Yeast Species

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Deborah Galpert

2015-01-01

Full Text Available Orthology detection requires more effective scaling algorithms. In this paper, a set of gene pair features based on similarity measures (alignment scores, sequence length, gene membership to conserved regions, and physicochemical profiles are combined in a supervised pairwise ortholog detection approach to improve effectiveness considering low ortholog ratios in relation to the possible pairwise comparison between two genomes. In this scenario, big data supervised classifiers managing imbalance between ortholog and nonortholog pair classes allow for an effective scaling solution built from two genomes and extended to other genome pairs. The supervised approach was compared with RBH, RSD, and OMA algorithms by using the following yeast genome pairs: Saccharomyces cerevisiae-Kluyveromyces lactis, Saccharomyces cerevisiae-Candida glabrata, and Saccharomyces cerevisiae-Schizosaccharomyces pombe as benchmark datasets. Because of the large amount of imbalanced data, the building and testing of the supervised model were only possible by using big data supervised classifiers managing imbalance. Evaluation metrics taking low ortholog ratios into account were applied. From the effectiveness perspective, MapReduce Random Oversampling combined with Spark SVM outperformed RBH, RSD, and OMA, probably because of the consideration of gene pair features beyond alignment similarities combined with the advances in big data supervised classification.

The Princeton Protein Orthology Database (P-POD): a comparative genomics analysis tool for biologists.

OpenAIRE

Sven Heinicke; Michael S Livstone; Charles Lu; Rose Oughtred; Fan Kang; Samuel V Angiuoli; Owen White; David Botstein; Kara Dolinski

2007-01-01

Many biological databases that provide comparative genomics information and tools are now available on the internet. While certainly quite useful, to our knowledge none of the existing databases combine results from multiple comparative genomics methods with manually curated information from the literature. Here we describe the Princeton Protein Orthology Database (P-POD, http://ortholog.princeton.edu), a user-friendly database system that allows users to find and visualize the phylogenetic r...

Clusters of orthologous genes for 41 archaeal genomes and implications for evolutionary genomics of archaea

OpenAIRE

Wolf Yuri I; Novichkov Pavel S; Sorokin Alexander V; Makarova Kira S; Koonin Eugene V

2007-01-01

Abstract Background An evolutionary classification of genes from sequenced genomes that distinguishes between orthologs and paralogs is indispensable for genome annotation and evolutionary reconstruction. Shortly after multiple genome sequences of bacteria, archaea, and unicellular eukaryotes became available, an attempt on such a classification was implemented in Clusters of Orthologous Groups of proteins (COGs). Rapid accumulation of genome sequences creates opportunities for refining COGs ...

OrthoVenn: a web server for genome wide comparison and annotation of orthologous clusters across multiple species

Science.gov (United States)

Genome wide analysis of orthologous clusters is an important component of comparative genomics studies. Identifying the overlap among orthologous clusters can enable us to elucidate the function and evolution of proteins across multiple species. Here, we report a web platform named OrthoVenn that i...

Cloning and transcription analysis of an AGAMOUS- and SEEDSTICK ortholog in the orchid Dendrobium thyrsiflorum (Reichb. f.)

DEFF Research Database (Denmark)

Skipper, Martin; Johansen, Louise Buchholt; Pedersen, Kim B.

2006-01-01

Studies have shown that several plant species posses AGAMOUS (AG) and SEEDSTICK (STK) orthologs. These genes are part of the so-called C- and D MADS-box gene lineages and play key roles in ovule development in Arabidopsis thaliana. We have cloned an AG- and STK ortholog in the orchid Dendrobium...

An integrated artificial neural networks approach for predicting global radiation

International Nuclear Information System (INIS)

Azadeh, A.; Maghsoudi, A.; Sohrabkhani, S.

2009-01-01

This article presents an integrated artificial neural network (ANN) approach for predicting solar global radiation by climatological variables. The integrated ANN trains and tests data with multi layer perceptron (MLP) approach which has the lowest mean absolute percentage error (MAPE). The proposed approach is particularly useful for locations where no available measurement equipment. Also, it considers all related climatological and meteorological parameters as input variables. To show the applicability and superiority of the integrated ANN approach, monthly data were collected for 6 years (1995-2000) in six nominal cities in Iran. Separate model for each city is considered and the quantity of solar global radiation in each city is calculated. Furthermore an integrated ANN model has been introduced for prediction of solar global radiation. The acquired results of the integrated model have shown high accuracy of about 94%. The results of the integrated model have been compared with traditional angstrom's model to show its considerable accuracy. Therefore, the proposed approach can be used as an efficient tool for prediction of solar radiation in the remote and rural locations with no direct measurement equipment.

Surveying alignment-free features for Ortholog detection in related yeast proteomes by using supervised big data classifiers.

Science.gov (United States)

Galpert, Deborah; Fernández, Alberto; Herrera, Francisco; Antunes, Agostinho; Molina-Ruiz, Reinaldo; Agüero-Chapin, Guillermin

2018-05-03

The development of new ortholog detection algorithms and the improvement of existing ones are of major importance in functional genomics. We have previously introduced a successful supervised pairwise ortholog classification approach implemented in a big data platform that considered several pairwise protein features and the low ortholog pair ratios found between two annotated proteomes (Galpert, D et al., BioMed Research International, 2015). The supervised models were built and tested using a Saccharomycete yeast benchmark dataset proposed by Salichos and Rokas (2011). Despite several pairwise protein features being combined in a supervised big data approach; they all, to some extent were alignment-based features and the proposed algorithms were evaluated on a unique test set. Here, we aim to evaluate the impact of alignment-free features on the performance of supervised models implemented in the Spark big data platform for pairwise ortholog detection in several related yeast proteomes. The Spark Random Forest and Decision Trees with oversampling and undersampling techniques, and built with only alignment-based similarity measures or combined with several alignment-free pairwise protein features showed the highest classification performance for ortholog detection in three yeast proteome pairs. Although such supervised approaches outperformed traditional methods, there were no significant differences between the exclusive use of alignment-based similarity measures and their combination with alignment-free features, even within the twilight zone of the studied proteomes. Just when alignment-based and alignment-free features were combined in Spark Decision Trees with imbalance management, a higher success rate (98.71%) within the twilight zone could be achieved for a yeast proteome pair that underwent a whole genome duplication. The feature selection study showed that alignment-based features were top-ranked for the best classifiers while the runners-up were

UK Environmental Prediction - integration and evaluation at the convective scale

Science.gov (United States)

Fallmann, Joachim; Lewis, Huw; Castillo, Juan Manuel; Pearson, David; Harris, Chris; Saulter, Andy; Bricheno, Lucy; Blyth, Eleanor

2016-04-01

Traditionally, the simulation of regional ocean, wave and atmosphere components of the Earth System have been considered separately, with some information on other components provided by means of boundary or forcing conditions. More recently, the potential value of a more integrated approach, as required for global climate and Earth System prediction, for regional short-term applications has begun to gain increasing research effort. In the UK, this activity is motivated by an understanding that accurate prediction and warning of the impacts of severe weather requires an integrated approach to forecasting. The substantial impacts on individuals, businesses and infrastructure of such events indicate a pressing need to understand better the value that might be delivered through more integrated environmental prediction. To address this need, the Met Office, NERC Centre for Ecology & Hydrology and NERC National Oceanography Centre have begun to develop the foundations of a coupled high resolution probabilistic forecast system for the UK at km-scale. This links together existing model components of the atmosphere, coastal ocean, land surface and hydrology. Our initial focus has been on a 2-year Prototype project to demonstrate the UK coupled prediction concept in research mode. This presentation will provide an update on UK environmental prediction activities. We will present the results from the initial implementation of an atmosphere-land-ocean coupled system, including a new eddy-permitting resolution ocean component, and discuss progress and initial results from further development to integrate wave interactions in this relatively high resolution system. We will discuss future directions and opportunities for collaboration in environmental prediction, and the challenges to realise the potential of integrated regional coupled forecasting for improving predictions and applications.

TaWRKY68 responses to biotic stresses are revealed by the orthologous genes from major cereals

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Bo Ding

2014-01-01

Full Text Available WRKY transcription factors have been extensively characterized in the past 20 years, but in wheat, studies onWRKY genes and their function are lagging behind many other species. To explore the function of wheat WRKY genes, we identified a TaWRKY68 gene from a common wheat cultivar. It encodes a protein comprising 313 amino acids which harbors 19 conserved motifs or active sites. Gene expression patterns were determined by analyzing microarray data of TaWRKY68 in wheat and of orthologous genes from maize, rice and barley using Genevestigator. TaWRKY68 orthologs were identified and clustered using DELTA-BLAST and COBALT programs available at NCBI. The results showed that these genes, which are expressed in all tissues tested, had relatively higher levels in the roots and were up-regulated in response to biotic stresses. Bioinformatics results were confirmed by RT-PCR experiments using wheat plants infected by Agrobacterium tumefaciens and Blumeria graminis, or treated with Deoxynivalenol, a Fusarium graminearum-induced mycotoxin in wheat or barley. In summary,TaWRKY68 functions differ during plant developmental stages and might be representing a hub gene function in wheat responses to various biotic stresses. It was also found that including data from major cereal genes in the bioinformatics analysis gave more accurate and comprehensive predictions of wheat gene functions.

BOG: R-package for Bacterium and virus analysis of Orthologous Groups

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Jincheol Park

2015-01-01

Full Text Available BOG (Bacterium and virus analysis of Orthologous Groups is a package for identifying groups of differentially regulated genes in the light of gene functions for various virus and bacteria genomes. It is designed to identify Clusters of Orthologous Groups (COGs that are enriched among genes that have gone through significant changes under different conditions. This would contribute to the detection of pathogens, an important scientific research area of relevance in uncovering bioterrorism, among others. Particular statistical analyses include hypergeometric, Mann–Whitney rank sum, and gene set enrichment. Results from the analyses are organized and presented in tabular and graphical forms for ease of understanding and dissemination of results. BOG is implemented as an R-package, which is available from CRAN or can be downloaded from http://www.stat.osu.edu/~statgen/SOFTWARE/BOG/.

Archaeal Clusters of Orthologous Genes (arCOGs): An Update and Application for Analysis of Shared Features between Thermococcales, Methanococcales, and Methanobacteriales

OpenAIRE

Makarova, Kira; Wolf, Yuri; Koonin, Eugene

2015-01-01

With the continuously accelerating genome sequencing from diverse groups of archaea and bacteria, accurate identification of gene orthology and availability of readily expandable clusters of orthologous genes are essential for the functional annotation of new genomes. We report an update of the collection of archaeal Clusters of Orthologous Genes (arCOGs) to cover, on average, 91% of the protein-coding genes in 168 archaeal genomes. The new arCOGs were constructed using refined algorithms for...

Cloning of the cDNA for murine von Willebrand factor and identification of orthologous genes reveals the extent of conservation among diverse species.

Science.gov (United States)

Chitta, Mohan S; Duhé, Roy J; Kermode, John C

2007-05-01

Interaction of von Willebrand factor (VWF) with circulating platelets promotes hemostasis when a blood vessel is injured. The A1 domain of VWF is responsible for the initial interaction with platelets and is well conserved among species. Knowledge of the cDNA and genomic DNA sequences for human VWF allowed us to predict the cDNA sequence for murine VWF in silico and amplify its entire coding region by RT-PCR. The murine VWF cDNA has an open reading frame of 8,442 bp, encoding a protein of 2,813 amino acid residues with 83% identity to human pre-pro-VWF. The same strategy was used to predict in silico the cDNA sequence for the ortholog of VWF in a further six species. Many of these predictions diverged substantially from the putative Reference Sequences derived by ab initio methods. Our predicted sequences indicated that the VWF gene has a conserved structure of 52 exons in all seven mammalian species examined, as well as in the chicken. There is a minor structural variation in the pufferfish Takifugu rubripes insofar as the VWF gene in this species has 53 exons. Comparison of the translated amino acid sequences also revealed a high degree of conservation. In particular, the cysteine residues are conserved precisely throughout both the pro-peptide and the mature VWF sequence in all species, with a minor exception in the pufferfish VWF ortholog where two adjacent cysteine residues are omitted. The marked conservation of cysteine residues emphasizes the importance of the intricate pattern of disulfide bonds in governing the structure of pro-VWF and regulating the function of the mature VWF protein. It should also be emphasized that many of the conserved features of the VWF gene and protein were obscured when the comparison among species was based on the putative Reference Sequences instead of our predicted cDNA sequences.

On the Use of Gene Ontology Annotations to Assess Functional Similarity among Orthologs and Paralogs: A Short Report.

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Paul D Thomas

Full Text Available A recent paper (Nehrt et al., PLoS Comput. Biol. 7:e1002073, 2011 has proposed a metric for the "functional similarity" between two genes that uses only the Gene Ontology (GO annotations directly derived from published experimental results. Applying this metric, the authors concluded that paralogous genes within the mouse genome or the human genome are more functionally similar on average than orthologous genes between these genomes, an unexpected result with broad implications if true. We suggest, based on both theoretical and empirical considerations, that this proposed metric should not be interpreted as a functional similarity, and therefore cannot be used to support any conclusions about the "ortholog conjecture" (or, more properly, the "ortholog functional conservation hypothesis". First, we reexamine the case studies presented by Nehrt et al. as examples of orthologs with divergent functions, and come to a very different conclusion: they actually exemplify how GO annotations for orthologous genes provide complementary information about conserved biological functions. We then show that there is a global ascertainment bias in the experiment-based GO annotations for human and mouse genes: particular types of experiments tend to be performed in different model organisms. We conclude that the reported statistical differences in annotations between pairs of orthologous genes do not reflect differences in biological function, but rather complementarity in experimental approaches. Our results underscore two general considerations for researchers proposing novel types of analysis based on the GO: 1 that GO annotations are often incomplete, potentially in a biased manner, and subject to an "open world assumption" (absence of an annotation does not imply absence of a function, and 2 that conclusions drawn from a novel, large-scale GO analysis should whenever possible be supported by careful, in-depth examination of examples, to help ensure the

Clusters of orthologous genes for 41 archaeal genomes and implications for evolutionary genomics of archaea

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Wolf Yuri I

2007-11-01

Full Text Available Abstract Background An evolutionary classification of genes from sequenced genomes that distinguishes between orthologs and paralogs is indispensable for genome annotation and evolutionary reconstruction. Shortly after multiple genome sequences of bacteria, archaea, and unicellular eukaryotes became available, an attempt on such a classification was implemented in Clusters of Orthologous Groups of proteins (COGs. Rapid accumulation of genome sequences creates opportunities for refining COGs but also represents a challenge because of error amplification. One of the practical strategies involves construction of refined COGs for phylogenetically compact subsets of genomes. Results New Archaeal Clusters of Orthologous Genes (arCOGs were constructed for 41 archaeal genomes (13 Crenarchaeota, 27 Euryarchaeota and one Nanoarchaeon using an improved procedure that employs a similarity tree between smaller, group-specific clusters, semi-automatically partitions orthology domains in multidomain proteins, and uses profile searches for identification of remote orthologs. The annotation of arCOGs is a consensus between three assignments based on the COGs, the CDD database, and the annotations of homologs in the NR database. The 7538 arCOGs, on average, cover ~88% of the genes in a genome compared to a ~76% coverage in COGs. The finer granularity of ortholog identification in the arCOGs is apparent from the fact that 4538 arCOGs correspond to 2362 COGs; ~40% of the arCOGs are new. The archaeal gene core (protein-coding genes found in all 41 genome consists of 166 arCOGs. The arCOGs were used to reconstruct gene loss and gene gain events during archaeal evolution and gene sets of ancestral forms. The Last Archaeal Common Ancestor (LACA is conservatively estimated to possess 996 genes compared to 1245 and 1335 genes for the last common ancestors of Crenarchaeota and Euryarchaeota, respectively. It is inferred that LACA was a chemoautotrophic hyperthermophile

GAPIT: genome association and prediction integrated tool.

Science.gov (United States)

Lipka, Alexander E; Tian, Feng; Wang, Qishan; Peiffer, Jason; Li, Meng; Bradbury, Peter J; Gore, Michael A; Buckler, Edward S; Zhang, Zhiwu

2012-09-15

Software programs that conduct genome-wide association studies and genomic prediction and selection need to use methodologies that maximize statistical power, provide high prediction accuracy and run in a computationally efficient manner. We developed an R package called Genome Association and Prediction Integrated Tool (GAPIT) that implements advanced statistical methods including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large datasets in excess of 10 000 individuals and 1 million single-nucleotide polymorphisms with minimal computational time, while providing user-friendly access and concise tables and graphs to interpret results. http://www.maizegenetics.net/GAPIT. zhiwu.zhang@cornell.edu Supplementary data are available at Bioinformatics online.

Experimental-confirmation and functional-annotation of predicted proteins in the chicken genome

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McCarthy Fiona M

2007-11-01

Full Text Available Abstract Background The chicken genome was sequenced because of its phylogenetic position as a non-mammalian vertebrate, its use as a biomedical model especially to study embryology and development, its role as a source of human disease organisms and its importance as the major source of animal derived food protein. However, genomic sequence data is, in itself, of limited value; generally it is not equivalent to understanding biological function. The benefit of having a genome sequence is that it provides a basis for functional genomics. However, the sequence data currently available is poorly structurally and functionally annotated and many genes do not have standard nomenclature assigned. Results We analysed eight chicken tissues and improved the chicken genome structural annotation by providing experimental support for the in vivo expression of 7,809 computationally predicted proteins, including 30 chicken proteins that were only electronically predicted or hypothetical translations in human. To improve functional annotation (based on Gene Ontology, we mapped these identified proteins to their human and mouse orthologs and used this orthology to transfer Gene Ontology (GO functional annotations to the chicken proteins. The 8,213 orthology-based GO annotations that we produced represent an 8% increase in currently available chicken GO annotations. Orthologous chicken products were also assigned standardized nomenclature based on current chicken nomenclature guidelines. Conclusion We demonstrate the utility of high-throughput expression proteomics for rapid experimental structural annotation of a newly sequenced eukaryote genome. These experimentally-supported predicted proteins were further annotated by assigning the proteins with standardized nomenclature and functional annotation. This method is widely applicable to a diverse range of species. Moreover, information from one genome can be used to improve the annotation of other genomes and

Integration of Multi-Modal Biomedical Data to Predict Cancer Grade and Patient Survival.

Science.gov (United States)

Phan, John H; Hoffman, Ryan; Kothari, Sonal; Wu, Po-Yen; Wang, May D

2016-02-01

The Big Data era in Biomedical research has resulted in large-cohort data repositories such as The Cancer Genome Atlas (TCGA). These repositories routinely contain hundreds of matched patient samples for genomic, proteomic, imaging, and clinical data modalities, enabling holistic and multi-modal integrative analysis of human disease. Using TCGA renal and ovarian cancer data, we conducted a novel investigation of multi-modal data integration by combining histopathological image and RNA-seq data. We compared the performances of two integrative prediction methods: majority vote and stacked generalization. Results indicate that integration of multiple data modalities improves prediction of cancer grade and outcome. Specifically, stacked generalization, a method that integrates multiple data modalities to produce a single prediction result, outperforms both single-data-modality prediction and majority vote. Moreover, stacked generalization reveals the contribution of each data modality (and specific features within each data modality) to the final prediction result and may provide biological insights to explain prediction performance.

BIPS: BIANA Interolog Prediction Server. A tool for protein-protein interaction inference.

Science.gov (United States)

Garcia-Garcia, Javier; Schleker, Sylvia; Klein-Seetharaman, Judith; Oliva, Baldo

2012-07-01

Protein-protein interactions (PPIs) play a crucial role in biology, and high-throughput experiments have greatly increased the coverage of known interactions. Still, identification of complete inter- and intraspecies interactomes is far from being complete. Experimental data can be complemented by the prediction of PPIs within an organism or between two organisms based on the known interactions of the orthologous genes of other organisms (interologs). Here, we present the BIANA (Biologic Interactions and Network Analysis) Interolog Prediction Server (BIPS), which offers a web-based interface to facilitate PPI predictions based on interolog information. BIPS benefits from the capabilities of the framework BIANA to integrate the several PPI-related databases. Additional metadata can be used to improve the reliability of the predicted interactions. Sensitivity and specificity of the server have been calculated using known PPIs from different interactomes using a leave-one-out approach. The specificity is between 72 and 98%, whereas sensitivity varies between 1 and 59%, depending on the sequence identity cut-off used to calculate similarities between sequences. BIPS is freely accessible at http://sbi.imim.es/BIPS.php.

Toward integration of genomic selection with crop modelling: the development of an integrated approach to predicting rice heading dates.

Science.gov (United States)

Onogi, Akio; Watanabe, Maya; Mochizuki, Toshihiro; Hayashi, Takeshi; Nakagawa, Hiroshi; Hasegawa, Toshihiro; Iwata, Hiroyoshi

2016-04-01

It is suggested that accuracy in predicting plant phenotypes can be improved by integrating genomic prediction with crop modelling in a single hierarchical model. Accurate prediction of phenotypes is important for plant breeding and management. Although genomic prediction/selection aims to predict phenotypes on the basis of whole-genome marker information, it is often difficult to predict phenotypes of complex traits in diverse environments, because plant phenotypes are often influenced by genotype-environment interaction. A possible remedy is to integrate genomic prediction with crop/ecophysiological modelling, which enables us to predict plant phenotypes using environmental and management information. To this end, in the present study, we developed a novel method for integrating genomic prediction with phenological modelling of Asian rice (Oryza sativa, L.), allowing the heading date of untested genotypes in untested environments to be predicted. The method simultaneously infers the phenological model parameters and whole-genome marker effects on the parameters in a Bayesian framework. By cultivating backcross inbred lines of Koshihikari × Kasalath in nine environments, we evaluated the potential of the proposed method in comparison with conventional genomic prediction, phenological modelling, and two-step methods that applied genomic prediction to phenological model parameters inferred from Nelder-Mead or Markov chain Monte Carlo algorithms. In predicting heading dates of untested lines in untested environments, the proposed and two-step methods tended to provide more accurate predictions than the conventional genomic prediction methods, particularly in environments where phenotypes from environments similar to the target environment were unavailable for training genomic prediction. The proposed method showed greater accuracy in prediction than the two-step methods in all cross-validation schemes tested, suggesting the potential of the integrated approach in

6-Pyruvoyltetrahydropterin synthase orthologs of either a single or dual domain structure are responsible for tetrahydrobiopterin synthesis in bacteria.

Science.gov (United States)

Kong, Jin Sun; Kang, Ji-Youn; Kim, Hye Lim; Kwon, O-Seob; Lee, Kon Ho; Park, Young Shik

2006-09-04

6-Pyruvoyltetrahydropterin synthase (PTPS) catalyzes the second step of tetrahydrobiopterin (BH4) synthesis. We previously identified PTPS orthologs (bPTPS-Is) in bacteria which do not produce BH4. In this study we disrupted the gene encoding bPTPS-I in Synechococcus sp. PCC 7942, which produces BH4-glucoside. The mutant was normal in BH4-glucoside production, demonstrating that bPTPS-I does not participate in BH4 synthesis in vivo and bringing us a new PTPS ortholog (bPTPS-II) of a bimodular polypeptide. The recombinant Synechococcus bPTPS-II was assayed in vitro to show PTPS activity higher than human enzyme. Further computational analysis revealed the presence of mono and bimodular bPTPS-II orthologs mostly in green sulfur bacteria and cyanobacteria, respectively, which are well known for BH4-glycoside production. In summary we found new bacterial PTPS orthologs, having either a single or dual domain structure and being responsible for BH4 synthesis in vivo, thereby disclosing all the bacterial PTPS homologs.

Database Description - PGDBj - Ortholog DB | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available e relevant data in the databases. By submitting queries to the PGDBj Ortholog DB with keywords or amino acid sequences, users... taxa including both model plants and crop plants. Following the links obtained, users can retrieve the actu

A multimetric approach for predicting the ecological integrity of New Zealand streams

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Clapcott J.E.

2014-01-01

Full Text Available Integrating multiple measures of stream health into a combined metric can provide a holistic assessment of the ecological integrity of a stream. The aim of this study was to develop a multimetric index (MMI of stream integrity based on predictive modelling of national data sets of water quality, macroinvertebrates, fish and ecosystem process metrics. We used a boosted regression tree approach to calculate an observed/expected score for each metric prior to combining metrics in a MMI based on data availability and the strength of predictive models. The resulting MMI provides a geographically meaningful prediction of the ecological integrity of rivers in New Zealand, but identifies limitations in data and approach, providing focus for ongoing research.

Proteinortho: Detection of (Co-)orthologs in large-scale analysis

OpenAIRE

Lechner, Marcus; Findeiß, Sven; Steiner, Lydia; Marz, Manja; Stadler, Peter F; Prohaska, Sonja J

2011-01-01

Abstract Background Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes i...

Frequent and recent retrotransposition of orthologous genes plays a role in the evolution of sperm glycolytic enzymes

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de Villena Fernando

2010-05-01

Full Text Available Abstract Background The central metabolic pathway of glycolysis converts glucose to pyruvate, with the net production of 2 ATP and 2 NADH per glucose molecule. Each of the ten reactions in this pathway is typically catalyzed by multiple isozymes encoded by a multigene family. Several isozymes in this pathway are expressed only during spermatogenesis, and gene targeting studies indicate that they are essential for sperm function and male fertility in mouse. At least three of the novel glycolytic isozymes are encoded by retrogenes (Pgk2, Aldoart1, and Aldoart2. Their restricted expression profile suggests that retrotransposition may play a significant role in the evolution of sperm glycolytic enzymes. Results We conducted a comprehensive genomic analysis of glycolytic enzymes in the human and mouse genomes and identified several intronless copies for all enzymes in the pathway, except Pfk. Within each gene family, a single orthologous gene was typically retrotransposed frequently and independently in both species. Several retroposed sequences maintained open reading frames (ORFs and/or provided evidence of alternatively spliced exons. We analyzed expression of sequences with ORFs and Gpi1 transcript in mouse spermatogenic cells. Conclusions Our analysis detected frequent, recent, and lineage-specific retrotransposition of orthologous glycolytic enzymes in the human and mouse genomes. Retrotransposition events are associated with LINE/LTR and genomic integration is random. We found evidence for the alternative splicing of parent genes. Many retroposed sequences have maintained ORFs, suggesting a functional role for these genes.

Structural integrity of frontostriatal connections predicts longitudinal changes in self-esteem.

Science.gov (United States)

Chavez, Robert S; Heatherton, Todd F

2017-06-01

Diverse neurological and psychiatric conditions are marked by a diminished sense of positive self-regard, and reductions in self-esteem are associated with risk for these disorders. Recent evidence has shown that the connectivity of frontostriatal circuitry reflects individual differences in self-esteem. However, it remains an open question as to whether the integrity of these connections can predict self-esteem changes over larger timescales. Using diffusion magnetic resonance imaging and probabilistic tractography, we demonstrate that the integrity of white matter pathways linking the medial prefrontal cortex to the ventral striatum predicts changes in self-esteem 8 months after initial scanning in a sample of 30 young adults. Individuals with greater integrity of this pathway during the scanning session at Time 1 showed increased levels of self-esteem at follow-up, whereas individuals with lower integrity showed stifled or decreased levels of self-esteem. These results provide evidence that frontostriatal white matter integrity predicts the trajectory of self-esteem development in early adulthood, which may contribute to blunted levels of positive self-regard seen in multiple psychiatric conditions, including depression and anxiety.

Genomic analysis of NAC transcription factors in banana (Musa acuminata) and definition of NAC orthologous groups for monocots and dicots.

Science.gov (United States)

Cenci, Albero; Guignon, Valentin; Roux, Nicolas; Rouard, Mathieu

2014-05-01

Identifying the molecular mechanisms underlying tolerance to abiotic stresses is important in crop breeding. A comprehensive understanding of the gene families associated with drought tolerance is therefore highly relevant. NAC transcription factors form a large plant-specific gene family involved in the regulation of tissue development and responses to biotic and abiotic stresses. The main goal of this study was to set up a framework of orthologous groups determined by an expert sequence comparison of NAC genes from both monocots and dicots. In order to clarify the orthologous relationships among NAC genes of different species, we performed an in-depth comparative study of four divergent taxa, in dicots and monocots, whose genomes have already been completely sequenced: Arabidopsis thaliana, Vitis vinifera, Musa acuminata and Oryza sativa. Due to independent evolution, NAC copy number is highly variable in these plant genomes. Based on an expert NAC sequence comparison, we propose forty orthologous groups of NAC sequences that were probably derived from an ancestor gene present in the most recent common ancestor of dicots and monocots. These orthologous groups provide a curated resource for large-scale protein sequence annotation of NAC transcription factors. The established orthology relationships also provide a useful reference for NAC function studies in newly sequenced genomes such as M. acuminata and other plant species.

Characterization of the Drosophila ortholog of the human Usher Syndrome type 1G protein sans.

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Fabio Demontis

Full Text Available BACKGROUND: The Usher syndrome (USH is the most frequent deaf-blindness hereditary disease in humans. Deafness is attributed to the disorganization of stereocilia in the inner ear. USH1, the most severe subtype, is associated with mutations in genes encoding myosin VIIa, harmonin, cadherin 23, protocadherin 15, and sans. Myosin VIIa, harmonin, cadherin 23, and protocadherin 15 physically interact in vitro and localize to stereocilia tips in vivo, indicating that they form functional complexes. Sans, in contrast, localizes to vesicle-like structures beneath the apical membrane of stereocilia-displaying hair cells. How mutations in sans result in deafness and blindness is not well understood. Orthologs of myosin VIIa and protocadherin 15 have been identified in Drosophila melanogaster and their genetic analysis has identified essential roles in auditory perception and microvilli morphogenesis, respectively. PRINCIPAL FINDINGS: Here, we have identified and characterized the Drosophila ortholog of human sans. Drosophila Sans is expressed in tubular organs of the embryo, in lens-secreting cone cells of the adult eye, and in microvilli-displaying follicle cells during oogenesis. Sans mutants are viable, fertile, and mutant follicle cells appear to form microvilli, indicating that Sans is dispensable for fly development and microvilli morphogenesis in the follicle epithelium. In follicle cells, Sans protein localizes, similar to its vertebrate ortholog, to intracellular punctate structures, which we have identified as early endosomes associated with the syntaxin Avalanche. CONCLUSIONS: Our work is consistent with an evolutionary conserved function of Sans in vesicle trafficking. Furthermore it provides a significant basis for further understanding of the role of this Usher syndrome ortholog in development and disease.

Identification of Putative Ortholog Gene Blocks Involved in Gestant and Lactating Mammary Gland Development: A Rodent Cross-Species Microarray Transcriptomics Approach

Science.gov (United States)

Rodríguez-Cruz, Maricela; Coral-Vázquez, Ramón M.; Hernández-Stengele, Gabriel; Sánchez, Raúl; Salazar, Emmanuel; Sanchez-Muñoz, Fausto; Encarnación-Guevara, Sergio; Ramírez-Salcedo, Jorge

2013-01-01

The mammary gland (MG) undergoes functional and metabolic changes during the transition from pregnancy to lactation, possibly by regulation of conserved genes. The objective was to elucidate orthologous genes, chromosome clusters and putative conserved transcriptional modules during MG development. We analyzed expression of 22,000 transcripts using murine microarrays and RNA samples of MG from virgin, pregnant, and lactating rats by cross-species hybridization. We identified 521 transcripts differentially expressed; upregulated in early (78%) and midpregnancy (89%) and early lactation (64%), but downregulated in mid-lactation (61%). Putative orthologous genes were identified. We mapped the altered genes to orthologous chromosomal locations in human and mouse. Eighteen sets of conserved genes associated with key cellular functions were revealed and conserved transcription factor binding site search entailed possible coregulation among all eight block sets of genes. This study demonstrates that the use of heterologous array hybridization for screening of orthologous gene expression from rat revealed sets of conserved genes arranged in chromosomal order implicated in signaling pathways and functional ontology. Results demonstrate the utilization power of comparative genomics and prove the feasibility of using rodent microarrays to identification of putative coexpressed orthologous genes involved in the control of human mammary gland development. PMID:24288657

An integrated logistic formula for prediction of complications from radiosurgery

International Nuclear Information System (INIS)

Flickinger, J.C.

1989-01-01

An integrated logistic model for predicting the probability of complications when small volumes of tissue receive an inhomogeneous radiation dose is described. This model can be used with either an exponential or linear quadratic correction for dose per fraction and time. Both the exponential and linear quadratic versions of this integrated logistic formula provide reasonable estimates of the tolerance of brain to radiosurgical dose distributions where there are small volumes of brain receiving high radiation doses and larger volumes receiving lower doses. This makes it possible to predict the probability of complications from stereotactic radiosurgery, as well as combinations of fractionated large volume irradiation with a radiosurgical boost. Complication probabilities predicted for single fraction radiosurgery with the Leksell Gamma Unit using 4, 8, 14, and 18 mm diameter collimators as well as for whole brain irradiation combined with a radiosurgical boost are presented. The exponential and linear quadratic versions of the integrated logistic formula provide useful methods of calculating the probability of complications from radiosurgical treatment

Cross activity of orthologous WRKY transcription factors in wheat and Arabidopsis

NARCIS (Netherlands)

Poietti, S.; Bertini, L.; Ent, S. van der; Leon Reyes, H.A.; Pieterse, C.M.J.; Tucci, M.; Caporale, C.; Caruso, C.

2011-01-01

WRKY proteins are transcription factors involved in many plant processes including plant responses to pathogens. Here, the cross activity of TaWRKY78 from the monocot wheat and AtWRKY20 from the dicot Arabidopsis on the cognate promoters of the orthologous PR4-type genes wPR4e and AtHEL of wheat and

Program integration of predictive maintenance with reliability centered maintenance

International Nuclear Information System (INIS)

Strong, D.K. Jr; Wray, D.M.

1990-01-01

This paper addresses improving the safety and reliability of power plants in a cost-effective manner by integrating the recently developed reliability centered maintenance techniques with the traditional predictive maintenance techniques of nuclear power plants. The topics of the paper include a description of reliability centered maintenance (RCM), enhancing RCM with predictive maintenance, predictive maintenance programs, condition monitoring techniques, performance test techniques, the mid-Atlantic Reliability Centered Maintenance Users Group, test guides and the benefits of shared guide development

A predicted protein interactome identifies conserved global networks and disease resistance subnetworks in maize.

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Matt eGeisler

2015-06-01

Full Text Available Interactomes are genome-wide roadmaps of protein-protein interactions. They have been produced for humans, yeast, the fruit fly, and Arabidopsis thaliana and have become invaluable tools for generating and testing hypotheses. A predicted interactome for Zea mays (PiZeaM is presented here as an aid to the research community for this valuable crop species. PiZeaM was built using a proven method of interologs (interacting orthologs that were identified using both one-to-one and many-to-many orthology between genomes of maize and reference species. Where both maize orthologs occurred for an experimentally determined interaction in the reference species, we predicted a likely interaction in maize. A total of 49,026 unique interactions for 6,004 maize proteins were predicted. These interactions are enriched for processes that are evolutionarily conserved, but include many otherwise poorly annotated proteins in maize. The predicted maize interactions were further analyzed by comparing annotation of interacting proteins, including different layers of ontology. A map of pairwise gene co-expression was also generated and compared to predicted interactions. Two global subnetworks were constructed for highly conserved interactions. These subnetworks showed clear clustering of proteins by function. Another subnetwork was created for disease response using a bait and prey strategy to capture interacting partners for proteins that respond to other organisms. Closer examination of this subnetwork revealed the connectivity between biotic and abiotic hormone stress pathways. We believe PiZeaM will provide a useful tool for the prediction of protein function and analysis of pathways for Z. mays researchers and is presented in this paper as a reference tool for the exploration of protein interactions in maize.

Predictive Solar-Integrated Commercial Building Load Control

Energy Technology Data Exchange (ETDEWEB)

Glasgow, Nathan [EdgePower Inc., Aspen, CO (United States)

2017-01-31

This report is the final technical report for the Department of Energy SunShot award number EE0007180 to EdgePower Inc., for the project entitled “Predictive Solar-Integrated Commercial Building Load Control.” The goal of this project was to successfully prove that the integration of solar forecasting and building load control can reduce demand charge costs for commercial building owners with solar PV. This proof of concept Tier 0 project demonstrated its value through a pilot project at a commercial building. This final report contains a summary of the work completed through he duration of the project. Clean Power Research was a sub-recipient on the award.

Online Sentence Comprehension in PPA: Verb-Based Integration and Prediction

Directory of Open Access Journals (Sweden)

Jennifer E Mack

2015-05-01

Full Text Available Introduction. Impaired language comprehension is frequently observed in primary progressive aphasia (PPA. Word comprehension deficits are characteristic of the semantic variant (PPA-S whereas sentence comprehension deficits are more prevalent in the agrammatic (PPA-G and logopenic (PPA-L variants (Amici et al., 2007; Gorno-Tempini et al., 2011; Thompson et al., 2013. Word and sentence comprehension deficits have also been shown to have distinct neural substrates in PPA (Mesulam, Thompson, Weintraub, & Rogalski, in press. However, little is known about the relationship between word and sentence comprehension processes in PPA, specifically how words are accessed, combined, and used to predict upcoming elements within a sentence. A previous study demonstrated that listeners with stroke-induced agrammatic aphasia rapidly access verb meanings and use them to semantically integrate verb-arguments; however, they show deficits in using verb meanings predictively (Mack, Ji, & Thompson, 2013. The present study tested whether listeners with PPA are able to access verb meanings and to use this information to integrate and predict verb-arguments. Methods. Fifteen adults with PPA (8 with PPA-G, 3 with PPA-L, and 4 with PPA-S and ten age-matched controls participated in two eyetracking experiments. In both experiments, participants heard sentences with restrictive verbs that were semantically compatible with only one object in a four-picture visual array (e.g., eat when the array included a cake and three non-edible objects and unrestrictive verbs (e.g., move that were compatible with all four objects. The verb-based integration experiment tested access to verb meaning and its effects on integration of the direct object (e.g., Susan will eat/move the cake; the verb-based prediction experiment examined prediction of the direct object (e.g., Susan will eat/move the …. The dependent variable was the rate of fixations on the target picture (e.g., the cake in the

Protein Homeostasis Imposes a Barrier on Functional Integration of Horizontally Transferred Genes in Bacteria.

Science.gov (United States)

Bershtein, Shimon; Serohijos, Adrian W R; Bhattacharyya, Sanchari; Manhart, Michael; Choi, Jeong-Mo; Mu, Wanmeng; Zhou, Jingwen; Shakhnovich, Eugene I

2015-10-01

Horizontal gene transfer (HGT) plays a central role in bacterial evolution, yet the molecular and cellular constraints on functional integration of the foreign genes are poorly understood. Here we performed inter-species replacement of the chromosomal folA gene, encoding an essential metabolic enzyme dihydrofolate reductase (DHFR), with orthologs from 35 other mesophilic bacteria. The orthologous inter-species replacements caused a marked drop (in the range 10-90%) in bacterial growth rate despite the fact that most orthologous DHFRs are as stable as E.coli DHFR at 37°C and are more catalytically active than E. coli DHFR. Although phylogenetic distance between E. coli and orthologous DHFRs as well as their individual molecular properties correlate poorly with growth rates, the product of the intracellular DHFR abundance and catalytic activity (kcat/KM), correlates strongly with growth rates, indicating that the drop in DHFR abundance constitutes the major fitness barrier to HGT. Serial propagation of the orthologous strains for ~600 generations dramatically improved growth rates by largely alleviating the fitness barriers. Whole genome sequencing and global proteome quantification revealed that the evolved strains with the largest fitness improvements have accumulated mutations that inactivated the ATP-dependent Lon protease, causing an increase in the intracellular DHFR abundance. In one case DHFR abundance increased further due to mutations accumulated in folA promoter, but only after the lon inactivating mutations were fixed in the population. Thus, by apparently distinguishing between self and non-self proteins, protein homeostasis imposes an immediate and global barrier to the functional integration of foreign genes by decreasing the intracellular abundance of their products. Once this barrier is alleviated, more fine-tuned evolution occurs to adjust the function/expression of the transferred proteins to the constraints imposed by the intracellular

Protein Homeostasis Imposes a Barrier on Functional Integration of Horizontally Transferred Genes in Bacteria.

Directory of Open Access Journals (Sweden)

Shimon Bershtein

2015-10-01

Full Text Available Horizontal gene transfer (HGT plays a central role in bacterial evolution, yet the molecular and cellular constraints on functional integration of the foreign genes are poorly understood. Here we performed inter-species replacement of the chromosomal folA gene, encoding an essential metabolic enzyme dihydrofolate reductase (DHFR, with orthologs from 35 other mesophilic bacteria. The orthologous inter-species replacements caused a marked drop (in the range 10-90% in bacterial growth rate despite the fact that most orthologous DHFRs are as stable as E.coli DHFR at 37°C and are more catalytically active than E. coli DHFR. Although phylogenetic distance between E. coli and orthologous DHFRs as well as their individual molecular properties correlate poorly with growth rates, the product of the intracellular DHFR abundance and catalytic activity (kcat/KM, correlates strongly with growth rates, indicating that the drop in DHFR abundance constitutes the major fitness barrier to HGT. Serial propagation of the orthologous strains for ~600 generations dramatically improved growth rates by largely alleviating the fitness barriers. Whole genome sequencing and global proteome quantification revealed that the evolved strains with the largest fitness improvements have accumulated mutations that inactivated the ATP-dependent Lon protease, causing an increase in the intracellular DHFR abundance. In one case DHFR abundance increased further due to mutations accumulated in folA promoter, but only after the lon inactivating mutations were fixed in the population. Thus, by apparently distinguishing between self and non-self proteins, protein homeostasis imposes an immediate and global barrier to the functional integration of foreign genes by decreasing the intracellular abundance of their products. Once this barrier is alleviated, more fine-tuned evolution occurs to adjust the function/expression of the transferred proteins to the constraints imposed by the

Synteny of orthologous genes conserved in human, mouse, snake, Drosophila, nematode, and fission yeast

Czech Academy of Sciences Publication Activity Database

Trachtulec, Zdeněk; Forejt, Jiří

2001-01-01

Roč. 12, č. 3 (2001), s. 227-231 ISSN 0938-8990 Institutional research plan: CEZ:AV0Z5052915 Keywords : synteny of orthologous genes Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 2.318, year: 2001

The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction.

Science.gov (United States)

Roche, Daniel B; Buenavista, Maria T; Tetchner, Stuart J; McGuffin, Liam J

2011-07-01

The IntFOLD server is a novel independent server that integrates several cutting edge methods for the prediction of structure and function from sequence. Our guiding principles behind the server development were as follows: (i) to provide a simple unified resource that makes our prediction software accessible to all and (ii) to produce integrated output for predictions that can be easily interpreted. The output for predictions is presented as a simple table that summarizes all results graphically via plots and annotated 3D models. The raw machine readable data files for each set of predictions are also provided for developers, which comply with the Critical Assessment of Methods for Protein Structure Prediction (CASP) data standards. The server comprises an integrated suite of five novel methods: nFOLD4, for tertiary structure prediction; ModFOLD 3.0, for model quality assessment; DISOclust 2.0, for disorder prediction; DomFOLD 2.0 for domain prediction; and FunFOLD 1.0, for ligand binding site prediction. Predictions from the IntFOLD server were found to be competitive in several categories in the recent CASP9 experiment. The IntFOLD server is available at the following web site: http://www.reading.ac.uk/bioinf/IntFOLD/.

Mycoplasma hyopneumoniae and Mycoplasma flocculare differential domains from orthologous surface proteins induce distinct cellular immune responses in mice.

Science.gov (United States)

Leal, Fernanda Munhoz Dos Anjos; Virginio, Veridiana Gomes; Martello, Carolina Lumertz; Paes, Jéssica Andrade; Borges, Thiago J; Jaeger, Natália; Bonorino, Cristina; Ferreira, Henrique Bunselmeyer

2016-07-15

Mycoplasma hyopneumoniae and Mycoplasma flocculare are two genetically close species found in the swine respiratory tract. Despite their similarities, while M. hyopneumoniae is the causative agent of porcine enzootic pneumonia, M. flocculare is a commensal bacterium. Genomic and transcriptional comparative analyses so far failed to explain the difference in pathogenicity between these two species. We then hypothesized that such difference might be, at least in part, explained by amino acid sequence and immunological or functional differences between ortholog surface proteins. In line with that, it was verified that approximately 85% of the ortholog surface proteins from M. hyopneumoniae 7448 and M. flocculare present one or more differential domains. To experimentally assess possible immunological implications of this kind of difference, the extracellular differential domains from one pair of orthologous surface proteins (MHP7448_0612, from M. hyopneumoniae, and MF_00357, from M. flocculare) were expressed in E. coli and used to immunize mice. The recombinant polypeptides (rMHP61267-169 and rMF35767-196, respectively) induced distinct cellular immune responses. While, rMHP61267-169 induced both Th1 and Th2 responses, rMF35767-196 induced just an early pro-inflammatory response. These results indicate that immunological properties determined by differential domains in orthologous surface protein might play a role in pathogenicity, contributing to elicit specific and differential immune responses against each species. Copyright © 2016 Elsevier B.V. All rights reserved.

Predicting Protein Function via Semantic Integration of Multiple Networks.

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Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhu, Hailong

2016-01-01

Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically integrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet.

The integration of weighted human gene association networks based on link prediction.

Science.gov (United States)

Yang, Jian; Yang, Tinghong; Wu, Duzhi; Lin, Limei; Yang, Fan; Zhao, Jing

2017-01-31

Physical and functional interplays between genes or proteins have important biological meaning for cellular functions. Some efforts have been made to construct weighted gene association meta-networks by integrating multiple biological resources, where the weight indicates the confidence of the interaction. However, it is found that these existing human gene association networks share only quite limited overlapped interactions, suggesting their incompleteness and noise. Here we proposed a workflow to construct a weighted human gene association network using information of six existing networks, including two weighted specific PPI networks and four gene association meta-networks. We applied link prediction algorithm to predict possible missing links of the networks, cross-validation approach to refine each network and finally integrated the refined networks to get the final integrated network. The common information among the refined networks increases notably, suggesting their higher reliability. Our final integrated network owns much more links than most of the original networks, meanwhile its links still keep high functional relevance. Being used as background network in a case study of disease gene prediction, the final integrated network presents good performance, implying its reliability and application significance. Our workflow could be insightful for integrating and refining existing gene association data.

SITEX 2.0: Projections of protein functional sites on eukaryotic genes. Extension with orthologous genes.

Science.gov (United States)

Medvedeva, Irina V; Demenkov, Pavel S; Ivanisenko, Vladimir A

2017-04-01

Functional sites define the diversity of protein functions and are the central object of research of the structural and functional organization of proteins. The mechanisms underlying protein functional sites emergence and their variability during evolution are distinguished by duplication, shuffling, insertion and deletion of the exons in genes. The study of the correlation between a site structure and exon structure serves as the basis for the in-depth understanding of sites organization. In this regard, the development of programming resources that allow the realization of the mutual projection of exon structure of genes and primary and tertiary structures of encoded proteins is still the actual problem. Previously, we developed the SitEx system that provides information about protein and gene sequences with mapped exon borders and protein functional sites amino acid positions. The database included information on proteins with known 3D structure. However, data with respect to orthologs was not available. Therefore, we added the projection of sites positions to the exon structures of orthologs in SitEx 2.0. We implemented a search through database using site conservation variability and site discontinuity through exon structure. Inclusion of the information on orthologs allowed to expand the possibilities of SitEx usage for solving problems regarding the analysis of the structural and functional organization of proteins. Database URL: http://www-bionet.sscc.ru/sitex/ .

Orthology Guided Assembly in highly heterozygous crops

DEFF Research Database (Denmark)

Ruttink, Tom; Sterck, Lieven; Rohde, Antje

2013-01-01

to outbreeding crop species hamper De Bruijn Graph-based de novo assembly algorithms, causing transcript fragmentation and the redundant assembly of allelic contigs. If multiple genotypes are sequenced to study genetic diversity, primary de novo assembly is best performed per genotype to limit the level......Despite current advances in next-generation sequencing data analysis procedures, de novo assembly of a reference sequence required for SNP discovery and expression analysis is still a major challenge in genetically uncharacterized, highly heterozygous species. High levels of polymorphism inherent...... of polymorphism and avoid transcript fragmentation. Here, we propose an Orthology Guided Assembly procedure that first uses sequence similarity (tBLASTn) to proteins of a model species to select allelic and fragmented contigs from all genotypes and then performs CAP3 clustering on a gene-by-gene basis. Thus, we...

eggNOG v2.0: extending the evolutionary genealogy of genes with enhanced non-supervised orthologous groups, species and functional annotations

DEFF Research Database (Denmark)

Muller, J; Szklarczyk, D; Julien, P

2010-01-01

The identification of orthologous relationships forms the basis for most comparative genomics studies. Here, we present the second version of the eggNOG database, which contains orthologous groups (OGs) constructed through identification of reciprocal best BLAST matches and triangular linkage...... of the tree of life; in addition to the species groups included in our first release (i.e. fungi, metazoa, insects, vertebrates and mammals), we have now constructed OGs for archaea, fishes, rodents and primates. We automatically annotate the non-supervised orthologous groups (NOGs) with functional...... descriptions, protein domains, and functional categories as defined initially for the COG/KOG database. In-depth analysis is facilitated by precomputed high-quality multiple sequence alignments and maximum-likelihood trees for each of the available OGs. Altogether, eggNOG covers 2,242 035 proteins (built from...

Integrating Biological Perspectives:. a Quantum Leap for Microarray Expression Analysis

Science.gov (United States)

Wanke, Dierk; Kilian, Joachim; Bloss, Ulrich; Mangelsen, Elke; Supper, Jochen; Harter, Klaus; Berendzen, Kenneth W.

2009-02-01

Biologists and bioinformatic scientists cope with the analysis of transcript abundance and the extraction of meaningful information from microarray expression data. By exploiting biological information accessible in public databases, we try to extend our current knowledge over the plant model organism Arabidopsis thaliana. Here, we give two examples of increasing the quality of information gained from large scale expression experiments by the integration of microarray-unrelated biological information: First, we utilize Arabidopsis microarray data to demonstrate that expression profiles are usually conserved between orthologous genes of different organisms. In an initial step of the analysis, orthology has to be inferred unambiguously, which then allows comparison of expression profiles between orthologs. We make use of the publicly available microarray expression data of Arabidopsis and barley, Hordeum vulgare. We found a generally positive correlation in expression trajectories between true orthologs although both organisms are only distantly related in evolutionary time scale. Second, extracting clusters of co-regulated genes implies similarities in transcriptional regulation via similar cis-regulatory elements (CREs). Vice versa approaches, where co-regulated gene clusters are found by investigating on CREs were not successful in general. Nonetheless, in some cases the presence of CREs in a defined position, orientation or CRE-combinations is positively correlated with co-regulated gene clusters. Here, we make use of genes involved in the phenylpropanoid biosynthetic pathway, to give one positive example for this approach.

Cross-species mapping of bidirectional promoters enables prediction of unannotated 5' UTRs and identification of species-specific transcripts

Directory of Open Access Journals (Sweden)

Lewin Harris A

2009-04-01

Full Text Available Abstract Background Bidirectional promoters are shared regulatory regions that influence the expression of two oppositely oriented genes. This type of regulatory architecture is found more frequently than expected by chance in the human genome, yet many specifics underlying the regulatory design are unknown. Given that the function of most orthologous genes is similar across species, we hypothesized that the architecture and regulation of bidirectional promoters might also be similar across species, representing a core regulatory structure and enabling annotation of these regions in additional mammalian genomes. Results By mapping the intergenic distances of genes in human, chimpanzee, bovine, murine, and rat, we show an enrichment for pairs of genes equal to or less than 1,000 bp between their adjacent 5' ends ("head-to-head" compared to pairs of genes that fall in the same orientation ("head-to-tail" or whose 3' ends are side-by-side ("tail-to-tail". A representative set of 1,369 human bidirectional promoters was mapped to orthologous sequences in other mammals. We confirmed predictions for 5' UTRs in nine of ten manual picks in bovine based on comparison to the orthologous human promoter set and in six of seven predictions in human based on comparison to the bovine dataset. The two predictions that did not have orthology as bidirectional promoters in the other species resulted from unique events that initiated transcription in the opposite direction in only those species. We found evidence supporting the independent emergence of bidirectional promoters from the family of five RecQ helicase genes, which gained their bidirectional promoters and partner genes independently rather than through a duplication process. Furthermore, by expanding our comparisons from pairwise to multispecies analyses we developed a map representing a core set of bidirectional promoters in mammals. Conclusion We show that the orthologous positions of bidirectional

Integrating geophysics and hydrology for reducing the uncertainty of groundwater model predictions and improved prediction performance

DEFF Research Database (Denmark)

Christensen, Nikolaj Kruse; Christensen, Steen; Ferre, Ty

the integration of geophysical data in the construction of a groundwater model increases the prediction performance. We suggest that modelers should perform a hydrogeophysical “test-bench” analysis of the likely value of geophysics data for improving groundwater model prediction performance before actually...... and the resulting predictions can be compared with predictions from the ‘true’ model. By performing this analysis we expect to give the modeler insight into how the uncertainty of model-based prediction can be reduced.......A major purpose of groundwater modeling is to help decision-makers in efforts to manage the natural environment. Increasingly, it is recognized that both the predictions of interest and their associated uncertainties should be quantified to support robust decision making. In particular, decision...

Integrated Simulation for HVAC Performance Prediction: State-of-the-Art Illustration

NARCIS (Netherlands)

Hensen, J.L.M.; Clarke, J.A.

2000-01-01

This paper aims to outline the current state-of-the-art in integrated building simulation for performance prediction of heating, ventilating and air-conditioning (HVAC) systems. The ESP-r system is used as an example where integrated simulation is a core philosophy behind the development. The

Edaphic history over seedling characters predicts integration and plasticity of integration across geologically variable populations of Arabidopsis thaliana.

Science.gov (United States)

Cousins, Elsa A; Murren, Courtney J

2017-12-01

Studies on phenotypic plasticity and plasticity of integration have uncovered functionally linked modules of aboveground traits and seedlings of Arabidopsis thaliana , but we lack details about belowground variation in adult plants. Functional modules can be comprised of additional suites of traits that respond to environmental variation. We assessed whether shoot and root responses to nutrient environments in adult A. thaliana were predictable from seedling traits or population-specific geologic soil characteristics at the site of origin. We compared 17 natural accessions from across the native range of A. thaliana using 14-day-old seedlings grown on agar or sand and plants grown to maturity across nutrient treatments in sand. We measured aboveground size, reproduction, timing traits, root length, and root diameter. Edaphic characteristics were obtained from a global-scale dataset and related to field data. We detected significant among-population variation in root traits of seedlings and adults and in plasticity in aboveground and belowground traits of adult plants. Phenotypic integration of roots and shoots varied by population and environment. Relative integration was greater in roots than in shoots, and integration was predicted by edaphic soil history, particularly organic carbon content, whereas seedling traits did not predict later ontogenetic stages. Soil environment of origin has significant effects on phenotypic plasticity in response to nutrients, and on phenotypic integration of root modules and shoot modules. Root traits varied among populations in reproductively mature individuals, indicating potential for adaptive and integrated functional responses of root systems in annuals. © 2017 Botanical Society of America.

COMPUTING THERAPY FOR PRECISION MEDICINE: COLLABORATIVE FILTERING INTEGRATES AND PREDICTS MULTI-ENTITY INTERACTIONS.

Science.gov (United States)

Regenbogen, Sam; Wilkins, Angela D; Lichtarge, Olivier

2016-01-01

Biomedicine produces copious information it cannot fully exploit. Specifically, there is considerable need to integrate knowledge from disparate studies to discover connections across domains. Here, we used a Collaborative Filtering approach, inspired by online recommendation algorithms, in which non-negative matrix factorization (NMF) predicts interactions among chemicals, genes, and diseases only from pairwise information about their interactions. Our approach, applied to matrices derived from the Comparative Toxicogenomics Database, successfully recovered Chemical-Disease, Chemical-Gene, and Disease-Gene networks in 10-fold cross-validation experiments. Additionally, we could predict each of these interaction matrices from the other two. Integrating all three CTD interaction matrices with NMF led to good predictions of STRING, an independent, external network of protein-protein interactions. Finally, this approach could integrate the CTD and STRING interaction data to improve Chemical-Gene cross-validation performance significantly, and, in a time-stamped study, it predicted information added to CTD after a given date, using only data prior to that date. We conclude that collaborative filtering can integrate information across multiple types of biological entities, and that as a first step towards precision medicine it can compute drug repurposing hypotheses.

The C. elegans Ortholog of USP7 controls DAF-16 stability in Insulin/IGF-1-like signaling.

Science.gov (United States)

Heimbucher, Thomas; Hunter, Tony

2015-01-01

FOXO family transcription factors are downstream effectors of Insulin/IGF-1 signaling (IIS) and are regulated by posttranslational modification and coregulators, including components of the ubiquitin-proteasome system (UPS). Cofactors promoting DAF-16/FOXO protein stability and function in IIS have not been described yet. In a recent study, we have identified the deubiquitylating enzyme MATH-33, the ortholog of mammalian USP7/HAUSP, as an essential DAF-16 coregulator. We found that MATH-33 actively stabilizes DAF-16 protein levels when IIS is downregulated. Here we discuss how DAF-16/FOXO transcription factors are regulated by the UPS, in particular by the interplay of E3-ubiquitin ligases and deubiquitylating enzymes, which is critical for balancing DAF-16/FOXO activity and degradation. Recent findings raise the intriguing possibility that regulated oscillations in DAF-16/FOXO steady state levels play an integral role in mechanisms controlling healthspan and lifespan extension.

Integrated Detection and Prediction of Influenza Activity for Real-Time Surveillance: Algorithm Design.

Science.gov (United States)

Spreco, Armin; Eriksson, Olle; Dahlström, Örjan; Cowling, Benjamin John; Timpka, Toomas

2017-06-15

Influenza is a viral respiratory disease capable of causing epidemics that represent a threat to communities worldwide. The rapidly growing availability of electronic "big data" from diagnostic and prediagnostic sources in health care and public health settings permits advance of a new generation of methods for local detection and prediction of winter influenza seasons and influenza pandemics. The aim of this study was to present a method for integrated detection and prediction of influenza virus activity in local settings using electronically available surveillance data and to evaluate its performance by retrospective application on authentic data from a Swedish county. An integrated detection and prediction method was formally defined based on a design rationale for influenza detection and prediction methods adapted for local surveillance. The novel method was retrospectively applied on data from the winter influenza season 2008-09 in a Swedish county (population 445,000). Outcome data represented individuals who met a clinical case definition for influenza (based on International Classification of Diseases version 10 [ICD-10] codes) from an electronic health data repository. Information from calls to a telenursing service in the county was used as syndromic data source. The novel integrated detection and prediction method is based on nonmechanistic statistical models and is designed for integration in local health information systems. The method is divided into separate modules for detection and prediction of local influenza virus activity. The function of the detection module is to alert for an upcoming period of increased load of influenza cases on local health care (using influenza-diagnosis data), whereas the function of the prediction module is to predict the timing of the activity peak (using syndromic data) and its intensity (using influenza-diagnosis data). For detection modeling, exponential regression was used based on the assumption that the beginning

New Insights on Eggplant/Tomato/Pepper Synteny and Identification of Eggplant and Pepper Orthologous QTL

Directory of Open Access Journals (Sweden)

Riccardo Rinaldi

2016-07-01

Full Text Available Eggplant, pepper and tomato are the most exploited berry-producing vegetables within the Solanaceae family. Their genomes differ in size, but each has 12 chromosomes which have undergone rearrangements causing a redistribution of loci. The genome sequences of all three species are available but differ in coverage, assembly quality and percentage of anchorage.Determining their syntenic relationship and QTL orthology will contribute to exploit genomic resources and genetic data for key agronomic traits.The syntenic analysis between tomato and pepper based on the alignment of 34,727 tomato CDS to the pepper genome sequence, identified 19,734 unique hits. The resulting synteny map confirmed the 14 inversions and 10 translocations previously documented, but also highlighted 3 new translocations and 4 major new inversions. Furthermore, each of the 12 chromosomes exhibited a number of rearrangements involving small regions of 0.5-0.7 Mbp.Due to high fragmentation of the publicly available eggplant genome sequence, physical localization of most eggplant QTL was not possible, thus, we compared the organization of the eggplant genetic map with the genome sequence of both tomato and pepper. The eggplant/tomato syntenic map confirmed all the 10 translocations but only 9 of the 14 known inversions; on the other hand, a newly detected inversion was recognized while another one was not confirmed. The eggplant/pepper syntenic map confirmed 10 translocations and 8 inversions already detected and suggested a putative new translocation.In order to perform the assessment of eggplant and pepper QTL orthology, the eggplant and pepper sequence-based markers located in their respective genetic map were aligned onto the pepper genome. GBrowse in pepper was used as reference platform for QTL positioning. A set of 151 pepper QTL were located as well as 212 eggplant QTL, including 76 major QTL (PVE ≥ 10% affecting key agronomic traits. Most were confirmed to cluster in

Prediction of rotor blade-vortex interaction using Volterra integrals

Energy Technology Data Exchange (ETDEWEB)

Wong, A.; Nitzsche, F. [Carleton Univ., Dept. of Mechanical and Aerospace Engineering, Ottawa, Ontario (Canada)]. E-mail: Fred_Nitzsche@carleton.ca; Khalid, M. [National Research Council Canada, Inst. for Aerospace Research, Ottawa, Ontario (Canada)

2004-07-01

The theory of Volterra integral equations for nonlinear system is applied to the prediction of the nonlinear aerodynamic response of an NACA 0012 airfoil experiencing blade-vortex interaction. The phenomenon is first modeled in two-dimensions using an Euler/Navier-Stoke code, and the resulting unsteady aerodynamic flow field sequences are appropriately combined to form a training dataset. The Volterra kernels are identified in the time-domain characteristics of the selected data, which is in turn used to predict the nonlinear aerodynamic response of the airfoil. The Volterra kernel based data is then compared against a standard airfoil response. The predicted lift time histories of the airfoil are shown to be in good agreement with the aerodynamic data. (author)

Prediction of rotor blade-vortex interaction using Volterra integrals

International Nuclear Information System (INIS)

Wong, A.; Nitzsche, F.; Khalid, M.

2004-01-01

The theory of Volterra integral equations for nonlinear system is applied to the prediction of the nonlinear aerodynamic response of an NACA 0012 airfoil experiencing blade-vortex interaction. The phenomenon is first modeled in two-dimensions using an Euler/Navier-Stoke code, and the resulting unsteady aerodynamic flow field sequences are appropriately combined to form a training dataset. The Volterra kernels are identified in the time-domain characteristics of the selected data, which is in turn used to predict the nonlinear aerodynamic response of the airfoil. The Volterra kernel based data is then compared against a standard airfoil response. The predicted lift time histories of the airfoil are shown to be in good agreement with the aerodynamic data. (author)

Protein function prediction involved on radio-resistant bacteria

International Nuclear Information System (INIS)

Mezhoud, Karim; Mankai, Houda; Sghaier, Haitham; Barkallah, Insaf

2009-01-01

Previously, we identified 58 proteins under positive selection in ionizing-radiation-resistant bacteria (IRRB) but absent in all ionizing-radiation-sensitive bacteria (IRSB). These are good reasons to believe these 58 proteins with their interactions with other proteins (interactomes) are a part of the answer to the question as to how IRRB resist to radiation, because our knowledge of interactomes of positively selected orphan proteins in IRRB might allow us to define cellular pathways important to ionizing-radiation resistance. Using the Database of Interacting Proteins and the PSIbase, we have predicted interactions of orthologs of the 58 proteins under positive selection in IRRB but absent in all IRSB. We used integrate experimental data sets with molecular interaction networks and protein structure prediction from databases. Among these, 18 proteins with their interactomes were identified in Deinococcus radiodurans R1. DNA checkpoint and repair, kinases pathways, energetic and nucleotide metabolisms were the important biological process that found. We predicted the interactomes of 58 proteins under positive selection in IRRB. It is hoped our data will provide new clues as to the cellular pathways that are important for ionizing-radiation resistance. We have identified news proteins involved on DNA management which were not previously mentioned. It is an important input in addition to protein that studied. It does still work to deepen our study on these new proteins

Integrated prediction based on GIS for sandstone-type uranium deposits in the northwest of Ordos Basin

International Nuclear Information System (INIS)

Han Shaoyang; Ke Dan; Hu Shuiqing; Guo Qingyin; Hou Huiqun

2005-01-01

The integrated prediction model of sandstone-type uranium deposits and its integrated evaluation methods as well as flow of the work based on GIS are studied. A software for extracting metallogenic information is also developed. A multi-source exploring information database is established in the northwest of Ordos Basin, and an integrated digital mineral deposit prospecting model of sandstone-type uranium deposits is designed based on GIS. The authors have completed metallogenic information extraction and integrated evaluation of sandstone-type uranium deposits based on GIS in the study area. Research results prove that the integrated prediction of sandstone-type uranium deposits based on GIS may further delineate prospective target areas rapidly and improve the predictive precision. (authors)

Predicting co-complexed protein pairs using genomic and proteomic data integration

Directory of Open Access Journals (Sweden)

King Oliver D

2004-04-01

Full Text Available Abstract Background Identifying all protein-protein interactions in an organism is a major objective of proteomics. A related goal is to know which protein pairs are present in the same protein complex. High-throughput methods such as yeast two-hybrid (Y2H and affinity purification coupled with mass spectrometry (APMS have been used to detect interacting proteins on a genomic scale. However, both Y2H and APMS methods have substantial false-positive rates. Aside from high-throughput interaction screens, other gene- or protein-pair characteristics may also be informative of physical interaction. Therefore it is desirable to integrate multiple datasets and utilize their different predictive value for more accurate prediction of co-complexed relationship. Results Using a supervised machine learning approach – probabilistic decision tree, we integrated high-throughput protein interaction datasets and other gene- and protein-pair characteristics to predict co-complexed pairs (CCP of proteins. Our predictions proved more sensitive and specific than predictions based on Y2H or APMS methods alone or in combination. Among the top predictions not annotated as CCPs in our reference set (obtained from the MIPS complex catalogue, a significant fraction was found to physically interact according to a separate database (YPD, Yeast Proteome Database, and the remaining predictions may potentially represent unknown CCPs. Conclusions We demonstrated that the probabilistic decision tree approach can be successfully used to predict co-complexed protein (CCP pairs from other characteristics. Our top-scoring CCP predictions provide testable hypotheses for experimental validation.

Integrative approaches to the prediction of protein functions based on the feature selection

Directory of Open Access Journals (Sweden)

Lee Hyunju

2009-12-01

Full Text Available Abstract Background Protein function prediction has been one of the most important issues in functional genomics. With the current availability of various genomic data sets, many researchers have attempted to develop integration models that combine all available genomic data for protein function prediction. These efforts have resulted in the improvement of prediction quality and the extension of prediction coverage. However, it has also been observed that integrating more data sources does not always increase the prediction quality. Therefore, selecting data sources that highly contribute to the protein function prediction has become an important issue. Results We present systematic feature selection methods that assess the contribution of genome-wide data sets to predict protein functions and then investigate the relationship between genomic data sources and protein functions. In this study, we use ten different genomic data sources in Mus musculus, including: protein-domains, protein-protein interactions, gene expressions, phenotype ontology, phylogenetic profiles and disease data sources to predict protein functions that are labelled with Gene Ontology (GO terms. We then apply two approaches to feature selection: exhaustive search feature selection using a kernel based logistic regression (KLR, and a kernel based L1-norm regularized logistic regression (KL1LR. In the first approach, we exhaustively measure the contribution of each data set for each function based on its prediction quality. In the second approach, we use the estimated coefficients of features as measures of contribution of data sources. Our results show that the proposed methods improve the prediction quality compared to the full integration of all data sources and other filter-based feature selection methods. We also show that contributing data sources can differ depending on the protein function. Furthermore, we observe that highly contributing data sets can be similar among

Evaluating and Predicting Patient Safety for Medical Devices With Integral Information Technology

Science.gov (United States)

2005-01-01

323 Evaluating and Predicting Patient Safety for Medical Devices with Integral Information Technology Jiajie Zhang, Vimla L. Patel, Todd R...errors are due to inappropriate designs for user interactions, rather than mechanical failures. Evaluating and predicting patient safety in medical ...the users on the identified trouble spots in the devices. We developed two methods for evaluating and predicting patient safety in medical devices

Subtask 2.4 - Integration and Synthesis in Climate Change Predictive Modeling

Energy Technology Data Exchange (ETDEWEB)

Jaroslav Solc

2009-06-01

The Energy & Environmental Research Center (EERC) completed a brief evaluation of the existing status of predictive modeling to assess options for integration of our previous paleohydrologic reconstructions and their synthesis with current global climate scenarios. Results of our research indicate that short-term data series available from modern instrumental records are not sufficient to reconstruct past hydrologic events or predict future ones. On the contrary, reconstruction of paleoclimate phenomena provided credible information on past climate cycles and confirmed their integration in the context of regional climate history is possible. Similarly to ice cores and other paleo proxies, acquired data represent an objective, credible tool for model calibration and validation of currently observed trends. It remains a subject of future research whether further refinement of our results and synthesis with regional and global climate observations could contribute to improvement and credibility of climate predictions on a regional and global scale.

Improving Allergen Prediction in Main Crops Using a Weighted Integrative Method.

Science.gov (United States)

Li, Jing; Wang, Jing; Li, Jing

2017-12-01

As a public health problem, food allergy is frequently caused by food allergy proteins, which trigger a type-I hypersensitivity reaction in the immune system of atopic individuals. The food allergens in our daily lives are mainly from crops including rice, wheat, soybean and maize. However, allergens in these main crops are far from fully uncovered. Although some bioinformatics tools or methods predicting the potential allergenicity of proteins have been proposed, each method has their limitation. In this paper, we built a novel algorithm PREAL W , which integrated PREAL, FAO/WHO criteria and motif-based method by a weighted average score, to benefit the advantages of different methods. Our results illustrated PREAL W has better performance significantly in the crops' allergen prediction. This integrative allergen prediction algorithm could be useful for critical food safety matters. The PREAL W could be accessed at http://lilab.life.sjtu.edu.cn:8080/prealw .

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks

Science.gov (United States)

Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E.; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A.; Kellis, Manolis

2012-01-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein–protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level. PMID:22456606

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks.

Science.gov (United States)

Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A; Kellis, Manolis

2012-07-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein-protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level.

Computational Identification of the Paralogs and Orthologs of Human Cytochrome P450 Superfamily and the Implication in Drug Discovery

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Shu-Ting Pan

2016-06-01

Full Text Available The human cytochrome P450 (CYP superfamily consisting of 57 functional genes is the most important group of Phase I drug metabolizing enzymes that oxidize a large number of xenobiotics and endogenous compounds, including therapeutic drugs and environmental toxicants. The CYP superfamily has been shown to expand itself through gene duplication, and some of them become pseudogenes due to gene mutations. Orthologs and paralogs are homologous genes resulting from speciation or duplication, respectively. To explore the evolutionary and functional relationships of human CYPs, we conducted this bioinformatic study to identify their corresponding paralogs, homologs, and orthologs. The functional implications and implications in drug discovery and evolutionary biology were then discussed. GeneCards and Ensembl were used to identify the paralogs of human CYPs. We have used a panel of online databases to identify the orthologs of human CYP genes: NCBI, Ensembl Compara, GeneCards, OMA (“Orthologous MAtrix” Browser, PATHER, TreeFam, EggNOG, and Roundup. The results show that each human CYP has various numbers of paralogs and orthologs using GeneCards and Ensembl. For example, the paralogs of CYP2A6 include CYP2A7, 2A13, 2B6, 2C8, 2C9, 2C18, 2C19, 2D6, 2E1, 2F1, 2J2, 2R1, 2S1, 2U1, and 2W1; CYP11A1 has 6 paralogs including CYP11B1, 11B2, 24A1, 27A1, 27B1, and 27C1; CYP51A1 has only three paralogs: CYP26A1, 26B1, and 26C1; while CYP20A1 has no paralog. The majority of human CYPs are well conserved from plants, amphibians, fishes, or mammals to humans due to their important functions in physiology and xenobiotic disposition. The data from different approaches are also cross-validated and validated when experimental data are available. These findings facilitate our understanding of the evolutionary relationships and functional implications of the human CYP superfamily in drug discovery.

Development and bin mapping of a Rosaceae Conserved Ortholog Set (COS of markers

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Kozik Alex

2009-01-01

Full Text Available Abstract Background Detailed comparative genome analyses within the economically important Rosaceae family have not been conducted. This is largely due to the lack of conserved gene-based molecular markers that are transferable among the important crop genera within the family [e.g. Malus (apple, Fragaria (strawberry, and Prunus (peach, cherry, apricot and almond]. The lack of molecular markers and comparative whole genome sequence analysis for this family severely hampers crop improvement efforts as well as QTL confirmation and validation studies. Results We identified a set of 3,818 rosaceaous unigenes comprised of two or more ESTs that correspond to single copy Arabidopsis genes. From this Rosaceae Conserved Orthologous Set (RosCOS, 1039 were selected from which 857 were used for the development of intron-flanking primers and allele amplification. This led to successful amplification and subsequent mapping of 613 RosCOS onto the Prunus TxE reference map resulting in a genome-wide coverage of 0.67 to 1.06 gene-based markers per cM per linkage group. Furthermore, the RosCOS primers showed amplification success rates from 23 to 100% across the family indicating that a substantial part of the RosCOS primers can be directly employed in other less studied rosaceaous crops. Comparisons of the genetic map positions of the RosCOS with the physical locations of the orthologs in the Populus trichocarpa genome identified regions of colinearity between the genomes of Prunus-Rosaceae and Populus-Salicaceae. Conclusion Conserved orthologous genes are extremely useful for the analysis of genome evolution among closely and distantly related species. The results presented in this study demonstrate the considerable potential of the mapped Prunus RosCOS for genome-wide marker employment and comparative whole genome studies within the Rosaceae family. Moreover, these markers will also function as useful anchor points for the genome sequencing efforts currently

Development and bin mapping of a Rosaceae Conserved Ortholog Set (COS) of markers.

Science.gov (United States)

Cabrera, Antonio; Kozik, Alex; Howad, Werner; Arus, Pere; Iezzoni, Amy F; van der Knaap, Esther

2009-11-29

Detailed comparative genome analyses within the economically important Rosaceae family have not been conducted. This is largely due to the lack of conserved gene-based molecular markers that are transferable among the important crop genera within the family [e.g. Malus (apple), Fragaria (strawberry), and Prunus (peach, cherry, apricot and almond)]. The lack of molecular markers and comparative whole genome sequence analysis for this family severely hampers crop improvement efforts as well as QTL confirmation and validation studies. We identified a set of 3,818 rosaceaous unigenes comprised of two or more ESTs that correspond to single copy Arabidopsis genes. From this Rosaceae Conserved Orthologous Set (RosCOS), 1039 were selected from which 857 were used for the development of intron-flanking primers and allele amplification. This led to successful amplification and subsequent mapping of 613 RosCOS onto the Prunus TxE reference map resulting in a genome-wide coverage of 0.67 to 1.06 gene-based markers per cM per linkage group. Furthermore, the RosCOS primers showed amplification success rates from 23 to 100% across the family indicating that a substantial part of the RosCOS primers can be directly employed in other less studied rosaceaous crops. Comparisons of the genetic map positions of the RosCOS with the physical locations of the orthologs in the Populus trichocarpa genome identified regions of colinearity between the genomes of Prunus-Rosaceae and Populus-Salicaceae. Conserved orthologous genes are extremely useful for the analysis of genome evolution among closely and distantly related species. The results presented in this study demonstrate the considerable potential of the mapped Prunus RosCOS for genome-wide marker employment and comparative whole genome studies within the Rosaceae family. Moreover, these markers will also function as useful anchor points for the genome sequencing efforts currently ongoing in this family as well as for comparative QTL

Integrated Computational Solution for Predicting Skin Sensitization Potential of Molecules.

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Konda Leela Sarath Kumar

Full Text Available Skin sensitization forms a major toxicological endpoint for dermatology and cosmetic products. Recent ban on animal testing for cosmetics demands for alternative methods. We developed an integrated computational solution (SkinSense that offers a robust solution and addresses the limitations of existing computational tools i.e. high false positive rate and/or limited coverage.The key components of our solution include: QSAR models selected from a combinatorial set, similarity information and literature-derived sub-structure patterns of known skin protein reactive groups. Its prediction performance on a challenge set of molecules showed accuracy = 75.32%, CCR = 74.36%, sensitivity = 70.00% and specificity = 78.72%, which is better than several existing tools including VEGA (accuracy = 45.00% and CCR = 54.17% with 'High' reliability scoring, DEREK (accuracy = 72.73% and CCR = 71.44% and TOPKAT (accuracy = 60.00% and CCR = 61.67%. Although, TIMES-SS showed higher predictive power (accuracy = 90.00% and CCR = 92.86%, the coverage was very low (only 10 out of 77 molecules were predicted reliably.Owing to improved prediction performance and coverage, our solution can serve as a useful expert system towards Integrated Approaches to Testing and Assessment for skin sensitization. It would be invaluable to cosmetic/ dermatology industry for pre-screening their molecules, and reducing time, cost and animal testing.

License - PGDBj - Ortholog DB | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us PGDBj - Ortholog DB License License to Use This Database Last updated : 2017/03/07 You may use this database...cifies the license terms regarding the use of this database and the requirements you must follow in using this database.... The license for this database is specified in the Creative Commons A...ttribution-Share Alike 4.0 International . If you use data from this database, please be sure attribute this database...hare Alike 4.0 International is found here . With regard to this database, you are licensed to: freely acces

A comparative gene analysis with rice identified orthologous group II HKT genes and their association with Na(+) concentration in bread wheat.

Science.gov (United States)

Ariyarathna, H A Chandima K; Oldach, Klaus H; Francki, Michael G

2016-01-19

Although the HKT transporter genes ascertain some of the key determinants of crop salt tolerance mechanisms, the diversity and functional role of group II HKT genes are not clearly understood in bread wheat. The advanced knowledge on rice HKT and whole genome sequence was, therefore, used in comparative gene analysis to identify orthologous wheat group II HKT genes and their role in trait variation under different saline environments. The four group II HKTs in rice identified two orthologous gene families from bread wheat, including the known TaHKT2;1 gene family and a new distinctly different gene family designated as TaHKT2;2. A single copy of TaHKT2;2 was found on each homeologous chromosome arm 7AL, 7BL and 7DL and each gene was expressed in leaf blade, sheath and root tissues under non-stressed and at 200 mM salt stressed conditions. The proteins encoded by genes of the TaHKT2;2 family revealed more than 93% amino acid sequence identity but ≤52% amino acid identity compared to the proteins encoded by TaHKT2;1 family. Specifically, variations in known critical domains predicted functional differences between the two protein families. Similar to orthologous rice genes on chromosome 6L, TaHKT2;1 and TaHKT2;2 genes were located approximately 3 kb apart on wheat chromosomes 7AL, 7BL and 7DL, forming a static syntenic block in the two species. The chromosomal region on 7AL containing TaHKT2;1 7AL-1 co-located with QTL for shoot Na(+) concentration and yield in some saline environments. The differences in copy number, genes sequences and encoded proteins between TaHKT2;2 homeologous genes and other group II HKT gene families within and across species likely reflect functional diversity for ion selectivity and transport in plants. Evidence indicated that neither TaHKT2;2 nor TaHKT2;1 were associated with primary root Na(+) uptake but TaHKT2;1 may be associated with trait variation for Na(+) exclusion and yield in some but not all saline environments.

Integrative Identification of Arabidopsis Mitochondrial Proteome and Its Function Exploitation through Protein Interaction Network

Science.gov (United States)

Cui, Jian; Liu, Jinghua; Li, Yuhua; Shi, Tieliu

2011-01-01

Mitochondria are major players on the production of energy, and host several key reactions involved in basic metabolism and biosynthesis of essential molecules. Currently, the majority of nucleus-encoded mitochondrial proteins are unknown even for model plant Arabidopsis. We reported a computational framework for predicting Arabidopsis mitochondrial proteins based on a probabilistic model, called Naive Bayesian Network, which integrates disparate genomic data generated from eight bioinformatics tools, multiple orthologous mappings, protein domain properties and co-expression patterns using 1,027 microarray profiles. Through this approach, we predicted 2,311 candidate mitochondrial proteins with 84.67% accuracy and 2.53% FPR performances. Together with those experimental confirmed proteins, 2,585 mitochondria proteins (named CoreMitoP) were identified, we explored those proteins with unknown functions based on protein-protein interaction network (PIN) and annotated novel functions for 26.65% CoreMitoP proteins. Moreover, we found newly predicted mitochondrial proteins embedded in particular subnetworks of the PIN, mainly functioning in response to diverse environmental stresses, like salt, draught, cold, and wound etc. Candidate mitochondrial proteins involved in those physiological acitivites provide useful targets for further investigation. Assigned functions also provide comprehensive information for Arabidopsis mitochondrial proteome. PMID:21297957

Supervisory Model Predictive Control of the Heat Integrated Distillation Column

DEFF Research Database (Denmark)

Meyer, Kristian; Bisgaard, Thomas; Huusom, Jakob Kjøbsted

2017-01-01

This paper benchmarks a centralized control system based on model predictive control for the operation of the heat integrated distillation column (HIDiC) against a fully decentralized control system using the most complete column model currently available in the literature. The centralized control...... system outperforms the decentralized system, because it handles the interactions in the HIDiC process better. The integral absolute error (IAE) is reduced by a factor of 2 and a factor of 4 for control of the top and bottoms compositions, respectively....

Morphogenesis of Strongyloides stercoralis infective larvae requires the DAF-16 ortholog FKTF-1.

Directory of Open Access Journals (Sweden)

Michelle L Castelletto

2009-04-01

Full Text Available Based on metabolic and morphological similarities between infective third-stage larvae of parasitic nematodes and dauer larvae of Caenorhabditis elegans, it is hypothesized that similar genetic mechanisms control the development of these forms. In the parasite Strongyloides stercoralis, FKTF-1 is an ortholog of DAF-16, a forkhead transcription factor that regulates dauer larval development in C. elegans. Using transgenesis, we investigated the role of FKTF-1 in S. stercoralis' infective larval development. In first-stage larvae, GFP-tagged recombinant FKTF-1b localizes to the pharynx and hypodermis, tissues remodeled in infective larvae. Activating and inactivating mutations at predicted AKT phosphorylation sites on FKTF-1b give constitutive cytoplasmic and nuclear localization of the protein, respectively, indicating that its post-translational regulation is similar to other FOXO-class transcription factors. Mutant constructs designed to interfere with endogenous FKTF-1b function altered the intestinal and pharyngeal development of the larvae and resulted in some transgenic larvae failing to arrest in the infective stage. Our findings indicate that FKTF-1b is required for proper morphogenesis of S. stercoralis infective larvae and support the overall hypothesis of similar regulation of dauer development in C. elegans and the formation of infective larvae in parasitic nematodes.

QuartetS: A Fast and Accurate Algorithm for Large-Scale Orthology Detection

Science.gov (United States)

2011-01-01

of these two genes with all other genes of the other one species. In addition, to be considered orthologs, the BBH pairs had to satisfy two conditions ...BBH pair computations employed as part of the outgroup and QuartetS methods, we used the same two conditions as the ones described above. In our...versus proteins. Genetica , 118, 209–216. 4. Serres,M.H., Kerr,A.R., McCormack,T.J. and Riley,M. (2009) Evolution by leaps: gene duplication in bacteria

Development of an integrated method for long-term water quality prediction using seasonal climate forecast

Directory of Open Access Journals (Sweden)

J. Cho

2016-10-01

Full Text Available The APEC Climate Center (APCC produces climate prediction information utilizing a multi-climate model ensemble (MME technique. In this study, four different downscaling methods, in accordance with the degree of utilizing the seasonal climate prediction information, were developed in order to improve predictability and to refine the spatial scale. These methods include: (1 the Simple Bias Correction (SBC method, which directly uses APCC's dynamic prediction data with a 3 to 6 month lead time; (2 the Moving Window Regression (MWR method, which indirectly utilizes dynamic prediction data; (3 the Climate Index Regression (CIR method, which predominantly uses observation-based climate indices; and (4 the Integrated Time Regression (ITR method, which uses predictors selected from both CIR and MWR. Then, a sampling-based temporal downscaling was conducted using the Mahalanobis distance method in order to create daily weather inputs to the Soil and Water Assessment Tool (SWAT model. Long-term predictability of water quality within the Wecheon watershed of the Nakdong River Basin was evaluated. According to the Korean Ministry of Environment's Provisions of Water Quality Prediction and Response Measures, modeling-based predictability was evaluated by using 3-month lead prediction data issued in February, May, August, and November as model input of SWAT. Finally, an integrated approach, which takes into account various climate information and downscaling methods for water quality prediction, was presented. This integrated approach can be used to prevent potential problems caused by extreme climate in advance.

Predicting Athletes’ Pre-Exercise Fluid Intake: A Theoretical Integration Approach

Directory of Open Access Journals (Sweden)

Chunxiao Li

2018-05-01

Full Text Available Pre-exercise fluid intake is an important healthy behavior for maintaining athletes’ sports performances and health. However, athletes’ behavioral adherence to fluid intake and its underlying psychological mechanisms have not been investigated. This prospective study aimed to use a health psychology model that integrates the self-determination theory and the theory of planned behavior for understanding pre-exercise fluid intake among athletes. Participants (n = 179 were athletes from college sport teams who completed surveys at two time points. Baseline (Time 1 assessment comprised psychological variables of the integrated model (i.e., autonomous and controlled motivation, attitude, subjective norm, perceived behavioral control, and intention and fluid intake (i.e., behavior was measured prospectively at one month (Time 2. Path analysis showed that the positive association between autonomous motivation and intention was mediated by subjective norm and perceived behavioral control. Controlled motivation positively predicted the subjective norm. Intentions positively predicted pre-exercise fluid intake behavior. Overall, the pattern of results was generally consistent with the integrated model, and it was suggested that athletes’ pre-exercise fluid intake behaviors were associated with the motivational and social cognitive factors of the model. The research findings could be informative for coaches and sport scientists to promote athletes’ pre-exercise fluid intake behaviors.

The Binding Sites of miR-619-5p in the mRNAs of Human and Orthologous Genes.

Science.gov (United States)

Atambayeva, Shara; Niyazova, Raigul; Ivashchenko, Anatoliy; Pyrkova, Anna; Pinsky, Ilya; Akimniyazova, Aigul; Labeit, Siegfried

2017-06-01

Normally, one miRNA interacts with the mRNA of one gene. However, there are miRNAs that can bind to many mRNAs, and one mRNA can be the target of many miRNAs. This significantly complicates the study of the properties of miRNAs and their diagnostic and medical applications. The search of 2,750 human microRNAs (miRNAs) binding sites in 12,175 mRNAs of human genes using the MirTarget program has been completed. For the binding sites of the miR-619-5p the hybridization free energy of the bonds was equal to 100% of the maximum potential free energy. The mRNAs of 201 human genes have complete complementary binding sites of miR-619-5p in the 3'UTR (214 sites), CDS (3 sites), and 5'UTR (4 sites). The mRNAs of CATAD1, ICA1L, GK5, POLH, and PRR11 genes have six miR-619-5p binding sites, and the mRNAs of OPA3 and CYP20A1 genes have eight and ten binding sites, respectively. All of these miR-619-5p binding sites are located in the 3'UTRs. The miR-619-5p binding site in the 5'UTR of mRNA of human USP29 gene is found in the mRNAs of orthologous genes of primates. Binding sites of miR-619-5p in the coding regions of mRNAs of C8H8orf44, C8orf44, and ISY1 genes encode the WLMPVIP oligopeptide, which is present in the orthologous proteins. Binding sites of miR-619-5p in the mRNAs of transcription factor genes ZNF429 and ZNF429 encode the AHACNP oligopeptide in another reading frame. Binding sites of miR-619-5p in the 3'UTRs of all human target genes are also present in the 3'UTRs of orthologous genes of mammals. The completely complementary binding sites for miR-619-5p are conservative in the orthologous mammalian genes. The majority of miR-619-5p binding sites are located in the 3'UTRs but some genes have miRNA binding sites in the 5'UTRs of mRNAs. Several genes have binding sites for miRNAs in the CDSs that are read in different open reading frames. Identical nucleotide sequences of binding sites encode different amino acids in different proteins. The binding sites of miR-619-5p

Kalman-predictive-proportional-integral-derivative (KPPID)

International Nuclear Information System (INIS)

Fluerasu, A.; Sutton, M.

2004-01-01

With third generation synchrotron X-ray sources, it is possible to acquire detailed structural information about the system under study with time resolution orders of magnitude faster than was possible a few years ago. These advances have generated many new challenges for changing and controlling the state of the system on very short time scales, in a uniform and controlled manner. For our particular X-ray experiments on crystallization or order-disorder phase transitions in metallic alloys, we need to change the sample temperature by hundreds of degrees as fast as possible while avoiding over or under shooting. To achieve this, we designed and implemented a computer-controlled temperature tracking system which combines standard Proportional-Integral-Derivative (PID) feedback, thermal modeling and finite difference thermal calculations (feedforward), and Kalman filtering of the temperature readings in order to reduce the noise. The resulting Kalman-Predictive-Proportional-Integral-Derivative (KPPID) algorithm allows us to obtain accurate control, to minimize the response time and to avoid over/under shooting, even in systems with inherently noisy temperature readings and time delays. The KPPID temperature controller was successfully implemented at the Advanced Photon Source at Argonne National Laboratories and was used to perform coherent and time-resolved X-ray diffraction experiments.

Integrating Models of Diffusion and Behavior to Predict Innovation Adoption, Maintenance, and Social Diffusion.

Science.gov (United States)

Smith, Rachel A; Kim, Youllee; Zhu, Xun; Doudou, Dimi Théodore; Sternberg, Eleanore D; Thomas, Matthew B

2018-01-01

This study documents an investigation into the adoption and diffusion of eave tubes, a novel mosquito vector control, during a large-scale scientific field trial in West Africa. The diffusion of innovations (DOI) and the integrated model of behavior (IMB) were integrated (i.e., innovation attributes with attitudes and social pressures with norms) to predict participants' (N = 329) diffusion intentions. The findings showed that positive attitudes about the innovation's attributes were a consistent positive predictor of diffusion intentions: adopting it, maintaining it, and talking with others about it. As expected by the DOI and the IMB, the social pressure created by a descriptive norm positively predicted intentions to adopt and maintain the innovation. Drawing upon sharing research, we argued that the descriptive norm may dampen future talk about the innovation, because it may no longer be seen as a novel, useful topic to discuss. As predicted, the results showed that as the descriptive norm increased, the intention to talk about the innovation decreased. These results provide broad support for integrating the DOI and the IMB to predict diffusion and for efforts to draw on other research to understand motivations for social diffusion.

Fast integration-based prediction bands for ordinary differential equation models.

Science.gov (United States)

Hass, Helge; Kreutz, Clemens; Timmer, Jens; Kaschek, Daniel

2016-04-15

To gain a deeper understanding of biological processes and their relevance in disease, mathematical models are built upon experimental data. Uncertainty in the data leads to uncertainties of the model's parameters and in turn to uncertainties of predictions. Mechanistic dynamic models of biochemical networks are frequently based on nonlinear differential equation systems and feature a large number of parameters, sparse observations of the model components and lack of information in the available data. Due to the curse of dimensionality, classical and sampling approaches propagating parameter uncertainties to predictions are hardly feasible and insufficient. However, for experimental design and to discriminate between competing models, prediction and confidence bands are essential. To circumvent the hurdles of the former methods, an approach to calculate a profile likelihood on arbitrary observations for a specific time point has been introduced, which provides accurate confidence and prediction intervals for nonlinear models and is computationally feasible for high-dimensional models. In this article, reliable and smooth point-wise prediction and confidence bands to assess the model's uncertainty on the whole time-course are achieved via explicit integration with elaborate correction mechanisms. The corresponding system of ordinary differential equations is derived and tested on three established models for cellular signalling. An efficiency analysis is performed to illustrate the computational benefit compared with repeated profile likelihood calculations at multiple time points. The integration framework and the examples used in this article are provided with the software package Data2Dynamics, which is based on MATLAB and freely available at http://www.data2dynamics.org helge.hass@fdm.uni-freiburg.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e

Integrative EEG biomarkers predict progression to Alzheimer's disease at the MCI stage

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Simon-Shlomo ePoil

2013-10-01

Full Text Available Alzheimer's disease (AD is a devastating disorder of increasing prevalence in modern society. Mild cognitive impairment (MCI is considered a transitional stage between normal aging and AD; however, not all subjects with MCI progress to AD. Prediction of conversion to AD at an early stage would enable an earlier, and potentially more effective, treatment of AD. Electroencephalography (EEG biomarkers would provide a non-invasive and relatively cheap screening tool to predict conversion to AD; however, traditional EEG biomarkers have not been considered accurate enough to be useful in clinical practice. Here, we aim to combine the information from multiple EEG biomarkers into a diagnostic classification index in order to improve the accuracy of predicting conversion from MCI to AD within a two-year period. We followed 86 patients initially diagnosed with MCI for two years during which 25 patients converted to AD. We show that multiple EEG biomarkers mainly related to activity in the beta-frequency range (13–30 Hz can predict conversion from MCI to AD. Importantly, by integrating six EEG biomarkers into a diagnostic index using logistic regression the prediction improved compared with the classification using the individual biomarkers, with a sensitivity of 88% and specificity of 82%, compared with a sensitivity of 64% and specificity of 62% of the best individual biomarker in this index. In order to identify this diagnostic index we developed a data mining approach implemented in the Neurophysiological Biomarker Toolbox (http://www.nbtwiki.net/. We suggest that this approach can be used to identify optimal combinations of biomarkers (integrative biomarkers also in other modalities. Potentially, these integrative biomarkers could be more sensitive to disease progression and response to therapeutic intervention.

Disturbance metrics predict a wetland Vegetation Index of Biotic Integrity

Science.gov (United States)

Stapanian, Martin A.; Mack, John; Adams, Jean V.; Gara, Brian; Micacchion, Mick

2013-01-01

Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas in the USA. Knowledge of the best predictors of VIBIs would enable management agencies to make better decisions regarding mitigation site selection and performance monitoring criteria. We use a novel statistical technique to develop predictive models for an established index of wetland vegetation integrity (Ohio VIBI), using as independent variables 20 indices and metrics of habitat quality, wetland disturbance, and buffer area land use from 149 wetlands in Ohio, USA. For emergent and forest wetlands, predictive models explained 61% and 54% of the variability, respectively, in Ohio VIBI scores. In both cases the most important predictor of Ohio VIBI score was a metric that assessed habitat alteration and development in the wetland. Of secondary importance as a predictor was a metric that assessed microtopography, interspersion, and quality of vegetation communities in the wetland. Metrics and indices assessing disturbance and land use of the buffer area were generally poor predictors of Ohio VIBI scores. Our results suggest that vegetation integrity of emergent and forest wetlands could be most directly enhanced by minimizing substrate and habitat disturbance within the wetland. Such efforts could include reducing or eliminating any practices that disturb the soil profile, such as nutrient enrichment from adjacent farm land, mowing, grazing, or cutting or removing woody plants.

Predicting adverse drug reaction profiles by integrating protein interaction networks with drug structures.

Science.gov (United States)

Huang, Liang-Chin; Wu, Xiaogang; Chen, Jake Y

2013-01-01

The prediction of adverse drug reactions (ADRs) has become increasingly important, due to the rising concern on serious ADRs that can cause drugs to fail to reach or stay in the market. We proposed a framework for predicting ADR profiles by integrating protein-protein interaction (PPI) networks with drug structures. We compared ADR prediction performances over 18 ADR categories through four feature groups-only drug targets, drug targets with PPI networks, drug structures, and drug targets with PPI networks plus drug structures. The results showed that the integration of PPI networks and drug structures can significantly improve the ADR prediction performance. The median AUC values for the four groups were 0.59, 0.61, 0.65, and 0.70. We used the protein features in the best two models, "Cardiac disorders" (median-AUC: 0.82) and "Psychiatric disorders" (median-AUC: 0.76), to build ADR-specific PPI networks with literature supports. For validation, we examined 30 drugs withdrawn from the U.S. market to see if our approach can predict their ADR profiles and explain why they were withdrawn. Except for three drugs having ADRs in the categories we did not predict, 25 out of 27 withdrawn drugs (92.6%) having severe ADRs were successfully predicted by our approach. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Linking the potato genome to the conserved ortholog set (COS) markers

Science.gov (United States)

2013-01-01

Background Conserved ortholog set (COS) markers are an important functional genomics resource that has greatly improved orthology detection in Asterid species. A comprehensive list of these markers is available at Sol Genomics Network (http://solgenomics.net/) and many of these have been placed on the genetic maps of a number of solanaceous species. Results We amplified over 300 COS markers from eight potato accessions involving two diploid landraces of Solanum tuberosum Andigenum group (formerly classified as S. goniocalyx, S. phureja), and a dihaploid clone derived from a modern tetraploid cultivar of S. tuberosum and the wild species S. berthaultii, S. chomatophilum, and S. paucissectum. By BLASTn (Basic Local Alignment Search Tool of the NCBI, National Center for Biotechnology Information) algorithm we mapped the DNA sequences of these markers into the potato genome sequence. Additionally, we mapped a subset of these markers genetically in potato and present a comparison between the physical and genetic locations of these markers in potato and in comparison with the genetic location in tomato. We found that most of the COS markers are single-copy in the reference genome of potato and that the genetic location in tomato and physical location in potato sequence are mostly in agreement. However, we did find some COS markers that are present in multiple copies and those that map in unexpected locations. Sequence comparisons between species show that some of these markers may be paralogs. Conclusions The sequence-based physical map becomes helpful in identification of markers for traits of interest thereby reducing the number of markers to be tested for applications like marker assisted selection, diversity, and phylogenetic studies. PMID:23758607

Neighborhood Integration and Connectivity Predict Cognitive Performance and Decline

Directory of Open Access Journals (Sweden)

Amber Watts PhD

2015-08-01

Full Text Available Objective: Neighborhood characteristics may be important for promoting walking, but little research has focused on older adults, especially those with cognitive impairment. We evaluated the role of neighborhood characteristics on cognitive function and decline over a 2-year period adjusting for measures of walking. Method: In a study of 64 older adults with and without mild Alzheimer’s disease (AD, we evaluated neighborhood integration and connectivity using geographical information systems data and space syntax analysis. In multiple regression analyses, we used these characteristics to predict 2-year declines in factor analytically derived cognitive scores (attention, verbal memory, mental status adjusting for age, sex, education, and self-reported walking. Results : Neighborhood integration and connectivity predicted cognitive performance at baseline, and changes in cognitive performance over 2 years. The relationships between neighborhood characteristics and cognitive performance were not fully explained by self-reported walking. Discussion : Clearer definitions of specific neighborhood characteristics associated with walkability are needed to better understand the mechanisms by which neighborhoods may impact cognitive outcomes. These results have implications for measuring neighborhood characteristics, design and maintenance of living spaces, and interventions to increase walking among older adults. We offer suggestions for future research measuring neighborhood characteristics and cognitive function.

Integrated predictive modelling simulations of burning plasma experiment designs

International Nuclear Information System (INIS)

Bateman, Glenn; Onjun, Thawatchai; Kritz, Arnold H

2003-01-01

Models for the height of the pedestal at the edge of H-mode plasmas (Onjun T et al 2002 Phys. Plasmas 9 5018) are used together with the Multi-Mode core transport model (Bateman G et al 1998 Phys. Plasmas 5 1793) in the BALDUR integrated predictive modelling code to predict the performance of the ITER (Aymar A et al 2002 Plasma Phys. Control. Fusion 44 519), FIRE (Meade D M et al 2001 Fusion Technol. 39 336), and IGNITOR (Coppi B et al 2001 Nucl. Fusion 41 1253) fusion reactor designs. The simulation protocol used in this paper is tested by comparing predicted temperature and density profiles against experimental data from 33 H-mode discharges in the JET (Rebut P H et al 1985 Nucl. Fusion 25 1011) and DIII-D (Luxon J L et al 1985 Fusion Technol. 8 441) tokamaks. The sensitivities of the predictions are evaluated for the burning plasma experimental designs by using variations of the pedestal temperature model that are one standard deviation above and below the standard model. Simulations of the fusion reactor designs are carried out for scans in which the plasma density and auxiliary heating power are varied

Development of an Integrated Moisture Index for predicting species composition

Science.gov (United States)

Louis R. Iverson; Charles T. Scott; Martin E. Dale; Anantha Prasad

1996-01-01

A geographic information system (GIS) approach was used to develop an Integrated Moisture Index (IMI), which was used to predict species composition for Ohio forests. Several landscape features (a slope-aspect shading index, cumulative flow of water downslope, curvature of the landscape, and the water-holding capacity of the soil) were derived from elevation and soils...

Integration of Fast Predictive Model and SLM Process Development Chamber, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — This STTR project seeks to develop a fast predictive model for selective laser melting (SLM) processes and then integrate that model with an SLM chamber that allows...

The Cyclin-Dependent Kinase Ortholog pUL97 of Human Cytomegalovirus Interacts with Cyclins

Directory of Open Access Journals (Sweden)

Laura Graf

2013-12-01

Full Text Available The human cytomegalovirus (HCMV-encoded protein kinase, pUL97, is considered a cyclin-dependent kinase (CDK ortholog, due to shared structural and functional characteristics. The primary mechanism of CDK activation is binding to corresponding cyclins, including cyclin T1, which is the usual regulatory cofactor of CDK9. This study provides evidence of direct interaction between pUL97 and cyclin T1 using yeast two-hybrid and co-immunoprecipitation analyses. Confocal immunofluorescence revealed partial colocalization of pUL97 with cyclin T1 in subnuclear compartments, most pronounced in viral replication centres. The distribution patterns of pUL97 and cyclin T1 were independent of HCMV strain and host cell type. The sequence domain of pUL97 responsible for the interaction with cyclin T1 was between amino acids 231–280. Additional co-immunoprecipitation analyses showed cyclin B1 and cyclin A as further pUL97 interaction partners. Investigation of the pUL97-cyclin T1 interaction in an ATP consumption assay strongly suggested phosphorylation of pUL97 by the CDK9/cyclin T1 complex in a substrate concentration-dependent manner. This is the first demonstration of interaction between a herpesviral CDK ortholog and cellular cyclins.

Brain systems for probabilistic and dynamic prediction: computational specificity and integration.

Directory of Open Access Journals (Sweden)

Jill X O'Reilly

2013-09-01

Full Text Available A computational approach to functional specialization suggests that brain systems can be characterized in terms of the types of computations they perform, rather than their sensory or behavioral domains. We contrasted the neural systems associated with two computationally distinct forms of predictive model: a reinforcement-learning model of the environment obtained through experience with discrete events, and continuous dynamic forward modeling. By manipulating the precision with which each type of prediction could be used, we caused participants to shift computational strategies within a single spatial prediction task. Hence (using fMRI we showed that activity in two brain systems (typically associated with reward learning and motor control could be dissociated in terms of the forms of computations that were performed there, even when both systems were used to make parallel predictions of the same event. A region in parietal cortex, which was sensitive to the divergence between the predictions of the models and anatomically connected to both computational networks, is proposed to mediate integration of the two predictive modes to produce a single behavioral output.

The Prediction-Focused Approach: An opportunity for hydrogeophysical data integration and interpretation

Science.gov (United States)

Hermans, Thomas; Nguyen, Frédéric; Klepikova, Maria; Dassargues, Alain; Caers, Jef

2017-04-01

Hydrogeophysics is an interdisciplinary field of sciences aiming at a better understanding of subsurface hydrological processes. If geophysical surveys have been successfully used to qualitatively characterize the subsurface, two important challenges remain for a better quantification of hydrological processes: (1) the inversion of geophysical data and (2) their integration in hydrological subsurface models. The classical inversion approach using regularization suffers from spatially and temporally varying resolution and yields geologically unrealistic solutions without uncertainty quantification, making their utilization for hydrogeological calibration less consistent. More advanced techniques such as coupled inversion allow for a direct use of geophysical data for conditioning groundwater and solute transport model calibration. However, the technique is difficult to apply in complex cases and remains computationally demanding to estimate uncertainty. In a recent study, we investigate a prediction-focused approach (PFA) to directly estimate subsurface physical properties from geophysical data, circumventing the need for classic inversions. In PFA, we seek a direct relationship between the data and the subsurface variables we want to predict (the forecast). This relationship is obtained through a prior set of subsurface models for which both data and forecast are computed. A direct relationship can often be derived through dimension reduction techniques. PFA offers a framework for both hydrogeophysical "inversion" and hydrogeophysical data integration. For hydrogeophysical "inversion", the considered forecast variable is the subsurface variable, such as the salinity. An ensemble of possible solutions is generated, allowing uncertainty quantification. For hydrogeophysical data integration, the forecast variable becomes the prediction we want to make with our subsurface models, such as the concentration of contaminant in a drinking water production well. Geophysical

Predicting Elementary Education Candidates' Technology Integration during Their Field Placement Instruction.

Science.gov (United States)

Negishi, Meiko; Elder, Anastasia D.; Hamil, J. Burnette; Mzoughi, Taha

A growing concern in teacher education programs is technology training. Research confirms that training positively affects perservice teachers' attitudes and technology proficiency. However, little is known about the kinds of factors that may predict preservice teachers' integration of technology into their own instruction. The goal of this study…

A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information.

Science.gov (United States)

Luo, Yunan; Zhao, Xinbin; Zhou, Jingtian; Yang, Jinglin; Zhang, Yanqing; Kuang, Wenhua; Peng, Jian; Chen, Ligong; Zeng, Jianyang

2017-09-18

The emergence of large-scale genomic, chemical and pharmacological data provides new opportunities for drug discovery and repositioning. In this work, we develop a computational pipeline, called DTINet, to predict novel drug-target interactions from a constructed heterogeneous network, which integrates diverse drug-related information. DTINet focuses on learning a low-dimensional vector representation of features, which accurately explains the topological properties of individual nodes in the heterogeneous network, and then makes prediction based on these representations via a vector space projection scheme. DTINet achieves substantial performance improvement over other state-of-the-art methods for drug-target interaction prediction. Moreover, we experimentally validate the novel interactions between three drugs and the cyclooxygenase proteins predicted by DTINet, and demonstrate the new potential applications of these identified cyclooxygenase inhibitors in preventing inflammatory diseases. These results indicate that DTINet can provide a practically useful tool for integrating heterogeneous information to predict new drug-target interactions and repurpose existing drugs.Network-based data integration for drug-target prediction is a promising avenue for drug repositioning, but performance is wanting. Here, the authors introduce DTINet, whose performance is enhanced in the face of noisy, incomplete and high-dimensional biological data by learning low-dimensional vector representations.

Identification of genes involved in a water stress response in timothy and mapping of orthologous loci in perennial ryegrass

DEFF Research Database (Denmark)

Jonavičienė, Kristina; Studer, Bruno; Asp, Torben

2012-01-01

In order to characterize the response of selected grasses to water stress, relative water content (RWC) in leaves and quantum efficiency of photosystem 2 (Fv/Fm) were measured in Phleum pratense L., P. bertolonii DC. and P. phleoides H. Karst. during 6 d of water stress. The results indicated...... differential responses to water stress among the three Phleum species with higher water deficit sensitivity of P. pratense and P. bertolonii than that of P. phleoides. The cDNA-amplified fragment length polymorphism (cDNA-AFLP) technique was applied to identify differentially expressed genes responding...... to water stress in P. pratense. Cloned and sequenced differentially expressed fragments (DEFs) were used for primer design in order to identify orthologous genes in Lolium perenne L. Twelve genes orthologous to P. pratense DEFs were mapped in the L. perenne mapping population VrnA based on a high...

Comparative analysis of function and interaction of transcription factors in nematodes: Extensive conservation of orthology coupled to rapid sequence evolution

Directory of Open Access Journals (Sweden)

Singh Rama S

2008-08-01

Full Text Available Abstract Background Much of the morphological diversity in eukaryotes results from differential regulation of gene expression in which transcription factors (TFs play a central role. The nematode Caenorhabditis elegans is an established model organism for the study of the roles of TFs in controlling the spatiotemporal pattern of gene expression. Using the fully sequenced genomes of three Caenorhabditid nematode species as well as genome information from additional more distantly related organisms (fruit fly, mouse, and human we sought to identify orthologous TFs and characterized their patterns of evolution. Results We identified 988 TF genes in C. elegans, and inferred corresponding sets in C. briggsae and C. remanei, containing 995 and 1093 TF genes, respectively. Analysis of the three gene sets revealed 652 3-way reciprocal 'best hit' orthologs (nematode TF set, approximately half of which are zinc finger (ZF-C2H2 and ZF-C4/NHR types and HOX family members. Examination of the TF genes in C. elegans and C. briggsae identified the presence of significant tandem clustering on chromosome V, the majority of which belong to ZF-C4/NHR family. We also found evidence for lineage-specific duplications and rapid evolution of many of the TF genes in the two species. A search of the TFs conserved among nematodes in Drosophila melanogaster, Mus musculus and Homo sapiens revealed 150 reciprocal orthologs, many of which are associated with important biological processes and human diseases. Finally, a comparison of the sequence, gene interactions and function indicates that nematode TFs conserved across phyla exhibit significantly more interactions and are enriched in genes with annotated mutant phenotypes compared to those that lack orthologs in other species. Conclusion Our study represents the first comprehensive genome-wide analysis of TFs across three nematode species and other organisms. The findings indicate substantial conservation of transcription

Predicting cycle time distributions for integrated processing workstations : an aggregate modeling approach

NARCIS (Netherlands)

Veeger, C.P.L.; Etman, L.F.P.; Lefeber, A.A.J.; Adan, I.J.B.F.; Herk, van J.; Rooda, J.E.

2011-01-01

To predict cycle time distributions of integrated processing workstations, detailed simulation models are almost exclusively used; these models require considerable development and maintenance effort. As an alternative, we propose an aggregate model that is a lumped-parameter representation of the

Integration of Predictive Display and Aircraft Flight Control System

Directory of Open Access Journals (Sweden)

Efremov A.V.

2017-01-01

Full Text Available The synthesis of predictive display information and direct lift control system are considered for the path control tracking tasks (in particular landing task. The both solutions are based on pilot-vehicle system analysis and requirements to provide the highest accuracy and lowest pilot workload. The investigation was carried out for cases with and without time delay in aircraft dynamics. The efficiency of the both ways for the flying qualities improvement and their integration is tested by ground based simulation.

An electrically actuated imperfect microbeam: Dynamical integrity for interpreting and predicting the device response

KAUST Repository

Ruzziconi, Laura

2013-02-20

In this study we deal with a microelectromechanical system (MEMS) and develop a dynamical integrity analysis to interpret and predict the experimental response. The device consists of a clamped-clamped polysilicon microbeam, which is electrostatically and electrodynamically actuated. It has non-negligible imperfections, which are a typical consequence of the microfabrication process. A single-mode reduced-order model is derived and extensive numerical simulations are performed in a neighborhood of the first symmetric natural frequency, via frequency response diagrams and behavior chart. The typical softening behavior is observed and the overall scenario is explored, when both the frequency and the electrodynamic voltage are varied. We show that simulations based on direct numerical integration of the equation of motion in time yield satisfactory agreement with the experimental data. Nevertheless, these theoretical predictions are not completely fulfilled in some aspects. In particular, the range of existence of each attractor is smaller in practice than in the simulations. This is because these theoretical curves represent the ideal limit case where disturbances are absent, which never occurs under realistic conditions. A reliable prediction of the actual (and not only theoretical) range of existence of each attractor is essential in applications. To overcome this discrepancy and extend the results to the practical case where disturbances exist, a dynamical integrity analysis is developed. After introducing dynamical integrity concepts, integrity profiles and integrity charts are drawn. They are able to describe if each attractor is robust enough to tolerate the disturbances. Moreover, they detect the parameter range where each branch can be reliably observed in practice and where, instead, becomes vulnerable, i.e. they provide valuable information to operate the device in safe conditions according to the desired outcome and depending on the expected disturbances

At the Nexus of History, Ecology, and Hydrobiogeochemistry: Improved Predictions across Scales through Integration.

Science.gov (United States)

Stegen, James C

2018-01-01

To improve predictions of ecosystem function in future environments, we need to integrate the ecological and environmental histories experienced by microbial communities with hydrobiogeochemistry across scales. A key issue is whether we can derive generalizable scaling relationships that describe this multiscale integration. There is a strong foundation for addressing these challenges. We have the ability to infer ecological history with null models and reveal impacts of environmental history through laboratory and field experimentation. Recent developments also provide opportunities to inform ecosystem models with targeted omics data. A major next step is coupling knowledge derived from such studies with multiscale modeling frameworks that are predictive under non-steady-state conditions. This is particularly true for systems spanning dynamic interfaces, which are often hot spots of hydrobiogeochemical function. We can advance predictive capabilities through a holistic perspective focused on the nexus of history, ecology, and hydrobiogeochemistry.

Systematic discovery of unannotated genes in 11 yeast species using a database of orthologous genomic segments

LENUS (Irish Health Repository)

OhEigeartaigh, Sean S

2011-07-26

Abstract Background In standard BLAST searches, no information other than the sequences of the query and the database entries is considered. However, in situations where two genes from different species have only borderline similarity in a BLAST search, the discovery that the genes are located within a region of conserved gene order (synteny) can provide additional evidence that they are orthologs. Thus, for interpreting borderline search results, it would be useful to know whether the syntenic context of a database hit is similar to that of the query. This principle has often been used in investigations of particular genes or genomic regions, but to our knowledge it has never been implemented systematically. Results We made use of the synteny information contained in the Yeast Gene Order Browser database for 11 yeast species to carry out a systematic search for protein-coding genes that were overlooked in the original annotations of one or more yeast genomes but which are syntenic with their orthologs. Such genes tend to have been overlooked because they are short, highly divergent, or contain introns. The key features of our software - called SearchDOGS - are that the database entries are classified into sets of genomic segments that are already known to be orthologous, and that very weak BLAST hits are retained for further analysis if their genomic location is similar to that of the query. Using SearchDOGS we identified 595 additional protein-coding genes among the 11 yeast species, including two new genes in Saccharomyces cerevisiae. We found additional genes for the mating pheromone a-factor in six species including Kluyveromyces lactis. Conclusions SearchDOGS has proven highly successful for identifying overlooked genes in the yeast genomes. We anticipate that our approach can be adapted for study of further groups of species, such as bacterial genomes. More generally, the concept of doing sequence similarity searches against databases to which external

Integrated petrophysical and reservoir characterization workflow to enhance permeability and water saturation prediction

Science.gov (United States)

Al-Amri, Meshal; Mahmoud, Mohamed; Elkatatny, Salaheldin; Al-Yousef, Hasan; Al-Ghamdi, Tariq

2017-07-01

Accurate estimation of permeability is essential in reservoir characterization and in determining fluid flow in porous media which greatly assists optimize the production of a field. Some of the permeability prediction techniques such as Porosity-Permeability transforms and recently artificial intelligence and neural networks are encouraging but still show moderate to good match to core data. This could be due to limitation to homogenous media while the knowledge about geology and heterogeneity is indirectly related or absent. The use of geological information from core description as in Lithofacies which includes digenetic information show a link to permeability when categorized into rock types exposed to similar depositional environment. The objective of this paper is to develop a robust combined workflow integrating geology and petrophysics and wireline logs in an extremely heterogeneous carbonate reservoir to accurately predict permeability. Permeability prediction is carried out using pattern recognition algorithm called multi-resolution graph-based clustering (MRGC). We will bench mark the prediction results with hard data from core and well test analysis. As a result, we showed how much better improvements are achieved in the permeability prediction when geology is integrated within the analysis. Finally, we use the predicted permeability as an input parameter in J-function and correct for uncertainties in saturation calculation produced by wireline logs using the classical Archie equation. Eventually, high level of confidence in hydrocarbon volumes estimation is reached when robust permeability and saturation height functions are estimated in presence of important geological details that are petrophysically meaningful.

Departure Queue Prediction for Strategic and Tactical Surface Scheduler Integration

Science.gov (United States)

Zelinski, Shannon; Windhorst, Robert

2016-01-01

A departure metering concept to be demonstrated at Charlotte Douglas International Airport (CLT) will integrate strategic and tactical surface scheduling components to enable the respective collaborative decision making and improved efficiency benefits these two methods of scheduling provide. This study analyzes the effect of tactical scheduling on strategic scheduler predictability. Strategic queue predictions and target gate pushback times to achieve a desired queue length are compared between fast time simulations of CLT surface operations with and without tactical scheduling. The use of variable departure rates as a strategic scheduler input was shown to substantially improve queue predictions over static departure rates. With target queue length calibration, the strategic scheduler can be tuned to produce average delays within one minute of the tactical scheduler. However, root mean square differences between strategic and tactical delays were between 12 and 15 minutes due to the different methods the strategic and tactical schedulers use to predict takeoff times and generate gate pushback clearances. This demonstrates how difficult it is for the strategic scheduler to predict tactical scheduler assigned gate delays on an individual flight basis as the tactical scheduler adjusts departure sequence to accommodate arrival interactions. Strategic/tactical scheduler compatibility may be improved by providing more arrival information to the strategic scheduler and stabilizing tactical scheduler changes to runway sequence in response to arrivals.

Energy-Efficient Integration of Continuous Context Sensing and Prediction into Smartwatches

Directory of Open Access Journals (Sweden)

Reza Rawassizadeh

2015-09-01

Full Text Available As the availability and use of wearables increases, they are becoming a promising platform for context sensing and context analysis. Smartwatches are a particularly interesting platform for this purpose, as they offer salient advantages, such as their proximity to the human body. However, they also have limitations associated with their small form factor, such as processing power and battery life, which makes it difficult to simply transfer smartphone-based context sensing and prediction models to smartwatches. In this paper, we introduce an energy-efficient, generic, integrated framework for continuous context sensing and prediction on smartwatches. Our work extends previous approaches for context sensing and prediction on wrist-mounted wearables that perform predictive analytics outside the device. We offer a generic sensing module and a novel energy-efficient, on-device prediction module that is based on a semantic abstraction approach to convert sensor data into meaningful information objects, similar to human perception of a behavior. Through six evaluations, we analyze the energy efficiency of our framework modules, identify the optimal file structure for data access and demonstrate an increase in accuracy of prediction through our semantic abstraction method. The proposed framework is hardware independent and can serve as a reference model for implementing context sensing and prediction on small wearable devices beyond smartwatches, such as body-mounted cameras.

Energy-Efficient Integration of Continuous Context Sensing and Prediction into Smartwatches.

Science.gov (United States)

Rawassizadeh, Reza; Tomitsch, Martin; Nourizadeh, Manouchehr; Momeni, Elaheh; Peery, Aaron; Ulanova, Liudmila; Pazzani, Michael

2015-09-08

As the availability and use of wearables increases, they are becoming a promising platform for context sensing and context analysis. Smartwatches are a particularly interesting platform for this purpose, as they offer salient advantages, such as their proximity to the human body. However, they also have limitations associated with their small form factor, such as processing power and battery life, which makes it difficult to simply transfer smartphone-based context sensing and prediction models to smartwatches. In this paper, we introduce an energy-efficient, generic, integrated framework for continuous context sensing and prediction on smartwatches. Our work extends previous approaches for context sensing and prediction on wrist-mounted wearables that perform predictive analytics outside the device. We offer a generic sensing module and a novel energy-efficient, on-device prediction module that is based on a semantic abstraction approach to convert sensor data into meaningful information objects, similar to human perception of a behavior. Through six evaluations, we analyze the energy efficiency of our framework modules, identify the optimal file structure for data access and demonstrate an increase in accuracy of prediction through our semantic abstraction method. The proposed framework is hardware independent and can serve as a reference model for implementing context sensing and prediction on small wearable devices beyond smartwatches, such as body-mounted cameras.

The XMAP215 Ortholog Alp14 Promotes Microtubule Nucleation in Fission Yeast.

Science.gov (United States)

Flor-Parra, Ignacio; Iglesias-Romero, Ana Belén; Chang, Fred

2018-06-04

The organization and number of microtubules (MTs) in a cell depend on the proper regulation of MT nucleation. Currently, the mechanism of nucleation is the most poorly understood aspect of MT dynamics. XMAP215/chTOG/Alp14/Stu2 proteins are MT polymerases that stimulate MT polymerization at MT plus ends by binding and releasing tubulin dimers. Although these proteins also localize to MT organizing centers and have nucleating activity in vitro, it is not yet clear whether these proteins participate in MT nucleation in vivo. Here, we demonstrate that in the fission yeast Schizosaccharomyces pombe, the XMAP215 ortholog Alp14 is critical for efficient MT nucleation in vivo. In multiple assays, loss of Alp14 function led to reduced nucleation rate and numbers of interphase MT bundles. Conversely, activation of Alp14 led to increased nucleation frequency. Alp14 associated with Mto1 and γ-tubulin complex components, and artificially targeting Alp14 to the γ-tubulin ring complexes (γ-TuRCs) stimulated nucleation. In imaging individual nucleation events, we found that Alp14 transiently associated with a γ-tubulin particle shortly before the appearance of a new MT. The transforming acidic coiled-coil (TACC) ortholog Alp7 mediated the localization of Alp14 at nucleation sites but not plus ends, and was required for efficient nucleation but not for MT polymerization. Our findings provide the strongest evidence to date that Alp14 serves as a critical MT nucleation factor in vivo. We suggest a model in which Alp14 associates with the γ-tubulin complex in an Alp7-dependent manner to facilitate the assembly or stabilization of the nascent MT. Copyright © 2018 Elsevier Ltd. All rights reserved.

Senataxin, the ortholog of a yeast RNA helicase, is mutant in ataxia-ocular apraxia 2.

Science.gov (United States)

Moreira, Maria-Céu; Klur, Sandra; Watanabe, Mitsunori; Németh, Andrea H; Le Ber, Isabelle; Moniz, José-Carlos; Tranchant, Christine; Aubourg, Patrick; Tazir, Meriem; Schöls, Lüdger; Pandolfo, Massimo; Schulz, Jörg B; Pouget, Jean; Calvas, Patrick; Shizuka-Ikeda, Masami; Shoji, Mikio; Tanaka, Makoto; Izatt, Louise; Shaw, Christopher E; M'Zahem, Abderrahim; Dunne, Eimear; Bomont, Pascale; Benhassine, Traki; Bouslam, Naïma; Stevanin, Giovanni; Brice, Alexis; Guimarães, João; Mendonça, Pedro; Barbot, Clara; Coutinho, Paula; Sequeiros, Jorge; Dürr, Alexandra; Warter, Jean-Marie; Koenig, Michel

2004-03-01

Ataxia-ocular apraxia 2 (AOA2) was recently identified as a new autosomal recessive ataxia. We have now identified causative mutations in 15 families, which allows us to clinically define this entity by onset between 10 and 22 years, cerebellar atrophy, axonal sensorimotor neuropathy, oculomotor apraxia and elevated alpha-fetoprotein (AFP). Ten of the fifteen mutations cause premature termination of a large DEAxQ-box helicase, the human ortholog of yeast Sen1p, involved in RNA maturation and termination.

Tissue expression and enzymologic characterization of human prostate specific membrane antigen and its rat and pig orthologs

Czech Academy of Sciences Publication Activity Database

Rovenská, Miroslava; Hlouchová, Klára; Šácha, Pavel; Mlčochová, Petra; Horák, Vratislav; Zámečník, J.; Bařinka, C.; Konvalinka, Jan

2008-01-01

Roč. 68, č. 2 (2008), s. 171-182 ISSN 0270-4137 R&D Projects: GA MŠk 1M0508; GA ČR GA524/04/0102 Institutional research plan: CEZ:AV0Z40550506; CEZ:AV0Z50450515 Keywords : prostate specific membrane antigen * glutamate carboxypeptidase II * animal orthologs * prostate cancer * animal model Subject RIV: CE - Biochemistry Impact factor: 3.069, year: 2008

Predictive Coding and Multisensory Integration: An Attentional Account of the Multisensory Mind

Directory of Open Access Journals (Sweden)

Durk eTalsma

2015-03-01

Full Text Available Multisensory integration involves a host of different cognitive processes, occurring at different stages of sensory processing. Here I argue that, despite recent insights suggesting that multisensory interactions can occur at very early latencies, the actual integration of individual sensory traces into an internally consistent mental representation is dependent on both top-down and bottom-up processes. Moreover, I argue that this integration is not limited to just sensory inputs, but that internal cognitive processes also shape the resulting mental representation. Studies showing that memory recall is affected by the initial multisensory context in which the stimuli were presented will be discussed, as well as several studies showing that mental imagery can affect multisensory illusions. This empirical evidence will be discussed from a predictive coding perspective, in which a central top-down attentional process is proposed to play a central role in coordinating the integration of all these inputs into a coherent mental representation.

Cloning of zebrafish Mustn1 orthologs and their expression during early development.

Science.gov (United States)

Camarata, Troy; Vasilyev, Aleksandr; Hadjiargyrou, Michael

2016-11-15

Mustn1 is a small nuclear protein that is involved in the development and regeneration of the musculoskeletal system. Previous work established a role for Mustn1 in myogenic and chondrogenic differentiation. In addition, recent evidence suggests a potential role for Mustn1 in cilia function in zebrafish. A detailed study of Mustn1 expression has yet to be conducted in zebrafish. As such, we report herein the cloning of the zebrafish Mustn1 orthologs, mustn1a and mustn1b, and their expression during zebrafish embryonic and larval development. Results indicate a 44% nucleotide identity between the two paralogs. Phylogenetic analysis further confirmed that the Mustn1a and 1b predicted proteins were highly related to other vertebrate members of the Mustn1 protein family. Whole mount in situ hybridization revealed expression of both mustn1a and 1b at the 7-somite stage through 72hpf in structures such as Kupffer's vesicle, segmental mesoderm, head structures, and otic vesicle. Additionally, in 5day old larva, mustn1a and 1b expression is detected in the neurocranium, otic capsule, and the gut. Although both were expressed in the neurocranium, mustn1a was localized in the hypophyseal fenestra whereas mustn1b was found near the posterior basicapsular commissure. mustn1b also displayed expression in the ceratohyal and ceratobranchial elements of the pharyngeal skeleton. These expression patterns were verified temporally by q-PCR analysis. Taken together, we conclude that Mustn1 expression is conserved in vertebrates and that the variations in expression of the two zebrafish paralogs suggest different modes of molecular regulation. Copyright © 2016 Elsevier B.V. All rights reserved.

Nuclear Envelope Phosphatase 1-Regulatory Subunit 1 (Formerly TMEM188) Is the Metazoan Spo7p Ortholog and Functions in the Lipin Activation Pathway*

Science.gov (United States)

Han, Sungwon; Bahmanyar, Shirin; Zhang, Peixiang; Grishin, Nick; Oegema, Karen; Crooke, Roseann; Graham, Mark; Reue, Karen; Dixon, Jack E.; Goodman, Joel M.

2012-01-01

Lipin-1 catalyzes the formation of diacylglycerol from phosphatidic acid. Lipin-1 mutations cause lipodystrophy in mice and acute myopathy in humans. It is heavily phosphorylated, and the yeast ortholog Pah1p becomes membrane-associated and active upon dephosphorylation by the Nem1p-Spo7p membrane complex. A mammalian ortholog of Nem1p is the C-terminal domain nuclear envelope phosphatase 1 (CTDNEP1, formerly “dullard”), but its Spo7p-like partner is unknown, and the need for its existence is debated. Here, we identify the metazoan ortholog of Spo7p, TMEM188, renamed nuclear envelope phosphatase 1-regulatory subunit 1 (NEP1-R1). CTDNEP1 and NEP1-R1 together complement a nem1Δspo7Δ strain to block endoplasmic reticulum proliferation and restore triacylglycerol levels and lipid droplet number. The two human orthologs are in a complex in cells, and the amount of CTDNEP1 is increased in the presence of NEP1-R1. In the Caenorhabditis elegans embryo, expression of nematode CTDNEP1 and NEP1-R1, as well as lipin-1, is required for normal nuclear membrane breakdown after zygote formation. The expression pattern of NEP1-R1 and CTDNEP1 in human and mouse tissues closely mirrors that of lipin-1. CTDNEP1 can dephosphorylate lipins-1a, -1b, and -2 in human cells only in the presence of NEP1-R1. The nuclear fraction of lipin-1b is increased when CTDNEP1 and NEP1-R1 are co-expressed. Therefore, NEP1-R1 is functionally conserved from yeast to humans and functions in the lipin activation pathway. PMID:22134922

Testing Predictive Models of Technology Integration in Mexico and the United States

Science.gov (United States)

Velazquez, Cesareo Morales

2008-01-01

Data from Mexico City, Mexico (N = 978) and from Texas, USA (N = 932) were used to test the predictive validity of the teacher professional development component of the Will, Skill, Tool Model of Technology Integration in a cross-cultural context. Structural equation modeling (SEM) was used to test the model. Analyses of these data yielded…

Guidelineness of the parameters using integrated test in down syndrome risk prediction

International Nuclear Information System (INIS)

Lee, Jin Won; Go, Sung Jin; Kang, Se Sik; Kim, Chang Soo

2016-01-01

This study was an evaluation of the significance of each parameter through aimed at pregnant women subjected to screening test(integrated test) in predicting risk of Down syndrome. We retrospectively analysed the correlation of risk of Down's syndrome with Nuchal Translucency(NT) images measured by ultrasound, Pregnancy Associated Plasma Protein A(PAPP-A), alpha-fetoprotein(AFP), unconjugated estriol(uE3), human chorionic gonadotrophin(hCG) and Inhibin A by maternal serum. As a result, a significant correlation with NT, uE3, hCG, Inhibin A is revealed with Down's syndrome risk(P<.001). In ROC analysis, AUC of Inhibin A is analysed as the biggest predictor of Down's syndrome(0.859). And the criterion for cut-off was inhibin A 1.4 MoM(sensitivity 81.8%, specificity 75.9%). In conclusion, Inhibin A was the most useful in parameters to predict Down's syndrome in the integrated test. If we make up for the weakness based on the cut-off value of parameters they will be able to be used as an independent indicator in the risk of Down's syndrome screening

Functional identification of an Arabidopsis snf4 ortholog by screening for heterologous multicopy suppressors of snf4 deficiency in yeast

DEFF Research Database (Denmark)

Kleinow, T.; Bhalerao, R.; Breuer, F.

2000-01-01

Yeast Snf4 is a prototype of activating gamma-subunits of conserved Snf1/AMPK-related protein kinases (SnRKs) controlling glucose and stress signaling in eukaryotes. The catalytic subunits of Arabidopsis SnRKs, AKIN10 and AKIN11, interact with Snf4 and suppress the snf1 and snf4 mutations in yeast....... By expression of an Arabidopsis cDNA library in yeast, heterologous multicopy snf4 suppressors were isolated. In addition to AKIN10 and AKIN11, the deficiency of yeast snf4 mutant to grown on non-fermentable carbon source was suppressed by Arabidopsis Myb30, CAAT-binding factor Hap3b, casein kinase I, zinc......-finger factors AZF2 and ZAT10, as well as orthologs of hexose/UDP-hexose transporters, calmodulin, SMC1-cohesin and Snf4. Here we describe the characterization of AtSNF4, a functional Arabidopsis Snf4 ortholog, that interacts with yeast Snf1 and specifically binds to the C-terminal regulatory domain...

Integrating principal component analysis and vector quantization with support vector regression for sulfur content prediction in HDS process

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Shokri Saeid

2015-01-01

Full Text Available An accurate prediction of sulfur content is very important for the proper operation and product quality control in hydrodesulfurization (HDS process. For this purpose, a reliable data- driven soft sensors utilizing Support Vector Regression (SVR was developed and the effects of integrating Vector Quantization (VQ with Principle Component Analysis (PCA were studied on the assessment of this soft sensor. First, in pre-processing step the PCA and VQ techniques were used to reduce dimensions of the original input datasets. Then, the compressed datasets were used as input variables for the SVR model. Experimental data from the HDS setup were employed to validate the proposed integrated model. The integration of VQ/PCA techniques with SVR model was able to increase the prediction accuracy of SVR. The obtained results show that integrated technique (VQ-SVR was better than (PCA-SVR in prediction accuracy. Also, VQ decreased the sum of the training and test time of SVR model in comparison with PCA. For further evaluation, the performance of VQ-SVR model was also compared to that of SVR. The obtained results indicated that VQ-SVR model delivered the best satisfactory predicting performance (AARE= 0.0668 and R2= 0.995 in comparison with investigated models.

Estimating cross-validatory predictive p-values with integrated importance sampling for disease mapping models.

Science.gov (United States)

Li, Longhai; Feng, Cindy X; Qiu, Shi

2017-06-30

An important statistical task in disease mapping problems is to identify divergent regions with unusually high or low risk of disease. Leave-one-out cross-validatory (LOOCV) model assessment is the gold standard for estimating predictive p-values that can flag such divergent regions. However, actual LOOCV is time-consuming because one needs to rerun a Markov chain Monte Carlo analysis for each posterior distribution in which an observation is held out as a test case. This paper introduces a new method, called integrated importance sampling (iIS), for estimating LOOCV predictive p-values with only Markov chain samples drawn from the posterior based on a full data set. The key step in iIS is that we integrate away the latent variables associated the test observation with respect to their conditional distribution without reference to the actual observation. By following the general theory for importance sampling, the formula used by iIS can be proved to be equivalent to the LOOCV predictive p-value. We compare iIS and other three existing methods in the literature with two disease mapping datasets. Our empirical results show that the predictive p-values estimated with iIS are almost identical to the predictive p-values estimated with actual LOOCV and outperform those given by the existing three methods, namely, the posterior predictive checking, the ordinary importance sampling, and the ghosting method by Marshall and Spiegelhalter (2003). Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Bioinformatics resource manager v2.3: an integrated software environment for systems biology with microRNA and cross-species analysis tools

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Tilton Susan C

2012-11-01

Full Text Available Abstract Background MicroRNAs (miRNAs are noncoding RNAs that direct post-transcriptional regulation of protein coding genes. Recent studies have shown miRNAs are important for controlling many biological processes, including nervous system development, and are highly conserved across species. Given their importance, computational tools are necessary for analysis, interpretation and integration of high-throughput (HTP miRNA data in an increasing number of model species. The Bioinformatics Resource Manager (BRM v2.3 is a software environment for data management, mining, integration and functional annotation of HTP biological data. In this study, we report recent updates to BRM for miRNA data analysis and cross-species comparisons across datasets. Results BRM v2.3 has the capability to query predicted miRNA targets from multiple databases, retrieve potential regulatory miRNAs for known genes, integrate experimentally derived miRNA and mRNA datasets, perform ortholog mapping across species, and retrieve annotation and cross-reference identifiers for an expanded number of species. Here we use BRM to show that developmental exposure of zebrafish to 30 uM nicotine from 6–48 hours post fertilization (hpf results in behavioral hyperactivity in larval zebrafish and alteration of putative miRNA gene targets in whole embryos at developmental stages that encompass early neurogenesis. We show typical workflows for using BRM to integrate experimental zebrafish miRNA and mRNA microarray datasets with example retrievals for zebrafish, including pathway annotation and mapping to human ortholog. Functional analysis of differentially regulated (p Conclusions BRM provides the ability to mine complex data for identification of candidate miRNAs or pathways that drive phenotypic outcome and, therefore, is a useful hypothesis generation tool for systems biology. The miRNA workflow in BRM allows for efficient processing of multiple miRNA and mRNA datasets in a single

Bioinformatics resource manager v2.3: an integrated software environment for systems biology with microRNA and cross-species analysis tools

Science.gov (United States)

2012-01-01

Background MicroRNAs (miRNAs) are noncoding RNAs that direct post-transcriptional regulation of protein coding genes. Recent studies have shown miRNAs are important for controlling many biological processes, including nervous system development, and are highly conserved across species. Given their importance, computational tools are necessary for analysis, interpretation and integration of high-throughput (HTP) miRNA data in an increasing number of model species. The Bioinformatics Resource Manager (BRM) v2.3 is a software environment for data management, mining, integration and functional annotation of HTP biological data. In this study, we report recent updates to BRM for miRNA data analysis and cross-species comparisons across datasets. Results BRM v2.3 has the capability to query predicted miRNA targets from multiple databases, retrieve potential regulatory miRNAs for known genes, integrate experimentally derived miRNA and mRNA datasets, perform ortholog mapping across species, and retrieve annotation and cross-reference identifiers for an expanded number of species. Here we use BRM to show that developmental exposure of zebrafish to 30 uM nicotine from 6–48 hours post fertilization (hpf) results in behavioral hyperactivity in larval zebrafish and alteration of putative miRNA gene targets in whole embryos at developmental stages that encompass early neurogenesis. We show typical workflows for using BRM to integrate experimental zebrafish miRNA and mRNA microarray datasets with example retrievals for zebrafish, including pathway annotation and mapping to human ortholog. Functional analysis of differentially regulated (p<0.05) gene targets in BRM indicates that nicotine exposure disrupts genes involved in neurogenesis, possibly through misregulation of nicotine-sensitive miRNAs. Conclusions BRM provides the ability to mine complex data for identification of candidate miRNAs or pathways that drive phenotypic outcome and, therefore, is a useful hypothesis

Accurate diffraction data integration by the EVAL15 profile prediction method : Application in chemical and biological crystallography

NARCIS (Netherlands)

Xian, X.

2009-01-01

Accurate integration of reflection intensities plays an essential role in structure determination of the crystallized compound. A new diffraction data integration method, EVAL15, is presented in this thesis. This method uses the principle of general impacts to predict ab inito three-dimensional

Fast and simple protein-alignment-guided assembly of orthologous gene families from microbiome sequencing reads.

Science.gov (United States)

Huson, Daniel H; Tappu, Rewati; Bazinet, Adam L; Xie, Chao; Cummings, Michael P; Nieselt, Kay; Williams, Rohan

2017-01-25

Microbiome sequencing projects typically collect tens of millions of short reads per sample. Depending on the goals of the project, the short reads can either be subjected to direct sequence analysis or be assembled into longer contigs. The assembly of whole genomes from metagenomic sequencing reads is a very difficult problem. However, for some questions, only specific genes of interest need to be assembled. This is then a gene-centric assembly where the goal is to assemble reads into contigs for a family of orthologous genes. We present a new method for performing gene-centric assembly, called protein-alignment-guided assembly, and provide an implementation in our metagenome analysis tool MEGAN. Genes are assembled on the fly, based on the alignment of all reads against a protein reference database such as NCBI-nr. Specifically, the user selects a gene family based on a classification such as KEGG and all reads binned to that gene family are assembled. Using published synthetic community metagenome sequencing reads and a set of 41 gene families, we show that the performance of this approach compares favorably with that of full-featured assemblers and that of a recently published HMM-based gene-centric assembler, both in terms of the number of reference genes detected and of the percentage of reference sequence covered. Protein-alignment-guided assembly of orthologous gene families complements whole-metagenome assembly in a new and very useful way.

Stock return predictability and market integration: The role of global and local information

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David G. McMillan

2016-12-01

Full Text Available This paper examines the predictability of a range of international stock markets where we allow the presence of both local and global predictive factors. Recent research has argued that US returns have predictive power for international stock returns. We expand this line of research, following work on market integration, to include a more general definition of the global factor, based on principal components analysis. Results identify three global expected returns factors, one related to the major stock markets of the US, UK and Asia and one related to the other markets analysed. The third component is related to dividend growth. A single dominant realised returns factor is also noted. A forecasting exercise comparing the principal components based factors to a US return factor and local market only factors, as well as the historical mean benchmark finds supportive evidence for the former approach. It is hoped that the results from this paper will be informative on three counts. First, to academics interested in understanding the dynamics asset price movement. Second, to market participants who aim to time the market and engage in portfolio and risk management. Third, to those (policy makers and others who are interested in linkages across international markets and the nature and degree of integration.

cdc-25.4, a Caenorhabditis elegans Ortholog of cdc25, Is Required for Male Mating Behavior

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Sangmi Oh

2016-12-01

Full Text Available Cell division cycle 25 (cdc25 is an evolutionarily conserved phosphatase that promotes cell cycle progression. Among the four cdc25 orthologs in Caenorhabditis elegans, we found that cdc-25.4 mutant males failed to produce outcrossed progeny. This was not caused by defects in sperm development, but by defects in male mating behavior. The cdc-25.4 mutant males showed various defects during male mating, including contact response, backing, turning, and vulva location. Aberrant turning behavior was the most prominent defect in the cdc-25.4 mutant males. We also found that cdc-25.4 is expressed in many neuronal cells throughout development. The turning defect in cdc-25.4 mutant males was recovered by cdc-25.4 transgenic expression in neuronal cells, suggesting that cdc-25.4 functions in neurons for male mating. However, the neuronal morphology of cdc-25.4 mutant males appeared to be normal, as examined with several neuronal markers. Also, RNAi depletion of wee-1.3, a C. elegans ortholog of Wee1/Myt1 kinase, failed to suppress the mating defects of cdc-25.4 mutant males. These findings suggest that, for successful male mating, cdc-25.4 does not target cell cycles that are required for neuronal differentiation and development. Rather, cdc-25.4 likely regulates noncanonical substrates in neuronal cells.

Guidelineness of the parameters using integrated test in down syndrome risk prediction

Energy Technology Data Exchange (ETDEWEB)

Lee, Jin Won [Graduate School of Catholic University of Pusan, Busan (Korea, Republic of); Go, Sung Jin; Kang, Se Sik; Kim, Chang Soo [Dept. Radiological Science, College of Health Sciences, Catholic University of Pusan, Busan (Korea, Republic of)

2016-12-15

This study was an evaluation of the significance of each parameter through aimed at pregnant women subjected to screening test(integrated test) in predicting risk of Down syndrome. We retrospectively analysed the correlation of risk of Down's syndrome with Nuchal Translucency(NT) images measured by ultrasound, Pregnancy Associated Plasma Protein A(PAPP-A), alpha-fetoprotein(AFP), unconjugated estriol(uE3), human chorionic gonadotrophin(hCG) and Inhibin A by maternal serum. As a result, a significant correlation with NT, uE3, hCG, Inhibin A is revealed with Down's syndrome risk(P<.001). In ROC analysis, AUC of Inhibin A is analysed as the biggest predictor of Down's syndrome(0.859). And the criterion for cut-off was inhibin A 1.4 MoM(sensitivity 81.8%, specificity 75.9%). In conclusion, Inhibin A was the most useful in parameters to predict Down's syndrome in the integrated test. If we make up for the weakness based on the cut-off value of parameters they will be able to be used as an independent indicator in the risk of Down's syndrome screening.

Analysis of predicted and measured performance of an integrated compound parabolic concentrator (ICPC)

Energy Technology Data Exchange (ETDEWEB)

Winston, R.; O' Gallagher, J.J.; Muschaweck, J.; Mahoney, A.R.; Dudley, V.

1999-07-01

A variety of configurations of evacuated Integrated Compound Parabolic Concentrator (ICPC) tubes have been under development for many years. A particularly favorable optical design corresponds to the unit concentration limit for a fin CPC solution which is then coupled to a practical, thin, wedge-shaped absorber. Prototype collector modules using tubes with two different fin orientations (horizontal and vertical) have been fabricated and tested. Comprehensive measurements of the optical characteristics of the reflector and absorber have been used together with a detailed ray trace analysis to predict the optical performance characteristics of these designs. The observed performance agrees well with the predicted performance.

A vision for an ultra-high resolution integrated water cycle observation and prediction system

Science.gov (United States)

Houser, P. R.

2013-05-01

Society's welfare, progress, and sustainable economic growth—and life itself—depend on the abundance and vigorous cycling and replenishing of water throughout the global environment. The water cycle operates on a continuum of time and space scales and exchanges large amounts of energy as water undergoes phase changes and is moved from one part of the Earth system to another. We must move toward an integrated observation and prediction paradigm that addresses broad local-to-global science and application issues by realizing synergies associated with multiple, coordinated observations and prediction systems. A central challenge of a future water and energy cycle observation strategy is to progress from single variable water-cycle instruments to multivariable integrated instruments in electromagnetic-band families. The microwave range in the electromagnetic spectrum is ideally suited for sensing the state and abundance of water because of water's dielectric properties. Eventually, a dedicated high-resolution water-cycle microwave-based satellite mission may be possible based on large-aperture antenna technology that can harvest the synergy that would be afforded by simultaneous multichannel active and passive microwave measurements. A partial demonstration of these ideas can even be realized with existing microwave satellite observations to support advanced multivariate retrieval methods that can exploit the totality of the microwave spectral information. The simultaneous multichannel active and passive microwave retrieval would allow improved-accuracy retrievals that are not possible with isolated measurements. Furthermore, the simultaneous monitoring of several of the land, atmospheric, oceanic, and cryospheric states brings synergies that will substantially enhance understanding of the global water and energy cycle as a system. The multichannel approach also affords advantages to some constituent retrievals—for instance, simultaneous retrieval of vegetation

Integration of RNA-Seq and RPPA data for survival time prediction in cancer patients.

Science.gov (United States)

Isik, Zerrin; Ercan, Muserref Ece

2017-10-01

Integration of several types of patient data in a computational framework can accelerate the identification of more reliable biomarkers, especially for prognostic purposes. This study aims to identify biomarkers that can successfully predict the potential survival time of a cancer patient by integrating the transcriptomic (RNA-Seq), proteomic (RPPA), and protein-protein interaction (PPI) data. The proposed method -RPBioNet- employs a random walk-based algorithm that works on a PPI network to identify a limited number of protein biomarkers. Later, the method uses gene expression measurements of the selected biomarkers to train a classifier for the survival time prediction of patients. RPBioNet was applied to classify kidney renal clear cell carcinoma (KIRC), glioblastoma multiforme (GBM), and lung squamous cell carcinoma (LUSC) patients based on their survival time classes (long- or short-term). The RPBioNet method correctly identified the survival time classes of patients with between 66% and 78% average accuracy for three data sets. RPBioNet operates with only 20 to 50 biomarkers and can achieve on average 6% higher accuracy compared to the closest alternative method, which uses only RNA-Seq data in the biomarker selection. Further analysis of the most predictive biomarkers highlighted genes that are common for both cancer types, as they may be driver proteins responsible for cancer progression. The novelty of this study is the integration of a PPI network with mRNA and protein expression data to identify more accurate prognostic biomarkers that can be used for clinical purposes in the future. Copyright © 2017 Elsevier Ltd. All rights reserved.

Microgravity Disturbance Predictions in the Combustion Integrated Rack

Science.gov (United States)

Just, M.; Grodsinsky, Carlos M.

2002-01-01

This paper will focus on the approach used to characterize microgravity disturbances in the Combustion Integrated Rack (CIR), currently scheduled for launch to the International Space Station (ISS) in 2005. Microgravity experiments contained within the CIR are extremely sensitive to vibratory and transient disturbances originating on-board and off-board the rack. Therefore, several techniques are implemented to isolate the critical science locations from external vibration. A combined testing and analysis approach is utilized to predict the resulting microgravity levels at the critical science location. The major topics to be addressed are: 1) CIR Vibration Isolation Approaches, 2) Disturbance Sources and Characterization, 3) Microgravity Predictive Modeling, 4) Science Microgravity Requirements, 6) Microgravity Control, and 7) On-Orbit Disturbance Measurement. The CIR is using the Passive Rack Isolation System (PaRIS) to isolate the rack from offboard rack disturbances. By utilizing this system, CIR is connected to the U.S. Lab module structure by either 13 or 14 umbilical lines and 8 spring / damper isolators. Some on-board CIR disturbers are locally isolated by grommets or wire ropes. CIR's environmental and science on board support equipment such as air circulation fans, pumps, water flow, air flow, solenoid valves, and computer hard drives cause disturbances within the rack. These disturbers along with the rack structure must be characterized to predict whether the on-orbit vibration levels during experimentation exceed the specified science microgravity vibration level requirements. Both vibratory and transient disturbance conditions are addressed. Disturbance levels/analytical inputs are obtained for each individual disturber in a "free floating" condition in the Glenn Research Center (GRC) Microgravity Emissions Lab (MEL). Flight spare hardware is tested on an Orbital Replacement Unit (ORU) basis. Based on test and analysis, maximum disturbance level

Efficient Generation of Orthologous Point Mutations in Pigs via CRISPR-assisted ssODN-mediated Homology-directed Repair

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Kankan Wang

2016-01-01

Full Text Available Precise genome editing in livestock is of great value for the fundamental investigation of disease modeling. However, genetically modified pigs carrying subtle point mutations were still seldom reported despite the rapid development of programmable endonucleases. Here, we attempt to investigate single-stranded oligonucleotides (ssODN mediated knockin by introducing two orthologous pathogenic mutations, p.E693G for Alzheimer's disease and p.G2019S for Parkinson's disease, into porcine APP and LRRK2 loci, respectively. Desirable homology-directed repair (HDR efficiency was achieved in porcine fetal fibroblasts (PFFs by optimizing the dosage and length of ssODN templates. Interestingly, incomplete HDR alleles harboring partial point mutations were observed in single-cell colonies, which indicate the complex mechanism of ssODN-mediated HDR. The effect of mutation-to-cut distance on incorporation rate was further analyzed by deep sequencing. We demonstrated that a mutation-to-cut distance of 11 bp resulted in a remarkable difference in HDR efficiency between two point mutations. Finally, we successfully obtained one cloned piglet harboring the orthologous p.C313Y mutation at the MSTN locus via somatic cell nuclear transfer (SCNT. Our proof-of-concept study demonstrated efficient ssODN-mediated incorporation of pathogenic point mutations in porcine somatic cells, thus facilitating further development of disease modeling and genetic breeding in pigs.

IMP 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks.

Science.gov (United States)

Wong, Aaron K; Krishnan, Arjun; Yao, Victoria; Tadych, Alicja; Troyanskaya, Olga G

2015-07-01

IMP (Integrative Multi-species Prediction), originally released in 2012, is an interactive web server that enables molecular biologists to interpret experimental results and to generate hypotheses in the context of a large cross-organism compendium of functional predictions and networks. The system provides biologists with a framework to analyze their candidate gene sets in the context of functional networks, expanding or refining their sets using functional relationships predicted from integrated high-throughput data. IMP 2.0 integrates updated prior knowledge and data collections from the last three years in the seven supported organisms (Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Danio rerio, Caenorhabditis elegans, and Saccharomyces cerevisiae) and extends function prediction coverage to include human disease. IMP identifies homologs with conserved functional roles for disease knowledge transfer, allowing biologists to analyze disease contexts and predictions across all organisms. Additionally, IMP 2.0 implements a new flexible platform for experts to generate custom hypotheses about biological processes or diseases, making sophisticated data-driven methods easily accessible to researchers. IMP does not require any registration or installation and is freely available for use at http://imp.princeton.edu. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Machine remaining useful life prediction: An integrated adaptive neuro-fuzzy and high-order particle filtering approach

Science.gov (United States)

Chen, Chaochao; Vachtsevanos, George; Orchard, Marcos E.

2012-04-01

Machine prognosis can be considered as the generation of long-term predictions that describe the evolution in time of a fault indicator, with the purpose of estimating the remaining useful life (RUL) of a failing component/subsystem so that timely maintenance can be performed to avoid catastrophic failures. This paper proposes an integrated RUL prediction method using adaptive neuro-fuzzy inference systems (ANFIS) and high-order particle filtering, which forecasts the time evolution of the fault indicator and estimates the probability density function (pdf) of RUL. The ANFIS is trained and integrated in a high-order particle filter as a model describing the fault progression. The high-order particle filter is used to estimate the current state and carry out p-step-ahead predictions via a set of particles. These predictions are used to estimate the RUL pdf. The performance of the proposed method is evaluated via the real-world data from a seeded fault test for a UH-60 helicopter planetary gear plate. The results demonstrate that it outperforms both the conventional ANFIS predictor and the particle-filter-based predictor where the fault growth model is a first-order model that is trained via the ANFIS.

Frontoparietal white matter integrity predicts haptic performance in chronic stroke

Directory of Open Access Journals (Sweden)

Alexandra L. Borstad

2016-01-01

. Age strongly correlated with the shared variance across tracts in the control, but not in the poststroke participants. A moderate to good relationship was found between ipsilesional T–M1 MD and affected hand HASTe score (r = −0.62, p = 0.006 and less affected hand HASTe score (r = −0.53, p = 0.022. Regression analysis revealed approximately 90% of the variance in affected hand HASTe score was predicted by the white matter integrity in the frontoparietal network (as indexed by MD in poststroke participants while 87% of the variance in HASTe score was predicted in control participants. This study demonstrates the importance of frontoparietal white matter in mediating haptic performance and specifically identifies that T–M1 and precuneus interhemispheric tracts may be appropriate targets for piloting rehabilitation interventions, such as noninvasive brain stimulation, when the goal is to improve poststroke haptic performance.

Frontoparietal white matter integrity predicts haptic performance in chronic stroke.

Science.gov (United States)

Borstad, Alexandra L; Choi, Seongjin; Schmalbrock, Petra; Nichols-Larsen, Deborah S

2016-01-01

strongly correlated with the shared variance across tracts in the control, but not in the poststroke participants. A moderate to good relationship was found between ipsilesional T-M1 MD and affected hand HASTe score (r = - 0.62, p = 0.006) and less affected hand HASTe score (r = - 0.53, p = 0.022). Regression analysis revealed approximately 90% of the variance in affected hand HASTe score was predicted by the white matter integrity in the frontoparietal network (as indexed by MD) in poststroke participants while 87% of the variance in HASTe score was predicted in control participants. This study demonstrates the importance of frontoparietal white matter in mediating haptic performance and specifically identifies that T-M1 and precuneus interhemispheric tracts may be appropriate targets for piloting rehabilitation interventions, such as noninvasive brain stimulation, when the goal is to improve poststroke haptic performance.

Integrated predictive modeling simulations of the Mega-Amp Spherical Tokamak

International Nuclear Information System (INIS)

Nguyen, Canh N.; Bateman, Glenn; Kritz, Arnold H.; Akers, Robert; Byrom, Calum; Sykes, Alan

2002-01-01

Integrated predictive modeling simulations are carried out using the BALDUR transport code [Singer et al., Comput. Phys. Commun. 49, 275 (1982)] for high confinement mode (H-mode) and low confinement mode (L-mode) discharges in the Mega-Amp Spherical Tokamak (MAST) [Sykes et al., Phys. Plasmas 8, 2101 (2001)]. Simulation results, obtained using either the Multi-Mode transport model (MMM95) or, alternatively, the mixed-Bohm/gyro-Bohm transport model, are compared with experimental data. In addition to the anomalous transport, neoclassical transport is included in the simulations and the ion thermal diffusivity in the inner third of the plasma is found to be predominantly neoclassical. The sawtooth oscillations in the simulations radially spread the neutral beam injection heating profiles across a broad sawtooth mixing region. The broad sawtooth oscillations also flatten the central temperature and electron density profiles. Simulation results for the electron temperature and density profiles are compared with experimental data to test the applicability of these models and the BALDUR integrated modeling code in the limit of low aspect ratio toroidal plasmas

PROSPER: an integrated feature-based tool for predicting protease substrate cleavage sites.

Directory of Open Access Journals (Sweden)

Jiangning Song

Full Text Available The ability to catalytically cleave protein substrates after synthesis is fundamental for all forms of life. Accordingly, site-specific proteolysis is one of the most important post-translational modifications. The key to understanding the physiological role of a protease is to identify its natural substrate(s. Knowledge of the substrate specificity of a protease can dramatically improve our ability to predict its target protein substrates, but this information must be utilized in an effective manner in order to efficiently identify protein substrates by in silico approaches. To address this problem, we present PROSPER, an integrated feature-based server for in silico identification of protease substrates and their cleavage sites for twenty-four different proteases. PROSPER utilizes established specificity information for these proteases (derived from the MEROPS database with a machine learning approach to predict protease cleavage sites by using different, but complementary sequence and structure characteristics. Features used by PROSPER include local amino acid sequence profile, predicted secondary structure, solvent accessibility and predicted native disorder. Thus, for proteases with known amino acid specificity, PROSPER provides a convenient, pre-prepared tool for use in identifying protein substrates for the enzymes. Systematic prediction analysis for the twenty-four proteases thus far included in the database revealed that the features we have included in the tool strongly improve performance in terms of cleavage site prediction, as evidenced by their contribution to performance improvement in terms of identifying known cleavage sites in substrates for these enzymes. In comparison with two state-of-the-art prediction tools, PoPS and SitePrediction, PROSPER achieves greater accuracy and coverage. To our knowledge, PROSPER is the first comprehensive server capable of predicting cleavage sites of multiple proteases within a single substrate

Integration of Tuyere, Raceway and Shaft Models for Predicting Blast Furnace Process

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Fu, Dong; Tang, Guangwu; Zhao, Yongfu; D'Alessio, John; Zhou, Chenn Q.

2018-06-01

A novel modeling strategy is presented for simulating the blast furnace iron making process. Such physical and chemical phenomena are taking place across a wide range of length and time scales, and three models are developed to simulate different regions of the blast furnace, i.e., the tuyere model, the raceway model and the shaft model. This paper focuses on the integration of the three models to predict the entire blast furnace process. Mapping output and input between models and an iterative scheme are developed to establish communications between models. The effects of tuyere operation and burden distribution on blast furnace fuel efficiency are investigated numerically. The integration of different models provides a way to realistically simulate the blast furnace by improving the modeling resolution on local phenomena and minimizing the model assumptions.

Functional evolution of a multigene family: orthologous and paralogous pheromone receptor genes in the turnip moth, Agrotis segetum.

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Dan-Dan Zhang

Full Text Available Lepidopteran pheromone receptors (PRs, for which orthologies are evident among closely related species, provide an intriguing example of gene family evolution in terms of how new functions may arise. However, only a limited number of PRs have been functionally characterized so far and thus evolutionary scenarios suffer from elements of speculation. In this study we investigated the turnip moth Agrotis segetum, in which female moths produce a mixture of chemically related pheromone components that elicit specific responses from receptor cells on male antennae. We cloned nine A. segetum PR genes and the Orco gene by degenerate primer based RT-PCR. The nine PR genes, named as AsegOR1 and AsegOR3-10, fall into four distinct orthologous clusters of known lepidopteran PRs, of which one contains six paralogues. The paralogues are under relaxed selective pressure, contrasting with the purifying selection on other clusters. We identified the receptors AsegOR9, AsegOR4 and AsegOR5, specific for the respective homologous pheromone components (Z-5-decenyl, (Z-7-dodecenyl and (Z-9-tetradecenyl acetates, by two-electrode voltage clamp recording from Xenopus laevis oocytes co-expressing Orco and each PR candidate. These receptors occur in three different orthologous clusters. We also found that the six paralogues with high sequence similarity vary dramatically in ligand selectivity and sensitivity. Different from AsegOR9, AsegOR6 showed a relatively large response to the behavioural antagonist (Z-5-decenol, and a small response to (Z-5-decenyl acetate. AsegOR1 was broadly tuned, but most responsive to (Z-5-decenyl acetate, (Z-7-dodecenyl acetate and the behavioural antagonist (Z-8-dodecenyl acetate. AsegOR8 and AsegOR7, which differ from AsegOR6 and AsegOR1 by 7 and 10 aa respectively, showed much lower sensitivities. AsegOR10 showed only small responses to all the tested compounds. These results suggest that new receptors arise through gene duplication, and

iSPUW: integrated sensing and prediction of urban water for sustainable cities

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Noh, S. J.; Nazari, B.; Habibi, H.; Norouzi, A.; Nabatian, M.; Seo, D. J.; Bartos, M. D.; Kerkez, B.; Lakshman, L.; Zink, M.; Lee, J.

2016-12-01

Many cities face tremendous water-related challenges in this Century of the City. Urban areas are particularly susceptible not only to excesses and shortages of water but also to impaired water quality. To addresses these challenges, we synergistically integrate advances in computing and cyber-infrastructure, environmental modeling, geoscience, and information science to develop integrative solutions for urban water challenges. In this presentation, we describe the various efforts that are currently ongoing in the Dallas-Fort Worth Metroplex (DFW) area for iSPUW: real-time high-resolution flash flood forecasting, inundation mapping for large urban areas, crowdsourcing of water observations in urban areas, real-time assimilation of crowdsourced observations for street and river flooding, integrated control of lawn irrigation and rainwater harvesting for water conservation and stormwater management, feature mining with causal discovery for flood prediction, and development of the Arlington Urban Hydroinformatics Testbed. Analyzed is the initial data of sensor network for water level and lawn monitoring, and cellphone applications for crowdsourcing flood reports. New data assimilation approaches to deal with categorical and continuous observations are also evaluated via synthetic experiments.

Genetic variation in the Solanaceae fruit bearing species lulo and tree tomato revealed by Conserved Ortholog (COSII) markers

OpenAIRE

Enciso-Rodríguez, Felix; Martínez, Rodrigo; Lobo, Mario; Barrero, Luz Stella

2010-01-01

The Lulo or naranjilla (Solanum quitoense Lam.) and the tree tomato or tamarillo (Solanum betaceum Cav. Sendt.) are both Andean tropical fruit species with high nutritional value and the potential for becoming premium products in local and export markets. Herein, we present a report on the genetic characterization of 62 accessions of lulos (n = 32) and tree tomatoes (n = 30) through the use of PCR-based markers developed from single-copy conserved orthologous genes (COSII) in other Solanaceae...

The conserved, disease-associated RNA binding protein dNab2 interacts with the Fragile-X protein ortholog in Drosophila neurons

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Bienkowski, Rick S.; Banerjee, Ayan; Rounds, J. Christopher; Rha, Jennifer; Omotade, Omotola F.; Gross, Christina; Morris, Kevin J.; Leung, Sara W.; Pak, ChangHui; Jones, Stephanie K.; Santoro, Michael R.; Warren, Stephen T.; Zheng, James Q.; Bassell, Gary J.; Corbett, Anita H.; Moberg, Kenneth H.

2017-01-01

Summary The Drosophila dNab2 protein is an ortholog of human ZC3H14, a poly(A) RNA-binding protein required for intellectual function. dNab2 supports memory and axon projection, but its molecular role in neurons is undefined. Here we present a network of interactions that links dNab2 to cytoplasmic control of neuronal mRNAs in conjunction with and the Fragile-X protein ortholog dFMRP. dNab2 and dfmr1 interact genetically in control of neurodevelopment and olfactory memory and their encoded proteins co-localize in puncta within neuronal processes. dNab2 regulates CaMKII but not futsch mRNA, implying a selective role in control of dFMRP-bound transcripts. Reciprocally, dFMRP and vertebrate FMRP restrict mRNA poly(A)-tail length similar to dNab2/ZC3H14. Parallel studies of murine hippocampal neurons indicate that ZC3H14 is also a cytoplasmic regulator of neuronal mRNAs. In sum these findings suggest that dNab2 represses expression of a subset of dFMRP-target mRNAs, which could underlie brain-specific defects in patients lacking ZC3H14. PMID:28793261

The Conserved, Disease-Associated RNA Binding Protein dNab2 Interacts with the Fragile X Protein Ortholog in Drosophila Neurons

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Rick S. Bienkowski

2017-08-01

Full Text Available The Drosophila dNab2 protein is an ortholog of human ZC3H14, a poly(A RNA binding protein required for intellectual function. dNab2 supports memory and axon projection, but its molecular role in neurons is undefined. Here, we present a network of interactions that links dNab2 to cytoplasmic control of neuronal mRNAs in conjunction with the fragile X protein ortholog dFMRP. dNab2 and dfmr1 interact genetically in control of neurodevelopment and olfactory memory, and their encoded proteins co-localize in puncta within neuronal processes. dNab2 regulates CaMKII, but not futsch, implying a selective role in control of dFMRP-bound transcripts. Reciprocally, dFMRP and vertebrate FMRP restrict mRNA poly(A tail length, similar to dNab2/ZC3H14. Parallel studies of murine hippocampal neurons indicate that ZC3H14 is also a cytoplasmic regulator of neuronal mRNAs. Altogether, these findings suggest that dNab2 represses expression of a subset of dFMRP-target mRNAs, which could underlie brain-specific defects in patients lacking ZC3H14.

IPF-LASSO: Integrative L1-Penalized Regression with Penalty Factors for Prediction Based on Multi-Omics Data

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Anne-Laure Boulesteix

2017-01-01

Full Text Available As modern biotechnologies advance, it has become increasingly frequent that different modalities of high-dimensional molecular data (termed “omics” data in this paper, such as gene expression, methylation, and copy number, are collected from the same patient cohort to predict the clinical outcome. While prediction based on omics data has been widely studied in the last fifteen years, little has been done in the statistical literature on the integration of multiple omics modalities to select a subset of variables for prediction, which is a critical task in personalized medicine. In this paper, we propose a simple penalized regression method to address this problem by assigning different penalty factors to different data modalities for feature selection and prediction. The penalty factors can be chosen in a fully data-driven fashion by cross-validation or by taking practical considerations into account. In simulation studies, we compare the prediction performance of our approach, called IPF-LASSO (Integrative LASSO with Penalty Factors and implemented in the R package ipflasso, with the standard LASSO and sparse group LASSO. The use of IPF-LASSO is also illustrated through applications to two real-life cancer datasets. All data and codes are available on the companion website to ensure reproducibility.

Predicting Examination Performance Using an Expanded Integrated Hierarchical Model of Test Emotions and Achievement Goals

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Putwain, Dave; Deveney, Carolyn

2009-01-01

The aim of this study was to examine an expanded integrative hierarchical model of test emotions and achievement goal orientations in predicting the examination performance of undergraduate students. Achievement goals were theorised as mediating the relationship between test emotions and performance. 120 undergraduate students completed…

ATGC: a database of orthologous genes from closely related prokaryotic genomes and a research platform for microevolution of prokaryotes

Energy Technology Data Exchange (ETDEWEB)

Novichkov, Pavel S.; Ratnere, Igor; Wolf, Yuri I.; Koonin, Eugene V.; Dubchak, Inna

2009-07-23

The database of Alignable Tight Genomic Clusters (ATGCs) consists of closely related genomes of archaea and bacteria, and is a resource for research into prokaryotic microevolution. Construction of a data set with appropriate characteristics is a major hurdle for this type of studies. With the current rate of genome sequencing, it is difficult to follow the progress of the field and to determine which of the available genome sets meet the requirements of a given research project, in particular, with respect to the minimum and maximum levels of similarity between the included genomes. Additionally, extraction of specific content, such as genomic alignments or families of orthologs, from a selected set of genomes is a complicated and time-consuming process. The database addresses these problems by providing an intuitive and efficient web interface to browse precomputed ATGCs, select appropriate ones and access ATGC-derived data such as multiple alignments of orthologous proteins, matrices of pairwise intergenomic distances based on genome-wide analysis of synonymous and nonsynonymous substitution rates and others. The ATGC database will be regularly updated following new releases of the NCBI RefSeq. The database is hosted by the Genomics Division at Lawrence Berkeley National laboratory and is publicly available at http://atgc.lbl.gov.

Using NCAP to predict RFI effects in linear bipolar integrated circuits

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Fang, T.-F.; Whalen, J. J.; Chen, G. K. C.

1980-11-01

Applications of the Nonlinear Circuit Analysis Program (NCAP) to calculate RFI effects in electronic circuits containing discrete semiconductor devices have been reported upon previously. The objective of this paper is to demonstrate that the computer program NCAP also can be used to calcuate RFI effects in linear bipolar integrated circuits (IC's). The IC's reported upon are the microA741 operational amplifier (op amp) which is one of the most widely used IC's, and a differential pair which is a basic building block in many linear IC's. The microA741 op amp was used as the active component in a unity-gain buffer amplifier. The differential pair was used in a broad-band cascode amplifier circuit. The computer program NCAP was used to predict how amplitude-modulated RF signals are demodulated in the IC's to cause undesired low-frequency responses. The predicted and measured results for radio frequencies in the 0.050-60-MHz range are in good agreement.

ANCAC: amino acid, nucleotide, and codon analysis of COGs--a tool for sequence bias analysis in microbial orthologs.

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Meiler, Arno; Klinger, Claudia; Kaufmann, Michael

2012-09-08

The COG database is the most popular collection of orthologous proteins from many different completely sequenced microbial genomes. Per definition, a cluster of orthologous groups (COG) within this database exclusively contains proteins that most likely achieve the same cellular function. Recently, the COG database was extended by assigning to every protein both the corresponding amino acid and its encoding nucleotide sequence resulting in the NUCOCOG database. This extended version of the COG database is a valuable resource connecting sequence features with the functionality of the respective proteins. Here we present ANCAC, a web tool and MySQL database for the analysis of amino acid, nucleotide, and codon frequencies in COGs on the basis of freely definable phylogenetic patterns. We demonstrate the usefulness of ANCAC by analyzing amino acid frequencies, codon usage, and GC-content in a species- or function-specific context. With respect to amino acids we, at least in part, confirm the cognate bias hypothesis by using ANCAC's NUCOCOG dataset as the largest one available for that purpose thus far. Using the NUCOCOG datasets, ANCAC connects taxonomic, amino acid, and nucleotide sequence information with the functional classification via COGs and provides a GUI for flexible mining for sequence-bias. Thereby, to our knowledge, it is the only tool for the analysis of sequence composition in the light of physiological roles and phylogenetic context without requirement of substantial programming-skills.

Mining predicted essential genes of Brugia malayi for nematode drug targets.

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Sanjay Kumar

Full Text Available We report results from the first genome-wide application of a rational drug target selection methodology to a metazoan pathogen genome, the completed draft sequence of Brugia malayi, a parasitic nematode responsible for human lymphatic filariasis. More than 1.5 billion people worldwide are at risk of contracting lymphatic filariasis and onchocerciasis, a related filarial disease. Drug treatments for filariasis have not changed significantly in over 20 years, and with the risk of resistance rising, there is an urgent need for the development of new anti-filarial drug therapies. The recent publication of the draft genomic sequence for B. malayi enables a genome-wide search for new drug targets. However, there is no functional genomics data in B. malayi to guide the selection of potential drug targets. To circumvent this problem, we have utilized the free-living model nematode Caenorhabditis elegans as a surrogate for B. malayi. Sequence comparisons between the two genomes allow us to map C. elegans orthologs to B. malayi genes. Using these orthology mappings and by incorporating the extensive genomic and functional genomic data, including genome-wide RNAi screens, that already exist for C. elegans, we identify potentially essential genes in B. malayi. Further incorporation of human host genome sequence data and a custom algorithm for prioritization enables us to collect and rank nearly 600 drug target candidates. Previously identified potential drug targets cluster near the top of our prioritized list, lending credibility to our methodology. Over-represented Gene Ontology terms, predicted InterPro domains, and RNAi phenotypes of C. elegans orthologs associated with the potential target pool are identified. By virtue of the selection procedure, the potential B. malayi drug targets highlight components of key processes in nematode biology such as central metabolism, molting and regulation of gene expression.

Factors Influencing College Women's Contraceptive Behavior: An Application of the Integrative Model of Behavioral Prediction

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Sutton, Jazmyne A.; Walsh-Buhi, Eric R.

2017-01-01

Objective: This study investigated variables within the Integrative Model of Behavioral Prediction (IMBP) as well as differences across socioeconomic status (SES) levels within the context of inconsistent contraceptive use among college women. Participants: A nonprobability sample of 515 female college students completed an Internet-based survey…

An integrated prediction and optimization model of biogas production system at a wastewater treatment facility.

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Akbaş, Halil; Bilgen, Bilge; Turhan, Aykut Melih

2015-11-01

This study proposes an integrated prediction and optimization model by using multi-layer perceptron neural network and particle swarm optimization techniques. Three different objective functions are formulated. The first one is the maximization of methane percentage with single output. The second one is the maximization of biogas production with single output. The last one is the maximization of biogas quality and biogas production with two outputs. Methane percentage, carbon dioxide percentage, and other contents' percentage are used as the biogas quality criteria. Based on the formulated models and data from a wastewater treatment facility, optimal values of input variables and their corresponding maximum output values are found out for each model. It is expected that the application of the integrated prediction and optimization models increases the biogas production and biogas quality, and contributes to the quantity of electricity production at the wastewater treatment facility. Copyright © 2015 Elsevier Ltd. All rights reserved.

Integration of research infrastructures and ecosystem models toward development of predictive ecology

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Luo, Y.; Huang, Y.; Jiang, J.; MA, S.; Saruta, V.; Liang, G.; Hanson, P. J.; Ricciuto, D. M.; Milcu, A.; Roy, J.

2017-12-01

The past two decades have witnessed rapid development in sensor technology. Built upon the sensor development, large research infrastructure facilities, such as National Ecological Observatory Network (NEON) and FLUXNET, have been established. Through networking different kinds of sensors and other data collections at many locations all over the world, those facilities generate large volumes of ecological data every day. The big data from those facilities offer an unprecedented opportunity for advancing our understanding of ecological processes, educating teachers and students, supporting decision-making, and testing ecological theory. The big data from the major research infrastructure facilities also provides foundation for developing predictive ecology. Indeed, the capability to predict future changes in our living environment and natural resources is critical to decision making in a world where the past is no longer a clear guide to the future. We are living in a period marked by rapid climate change, profound alteration of biogeochemical cycles, unsustainable depletion of natural resources, and deterioration of air and water quality. Projecting changes in future ecosystem services to the society becomes essential not only for science but also for policy making. We will use this panel format to outline major opportunities and challenges in integrating research infrastructure and ecosystem models toward developing predictive ecology. Meanwhile, we will also show results from an interactive model-experiment System - Ecological Platform for Assimilating Data into models (EcoPAD) - that have been implemented at the Spruce and Peatland Responses Under Climatic and Environmental change (SPRUCE) experiment in Northern Minnesota and Montpellier Ecotron, France. EcoPAD is developed by integrating web technology, eco-informatics, data assimilation techniques, and ecosystem modeling. EcoPAD is designed to streamline data transfer seamlessly from research infrastructure

Understanding Eating Behaviors through Parental Communication and the Integrative Model of Behavioral Prediction.

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Scheinfeld, Emily; Shim, Minsun

2017-05-01

Emerging adulthood (EA) is an important yet overlooked period for developing long-term health behaviors. During these years, emerging adults adopt health behaviors that persist throughout life. This study applies the Integrative Model of Behavioral Prediction (IMBP) to examine the role of childhood parental communication in predicting engagement in healthful eating during EA. Participants included 239 college students, ages 18 to 25, from a large university in the southern United States. Participants were recruited and data collection occurred spring 2012. Participants responded to measures to assess perceived parental communication, eating behaviors, attitudes, subjective norms, and behavioral control over healthful eating. SEM and mediation analyses were used to address the hypotheses posited. Data demonstrated that perceived parent-child communication - specifically, its quality and target-specific content - significantly predicted emerging adults' eating behaviors, mediated through subjective norm and perceived behavioral control. This study sets the stage for further exploration and understanding of different ways parental communication influences emerging adults' healthy behavior enactment.

Genetic or pharmacological activation of the Drosophila PGC-1α ortholog spargel rescues the disease phenotypes of genetic models of Parkinson's disease.

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Ng, Chee-Hoe; Basil, Adeline H; Hang, Liting; Tan, Royston; Goh, Kian-Leong; O'Neill, Sharon; Zhang, Xiaodong; Yu, Fengwei; Lim, Kah-Leong

2017-07-01

Despite intensive research, the etiology of Parkinson's disease (PD) remains poorly understood and the disease remains incurable. However, compelling evidence gathered over decades of research strongly support a role for mitochondrial dysfunction in PD pathogenesis. Related to this, PGC-1α, a key regulator of mitochondrial biogenesis, has recently been proposed to be an attractive target for intervention in PD. Here, we showed that silencing of expression of the Drosophila PGC-1α ortholog spargel results in PD-related phenotypes in flies and also seem to negate the effects of AMPK activation, which we have previously demonstrated to be neuroprotective, that is, AMPK-mediated neuroprotection appears to require PGC-1α. Importantly, we further showed that genetic or pharmacological activation of the Drosophila PGC-1α ortholog spargel is sufficient to rescue the disease phenotypes of Parkin and LRRK2 genetic fly models of PD, thus supporting the proposed use of PGC-1α-related strategies for neuroprotection in PD. Copyright © 2017 National Neuroscience Institute. Published by Elsevier Inc. All rights reserved.

Reranking candidate gene models with cross-species comparison for improved gene prediction

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Pereira Fernando CN

2008-10-01

Full Text Available Abstract Background Most gene finders score candidate gene models with state-based methods, typically HMMs, by combining local properties (coding potential, splice donor and acceptor patterns, etc. Competing models with similar state-based scores may be distinguishable with additional information. In particular, functional and comparative genomics datasets may help to select among competing models of comparable probability by exploiting features likely to be associated with the correct gene models, such as conserved exon/intron structure or protein sequence features. Results We have investigated the utility of a simple post-processing step for selecting among a set of alternative gene models, using global scoring rules to rerank competing models for more accurate prediction. For each gene locus, we first generate the K best candidate gene models using the gene finder Evigan, and then rerank these models using comparisons with putative orthologous genes from closely-related species. Candidate gene models with lower scores in the original gene finder may be selected if they exhibit strong similarity to probable orthologs in coding sequence, splice site location, or signal peptide occurrence. Experiments on Drosophila melanogaster demonstrate that reranking based on cross-species comparison outperforms the best gene models identified by Evigan alone, and also outperforms the comparative gene finders GeneWise and Augustus+. Conclusion Reranking gene models with cross-species comparison improves gene prediction accuracy. This straightforward method can be readily adapted to incorporate additional lines of evidence, as it requires only a ranked source of candidate gene models.

The fission yeast MTREC and EJC orthologs ensure the maturation of meiotic transcripts during meiosis.

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Marayati, Bahjat Fadi; Hoskins, Victoria; Boger, Robert W; Tucker, James F; Fishman, Emily S; Bray, Andrew S; Zhang, Ke

2016-09-01

Meiosis is a highly regulated process by which genetic information is transmitted through sexual reproduction. It encompasses unique mechanisms that do not occur in vegetative cells, producing a distinct, well-regulated meiotic transcriptome. During vegetative growth, many meiotic genes are constitutively transcribed, but most of the resulting mRNAs are rapidly eliminated by the Mmi1-MTREC (Mtl1-Red1 core) complex. While Mmi1-MTREC targets premature meiotic RNAs for degradation by the nuclear 3'-5' exoribonuclease exosome during mitotic growth, its role in meiotic gene expression during meiosis is not known. Here, we report that Red5, an essential MTREC component, interacts with pFal1, an ortholog of eukaryotic translation initiation factor eIF4aIII in the fission yeast Schizosaccharomyces pombe In mammals, together with MAGO (Mnh1), Rnps1, and Y14, elF4AIII (pFal1) forms the core of the exon junction complex (EJC), which is essential for transcriptional surveillance and localization of mature mRNAs. In fission yeast, two EJC orthologs, pFal1 and Mnh1, are functionally connected with MTREC, specifically in the process of meiotic gene expression during meiosis. Although pFal1 interacts with Mnh1, Y14, and Rnps1, its association with Mnh1 is not disrupted upon loss of Y14 or Rnps1. Mutations of Red1, Red5, pFal1, or Mnh1 produce severe meiotic defects; the abundance of meiotic transcripts during meiosis decreases; and mRNA maturation processes such as splicing are impaired. Since studying meiosis in mammalian germline cells is difficult, our findings in fission yeast may help to define the general mechanisms involved in accurate meiotic gene expression in higher eukaryotes. © 2016 Marayati et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Inference of gene-phenotype associations via protein-protein interaction and orthology.

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Panwen Wang

Full Text Available One of the fundamental goals of genetics is to understand gene functions and their associated phenotypes. To achieve this goal, in this study we developed a computational algorithm that uses orthology and protein-protein interaction information to infer gene-phenotype associations for multiple species. Furthermore, we developed a web server that provides genome-wide phenotype inference for six species: fly, human, mouse, worm, yeast, and zebrafish. We evaluated our inference method by comparing the inferred results with known gene-phenotype associations. The high Area Under the Curve values suggest a significant performance of our method. By applying our method to two human representative diseases, Type 2 Diabetes and Breast Cancer, we demonstrated that our method is able to identify related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The web server can be used to infer functions and putative phenotypes of a gene along with the candidate genes of a phenotype, and thus aids in disease candidate gene discovery. Our web server is available at http://jjwanglab.org/PhenoPPIOrth.

Comparison of experimental pulse-height distributions in germanium detectors with integrated-tiger-series-code predictions

International Nuclear Information System (INIS)

Beutler, D.E.; Halbleib, J.A.; Knott, D.P.

1989-01-01

This paper reports pulse-height distributions in two different types of Ge detectors measured for a variety of medium-energy x-ray bremsstrahlung spectra. These measurements have been compared to predictions using the integrated tiger series (ITS) Monte Carlo electron/photon transport code. In general, the authors find excellent agreement between experiments and predictions using no free parameters. These results demonstrate that the ITS codes can predict the combined bremsstrahlung production and energy deposition with good precision (within measurement uncertainties). The one region of disagreement observed occurs for low-energy (<50 keV) photons using low-energy bremsstrahlung spectra. In this case the ITS codes appear to underestimate the produced and/or absorbed radiation by almost an order of magnitude

Chemically engineering ligand selectivity at the free fatty acid receptor 2 based on pharmacological variation between species orthologs

DEFF Research Database (Denmark)

Hudson, Brian D; Christiansen, Elisabeth; Tikhonova, Irina G

2012-01-01

When it is difficult to develop selective ligands within a family of related G-protein-coupled receptors (GPCRs), chemically engineered receptors activated solely by synthetic ligands (RASSLs) are useful alternatives for probing receptor function. In the present work, we explored whether a RASSL...... on this receptor and demonstrates that exploitation of pharmacological variation between species orthologs is a powerful method to generate novel chemically engineered GPCRs.-Hudson, B. D., Christiansen, E., Tikhonova, I. G., Grundmann, M., Kostenis, E., Adams, D. R., Ulven, T., Milligan, G. Chemically engineering...

Integrating environmental and genetic effects to predict responses of tree populations to climate.

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Wang, Tongli; O'Neill, Gregory A; Aitken, Sally N

2010-01-01

Climate is a major environmental factor affecting the phenotype of trees and is also a critical agent of natural selection that has molded among-population genetic variation. Population response functions describe the environmental effect of planting site climates on the performance of a single population, whereas transfer functions describe among-population genetic variation molded by natural selection for climate. Although these approaches are widely used to predict the responses of trees to climate change, both have limitations. We present a novel approach that integrates both genetic and environmental effects into a single "universal response function" (URF) to better predict the influence of climate on phenotypes. Using a large lodgepole pine (Pinus contorta Dougl. ex Loud.) field transplant experiment composed of 140 populations planted on 62 sites to demonstrate the methodology, we show that the URF makes full use of data from provenance trials to: (1) improve predictions of climate change impacts on phenotypes; (2) reduce the size and cost of future provenance trials without compromising predictive power; (3) more fully exploit existing, less comprehensive provenance tests; (4) quantify and compare environmental and genetic effects of climate on population performance; and (5) predict the performance of any population growing in any climate. Finally, we discuss how the last attribute allows the URF to be used as a mechanistic model to predict population and species ranges for the future and to guide assisted migration of seed for reforestation, restoration, or afforestation and genetic conservation in a changing climate.

Predicting sugar consumption: Application of an integrated dual-process, dual-phase model.

Science.gov (United States)

Hagger, Martin S; Trost, Nadine; Keech, Jacob J; Chan, Derwin K C; Hamilton, Kyra

2017-09-01

Excess consumption of added dietary sugars is related to multiple metabolic problems and adverse health conditions. Identifying the modifiable social cognitive and motivational constructs that predict sugar consumption is important to inform behavioral interventions aimed at reducing sugar intake. We tested the efficacy of an integrated dual-process, dual-phase model derived from multiple theories to predict sugar consumption. Using a prospective design, university students (N = 90) completed initial measures of the reflective (autonomous and controlled motivation, intentions, attitudes, subjective norm, perceived behavioral control), impulsive (implicit attitudes), volitional (action and coping planning), and behavioral (past sugar consumption) components of the proposed model. Self-reported sugar consumption was measured two weeks later. A structural equation model revealed that intentions, implicit attitudes, and, indirectly, autonomous motivation to reduce sugar consumption had small, significant effects on sugar consumption. Attitudes, subjective norm, and, indirectly, autonomous motivation to reduce sugar consumption predicted intentions. There were no effects of the planning constructs. Model effects were independent of the effects of past sugar consumption. The model identified the relative contribution of reflective and impulsive components in predicting sugar consumption. Given the prominent role of the impulsive component, interventions that assist individuals in managing cues-to-action and behavioral monitoring are likely to be effective in regulating sugar consumption. Copyright © 2017 Elsevier Ltd. All rights reserved.

An integrated multi-label classifier with chemical-chemical interactions for prediction of chemical toxicity effects.

Science.gov (United States)

Liu, Tao; Chen, Lei; Pan, Xiaoyong

2018-05-31

Chemical toxicity effect is one of the major reasons for declining candidate drugs. Detecting the toxicity effects of all chemicals can accelerate the procedures of drug discovery. However, it is time-consuming and expensive to identify the toxicity effects of a given chemical through traditional experiments. Designing quick, reliable and non-animal-involved computational methods is an alternative way. In this study, a novel integrated multi-label classifier was proposed. First, based on five types of chemical-chemical interactions retrieved from STITCH, each of which is derived from one aspect of chemicals, five individual classifiers were built. Then, several integrated classifiers were built by integrating some or all individual classifiers. By testing the integrated classifiers on a dataset with chemicals and their toxicity effects in Accelrys Toxicity database and non-toxic chemicals with their performance evaluated by jackknife test, an optimal integrated classifier was selected as the proposed classifier, which provided quite high prediction accuracies and wide applications. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Global identification predicts gay-male identity integration and well-being among Turkish gay men.

Science.gov (United States)

Koc, Yasin; Vignoles, Vivian L

2016-12-01

In most parts of the world, hegemonic masculinity requires men to endorse traditional masculine ideals, one of which is rejection of homosexuality. Wherever hegemonic masculinity favours heterosexuality over homosexuality, gay males may feel under pressure to negotiate their conflicting male gender and gay sexual identities to maintain positive self-perceptions. However, globalization, as a source of intercultural interaction, might provide a beneficial context for people wishing to create alternative masculinities in the face of hegemonic masculinity. Hence, we tested if global identification would predict higher levels of gay-male identity integration, and indirectly subjective well-being, via alternative masculinity representations for gay and male identities. A community sample of 219 gay and bisexual men from Turkey completed the study. Structural equation modelling revealed that global identification positively predicted gay-male identity integration, and indirectly subjective well-being; however, alternative masculinity representations did not mediate this relationship. Our findings illustrate how identity categories in different domains can intersect and affect each other in complex ways. Moreover, we discuss mental health and well-being implications for gay men living in cultures where they experience high levels of prejudice and stigma. © 2016 The British Psychological Society.

An integrated numerical model for the prediction of Gaussian and billet shapes

DEFF Research Database (Denmark)

Hattel, Jesper; Pryds, Nini; Pedersen, Trine Bjerre

2004-01-01

Separate models for the atomisation and the deposition stages were recently integrated by the authors to form a unified model describing the entire spray-forming process. In the present paper, the focus is on describing the shape of the deposited material during the spray-forming process, obtained...... by this model. After a short review of the models and their coupling, the important factors which influence the resulting shape, i.e. Gaussian or billet, are addressed. The key parameters, which are utilized to predict the geometry and dimension of the deposited material, are the sticking efficiency...

An integrated computational validation approach for potential novel miRNA prediction

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Pooja Viswam

2017-12-01

Full Text Available MicroRNAs (miRNAs are short, non-coding RNAs between 17bp-24bp length that regulate gene expression by targeting mRNA molecules. The regulatory functions of miRNAs are known to be majorly associated with disease phenotypes such as cancer, cell signaling, cell division, growth and other metabolisms. Novel miRNAs are defined as sequences which does not have any similarity with the existing known sequences and void of any experimental evidences. In recent decades, the advent of next-generation sequencing allows us to capture the small RNA molecules form the cells and developing methods to estimate their expression levels. Several computational algorithms are available to predict the novel miRNAs from the deep sequencing data. In this work, we integrated three novel miRNA prediction programs miRDeep, miRanalyzer and miRPRo to compare and validate their prediction efficiency. The dicer cleavage sites, alignment density, seed conservation, minimum free energy, AU-GC percentage, secondary loop scores, false discovery rates and confidence scores will be considered for comparison and evaluation. Efficiency to identify isomiRs and base pair mismatches in a strand specific manner will also be considered for the computational validation. Further, the criteria and parameters for the identification of the best possible novel miRNA with minimal false positive rates were deduced.

Integration of relational and hierarchical network information for protein function prediction

Directory of Open Access Journals (Sweden)

Jiang Xiaoyu

2008-08-01

Full Text Available Abstract Background In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions. Results We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing. Conclusion A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased

Predicting spatial and temporal gene expression using an integrative model of transcription factor occupancy and chromatin state.

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Bartek Wilczynski

Full Text Available Precise patterns of spatial and temporal gene expression are central to metazoan complexity and act as a driving force for embryonic development. While there has been substantial progress in dissecting and predicting cis-regulatory activity, our understanding of how information from multiple enhancer elements converge to regulate a gene's expression remains elusive. This is in large part due to the number of different biological processes involved in mediating regulation as well as limited availability of experimental measurements for many of them. Here, we used a Bayesian approach to model diverse experimental regulatory data, leading to accurate predictions of both spatial and temporal aspects of gene expression. We integrated whole-embryo information on transcription factor recruitment to multiple cis-regulatory modules, insulator binding and histone modification status in the vicinity of individual gene loci, at a genome-wide scale during Drosophila development. The model uses Bayesian networks to represent the relation between transcription factor occupancy and enhancer activity in specific tissues and stages. All parameters are optimized in an Expectation Maximization procedure providing a model capable of predicting tissue- and stage-specific activity of new, previously unassayed genes. Performing the optimization with subsets of input data demonstrated that neither enhancer occupancy nor chromatin state alone can explain all gene expression patterns, but taken together allow for accurate predictions of spatio-temporal activity. Model predictions were validated using the expression patterns of more than 600 genes recently made available by the BDGP consortium, demonstrating an average 15-fold enrichment of genes expressed in the predicted tissue over a naïve model. We further validated the model by experimentally testing the expression of 20 predicted target genes of unknown expression, resulting in an accuracy of 95% for temporal

Integrating sequence stratigraphy and rock-physics to interpret seismic amplitudes and predict reservoir quality

Science.gov (United States)

Dutta, Tanima

This dissertation focuses on the link between seismic amplitudes and reservoir properties. Prediction of reservoir properties, such as sorting, sand/shale ratio, and cement-volume from seismic amplitudes improves by integrating knowledge from multiple disciplines. The key contribution of this dissertation is to improve the prediction of reservoir properties by integrating sequence stratigraphy and rock physics. Sequence stratigraphy has been successfully used for qualitative interpretation of seismic amplitudes to predict reservoir properties. Rock physics modeling allows quantitative interpretation of seismic amplitudes. However, often there is uncertainty about selecting geologically appropriate rock physics model and its input parameters, away from the wells. In the present dissertation, we exploit the predictive power of sequence stratigraphy to extract the spatial trends of sedimentological parameters that control seismic amplitudes. These spatial trends of sedimentological parameters can serve as valuable constraints in rock physics modeling, especially away from the wells. Consequently, rock physics modeling, integrated with the trends from sequence stratigraphy, become useful for interpreting observed seismic amplitudes away from the wells in terms of underlying sedimentological parameters. We illustrate this methodology using a comprehensive dataset from channelized turbidite systems, deposited in minibasin settings in the offshore Equatorial Guinea, West Africa. First, we present a practical recipe for using closed-form expressions of effective medium models to predict seismic velocities in unconsolidated sandstones. We use an effective medium model that combines perfectly rough and smooth grains (the extended Walton model), and use that model to derive coordination number, porosity, and pressure relations for P and S wave velocities from experimental data. Our recipe provides reasonable fits to other experimental and borehole data, and specifically

An integrated Modelling framework to monitor and predict trends of agricultural management (iMSoil)

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Keller, Armin; Della Peruta, Raneiro; Schaepman, Michael; Gomez, Marta; Mann, Stefan; Schulin, Rainer

2014-05-01

Agricultural systems lay at the interface between natural ecosystems and the anthroposphere. Various drivers induce pressures on the agricultural systems, leading to changes in farming practice. The limitation of available land and the socio-economic drivers are likely to result in further intensification of agricultural land management, with implications on fertilization practices, soil and pest management, as well as crop and livestock production. In order to steer the development into desired directions, tools are required by which the effects of these pressures on agricultural management and resulting impacts on soil functioning can be detected as early as possible, future scenarios predicted and suitable management options and policies defined. In this context, the use of integrated models can play a major role in providing long-term predictions of soil quality and assessing the sustainability of agricultural soil management. Significant progress has been made in this field over the last decades. Some of these integrated modelling frameworks include biophysical parameters, but often the inherent characteristics and detailed processes of the soil system have been very simplified. The development of such tools has been hampered in the past by a lack of spatially explicit soil and land management information at regional scale. The iMSoil project, funded by the Swiss National Science Foundation in the national research programme NRP68 "soil as a resource" (www.nrp68.ch) aims at developing and implementing an integrated modeling framework (IMF) which can overcome the limitations mentioned above, by combining socio-economic, agricultural land management, and biophysical models, in order to predict the long-term impacts of different socio-economic scenarios on the soil quality. In our presentation we briefly outline the approach that is based on an interdisciplinary modular framework that builds on already existing monitoring tools and model components that are

Identification and localization of gonadotropin-inhibitory hormone (GnIH) orthologs in the hypothalamus of the red-eared slider turtle, Trachemys scripta elegans.

Science.gov (United States)

Ukena, Kazuyoshi; Iwakoshi-Ukena, Eiko; Osugi, Tomohiro; Tsutsui, Kazuyoshi

2016-02-01

Gonadotropin-inhibitory hormone (GnIH) was discovered in 2000 as a novel hypothalamic neuropeptide that inhibited gonadotropin release in the Japanese quail. GnIH and its orthologs have a common C-terminal LPXRFamide (X=L or Q) motif, and have been identified in vertebrates from agnathans to humans, apart from reptiles. In the present study, we characterized a cDNA encoding GnIH orthologs in the brain of the red-eared slider turtle. The deduced precursor protein consisted of 205 amino-acid residues, encoding three putative peptide sequences that included the LPXRFamide motif at their C-termini. In addition, the precursor sequence was most similar to those of avian species. Immunoaffinity purification combined with mass spectrometry confirmed that three mature peptides were produced in the brain. In situ hybridization and immunohistochemistry showed that turtle GnIH-containing cells were restricted to the periventricular hypothalamic nucleus. Immunoreactive fibers were densely distributed in the median eminence. Thus, GnIH and related peptides may act on the pituitary to regulate pituitary hormone release in turtles as well as other vertebrates. Copyright © 2015 Elsevier Inc. All rights reserved.

Identification of single-copy orthologous genes between Physalis and Solanum lycopersicum and analysis of genetic diversity in Physalis using molecular markers.

Science.gov (United States)

Wei, Jingli; Hu, Xiaorong; Yang, Jingjing; Yang, Wencai

2012-01-01

The genus Physalis includes a number of commercially important edible and ornamental species. Its high nutritional value and potential medicinal properties leads to the increased commercial interest in the products of this genus worldwide. However, lack of molecular markers prevents the detailed study of genetics and phylogeny in Physalis, which limits the progress of breeding. In the present study, we compared the DNA sequences between Physalis and tomato, and attempted to analyze genetic diversity in Physalis using tomato markers. Blasting 23180 DNA sequences derived from Physalis against the International Tomato Annotation Group (ITAG) Release2.3 Predicted CDS (SL2.40) discovered 3356 single-copy orthologous genes between them. A total of 38 accessions from at least six species of Physalis were subjected to genetic diversity analysis using 97 tomato markers and 25 SSR markers derived from P. peruviana. Majority (73.2%) of tomato markers could amplify DNA fragments from at least one accession of Physalis. Diversity in Physalis at molecular level was also detected. The average Nei's genetic distance between accessions was 0.3806 with a range of 0.2865 to 0.7091. These results indicated Physalis and tomato had similarity at both molecular marker and DNA sequence levels. Therefore, the molecular markers developed in tomato can be used in genetic study in Physalis.

Integrative Analysis of Gene Expression Data Including an Assessment of Pathway Enrichment for Predicting Prostate Cancer

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Pingzhao Hu

2006-01-01

biological pathways. In particular, we observed that by integrating information from the insulin signalling pathway into our prediction model, we achieved better prediction of prostate cancer. Conclusions: Our data integration methodology provides an efficient way to identify biologically sound and statistically significant pathways from gene expression data. The significant gene expression phenotypes identified in our study have the potential to characterize complex genetic alterations in prostate cancer.

MimiLook: A Phylogenetic Workflow for Detection of Gene Acquisition in Major Orthologous Groups of Megavirales.

Science.gov (United States)

Jain, Sourabh; Panda, Arup; Colson, Philippe; Raoult, Didier; Pontarotti, Pierre

2017-04-07

With the inclusion of new members, understanding about evolutionary mechanisms and processes by which members of the proposed order, Megavirales, have evolved has become a key area of interest. The central role of gene acquisition has been shown in previous studies. However, the major drawback in gene acquisition studies is the focus on few MV families or putative families with large variation in their genetic structure. Thus, here we have tried to develop a methodology by which we can detect horizontal gene transfers (HGTs), taking into consideration orthologous groups of distantly related Megavirale families. Here, we report an automated workflow MimiLook, prepared as a Perl command line program, that deduces orthologous groups (OGs) from ORFomes of Megavirales and constructs phylogenetic trees by performing alignment generation, alignment editing and protein-protein BLAST (BLASTP) searching across the National Center for Biotechnology Information (NCBI) non-redundant (nr) protein sequence database. Finally, this tool detects statistically validated events of gene acquisitions with the help of the T-REX algorithm by comparing individual gene tree with NCBI species tree. In between the steps, the workflow decides about handling paralogs, filtering outputs, identifying Megavirale specific OGs, detection of HGTs, along with retrieval of information about those OGs that are monophyletic with organisms from cellular domains of life. By implementing MimiLook, we noticed that nine percent of Megavirale gene families (i.e., OGs) have been acquired by HGT, 80% OGs were Megaviralespecific and eight percent were found to be sharing common ancestry with members of cellular domains (Eukaryote, Bacteria, Archaea, Phages or other viruses) and three percent were ambivalent. The results are briefly discussed to emphasize methodology. Also, MimiLook is relevant for detecting evolutionary scenarios in other targeted phyla with user defined modifications. It can be accessed at

MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions.

Science.gov (United States)

Hayashi, Takanori; Matsuzaki, Yuri; Yanagisawa, Keisuke; Ohue, Masahito; Akiyama, Yutaka

2018-05-08

Protein-protein interactions (PPIs) play several roles in living cells, and computational PPI prediction is a major focus of many researchers. The three-dimensional (3D) structure and binding surface are important for the design of PPI inhibitors. Therefore, rigid body protein-protein docking calculations for two protein structures are expected to allow elucidation of PPIs different from known complexes in terms of 3D structures because known PPI information is not explicitly required. We have developed rapid PPI prediction software based on protein-protein docking, called MEGADOCK. In order to fully utilize the benefits of computational PPI predictions, it is necessary to construct a comprehensive database to gather prediction results and their predicted 3D complex structures and to make them easily accessible. Although several databases exist that provide predicted PPIs, the previous databases do not contain a sufficient number of entries for the purpose of discovering novel PPIs. In this study, we constructed an integrated database of MEGADOCK PPI predictions, named MEGADOCK-Web. MEGADOCK-Web provides more than 10 times the number of PPI predictions than previous databases and enables users to conduct PPI predictions that cannot be found in conventional PPI prediction databases. In MEGADOCK-Web, there are 7528 protein chains and 28,331,628 predicted PPIs from all possible combinations of those proteins. Each protein structure is annotated with PDB ID, chain ID, UniProt AC, related KEGG pathway IDs, and known PPI pairs. Additionally, MEGADOCK-Web provides four powerful functions: 1) searching precalculated PPI predictions, 2) providing annotations for each predicted protein pair with an experimentally known PPI, 3) visualizing candidates that may interact with the query protein on biochemical pathways, and 4) visualizing predicted complex structures through a 3D molecular viewer. MEGADOCK-Web provides a huge amount of comprehensive PPI predictions based on

Energy optimization and prediction of complex petrochemical industries using an improved artificial neural network approach integrating data envelopment analysis

International Nuclear Information System (INIS)

Han, Yong-Ming; Geng, Zhi-Qiang; Zhu, Qun-Xiong

2016-01-01

Graphical abstract: This paper proposed an energy optimization and prediction of complex petrochemical industries based on a DEA-integrated ANN approach (DEA-ANN). The proposed approach utilizes the DEA model with slack variables for sensitivity analysis to determine the effective decision making units (DMUs) and indicate the optimized direction of the ineffective DMUs. Compared with the traditional ANN approach, the DEA-ANN prediction model is effectively verified by executing a linear comparison between all DMUs and the effective DMUs through the standard data source from the UCI (University of California at Irvine) repository. Finally, the proposed model is validated through an application in a complex ethylene production system of China petrochemical industry. Meanwhile, the optimization result and the prediction value are obtained to reduce energy consumption of the ethylene production system, guide ethylene production and improve energy efficiency. - Highlights: • The DEA-integrated ANN approach is proposed. • The DEA-ANN prediction model is effectively verified through the standard data source from the UCI repository. • The energy optimization and prediction framework of complex petrochemical industries based on the proposed method is obtained. • The proposed method is valid and efficient in improvement of energy efficiency in complex petrochemical plants. - Abstract: Since the complex petrochemical data have characteristics of multi-dimension, uncertainty and noise, it is difficult to accurately optimize and predict the energy usage of complex petrochemical systems. Therefore, this paper proposes a data envelopment analysis (DEA) integrated artificial neural network (ANN) approach (DEA-ANN). The proposed approach utilizes the DEA model with slack variables for sensitivity analysis to determine the effective decision making units (DMUs) and indicate the optimized direction of the ineffective DMUs. Compared with the traditional ANN approach, the DEA

The Prediction of Exchange Rates with the Use of Auto-Regressive Integrated Moving-Average Models

Directory of Open Access Journals (Sweden)

Daniela Spiesová

2014-10-01

Full Text Available Currency market is recently the largest world market during the existence of which there have been many theories regarding the prediction of the development of exchange rates based on macroeconomic, microeconomic, statistic and other models. The aim of this paper is to identify the adequate model for the prediction of non-stationary time series of exchange rates and then use this model to predict the trend of the development of European currencies against Euro. The uniqueness of this paper is in the fact that there are many expert studies dealing with the prediction of the currency pairs rates of the American dollar with other currency but there is only a limited number of scientific studies concerned with the long-term prediction of European currencies with the help of the integrated ARMA models even though the development of exchange rates has a crucial impact on all levels of economy and its prediction is an important indicator for individual countries, banks, companies and businessmen as well as for investors. The results of this study confirm that to predict the conditional variance and then to estimate the future values of exchange rates, it is adequate to use the ARIMA (1,1,1 model without constant, or ARIMA [(1,7,1,(1,7] model, where in the long-term, the square root of the conditional variance inclines towards stable value.

ANCAC: amino acid, nucleotide, and codon analysis of COGs – a tool for sequence bias analysis in microbial orthologs

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Meiler Arno

2012-09-01

Full Text Available Abstract Background The COG database is the most popular collection of orthologous proteins from many different completely sequenced microbial genomes. Per definition, a cluster of orthologous groups (COG within this database exclusively contains proteins that most likely achieve the same cellular function. Recently, the COG database was extended by assigning to every protein both the corresponding amino acid and its encoding nucleotide sequence resulting in the NUCOCOG database. This extended version of the COG database is a valuable resource connecting sequence features with the functionality of the respective proteins. Results Here we present ANCAC, a web tool and MySQL database for the analysis of amino acid, nucleotide, and codon frequencies in COGs on the basis of freely definable phylogenetic patterns. We demonstrate the usefulness of ANCAC by analyzing amino acid frequencies, codon usage, and GC-content in a species- or function-specific context. With respect to amino acids we, at least in part, confirm the cognate bias hypothesis by using ANCAC’s NUCOCOG dataset as the largest one available for that purpose thus far. Conclusions Using the NUCOCOG datasets, ANCAC connects taxonomic, amino acid, and nucleotide sequence information with the functional classification via COGs and provides a GUI for flexible mining for sequence-bias. Thereby, to our knowledge, it is the only tool for the analysis of sequence composition in the light of physiological roles and phylogenetic context without requirement of substantial programming-skills.

ANCAC: amino acid, nucleotide, and codon analysis of COGs – a tool for sequence bias analysis in microbial orthologs

Science.gov (United States)

2012-01-01

Background The COG database is the most popular collection of orthologous proteins from many different completely sequenced microbial genomes. Per definition, a cluster of orthologous groups (COG) within this database exclusively contains proteins that most likely achieve the same cellular function. Recently, the COG database was extended by assigning to every protein both the corresponding amino acid and its encoding nucleotide sequence resulting in the NUCOCOG database. This extended version of the COG database is a valuable resource connecting sequence features with the functionality of the respective proteins. Results Here we present ANCAC, a web tool and MySQL database for the analysis of amino acid, nucleotide, and codon frequencies in COGs on the basis of freely definable phylogenetic patterns. We demonstrate the usefulness of ANCAC by analyzing amino acid frequencies, codon usage, and GC-content in a species- or function-specific context. With respect to amino acids we, at least in part, confirm the cognate bias hypothesis by using ANCAC’s NUCOCOG dataset as the largest one available for that purpose thus far. Conclusions Using the NUCOCOG datasets, ANCAC connects taxonomic, amino acid, and nucleotide sequence information with the functional classification via COGs and provides a GUI for flexible mining for sequence-bias. Thereby, to our knowledge, it is the only tool for the analysis of sequence composition in the light of physiological roles and phylogenetic context without requirement of substantial programming-skills. PMID:22958836

Multiple Kernel Learning with Random Effects for Predicting Longitudinal Outcomes and Data Integration

Science.gov (United States)

Chen, Tianle; Zeng, Donglin

2015-01-01

Summary Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although kernel-based statistical learning methods are proven to be powerful for a wide range of disease prediction problems, these methods are only well studied for independent data but not for longitudinal data. It is thus important to develop time-sensitive prediction rules that make use of the longitudinal nature of the data. In this paper, we develop a novel statistical learning method for longitudinal data by introducing subject-specific short-term and long-term latent effects through a designed kernel to account for within-subject correlation of longitudinal measurements. Since the presence of multiple sources of data is increasingly common, we embed our method in a multiple kernel learning framework and propose a regularized multiple kernel statistical learning with random effects to construct effective nonparametric prediction rules. Our method allows easy integration of various heterogeneous data sources and takes advantage of correlation among longitudinal measures to increase prediction power. We use different kernels for each data source taking advantage of the distinctive feature of each data modality, and then optimally combine data across modalities. We apply the developed methods to two large epidemiological studies, one on Huntington's disease and the other on Alzheimer's Disease (Alzheimer's Disease Neuroimaging Initiative, ADNI) where we explore a unique opportunity to combine imaging and genetic data to study prediction of mild cognitive impairment, and show a substantial gain in performance while accounting for the longitudinal aspect of the data. PMID:26177419

Mutations that Allow SIR2 Orthologs to Function in a NAD+-Depleted Environment.

Science.gov (United States)

Ondracek, Caitlin R; Frappier, Vincent; Ringel, Alison E; Wolberger, Cynthia; Guarente, Leonard

2017-03-07

Sirtuin enzymes depend on NAD + to catalyze protein deacetylation. Therefore, the lowering of NAD + during aging leads to decreased sirtuin activity and may speed up aging processes in laboratory animals and humans. In this study, we used a genetic screen to identify two mutations in the catalytic domain of yeast Sir2 that allow the enzyme to function in an NAD + -depleted environment. These mutant enzymes give rise to a significant increase of yeast replicative lifespan and increase deacetylation by the Sir2 ortholog, SIRT1, in mammalian cells. Our data suggest that these mutations increase the stability of the conserved catalytic sirtuin domain, thereby increasing the catalytic efficiency of the mutant enzymes. Our approach to identifying sirtuin mutants that permit function in NAD + -limited environments may inform the design of small molecules that can maintain sirtuin activity in aging organisms. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Silencing of the Drosophila ortholog of SOX5 leads to abnormal neuronal development and behavioral impairment.

Science.gov (United States)

Li, Airong; Hooli, Basavaraj; Mullin, Kristina; Tate, Rebecca E; Bubnys, Adele; Kirchner, Rory; Chapman, Brad; Hofmann, Oliver; Hide, Winston; Tanzi, Rudolph E

2017-04-15

SOX5 encodes a transcription factor that is expressed in multiple tissues including heart, lung and brain. Mutations in SOX5 have been previously found in patients with amyotrophic lateral sclerosis (ALS) and developmental delay, intellectual disability and dysmorphic features. To characterize the neuronal role of SOX5, we silenced the Drosophila ortholog of SOX5, Sox102F, by RNAi in various neuronal subtypes in Drosophila. Silencing of Sox102F led to misorientated and disorganized michrochaetes, neurons with shorter dendritic arborization (DA) and reduced complexity, diminished larval peristaltic contractions, loss of neuromuscular junction bouton structures, impaired olfactory perception, and severe neurodegeneration in brain. Silencing of SOX5 in human SH-SY5Y neuroblastoma cells resulted in a significant repression of WNT signaling activity and altered expression of WNT-related genes. Genetic association and meta-analyses of the results in several large family-based and case-control late-onset familial Alzheimer's disease (LOAD) samples of SOX5 variants revealed several variants that show significant association with AD disease status. In addition, analysis for rare and highly penetrate functional variants revealed four novel variants/mutations in SOX5, which taken together with functional prediction analysis, suggests a strong role of SOX5 causing AD in the carrier families. Collectively, these findings indicate that SOX5 is a novel candidate gene for LOAD with an important role in neuronal function. The genetic findings warrant further studies to identify and characterize SOX5 variants that confer risk for AD, ALS and intellectual disability. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

An Integrated Model to Predict Corporate Failure of Listed Companies in Sri Lanka

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Nisansala Wijekoon

2015-07-01

Full Text Available The primary objective of this study is to develop an integrated model to predict corporate failure of listed companies in Sri Lanka. The logistic regression analysis was employed to a data set of 70 matched-pairs of failed and non-failed companies listed in the Colombo Stock Exchange (CSE in Sri Lanka over the period 2002 to 2010. A total of fifteen financial ratios and eight corporate governance variables were used as predictor variables of corporate failure. Analysis of the statistical testing results indicated that model consists with both corporate governance variables and financial ratios improved the prediction accuracy to reach 88.57 per cent one year prior to failure. Furthermore, predictive accuracy of this model in all three years prior to failure is above 80 per cent. Hence model is robust in obtaining accurate results for up to three years prior to failure. It was further found that two financial ratios, working capital to total assets and cash flow from operating activities to total assets, and two corporate governance variables, outside director ratio and company audit committee are having more explanatory power to predict corporate failure. Therefore, model developed in this study can assist investors, managers, shareholders, financial institutions, auditors and regulatory agents in Sri Lanka to forecast corporate failure of listed companies.

A Network Integration Approach to Predict Conserved Regulators Related to Pathogenicity of Influenza and SARS-CoV Respiratory Viruses

Energy Technology Data Exchange (ETDEWEB)

Mitchell, Hugh D.; Eisfeld, Amie J.; Sims, Amy; McDermott, Jason E.; Matzke, Melissa M.; Webb-Robertson, Bobbie-Jo M.; Tilton, Susan C.; Tchitchek, Nicholas; Josset, Laurence; Li, Chengjun; Ellis, Amy L.; Chang, Jean H.; Heegel, Robert A.; Luna, Maria L.; Schepmoes, Athena A.; Shukla, Anil K.; Metz, Thomas O.; Neumann, Gabriele; Benecke, Arndt; Smith, Richard D.; Baric, Ralph; Kawaoka, Yoshihiro; Katze, Michael G.; Waters, Katrina M.

2013-07-25

Respiratory infections stemming from influenza viruses and the Severe Acute Respiratory Syndrome corona virus (SARS-CoV) represent a serious public health threat as emerging pandemics. Despite efforts to identify the critical interactions of these viruses with host machinery, the key regulatory events that lead to disease pathology remain poorly targeted with therapeutics. Here we implement an integrated network interrogation approach, in which proteome and transcriptome datasets from infection of both viruses in human lung epithelial cells are utilized to predict regulatory genes involved in the host response. We take advantage of a novel “crowd-based” approach to identify and combine ranking metrics that isolate genes/proteins likely related to the pathogenicity of SARS-CoV and influenza virus. Subsequently, a multivariate regression model is used to compare predicted lung epithelial regulatory influences with data derived from other respiratory virus infection models. We predicted a small set of regulatory factors with conserved behavior for consideration as important components of viral pathogenesis that might also serve as therapeutic targets for intervention. Our results demonstrate the utility of integrating diverse ‘omic datasets to predict and prioritize regulatory features conserved across multiple pathogen infection models.

Archaeal orthologs of Cdc45 and GINS form a stable complex that stimulates the helicase activity of MCM.

Science.gov (United States)

Xu, Yuli; Gristwood, Tamzin; Hodgson, Ben; Trinidad, Jonathan C; Albers, Sonja-Verena; Bell, Stephen D

2016-11-22

The regulated recruitment of Cdc45 and GINS is key to activating the eukaryotic MCM(2-7) replicative helicase. We demonstrate that the homohexameric archaeal MCM helicase associates with orthologs of GINS and Cdc45 in vivo and in vitro. Association of these factors with MCM robustly stimulates the MCM helicase activity. In contrast to the situation in eukaryotes, archaeal Cdc45 and GINS form an extremely stable complex before binding MCM. Further, the archaeal GINS•Cdc45 complex contains two copies of Cdc45. Our analyses give insight into the function and evolution of the conserved core of the archaeal/eukaryotic replisome.

[Prediction of regional soil quality based on mutual information theory integrated with decision tree algorithm].

Science.gov (United States)

Lin, Fen-Fang; Wang, Ke; Yang, Ning; Yan, Shi-Guang; Zheng, Xin-Yu

2012-02-01

In this paper, some main factors such as soil type, land use pattern, lithology type, topography, road, and industry type that affect soil quality were used to precisely obtain the spatial distribution characteristics of regional soil quality, mutual information theory was adopted to select the main environmental factors, and decision tree algorithm See 5.0 was applied to predict the grade of regional soil quality. The main factors affecting regional soil quality were soil type, land use, lithology type, distance to town, distance to water area, altitude, distance to road, and distance to industrial land. The prediction accuracy of the decision tree model with the variables selected by mutual information was obviously higher than that of the model with all variables, and, for the former model, whether of decision tree or of decision rule, its prediction accuracy was all higher than 80%. Based on the continuous and categorical data, the method of mutual information theory integrated with decision tree could not only reduce the number of input parameters for decision tree algorithm, but also predict and assess regional soil quality effectively.

Framework for Infectious Disease Analysis: A comprehensive and integrative multi-modeling approach to disease prediction and management.

Science.gov (United States)

Erraguntla, Madhav; Zapletal, Josef; Lawley, Mark

2017-12-01

The impact of infectious disease on human populations is a function of many factors including environmental conditions, vector dynamics, transmission mechanics, social and cultural behaviors, and public policy. A comprehensive framework for disease management must fully connect the complete disease lifecycle, including emergence from reservoir populations, zoonotic vector transmission, and impact on human societies. The Framework for Infectious Disease Analysis is a software environment and conceptual architecture for data integration, situational awareness, visualization, prediction, and intervention assessment. Framework for Infectious Disease Analysis automatically collects biosurveillance data using natural language processing, integrates structured and unstructured data from multiple sources, applies advanced machine learning, and uses multi-modeling for analyzing disease dynamics and testing interventions in complex, heterogeneous populations. In the illustrative case studies, natural language processing from social media, news feeds, and websites was used for information extraction, biosurveillance, and situation awareness. Classification machine learning algorithms (support vector machines, random forests, and boosting) were used for disease predictions.

Revisiting EOR Projects in Indonesia through Integrated Study: EOR Screening, Predictive Model, and Optimisation

KAUST Repository

Hartono, A. D.; Hakiki, Farizal; Syihab, Z.; Ambia, F.; Yasutra, A.; Sutopo, S.; Efendi, M.; Sitompul, V.; Primasari, I.; Apriandi, R.

2017-01-01

EOR preliminary analysis is pivotal to be performed at early stage of assessment in order to elucidate EOR feasibility. This study proposes an in-depth analysis toolkit for EOR preliminary evaluation. The toolkit incorporates EOR screening, predictive, economic, risk analysis and optimisation modules. The screening module introduces algorithms which assimilates statistical and engineering notions into consideration. The United States Department of Energy (U.S. DOE) predictive models were implemented in the predictive module. The economic module is available to assess project attractiveness, while Monte Carlo Simulation is applied to quantify risk and uncertainty of the evaluated project. Optimization scenario of EOR practice can be evaluated using the optimisation module, in which stochastic methods of Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Evolutionary Strategy (ES) were applied in the algorithms. The modules were combined into an integrated package of EOR preliminary assessment. Finally, we utilised the toolkit to evaluate several Indonesian oil fields for EOR evaluation (past projects) and feasibility (future projects). The attempt was able to update the previous consideration regarding EOR attractiveness and open new opportunity for EOR implementation in Indonesia.

Revisiting EOR Projects in Indonesia through Integrated Study: EOR Screening, Predictive Model, and Optimisation

KAUST Repository

Hartono, A. D.

2017-10-17

EOR preliminary analysis is pivotal to be performed at early stage of assessment in order to elucidate EOR feasibility. This study proposes an in-depth analysis toolkit for EOR preliminary evaluation. The toolkit incorporates EOR screening, predictive, economic, risk analysis and optimisation modules. The screening module introduces algorithms which assimilates statistical and engineering notions into consideration. The United States Department of Energy (U.S. DOE) predictive models were implemented in the predictive module. The economic module is available to assess project attractiveness, while Monte Carlo Simulation is applied to quantify risk and uncertainty of the evaluated project. Optimization scenario of EOR practice can be evaluated using the optimisation module, in which stochastic methods of Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Evolutionary Strategy (ES) were applied in the algorithms. The modules were combined into an integrated package of EOR preliminary assessment. Finally, we utilised the toolkit to evaluate several Indonesian oil fields for EOR evaluation (past projects) and feasibility (future projects). The attempt was able to update the previous consideration regarding EOR attractiveness and open new opportunity for EOR implementation in Indonesia.

Critical role of the virus-encoded microRNA-155 ortholog in the induction of Marek's disease lymphomas.

Directory of Open Access Journals (Sweden)

Yuguang Zhao

2011-02-01

Full Text Available Notwithstanding the well-characterised roles of a number of oncogenes in neoplastic transformation, microRNAs (miRNAs are increasingly implicated in several human cancers. Discovery of miRNAs in several oncogenic herpesviruses such as KSHV has further highlighted the potential of virus-encoded miRNAs to contribute to their oncogenic capabilities. Nevertheless, despite the identification of several possible cancer-related genes as their targets, the direct in vivo role of virus-encoded miRNAs in neoplastic diseases such as those induced by KSHV is difficult to demonstrate in the absence of suitable models. However, excellent natural disease models of rapid-onset Marek's disease (MD lymphomas in chickens allow examination of the oncogenic potential of virus-encoded miRNAs. Using viruses modified by reverse genetics of the infectious BAC clone of the oncogenic RB-1B strain of MDV, we show that the deletion of the six-miRNA cluster 1 from the viral genome abolished the oncogenicity of the virus. This loss of oncogenicity appeared to be primarily due to the single miRNA within the cluster, miR-M4, the ortholog of cellular miR-155, since its deletion or a 2-nucleotide mutation within its seed region was sufficient to inhibit the induction of lymphomas. The definitive role of this miR-155 ortholog in oncogenicity was further confirmed by the rescue of oncogenic phenotype by revertant viruses that expressed either the miR-M4 or the cellular homolog gga-miR-155. This is the first demonstration of the direct in vivo role of a virus-encoded miRNA in inducing tumors in a natural infection model. Furthermore, the use of viruses deleted in miRNAs as effective vaccines against virulent MDV challenge, enables the prospects of generating genetically defined attenuated vaccines.

A novel firmicute protein family related to the actinobacterial resuscitation-promoting factors by non-orthologous domain displacement

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Finan Christopher L

2005-03-01

Full Text Available Abstract Background In Micrococcus luteus growth and resuscitation from starvation-induced dormancy is controlled by the production of a secreted growth factor. This autocrine resuscitation-promoting factor (Rpf is the founder member of a family of proteins found throughout and confined to the actinobacteria (high G + C Gram-positive bacteria. The aim of this work was to search for and characterise a cognate gene family in the firmicutes (low G + C Gram-positive bacteria and obtain information about how they may control bacterial growth and resuscitation. Results In silico analysis of the accessory domains of the Rpf proteins permitted their classification into several subfamilies. The RpfB subfamily is related to a group of firmicute proteins of unknown function, represented by YabE of Bacillus subtilis. The actinobacterial RpfB and firmicute YabE proteins have very similar domain structures and genomic contexts, except that in YabE, the actinobacterial Rpf domain is replaced by another domain, which we have called Sps. Although totally unrelated in both sequence and secondary structure, the Rpf and Sps domains fulfil the same function. We propose that these proteins have undergone "non-orthologous domain displacement", a phenomenon akin to "non-orthologous gene displacement" that has been described previously. Proteins containing the Sps domain are widely distributed throughout the firmicutes and they too fall into a number of distinct subfamilies. Comparative analysis of the accessory domains in the Rpf and Sps proteins, together with their weak similarity to lytic transglycosylases, provide clear evidence that they are muralytic enzymes. Conclusions The results indicate that the firmicute Sps proteins and the actinobacterial Rpf proteins are cognate and that they control bacterial culturability via enzymatic modification of the bacterial cell envelope.

Crack Growth-Based Predictive Methodology for the Maintenance of the Structural Integrity of Repaired and Nonrepaired Aging Engine Stationary Components

National Research Council Canada - National Science Library

Barron, Michael

1999-01-01

.... Specifically, the FAA's goal was to develop "Crack Growth-Based Predictive Methodologies for the Maintenance of the Structural Integrity of Repaired and Nonrepaired Aging Engine Stationary Components...

An Integrated Ensemble-Based Operational Framework to Predict Urban Flooding: A Case Study of Hurricane Sandy in the Passaic and Hackensack River Basins

Science.gov (United States)

Saleh, F.; Ramaswamy, V.; Georgas, N.; Blumberg, A. F.; Wang, Y.

2016-12-01

Advances in computational resources and modeling techniques are opening the path to effectively integrate existing complex models. In the context of flood prediction, recent extreme events have demonstrated the importance of integrating components of the hydrosystem to better represent the interactions amongst different physical processes and phenomena. As such, there is a pressing need to develop holistic and cross-disciplinary modeling frameworks that effectively integrate existing models and better represent the operative dynamics. This work presents a novel Hydrologic-Hydraulic-Hydrodynamic Ensemble (H3E) flood prediction framework that operationally integrates existing predictive models representing coastal (New York Harbor Observing and Prediction System, NYHOPS), hydrologic (US Army Corps of Engineers Hydrologic Modeling System, HEC-HMS) and hydraulic (2-dimensional River Analysis System, HEC-RAS) components. The state-of-the-art framework is forced with 125 ensemble meteorological inputs from numerical weather prediction models including the Global Ensemble Forecast System, the European Centre for Medium-Range Weather Forecasts (ECMWF), the Canadian Meteorological Centre (CMC), the Short Range Ensemble Forecast (SREF) and the North American Mesoscale Forecast System (NAM). The framework produces, within a 96-hour forecast horizon, on-the-fly Google Earth flood maps that provide critical information for decision makers and emergency preparedness managers. The utility of the framework was demonstrated by retrospectively forecasting an extreme flood event, hurricane Sandy in the Passaic and Hackensack watersheds (New Jersey, USA). Hurricane Sandy caused significant damage to a number of critical facilities in this area including the New Jersey Transit's main storage and maintenance facility. The results of this work demonstrate that ensemble based frameworks provide improved flood predictions and useful information about associated uncertainties, thus

Characterization of gana-1, a Caenorhabditis elegans gene encoding a single ortholog of vertebrate α-galactosidase and α-N-acetylgalactosaminidase

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Kostrouchová Marta

2005-01-01

Full Text Available Abstract Background Human α-galactosidase A (α-GAL and α-N-acetylgalactosaminidase (α-NAGA are presumed to share a common ancestor. Deficiencies of these enzymes cause two well-characterized human lysosomal storage disorders (LSD – Fabry (α-GAL deficiency and Schindler (α-NAGA deficiency diseases. Caenorhabditis elegans was previously shown to be a relevant model organism for several late endosomal/lysosomal membrane proteins associated with LSDs. The aim of this study was to identify and characterize C. elegans orthologs to both human lysosomal luminal proteins α-GAL and α-NAGA. Results BlastP searches for orthologs of human α-GAL and α-NAGA revealed a single C. elegans gene (R07B7.11 with homology to both human genes (α-galactosidase and α-N-acetylgalactosaminidase – gana-1. We cloned and sequenced the complete gana-1 cDNA and elucidated the gene organization. Phylogenetic analyses and homology modeling of GANA-1 based on the 3D structure of chicken α-NAGA, rice α-GAL and human α-GAL suggest a close evolutionary relationship of GANA-1 to both human α-GAL and α-NAGA. Both α-GAL and α-NAGA enzymatic activities were detected in C. elegans mixed culture homogenates. However, α-GAL activity on an artificial substrate was completely inhibited by the α-NAGA inhibitor, N-acetyl-D-galactosamine. A GANA-1::GFP fusion protein expressed from a transgene, containing the complete gana-1 coding region and 3 kb of its hypothetical promoter, was not detectable under the standard laboratory conditions. The GFP signal was observed solely in a vesicular compartment of coelomocytes of the animals treated with Concanamycin A (CON A or NH4Cl, agents that increase the pH of the cellular acidic compartment. Immunofluorescence detection of the fusion protein using polyclonal anti-GFP antibody showed a broader and coarsely granular cytoplasmic expression pattern in body wall muscle cells, intestinal cells, and a vesicular compartment of

Using the Integrative Model of Behavioral Prediction to Understand College Students' STI Testing Beliefs, Intentions, and Behaviors.

Science.gov (United States)

Wombacher, Kevin; Dai, Minhao; Matig, Jacob J; Harrington, Nancy Grant

2018-03-22

To identify salient behavioral determinants related to STI testing among college students by testing a model based on the integrative model of behavioral (IMBP) prediction. 265 undergraduate students from a large university in the Southeastern US. Formative and survey research to test an IMBP-based model that explores the relationships between determinants and STI testing intention and behavior. Results of path analyses supported a model in which attitudinal beliefs predicted intention and intention predicted behavior. Normative beliefs and behavioral control beliefs were not significant in the model; however, select individual normative and control beliefs were significantly correlated with intention and behavior. Attitudinal beliefs are the strongest predictor of STI testing intention and behavior. Future efforts to increase STI testing rates should identify and target salient attitudinal beliefs.

Integrated Design Software Predicts the Creep Life of Monolithic Ceramic Components

Science.gov (United States)

1996-01-01

Significant improvements in propulsion and power generation for the next century will require revolutionary advances in high-temperature materials and structural design. Advanced ceramics are candidate materials for these elevated-temperature applications. As design protocols emerge for these material systems, designers must be aware of several innate features, including the degrading ability of ceramics to carry sustained load. Usually, time-dependent failure in ceramics occurs because of two different, delayedfailure mechanisms: slow crack growth and creep rupture. Slow crack growth initiates at a preexisting flaw and continues until a critical crack length is reached, causing catastrophic failure. Creep rupture, on the other hand, occurs because of bulk damage in the material: void nucleation and coalescence that eventually leads to macrocracks which then propagate to failure. Successful application of advanced ceramics depends on proper characterization of material behavior and the use of an appropriate design methodology. The life of a ceramic component can be predicted with the NASA Lewis Research Center's Ceramics Analysis and Reliability Evaluation of Structures (CARES) integrated design programs. CARES/CREEP determines the expected life of a component under creep conditions, and CARES/LIFE predicts the component life due to fast fracture and subcritical crack growth. The previously developed CARES/LIFE program has been used in numerous industrial and Government applications.

Identification of novel human damage response proteins targeted through yeast orthology.

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J Peter Svensson

Full Text Available Studies in Saccharomyces cerevisiae show that many proteins influence cellular survival upon exposure to DNA damaging agents. We hypothesized that human orthologs of these S. cerevisiae proteins would also be required for cellular survival after treatment with DNA damaging agents. For this purpose, human homologs of S. cerevisiae proteins were identified and mapped onto the human protein-protein interaction network. The resulting human network was highly modular and a series of selection rules were implemented to identify 45 candidates for human toxicity-modulating proteins. The corresponding transcripts were targeted by RNA interference in human cells. The cell lines with depleted target expression were challenged with three DNA damaging agents: the alkylating agents MMS and 4-NQO, and the oxidizing agent t-BuOOH. A comparison of the survival revealed that the majority (74% of proteins conferred either sensitivity or resistance. The identified human toxicity-modulating proteins represent a variety of biological functions: autophagy, chromatin modifications, RNA and protein metabolism, and telomere maintenance. Further studies revealed that MMS-induced autophagy increase the survival of cells treated with DNA damaging agents. In summary, we show that damage recovery proteins in humans can be identified through homology to S. cerevisiae and that many of the same pathways are represented among the toxicity modulators.

ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

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Milos Bogdanovic

2013-08-01

Full Text Available Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.

ESB-based Sensor Web integration for the prediction of electric power supply system vulnerability.

Science.gov (United States)

Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

2013-08-15

Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.

ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

Science.gov (United States)

Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

2013-01-01

Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application. PMID:23955435

Identification of single-copy orthologous genes between Physalis and Solanum lycopersicum and analysis of genetic diversity in Physalis using molecular markers.

Directory of Open Access Journals (Sweden)

Jingli Wei

Full Text Available The genus Physalis includes a number of commercially important edible and ornamental species. Its high nutritional value and potential medicinal properties leads to the increased commercial interest in the products of this genus worldwide. However, lack of molecular markers prevents the detailed study of genetics and phylogeny in Physalis, which limits the progress of breeding. In the present study, we compared the DNA sequences between Physalis and tomato, and attempted to analyze genetic diversity in Physalis using tomato markers. Blasting 23180 DNA sequences derived from Physalis against the International Tomato Annotation Group (ITAG Release2.3 Predicted CDS (SL2.40 discovered 3356 single-copy orthologous genes between them. A total of 38 accessions from at least six species of Physalis were subjected to genetic diversity analysis using 97 tomato markers and 25 SSR markers derived from P. peruviana. Majority (73.2% of tomato markers could amplify DNA fragments from at least one accession of Physalis. Diversity in Physalis at molecular level was also detected. The average Nei's genetic distance between accessions was 0.3806 with a range of 0.2865 to 0.7091. These results indicated Physalis and tomato had similarity at both molecular marker and DNA sequence levels. Therefore, the molecular markers developed in tomato can be used in genetic study in Physalis.

Model Predictive Control of Integrated Gasification Combined Cycle Power Plants

Energy Technology Data Exchange (ETDEWEB)

B. Wayne Bequette; Priyadarshi Mahapatra

2010-08-31

The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.

Integrating Non-Tidal Sea Level data from altimetry and tide gauges for coastal sea level prediction

DEFF Research Database (Denmark)

Cheng, Yongcun; Andersen, Ole Baltazar; Knudsen, Per

2012-01-01

The main objective of this paper is to integrate Non-Tidal Sea Level (NSL) from the joint TOPEX, Jason-1 and Jason-2 satellite altimetry with tide gauge data at the west and north coast of the United Kingdom for coastal sea level prediction. The temporal correlation coefficient between altimetric...... NSLs and tide gauge data reaches a maximum higher than 90% for each gauge. The results show that the multivariate regression approach can efficiently integrate the two types of data in the coastal waters of the area. The Multivariate Regression Model is established by integrating the along-track NSL...... from the joint TOPEX/Jason-1/Jason-2 altimeters with that from eleven tide gauges. The model results give a maximum hindcast skill of 0.95, which means maximum 95% of NSL variance can be explained by the model. The minimum Root Mean Square Error (RMSe) between altimetric observations and model...

Internally-directed cognition and mindfulness:An integrative perspective derived from reactive versus predictive control systems theory

Directory of Open Access Journals (Sweden)

Mattie eTops

2014-05-01

Full Text Available In the present paper we will apply the Predictive And Reactive Control Systems (PARCS theory as a framework that integrates competing theories of neural substrates of awareness by describing the default mode network (DMN and anterior insula (AI as parts of two different behavioral and homeostatic control systems. The DMN, a network that becomes active at rest when there is no external stimulation or task to perform, has been implicated in self-reflective awareness and prospection. By contrast, the AI is associated with awareness and task-related attention. This has led to competing theories stressing the role of the DMN in self-awareness versus the role of interoceptive and emotional information integration in the AI in awareness of the emotional moment. In PARCS, the respective functions of the DMN and AI in a specific control system explains their association with different qualities of awareness, and how mental states can shift from one state (e.g., prospective self-reflection to the other (e.g., awareness of the emotional moment depending on the relative dominance of control systems. These shifts between reactive and predictive control are part of processes that enable the intake of novel information, integration of this novel information within existing knowledge structures, and the creation of a continuous personal context in which novel information can be integrated and understood. As such, PARCS can explain key characteristics of mental states, such as their temporal and spatial focus (e.g., a focus on the here and now vs. the future; a 1st person vs. a 3rd person perspective. PARCS further relates mental states to brain states and functions, such as activation of the DMN or hemispheric asymmetry in frontal cortical functions. Together, PARCS deepens the understanding of a broad range of mental states, including mindfulness, mind wandering, rumination, autobiographical memory, imagery, and the experience of self.

Study on integrated approach of Nuclear Accident Hazard Predicting, Warning, and Optimized Controlling System based on GIS

International Nuclear Information System (INIS)

Tang Lijuan; Huang Shunxiang; Wang Xinming

2012-01-01

The issue of nuclear safety becomes the attention focus of international society after the nuclear accident happened in Fukushima. Aiming at the requirements of the prevention and controlling of Nuclear Accident establishment of Nuclear Accident Hazard Predicting, Warning and optimized Controlling System (NAPWS) is a imperative project that our country and army are desiderating, which includes multiple fields of subject as nuclear physics, atmospheric science, security science, computer science and geographical information technology, etc. Multiplatform, multi-system and multi-mode are integrated effectively based on GIS, accordingly the Predicting, Warning, and Optimized Controlling technology System of Nuclear Accident Hazard is established. (authors)

Observing others stay or switch - How social prediction errors are integrated into reward reversal learning.

Science.gov (United States)

Ihssen, Niklas; Mussweiler, Thomas; Linden, David E J

2016-08-01

Reward properties of stimuli can undergo sudden changes, and the detection of these 'reversals' is often made difficult by the probabilistic nature of rewards/punishments. Here we tested whether and how humans use social information (someone else's choices) to overcome uncertainty during reversal learning. We show a substantial social influence during reversal learning, which was modulated by the type of observed behavior. Participants frequently followed observed conservative choices (no switches after punishment) made by the (fictitious) other player but ignored impulsive choices (switches), even though the experiment was set up so that both types of response behavior would be similarly beneficial/detrimental (Study 1). Computational modeling showed that participants integrated the observed choices as a 'social prediction error' instead of ignoring or blindly following the other player. Modeling also confirmed higher learning rates for 'conservative' versus 'impulsive' social prediction errors. Importantly, this 'conservative bias' was boosted by interpersonal similarity, which in conjunction with the lack of effects observed in a non-social control experiment (Study 2) confirmed its social nature. A third study suggested that relative weighting of observed impulsive responses increased with increased volatility (frequency of reversals). Finally, simulations showed that in the present paradigm integrating social and reward information was not necessarily more adaptive to maximize earnings than learning from reward alone. Moreover, integrating social information increased accuracy only when conservative and impulsive choices were weighted similarly during learning. These findings suggest that to guide decisions in choice contexts that involve reward reversals humans utilize social cues conforming with their preconceptions more strongly than cues conflicting with them, especially when the other is similar. Copyright © 2016 The Authors. Published by Elsevier B

Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

Science.gov (United States)

Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

2015-12-01

Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we

ChlamyCyc: an integrative systems biology database and web-portal for Chlamydomonas reinhardtii.

Science.gov (United States)

May, Patrick; Christian, Jan-Ole; Kempa, Stefan; Walther, Dirk

2009-05-04

The unicellular green alga Chlamydomonas reinhardtii is an important eukaryotic model organism for the study of photosynthesis and plant growth. In the era of modern high-throughput technologies there is an imperative need to integrate large-scale data sets from high-throughput experimental techniques using computational methods and database resources to provide comprehensive information about the molecular and cellular organization of a single organism. In the framework of the German Systems Biology initiative GoFORSYS, a pathway database and web-portal for Chlamydomonas (ChlamyCyc) was established, which currently features about 250 metabolic pathways with associated genes, enzymes, and compound information. ChlamyCyc was assembled using an integrative approach combining the recently published genome sequence, bioinformatics methods, and experimental data from metabolomics and proteomics experiments. We analyzed and integrated a combination of primary and secondary database resources, such as existing genome annotations from JGI, EST collections, orthology information, and MapMan classification. ChlamyCyc provides a curated and integrated systems biology repository that will enable and assist in systematic studies of fundamental cellular processes in Chlamydomonas. The ChlamyCyc database and web-portal is freely available under http://chlamycyc.mpimp-golm.mpg.de.

MirZ: an integrated microRNA expression atlas and target prediction resource.

Science.gov (United States)

Hausser, Jean; Berninger, Philipp; Rodak, Christoph; Jantscher, Yvonne; Wirth, Stefan; Zavolan, Mihaela

2009-07-01

MicroRNAs (miRNAs) are short RNAs that act as guides for the degradation and translational repression of protein-coding mRNAs. A large body of work showed that miRNAs are involved in the regulation of a broad range of biological functions, from development to cardiac and immune system function, to metabolism, to cancer. For most of the over 500 miRNAs that are encoded in the human genome the functions still remain to be uncovered. Identifying miRNAs whose expression changes between cell types or between normal and pathological conditions is an important step towards characterizing their function as is the prediction of mRNAs that could be targeted by these miRNAs. To provide the community the possibility of exploring interactively miRNA expression patterns and the candidate targets of miRNAs in an integrated environment, we developed the MirZ web server, which is accessible at www.mirz.unibas.ch. The server provides experimental and computational biologists with statistical analysis and data mining tools operating on up-to-date databases of sequencing-based miRNA expression profiles and of predicted miRNA target sites in species ranging from Caenorhabditis elegans to Homo sapiens.

Improved prediction of drug-target interactions using regularized least squares integrating with kernel fusion technique

Energy Technology Data Exchange (ETDEWEB)

Hao, Ming; Wang, Yanli, E-mail: ywang@ncbi.nlm.nih.gov; Bryant, Stephen H., E-mail: bryant@ncbi.nlm.nih.gov

2016-02-25

Identification of drug-target interactions (DTI) is a central task in drug discovery processes. In this work, a simple but effective regularized least squares integrating with nonlinear kernel fusion (RLS-KF) algorithm is proposed to perform DTI predictions. Using benchmark DTI datasets, our proposed algorithm achieves the state-of-the-art results with area under precision–recall curve (AUPR) of 0.915, 0.925, 0.853 and 0.909 for enzymes, ion channels (IC), G protein-coupled receptors (GPCR) and nuclear receptors (NR) based on 10 fold cross-validation. The performance can further be improved by using a recalculated kernel matrix, especially for the small set of nuclear receptors with AUPR of 0.945. Importantly, most of the top ranked interaction predictions can be validated by experimental data reported in the literature, bioassay results in the PubChem BioAssay database, as well as other previous studies. Our analysis suggests that the proposed RLS-KF is helpful for studying DTI, drug repositioning as well as polypharmacology, and may help to accelerate drug discovery by identifying novel drug targets. - Graphical abstract: Flowchart of the proposed RLS-KF algorithm for drug-target interaction predictions. - Highlights: • A nonlinear kernel fusion algorithm is proposed to perform drug-target interaction predictions. • Performance can further be improved by using the recalculated kernel. • Top predictions can be validated by experimental data.

Improved prediction of drug-target interactions using regularized least squares integrating with kernel fusion technique

International Nuclear Information System (INIS)

Hao, Ming; Wang, Yanli; Bryant, Stephen H.

2016-01-01

Identification of drug-target interactions (DTI) is a central task in drug discovery processes. In this work, a simple but effective regularized least squares integrating with nonlinear kernel fusion (RLS-KF) algorithm is proposed to perform DTI predictions. Using benchmark DTI datasets, our proposed algorithm achieves the state-of-the-art results with area under precision–recall curve (AUPR) of 0.915, 0.925, 0.853 and 0.909 for enzymes, ion channels (IC), G protein-coupled receptors (GPCR) and nuclear receptors (NR) based on 10 fold cross-validation. The performance can further be improved by using a recalculated kernel matrix, especially for the small set of nuclear receptors with AUPR of 0.945. Importantly, most of the top ranked interaction predictions can be validated by experimental data reported in the literature, bioassay results in the PubChem BioAssay database, as well as other previous studies. Our analysis suggests that the proposed RLS-KF is helpful for studying DTI, drug repositioning as well as polypharmacology, and may help to accelerate drug discovery by identifying novel drug targets. - Graphical abstract: Flowchart of the proposed RLS-KF algorithm for drug-target interaction predictions. - Highlights: • A nonlinear kernel fusion algorithm is proposed to perform drug-target interaction predictions. • Performance can further be improved by using the recalculated kernel. • Top predictions can be validated by experimental data.

Integration of meanline and one-dimensional methods for prediction of pulsating performance of a turbocharger turbine

International Nuclear Information System (INIS)

Chiong, M.S.; Rajoo, S.; Romagnoli, A.; Costall, A.W.; Martinez-Botas, R.F.

2014-01-01

Highlights: • Unsteady turbine performance prediction by integrating the 1-D and meanline models. • The optimum discretization length/diameter ratio is identified. • No improvement is gained by increasing the number of rotor entries. • The predicted instantaneous mass flow and output power are analysed in detail. - Abstract: Stringent emission regulations are driving engine manufacturers to increase investment into enabling technologies to achieve better specific fuel consumption, thermal efficiency and most importantly carbon reduction. Engine downsizing is seen as a key enabler to successfully achieve all of these requirements. Boosting through turbocharging is widely regarded as one of the most promising technologies for engine downsizing. However, the wide range of engine speeds and loads requires enhanced quality of engine-turbocharger matching, compared to the conventional approach which considers only the full load condition. Thus, development of computational models capable of predicting the unsteady behaviour of a turbocharger turbine is crucial to the overall matching process. A purely one-dimensional (1D) turbine model is capable of good unsteady swallowing capacity predictions, however it has not been fully exploited to predict instantaneous turbine power. On the contrary, meanline models (zero-dimensional) are regarded as a good tool to determine turbine efficiency in steady state but they do not include any information about the pressure wave action occurring within the turbine. This paper explores an alternative methodology to predict instantaneous turbine power and swallowing capacity by integrating one-dimensional and meanline models. A single entry mixed-flow turbine is modelled using a 1D gas dynamic code to solve the unsteady flow state in the volute, consequently used as the input for a meanline model to evaluate the instantaneous turbine power. The key in the effectiveness of this methodology relies on the synchronisation of the flow

Integration of metabolomic and transcriptomic networks in pregnant women reveals biological pathways and predictive signatures associated with preeclampsia.

Science.gov (United States)

Kelly, Rachel S; Croteau-Chonka, Damien C; Dahlin, Amber; Mirzakhani, Hooman; Wu, Ann C; Wan, Emily S; McGeachie, Michael J; Qiu, Weiliang; Sordillo, Joanne E; Al-Garawi, Amal; Gray, Kathryn J; McElrath, Thomas F; Carey, Vincent J; Clish, Clary B; Litonjua, Augusto A; Weiss, Scott T; Lasky-Su, Jessica A

2017-01-01

Preeclampsia is a leading cause of maternal and fetal mortality worldwide, yet its exact pathogenesis remains elusive. This study, nested within the Vitamin D Antenatal Asthma Reduction Trial (VDAART), aimed to develop integrated omics models of preeclampsia that have utility in both prediction and in the elucidation of underlying biological mechanisms. Metabolomic profiling was performed on first trimester plasma samples of 47 pregnant women from VDAART who subsequently developed preeclampsia and 62 controls with healthy pregnancies, using liquid-chromatography tandem mass-spectrometry. Metabolomic profiles were generated based on logistic regression models and assessed using Received Operator Characteristic Curve analysis. These profiles were compared to profiles from generated using third trimester samples. The first trimester metabolite profile was then integrated with a pre-existing transcriptomic profile using network methods. In total, 72 (0.9%) metabolite features were associated (pIntegration with the transcriptomic signature refined these results suggesting a particular role for lipid imbalance, immune function and the circulatory system. These findings suggest it is possible to develop a predictive metabolomic profile of preeclampsia. This profile is characterized by changes in lipid and amino acid metabolism and dysregulation of immune response and can be refined through interaction with transcriptomic data. However validation in larger and more diverse populations is required.

Thought insertion as a self-disturbance: An integration of predictive coding and phenomenological approaches

Directory of Open Access Journals (Sweden)

Philipp Sterzer

2016-10-01

Full Text Available Current theories in the framework of hierarchical predictive coding propose that positive symptoms of schizophrenia, such as delusions and hallucinations, arise from an alteration in Bayesian inference, the term inference referring to a process by which learned predictions are used to infer probable causes of sensory data. However, for one particularly striking and frequent symptom of schizophrenia, thought insertion, no plausible account has been proposed in terms of the predictive-coding framework. Here we propose that thought insertion is due to an altered experience of thoughts as coming from nowhere, as is already indicated by the early 20th century phenomenological accounts by the early Heidelberg School of psychiatry. These accounts identified thought insertion as one of the self-disturbances (from German: Ichstörungen of schizophrenia and used mescaline as a model-psychosis in healthy individuals to explore the possible mechanisms. The early Heidelberg School (Gruhle, Mayer-Gross, Beringer first named and defined the self-disturbances, and proposed that thought insertion involves a disruption of the inner connectedness of thoughts and experiences, and a becoming sensory of those thoughts experienced as inserted. This account offers a novel way to integrate the phenomenology of thought insertion with the predictive coding framework. We argue that the altered experience of thoughts may be caused by a reduced precision of context-dependent predictions, relative to sensory precision. According to the principles of Bayesian inference, this reduced precision leads to increased prediction-error signals evoked by the neural activity that encodes thoughts. Thus, in analogy with the prediction-error related aberrant salience of external events that has been proposed previously, internal events such as thoughts (including volitions, emotions and memories can also be associated with increased prediction-error signaling and are thus imbued with

Protein (Viridiplantae): 159470305 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available predicted protein Chlamydomonas reinhardtii MSSRPKRAASANMANVIAAEKANKAAALHAWPKMWATKLEAQLQLMFMPTRLHRRPLHQGTCRNYSTAPGITGVIELTSAFYRMYPNATFVFNKETAAKGTYRGEEETAASWWLKHVGSKLEIYLSPLRCRPEVSR ...

Performance prediction for silicon photonics integrated circuits with layout-dependent correlated manufacturing variability.

Science.gov (United States)

Lu, Zeqin; Jhoja, Jaspreet; Klein, Jackson; Wang, Xu; Liu, Amy; Flueckiger, Jonas; Pond, James; Chrostowski, Lukas

2017-05-01

This work develops an enhanced Monte Carlo (MC) simulation methodology to predict the impacts of layout-dependent correlated manufacturing variations on the performance of photonics integrated circuits (PICs). First, to enable such performance prediction, we demonstrate a simple method with sub-nanometer accuracy to characterize photonics manufacturing variations, where the width and height for a fabricated waveguide can be extracted from the spectral response of a racetrack resonator. By measuring the spectral responses for a large number of identical resonators spread over a wafer, statistical results for the variations of waveguide width and height can be obtained. Second, we develop models for the layout-dependent enhanced MC simulation. Our models use netlist extraction to transfer physical layouts into circuit simulators. Spatially correlated physical variations across the PICs are simulated on a discrete grid and are mapped to each circuit component, so that the performance for each component can be updated according to its obtained variations, and therefore, circuit simulations take the correlated variations between components into account. The simulation flow and theoretical models for our layout-dependent enhanced MC simulation are detailed in this paper. As examples, several ring-resonator filter circuits are studied using the developed enhanced MC simulation, and statistical results from the simulations can predict both common-mode and differential-mode variations of the circuit performance.

Molecular evolutionary analysis of a gender-limited MID ortholog from the homothallic species Volvox africanus with male and monoecious spheroids.

Directory of Open Access Journals (Sweden)

Kayoko Yamamoto

Full Text Available Volvox is a very interesting oogamous organism that exhibits various types of sexuality and/or sexual spheroids depending upon species or strains. However, molecular bases of such sexual reproduction characteristics have not been studied in this genus. In the model species V. carteri, an ortholog of the minus mating type-determining or minus dominance gene (MID of isogamous Chlamydomonas reinhardtii is male-specific and determines the sperm formation. Male and female genders are genetically determined (heterothallism in V. carteri, whereas in several other species of Volvox both male and female gametes (sperm and eggs are formed within the same clonal culture (homothallism. To resolve the molecular basis of the evolution of Volvox species with monoecious spheroids, we here describe a MID ortholog in the homothallic species V. africanus that produces both monoecious and male spheroids within a single clonal culture. Comparison of synonymous and nonsynonymous nucleotide substitutions in MID genes between V. africanus and heterothallic volvocacean species suggests that the MID gene of V. africanus evolved under the same degree of functional constraint as those of the heterothallic species. Based on semi quantitative reverse transcription polymerase chain reaction analyses using the asexual, male and monoecious spheroids isolated from a sexually induced V. africanus culture, the MID mRNA level was significantly upregulated in the male spheroids, but suppressed in the monoecious spheroids. These results suggest that the monoecious spheroid-specific down regulation of gene expression of the MID homolog correlates with the formation of both eggs and sperm in the same spheroid in V. africanus.

An integrated numerical model for the prediction of Gaussian and billet shapes

International Nuclear Information System (INIS)

Hattel, J.H.; Pryds, N.H.; Pedersen, T.B.

2004-01-01

Separate models for the atomisation and the deposition stages were recently integrated by the authors to form a unified model describing the entire spray-forming process. In the present paper, the focus is on describing the shape of the deposited material during the spray-forming process, obtained by this model. After a short review of the models and their coupling, the important factors which influence the resulting shape, i.e. Gaussian or billet, are addressed. The key parameters, which are utilized to predict the geometry and dimension of the deposited material, are the sticking efficiency and the shading effect for Gaussian and billet shape, respectively. From the obtained results, the effect of these parameters on the final shape is illustrated

The tomato RLK superfamily: phylogeny and functional predictions about the role of the LRRII-RLK subfamily in antiviral defense.

Science.gov (United States)

Sakamoto, Tetsu; Deguchi, Michihito; Brustolini, Otávio J B; Santos, Anésia A; Silva, Fabyano F; Fontes, Elizabeth P B

2012-12-02

Receptor-like kinases (RLKs) play key roles during development and in responses to the environment. Despite the relevance of the RLK family and the completion of the tomato genome sequencing, the tomato RLK family has not yet been characterized, and a framework for functional predictions of the members of the family is lacking. To generate a complete list of all the members of the tomato RLK family, we performed a phylogenetic analysis using the Arabidopsis family as a template. A total of 647 RLKs were identified in the tomato genome, which were organized into the same subfamily clades as Arabidopsis RLKs. Only eight of 58 RLK subfamilies exhibited specific expansion/reduction compared to their Arabidopsis counterparts. We also characterized the LRRII-RLK family by phylogeny, genomic analysis, expression profile and interaction with the virulence factor from begomoviruses, the nuclear shuttle protein (NSP). The LRRII subfamily members from tomato and Arabidopsis were highly conserved in both sequence and structure. Nevertheless, the majority of the orthologous pairs did not display similar conservation in the gene expression profile, indicating that these orthologs may have diverged in function after speciation. Based on the fact that members of the Arabidopsis LRRII subfamily (AtNIK1, AtNIK2 and AtNIK3) interact with the begomovirus nuclear shuttle protein (NSP), we examined whether the tomato orthologs of NIK, BAK1 and NsAK genes interact with NSP of Tomato Yellow Spot Virus (ToYSV). The tomato orthologs of NSP interactors, SlNIKs and SlNsAK, interacted specifically with NSP in yeast and displayed an expression pattern consistent with the pattern of geminivirus infection. In addition to suggesting a functional analogy between these phylogenetically classified orthologs, these results expand our previous observation that NSP-NIK interactions are neither virus-specific nor host-specific. The tomato RLK superfamily is made-up of 647 proteins that form a

The tomato RLK superfamily: phylogeny and functional predictions about the role of the LRRII-RLK subfamily in antiviral defense

Directory of Open Access Journals (Sweden)

Sakamoto Tetsu

2012-12-01

Full Text Available Abstract Background Receptor-like kinases (RLKs play key roles during development and in responses to the environment. Despite the relevance of the RLK family and the completion of the tomato genome sequencing, the tomato RLK family has not yet been characterized, and a framework for functional predictions of the members of the family is lacking. Results To generate a complete list of all the members of the tomato RLK family, we performed a phylogenetic analysis using the Arabidopsis family as a template. A total of 647 RLKs were identified in the tomato genome, which were organized into the same subfamily clades as Arabidopsis RLKs. Only eight of 58 RLK subfamilies exhibited specific expansion/reduction compared to their Arabidopsis counterparts. We also characterized the LRRII-RLK family by phylogeny, genomic analysis, expression profile and interaction with the virulence factor from begomoviruses, the nuclear shuttle protein (NSP. The LRRII subfamily members from tomato and Arabidopsis were highly conserved in both sequence and structure. Nevertheless, the majority of the orthologous pairs did not display similar conservation in the gene expression profile, indicating that these orthologs may have diverged in function after speciation. Based on the fact that members of the Arabidopsis LRRII subfamily (AtNIK1, AtNIK2 and AtNIK3 interact with the begomovirus nuclear shuttle protein (NSP, we examined whether the tomato orthologs of NIK, BAK1 and NsAK genes interact with NSP of Tomato Yellow Spot Virus (ToYSV. The tomato orthologs of NSP interactors, SlNIKs and SlNsAK, interacted specifically with NSP in yeast and displayed an expression pattern consistent with the pattern of geminivirus infection. In addition to suggesting a functional analogy between these phylogenetically classified orthologs, these results expand our previous observation that NSP-NIK interactions are neither virus-specific nor host-specific. Conclusions The tomato RLK

Bloom syndrome ortholog HIM-6 maintains genomic stability in C. elegans.

Science.gov (United States)

Grabowski, Melissa M; Svrzikapa, Nenad; Tissenbaum, Heidi A

2005-12-01

Bloom syndrome is caused by mutation of the Bloom helicase (BLM), a member of the RecQ helicase family. Loss of BLM function results in genomic instability that causes a high incidence of cancer. It has been demonstrated that BLM is important for maintaining genomic stability by playing a role in DNA recombination and repair; however, the exact function of BLM is not clearly understood. To determine the mechanism by which BLM controls genomic stability in vivo, we examined the phenotypes caused by mutation of the C. elegans BLM helicase ortholog, HIM-6. We find that the loss of HIM-6 leads to genomic instability as evidenced by an increased number of genomic insertions and deletions, which results in visible random mutant phenotypes. In addition to the mutator phenotype, him-6 mutants have a low brood size, a high incidence of males, a shortened life span, and an increased amount of germ line apoptosis. Upon exposure to high temperature, him-6 mutants that are serially passed become sterile demonstrating a mortal germ line phenotype. Our data suggest a model in which loss of HIM-6 results in genomic instability due to an increased number of DNA lesions, which either cannot be repaired and/or are introduced by low fidelity recombination events. The increased level of genomic instability that leads to him-6(ok412) mutants having a shortened life span.

Protein (Viridiplantae): 224169381 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 5297 3694:5297 predicted protein Populus trichocarpa MMINVVFAADSGLGSDAVFAADAEIGSDAVFAADSGLGSDAVFAADAEIGSDAVFAADSGLGSDAVFAADSGLVFAA...DSGLGNDAVFAADSGLGSDAVFAADAEIDSDAVFAADSGMGSDAAFAADSGLGSDAVFAADAEISSDAVFAADSGLGSDAVFAA...HFLIGSDAVFAADAEIGSDAVFAADAEIGSDAVFAADFSMNSDAELGGRGKTDFR ...

Protein (Viridiplantae): 145354532 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 436017:4420 predicted protein Ostreococcus lucimarinus CCE9901 MSTRRPTTRARADDGFARDDDEDDGAHDDVAANTIVVYTKPGCCLCDGLKDKLDAAVDAAARAPPGASL...ECLRDFALCVRDVSTNAAWAESYAGSVPRVFVRVAVDAASTERSSVVSREFARPPPKRAAARVAEDLASLVRRACAPARAGWTVVTTTAWDAPSSSF ...

Experimental validation of alternate integral-formulation method for predicting acoustic radiation based on particle velocity measurements.

Science.gov (United States)

Ni, Zhi; Wu, Sean F

2010-09-01

This paper presents experimental validation of an alternate integral-formulation method (AIM) for predicting acoustic radiation from an arbitrary structure based on the particle velocities specified on a hypothetical surface enclosing the target source. Both the normal and tangential components of the particle velocity on this hypothetical surface are measured and taken as the input to AIM codes to predict the acoustic pressures in both exterior and interior regions. The results obtained are compared with the benchmark values measured by microphones at the same locations. To gain some insight into practical applications of AIM, laser Doppler anemometer (LDA) and double hotwire sensor (DHS) are used as measurement devices to collect the particle velocities in the air. Measurement limitations of using LDA and DHS are discussed.

Studies on improvement of tomato productivity in a large-scale greenhouse: Prediction of tomato yield based on integrated solar radiation

International Nuclear Information System (INIS)

Hisaeda, K.; Nishina, H.

2007-01-01

As there are currently many large-scale production facilities that have contracts with the large retailing companies, accurate prediction of yield is necessary. The present study developed a method to predict tomato yield accurately using the data on the outside solar radiation. The present study was conducted in a Venlo-type greenhouse (29,568 square m) at Sera Farm Co., Ltd. in Sera-cho in Hiroshima prefecture. The cultivar used for this experiment was plum tomato. The sowing took place on July 18, the planting took place on August 30, and the harvesting started on October 9, 2002. The planting density was 2.5 plants msup(-2). As the results of the analysis of correlation between the weekly tomato yield and the integrated solar radiation for the period from October 7 to July 28 (43 weeks), the highest correlation (r = 0.518) between the weekly tomato yield and the solar radiation integrated from seven to one weeks before the harvesting was observed. Further investigation by the same correlation analysis was conducted for the 25 weeks period from December 8 to May 26, during which time the effect of growing stages and air temperature were considered to be relatively small. The results showed the highest correlation (r = 0.730) between the weekly tomato yield and the solar radiation integrated from eight to one weeks before the harvesting. The tomato yield occasionally needed to be adjusted at Sera Farm. Consequently, the correlation between the three-week moving average of tomato yield and the integrated solar radiation was calculated. The results showed the highest correlation was obtained for the period from eight to one weeks before the harvesting (r = 0.860). This study therefore showed that it was possible to predict the tomato yield (y: kg.msup(-2).weeksup(-1)) using the following equation on the solar radiation integrated from eight to one weeks before the harvesting(x: MJ.msup(-2)): y = 7.50 x 10 sup(-6)x + 0.148 (rsup(2) = 0.740)

Predictive networks: a flexible, open source, web application for integration and analysis of human gene networks.

Science.gov (United States)

Haibe-Kains, Benjamin; Olsen, Catharina; Djebbari, Amira; Bontempi, Gianluca; Correll, Mick; Bouton, Christopher; Quackenbush, John

2012-01-01

Genomics provided us with an unprecedented quantity of data on the genes that are activated or repressed in a wide range of phenotypes. We have increasingly come to recognize that defining the networks and pathways underlying these phenotypes requires both the integration of multiple data types and the development of advanced computational methods to infer relationships between the genes and to estimate the predictive power of the networks through which they interact. To address these issues we have developed Predictive Networks (PN), a flexible, open-source, web-based application and data services framework that enables the integration, navigation, visualization and analysis of gene interaction networks. The primary goal of PN is to allow biomedical researchers to evaluate experimentally derived gene lists in the context of large-scale gene interaction networks. The PN analytical pipeline involves two key steps. The first is the collection of a comprehensive set of known gene interactions derived from a variety of publicly available sources. The second is to use these 'known' interactions together with gene expression data to infer robust gene networks. The PN web application is accessible from http://predictivenetworks.org. The PN code base is freely available at https://sourceforge.net/projects/predictivenets/.

Integrated predictive modeling of high-mode tokamak plasmas using a combination of core and pedestal models

International Nuclear Information System (INIS)

Bateman, Glenn; Bandres, Miguel A.; Onjun, Thawatchai; Kritz, Arnold H.; Pankin, Alexei

2003-01-01

A new integrated modeling protocol is developed using a model for the temperature and density pedestal at the edge of high-mode (H-mode) plasmas [Onjun et al., Phys. Plasmas 9, 5018 (2002)] together with the Multi-Mode core transport model (MMM95) [Bateman et al., Phys. Plasmas 5, 1793 (1998)] in the BALDUR integrated modeling code to predict the temperature and density profiles of 33 H-mode discharges. The pedestal model is used to provide the boundary conditions in the simulations, once the heating power rises above the H-mode power threshold. Simulations are carried out for 20 discharges in the Joint European Torus and 13 discharges in the DIII-D tokamak. These discharges include systematic scans in normalized gyroradius, plasma pressure, collisionality, isotope mass, elongation, heating power, and plasma density. The average rms deviation between experimental data and the predicted profiles of temperature and density, normalized by central values, is found to be about 10%. It is found that the simulations tend to overpredict the temperature profiles in discharges with low heating power per plasma particle and to underpredict the temperature profiles in discharges with high heating power per particle. Variations of the pedestal model are used to test the sensitivity of the simulation results

Protein (Viridiplantae): 714399 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 3051:329 ... 3052:329 ... 3055:329 ... predicted protein Chlamydomonas reinhardtii MAPAALPGRSVKSKQAHLLRTDAHRVKSKQAHLLRTDAHRVKSKQAHLLRTDA...HRVKSKQAHLLRTDAHRVKSKQAHLLRTDAHRVALTTLTGALSLFGGACTATSFVLQVSASAASYAASLRLSCPAVPSLTDVA

Protein (Viridiplantae): 224094212 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 5297 3694:5297 predicted protein Populus trichocarpa MMMNAVFAADAEIGSDAVFAADSGLGSDAVFAADFGLGSDAVFAADAEIGSDAVFAA...DSGLGSDTAFTTDTEIGSNTVFAAHFLIGSDAVFAADAEIGSDAVFAADFSMNSDAELGGRVFAADAEIGSDAVFAADSGLGSEAVFAADSGLGSDAVFAA...DAEIGSDAVFAADSGLGSDAVFAADSGLGSDAVFAADAEIGSDKVFAADSGLGSDAVFAADSGLGSHAVFAADAEIGSDAVFAADSGLGSDAVFAA...DSGLGSDAAFTTDTEIGSDTVFAAHFLIGSDAVFAADAEIGSDAVFAADFSMNSDAELGGRGKNWF ...

The Nature and Predictive Value of Mothers’ Beliefs Regarding Infants’ and Toddlers’ TV/Video Viewing: Applying the Integrative Model of Behavioral Prediction

Science.gov (United States)

Vaala, Sarah E.

2014-01-01

Viewing television and video programming has become a normative behavior among US infants and toddlers. Little is understood about parents’ decision-making about the extent of their young children’s viewing, though numerous organizations are interested in reducing time spent viewing among infants and toddlers. Prior research has examined parents’ belief in the educational value of TV/videos for young children and the predictive value of this belief for understanding infant/toddler viewing rates, though other possible salient beliefs remain largely unexplored. This study employs the integrative model of behavioral prediction (Fishbein & Ajzen, 2010) to examine 30 maternal beliefs about infants’ and toddlers’ TV/video viewing which were elicited from a prior sample of mothers. Results indicate that mothers tend to hold more positive than negative beliefs about the outcomes associated with young children’s TV/video viewing, and that the nature of the aggregate set of beliefs is predictive of their general attitudes and intentions to allow their children to view, as well as children’s estimated viewing rates. Analyses also uncover multiple dimensions within the full set of beliefs, which explain more variance in mothers’ attitudes and intentions and children’s viewing than the uni-dimensional index. The theoretical and practical implications of the findings are discussed. PMID:25431537

CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation.

Science.gov (United States)

Nikulova, Anna A; Favorov, Alexander V; Sutormin, Roman A; Makeev, Vsevolod J; Mironov, Andrey A

2012-07-01

Identification of transcriptional regulatory regions and tracing their internal organization are important for understanding the eukaryotic cell machinery. Cis-regulatory modules (CRMs) of higher eukaryotes are believed to possess a regulatory 'grammar', or preferred arrangement of binding sites, that is crucial for proper regulation and thus tends to be evolutionarily conserved. Here, we present a method CORECLUST (COnservative REgulatory CLUster STructure) that predicts CRMs based on a set of positional weight matrices. Given regulatory regions of orthologous and/or co-regulated genes, CORECLUST constructs a CRM model by revealing the conserved rules that describe the relative location of binding sites. The constructed model may be consequently used for the genome-wide prediction of similar CRMs, and thus detection of co-regulated genes, and for the investigation of the regulatory grammar of the system. Compared with related methods, CORECLUST shows better performance at identification of CRMs conferring muscle-specific gene expression in vertebrates and early-developmental CRMs in Drosophila.

Protein (Viridiplantae): 203761 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 017 ... 38832:3226 ... 38833:3539 ... 564608:3539 predicted protein Micromonas pusilla CCMP1545 MHPPLTLENHPLCKDVVIALKRCHRDNPWARAWGACNEQKWALDDCLKKQKLFKFRANHAKAKAQQDRLRRRVEKYGHATTNGQFKG

Analytical solutions for prediction of the ignition time of wood particles based on a time and space integral method

NARCIS (Netherlands)

Haseli, Y.; Oijen, van J.A.; Goey, de L.P.H.

2012-01-01

The main idea of this paper is to establish a simple approach for prediction of the ignition time of a wood particle assuming that the thermo-physical properties remain constant and ignition takes place at a characteristic ignition temperature. Using a time and space integral method, explicit

A GIS-derived integrated moisture index to predict forest composition and productivity of Ohio forests (U.S.A.)

Science.gov (United States)

Louis R. Iverson; Martin E. Dale; Charles T. Scott; Anantha Prasad; Anantha Prasad

1997-01-01

A geographic information system (GIS) approach was used in conjunction with forest-plot data to develop an integrated moisture index (IMI), which was then used to predict forest productivity (site index) and species composition for forests in Ohio. In this region, typical of eastern hardwoods across the Midwest and southern Appalachians, topographic aspect and position...

Protein (Viridiplantae): 788948 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 832:429 ... 296587:152 ... predicted protein Micromonas sp. RCC299 MRARGKVEVELQGVQRLSARCKECGGSQICEHGRQRFHCRECGGSGICEHGRGRHRCKECG...GSQICEHGRVRSQCKECGGSGICEHGRRRSLCKECGGSGICEHGRQRYSCKECGGAGICEHGRERYSCKECRAAKAGTFPDVDVEVGVTEDA...SSKGAKRKRAPYTKGPCEHGVKYRSQCKVCSACPHGRQRNKCKECGGASICVHGRERNKCKECGGASICEHGRQRSHCKECGGASICVHARERNKCKECG...GASFCEHGRQRRYCKECGGSQICEHGRVRRLCKECGGSGICEHGRQRPQCKECGGSQICEHGRQRYSCKECRAAKAKQR

Protein (Viridiplantae): 788912 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 8832:429 ... 296587:152 ... predicted protein Micromonas sp. RCC299 MLPDVDVEVGVTEDASSKGTKRKRAPKTKGPCEHGVKRRSNCKVCSACPHGKWRYWCKECG...GAGICEHGRERRRCKECGGASICEHGRQRRYCKECGGGSICEHGRVRYYCKECGGSGICEHGRDRSRCKECGGGSICEHGRERYYCKECGGSQICEHGRRRSECKECG...GSQICEHGRRRSECKECGGSAICEHGRQRYYCKECGGSGICEHGRDRSRCKECGGGSICEHGRERYYCKECG...GAGICEHGRIRSTCKECGGSRICEHDRQRHTCKDCGGSQICEHGRVRSKCKECGGSGICEHGRHRQYCKECGGGSFCEHGRQRRKCKECGGSQI

Protein (Viridiplantae): 788908 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 8832:429 ... 296587:152 ... predicted protein Micromonas sp. RCC299 MPAIWNVSGPLPDVDVEVGVTEDASSKGTKRKRAPPTKGPCEHG...VKPRSKCKVCSACPHGKRRSECKECGGSQICEHGRRRTQCKECGGSQICEHGRVRSTCKECGGSGLCEHGRERSRCKECGGPGICEHGRVRSRCKECGGSQICEHGRQRSKCKECG...GGSICEHGRIRSTCKECGGSQICEHGRERSKCKECGGGAICEHGRIRSTCKECGGGAICEHGRERHRCKECGGSGICEHGRRRSQCKECG...GSAICEHGRHRQYCKECGGGSICEHGRIRSTCKECGGGAICEHGRQRHRCKECGGASFCEHGRQRSRCKECGGSGICEHGRRRSTCKECRAAN

Protein (Viridiplantae): 746637 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 218 ... 38832:274 ... 38833:414 ... 564608:414 predicted protein Micromonas pusilla CCMP1545 MAQLPSYEVDDGEDSMPGAPGEGPMTDSMQGPPVEVPTSDSM...PGAPGEVPTMDSMHGPPVEVPTMDSMHGAPVEVPMMDSMPGAPVEVPTMDSMQGPPVEVPTMDSMQGAPGEGPMTDSMHGAPGEGPTMDSMNSGNPTKCVVPDWCSTYPPEMQKSKPECQCPDDSHP

Individualized prediction of schizophrenia based on the whole-brain pattern of altered white matter tract integrity.

Science.gov (United States)

Chen, Yu-Jen; Liu, Chih-Min; Hsu, Yung-Chin; Lo, Yu-Chun; Hwang, Tzung-Jeng; Hwu, Hai-Gwo; Lin, Yi-Tin; Tseng, Wen-Yih Isaac

2018-01-01

A schizophrenia diagnosis relies on characteristic symptoms identified by trained physicians, and is thus prone to subjectivity. This study developed a procedure for the individualized prediction of schizophrenia based on whole-brain patterns of altered white matter tract integrity. The study comprised training (108 patients and 144 controls) and testing (60 patients and 60 controls) groups. Male and female participants were comparable in each group and were analyzed separately. All participants underwent diffusion spectrum imaging of the head, and the data were analyzed using the tract-based automatic analysis method to generate a standardized two-dimensional array of white matter tract integrity, called the connectogram. Unique patterns in the connectogram that most accurately identified schizophrenia were systematically reviewed in the training group. Then, the diagnostic performance of the patterns was individually verified in the testing group by using receiver-operating characteristic curve analysis. The performance was high in men (accuracy = 0.85) and satisfactory in women (accuracy = 0.75). In men, the pattern was located in discrete fiber tracts, as has been consistently reported in the literature; by contrast, the pattern was widespread over all tracts in women. These distinct patterns suggest that there is a higher variability in the microstructural alterations in female patients than in male patients. The individualized prediction of schizophrenia is feasible based on the different whole-brain patterns of tract integrity. The optimal masks and their corresponding regions in the fiber tracts could serve as potential imaging biomarkers for schizophrenia. Hum Brain Mapp 39:575-587, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A Distributed Model Predictive Control approach for the integration of flexible loads, storage and renewables

DEFF Research Database (Denmark)

Ferrarini, Luca; Mantovani, Giancarlo; Costanzo, Giuseppe Tommaso

2014-01-01

This paper presents an innovative solution based on distributed model predictive controllers to integrate the control and management of energy consumption, energy storage, PV and wind generation at customer side. The overall goal is to enable an advanced prosumer to autoproduce part of the energy...... he needs with renewable sources and, at the same time, to optimally exploit the thermal and electrical storages, to trade off its comfort requirements with different pricing schemes (including real-time pricing), and apply optimal control techniques rather than sub-optimal heuristics....

Protein (Viridiplantae): 780231 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 401 ... 38832:1362 ... 38833:877 ... 564608:877 predicted protein Micromonas pusilla CCMP1545 MQDSMHDTMHDSIQDSMHDSIQDSMQDSM...AKEEEEPAEPPAKEEEAHAEPPAKEEEAHAEPPAKEEDYAEPPAKEEDYAEPPAKEEAHSMDSMDSMDSMDSMDSMDSMHSMDSMDSMDSMDSMHSMDSMDSMDSM...DSMHSMDSMDSMDSMDSMDSMDSMHSMDTSIDAVDAAANVTDAADTAGAAANVTDAADTAGAAAEEKPPENASVDSLDSLLDG

Predicting 2D target velocity cannot help 2D motion integration for smooth pursuit initiation.

Science.gov (United States)

Montagnini, Anna; Spering, Miriam; Masson, Guillaume S

2006-12-01

Smooth pursuit eye movements reflect the temporal dynamics of bidimensional (2D) visual motion integration. When tracking a single, tilted line, initial pursuit direction is biased toward unidimensional (1D) edge motion signals, which are orthogonal to the line orientation. Over 200 ms, tracking direction is slowly corrected to finally match the 2D object motion during steady-state pursuit. We now show that repetition of line orientation and/or motion direction does not eliminate the transient tracking direction error nor change the time course of pursuit correction. Nonetheless, multiple successive presentations of a single orientation/direction condition elicit robust anticipatory pursuit eye movements that always go in the 2D object motion direction not the 1D edge motion direction. These results demonstrate that predictive signals about target motion cannot be used for an efficient integration of ambiguous velocity signals at pursuit initiation.

Protein (Viridiplantae): 832567 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available NYNSMNASIEIKQQESCQTNINHESCMFSKCMGGMQRFAIPPLPSFEVEQLNVVQGSRHCLSPHFQNSLVTFISYQKEKES... ... 1003877:124 ... 3655:124 ... 3656:1142 ... PREDICTED: transcription factor bHLH143-like Cucumis melo MVGTDTWQLH

Protein (Viridiplantae): 128519 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 9:7 3650:7 ... 1003877:7 ... 3655:7 ... 3656:1095 ... PREDICTED: pectinesterase inhibitor-like Cucumis melo MANNSCLV...IVSLIGVLLFTIILNVASSNYVISTICSKSSNPPFCSSVLKSSGTTYLKGLAVYTLNLAHTNASKSLTLARSLATTTTNPQ

Evolution and functional insights of different ancestral orthologous clades of chitin synthase genes in the fungal tree of life

Directory of Open Access Journals (Sweden)

Mu eLi

2016-02-01

Full Text Available Chitin synthases (CHSs are key enzymes in the biosynthesis of chitin, an important structural component of fungal cell walls that can trigger innate immune responses in host plants and animals. Members of CHS gene family perform various functions in fungal cellular processes. Previous studies focused primarily on classifying diverse CHSs into different classes, regardless of their functional diversification, or on characterizing their functions in individual fungal species. A complete and systematic comparative analysis of CHS genes based on their orthologous relationships will be valuable for elucidating the evolution and functions of different CHS genes in fungi. Here, we identified and compared members of the CHS gene family across the fungal tree of life, including 18 divergent fungal lineages. Phylogenetic analysis revealed that the fungal CHS gene family is comprised of at least 10 ancestral orthologous clades, which have undergone multiple independent duplications and losses in different fungal lineages during evolution. Interestingly, one of these CHS clades (class III was expanded in plant or animal pathogenic fungi belonging to different fungal lineages. Two clades (classes VIb and VIc identified for the first time in this study occurred mainly in plant pathogenic fungi from Sordariomycetes and Dothideomycetes. Moreover, members of classes III and VIb were specifically up-regulated during plant infection, suggesting important roles in pathogenesis. In addition, CHS-associated networks conserved among plant pathogenic fungi are involved in various biological processes, including sexual reproduction and plant infection. We also identified specificity-determining sites, many of which are located at or adjacent to important structural and functional sites that are potentially responsible for functional divergence of different CHS classes. Overall, our results provide new insights into the evolution and function of members of CHS gene

Predict-first experimental analysis using automated and integrated magnetohydrodynamic modeling

Science.gov (United States)

Lyons, B. C.; Paz-Soldan, C.; Meneghini, O.; Lao, L. L.; Weisberg, D. B.; Belli, E. A.; Evans, T. E.; Ferraro, N. M.; Snyder, P. B.

2018-05-01

An integrated-modeling workflow has been developed for the purpose of performing predict-first analysis of transient-stability experiments. Starting from an existing equilibrium reconstruction from a past experiment, the workflow couples together the EFIT Grad-Shafranov solver [L. Lao et al., Fusion Sci. Technol. 48, 968 (2005)], the EPED model for the pedestal structure [P. B. Snyder et al., Phys. Plasmas 16, 056118 (2009)], and the NEO drift-kinetic-equation solver [E. A. Belli and J. Candy, Plasma Phys. Controlled Fusion 54, 015015 (2012)] (for bootstrap current calculations) in order to generate equilibria with self-consistent pedestal structures as the plasma shape and various scalar parameters (e.g., normalized β, pedestal density, and edge safety factor [q95]) are changed. These equilibria are then analyzed using automated M3D-C1 extended-magnetohydrodynamic modeling [S. C. Jardin et al., Comput. Sci. Discovery 5, 014002 (2012)] to compute the plasma response to three-dimensional magnetic perturbations. This workflow was created in conjunction with a DIII-D experiment examining the effect of triangularity on the 3D plasma response. Several versions of the workflow were developed, and the initial ones were used to help guide experimental planning (e.g., determining the plasma current necessary to maintain the constant edge safety factor in various shapes). Subsequent validation with the experimental results was then used to revise the workflow, ultimately resulting in the complete model presented here. We show that quantitative agreement was achieved between the M3D-C1 plasma response calculated for equilibria generated by the final workflow and equilibria reconstructed from experimental data. A comparison of results from earlier workflows is used to show the importance of properly matching certain experimental parameters in the generated equilibria, including the normalized β, pedestal density, and q95. On the other hand, the details of the pedestal

Overexpression of DOSOC1, an ortholog of Arabidopsis SOC1, promotes flowering in the orchid Dendrobium Chao Parya Smile.

Science.gov (United States)

Ding, Lihua; Wang, Yanwen; Yu, Hao

2013-04-01

SUPPRESSOR OF OVEREXPRESSION OF CONSTANS1 (SOC1) encodes a MADS-box protein that plays an essential role in integrating multiple flowering signals to regulate the transition from vegetative to reproductive development in the model plant Arabidopsis. Although SOC1-like genes have been isolated in various angiosperms, its orthologs in Orchidaceae, one of the largest families of flowering plants, are so far unknown. To investigate the regulatory mechanisms of flowering time control in orchids, we isolated a SOC1-like gene, DOSOC1, from Dendrobium Chao Praya Smile. DOSOC1 was highly expressed in reproductive organs, including inflorescence apices, pedicels, floral buds and open flowers. Its expression significantly increased in whole plantlets during the transition from vegetative to reproductive development, which usually occurred after 8 weeks of culture in Dendrobium Chao Praya Smile. In the shoot apex at the floral transitional stage, DOSOC1 was particularly expressed in emerging floral meristems. Overexpression of DOSOC1 in wild-type Arabidopsis plants resulted in early flowering, which was coupled with the up-regulation of two other flowering promoters, AGAMOUS-LIKE 24 and LEAFY. In addition, overexpression of DOSOC1 was able partially to complement the late-flowering phenotype of Arabidopsis soc1-2 loss-of-function mutants. Furthermore, we successfully created seven 35S:DOSOC1 transgenic Dendrobium orchid lines, which consistently exhibited earlier flowering than wild-type orchids. Our results suggest that SOC1-like genes play an evolutionarily conserved role in promoting flowering in the Orchidaceae family, and that DOSOC1 isolated from Dendrobium Chao Praya Smile could serve as an important target for genetic manipulation of flowering time in orchids.

Protein (Viridiplantae): 786990 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 79506 Solanum tuberosum MEETSTSSNNAKAKARVRVCITRKKTLKDKRAKLYIIRRCLYMLLCWKERAEFCNVGNRESTA ...3993 4070:3993 ... 424551:3993 ... 424574:3993 ... 4107:3993 ... 4113:2476 ... PREDICTED: uncharacterized protein LOC1025

Model Predictive Control of Grid Connected Modular Multilevel Converter for Integration of Photovoltaic Power Systems

DEFF Research Database (Denmark)

Hajizadeh, Amin; Shahirinia, Amir

2017-01-01

Investigation of an advanced control structure for integration of Photovoltaic Power Systems through Grid Connected-Modular Multilevel Converter (GC-MMC) is proposed in this paper. To achieve this goal, a non-linear model of MMC regarding considering of negative and positive sequence components has...... been presented. Then, due to existence of unbalance voltage faults in distribution grid, non-linarites and uncertainties in model, model predictive controller which is developed for GC-MMC. They are implemented based upon positive and negative components of voltage and current to mitigate the power...

ChlamyCyc: an integrative systems biology database and web-portal for Chlamydomonas reinhardtii

Directory of Open Access Journals (Sweden)

Kempa Stefan

2009-05-01

Full Text Available Abstract Background The unicellular green alga Chlamydomonas reinhardtii is an important eukaryotic model organism for the study of photosynthesis and plant growth. In the era of modern high-throughput technologies there is an imperative need to integrate large-scale data sets from high-throughput experimental techniques using computational methods and database resources to provide comprehensive information about the molecular and cellular organization of a single organism. Results In the framework of the German Systems Biology initiative GoFORSYS, a pathway database and web-portal for Chlamydomonas (ChlamyCyc was established, which currently features about 250 metabolic pathways with associated genes, enzymes, and compound information. ChlamyCyc was assembled using an integrative approach combining the recently published genome sequence, bioinformatics methods, and experimental data from metabolomics and proteomics experiments. We analyzed and integrated a combination of primary and secondary database resources, such as existing genome annotations from JGI, EST collections, orthology information, and MapMan classification. Conclusion ChlamyCyc provides a curated and integrated systems biology repository that will enable and assist in systematic studies of fundamental cellular processes in Chlamydomonas. The ChlamyCyc database and web-portal is freely available under http://chlamycyc.mpimp-golm.mpg.de.

Protein (Viridiplantae): 850873 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available OC100796589 Glycine max MEETSWEQRVQALTHILTSPTTTPSLHSQFFIATQIPCYLNWDYPPFLCSSNPQLLK...803:12853 ... 3814:12853 ... 163735:5410 ... 3846:8024 1462606:8024 3847:8024 ... PREDICTED: uncharacterized protein L

Protein (Viridiplantae): 816751 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 0:266 ... 424551:266 ... 424574:266 ... 4107:266 ... 4113:1088 ... PREDICTED: proteoglycan 4-like Solanum tuberosum MPTLSKLEIPNSPNPET...PGSPKSVTPSISKPKTPSFSKPETPSFSTPETPSFSRPETPSFSKPETPSSSKPEAPSSLTPETPSFSKPETLSFSKPET...PSSPKLEIRNSAKPETPSFSKPETPSFSKPKTPSSPKPETPSFSKPKTPSSPNLKTPTPSSPNSQTPSFSNSRKPEAPTFLKPETPSSPKPKTPSFSTPETPTFSKPET...PNFSKSETPSFSKPETPSSFKPETHSFLKSETPSSPKPETPSSPKFEPPSSPKPETPSSPKTENPSSPNTETPNFSKPETPSSPKPNTPSFPKLDTPSFSNPKTPSYETPSFPKFETTSSQKPETPNSPKFGTPSLPKSKIPSDPIFETISFSKPETSNSSKPKIPTTP

Protein (Viridiplantae): 128879 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 5:248 3803:248 ... 3814:248 ... 163722:3689 ... 3826:3689 ... 3827:3689 ... PREDICTED: uncharacterized protein LOC101515541 Cicer arietinum MNSSTI...CSLFLGLILISQSANAKGHGGGLVVTICKGATDRAACENILGSNSEISHAKSFSQL

An integrative typology of personality assessment for aggression: implications for predicting counterproductive workplace behavior.

Science.gov (United States)

Bing, Mark N; Stewart, Susan M; Davison, H Kristl; Green, Philip D; McIntyre, Michael D; James, Lawrence R

2007-05-01

This study presents an integrative typology of personality assessment for aggression. In this typology, self-report and conditional reasoning (L. R. James, 1998) methodologies are used to assess 2 separate, yet often congruent, components of aggressive personalities. Specifically, self-report is used to assess explicit components of aggressive tendencies, such as self-perceived aggression, whereas conditional reasoning is used to assess implicit components, in particular, the unconscious biases in reasoning that are used to justify aggressive acts. These 2 separate components are then integrated to form a new theoretical typology of personality assessment for aggression. Empirical tests of the typology were subsequently conducted using data gathered across 3 samples in laboratory and field settings and reveal that explicit and implicit components of aggression can interact in the prediction of counterproductive, deviant, and prosocial behaviors. These empirical tests also reveal that when either the self-report or conditional reasoning methodology is used in isolation, the resulting assessment of aggression may be incomplete. Implications for personnel selection, team composition, and executive coaching are discussed. 2007 APA, all rights reserved

Predicting freshwater habitat integrity using land-use surrogates

African Journals Online (AJOL)

2007-04-02

Apr 2, 2007 ... Quantification of potential surrogates of freshwater habitat integrity. We chose a series of land-use variables that might be suitable predictors for assessing freshwater habitat integrity from the land cover map (CSIR 2005) and added separate GIS surfaces for human population density and the distribution of ...

Protein (Viridiplantae): 175805 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 745:703 ... 171637:1864 ... 721813:1696 ... 3749:1696 ... 3750:1696 ... PREDICTED: cytochrome P450 87A3-like Malus domest...ica MWSLVGLSFLVSLVVIFITPWIXKWRYPKCNGALPPGSMGLPFIGETLSLIIPSYSHDLLPFIKKRVRRYGPIFRTS

Protein (Viridiplantae): 175804 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 745:703 ... 171637:1864 ... 721813:1696 ... 3749:1696 ... 3750:1696 ... PREDICTED: cytochrome P450 87A3-like Malus domest...ica MWSLVGLSFLVSLVVIFITPWIXKWRYPKCNGALPPGSMGLPFIGETLSLIIPSYSHDLLPFIKKRVRRYGPIFRTS

Protein (Viridiplantae): 94306 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 47368:3137 ... 147385:3137 ... 15367:3137 ... 15368:3137 ... PREDICTED: bifunctional monodehydroascorbate reductase and carbonic anhydrase nect...arin-3-like Brachypodium distachyon MATRVGNAVVFALLLCARFL

Global analysis of small molecule binding to related protein targets.

Directory of Open Access Journals (Sweden)

Felix A Kruger

2012-01-01

Full Text Available We report on the integration of pharmacological data and homology information for a large scale analysis of small molecule binding to related targets. Differences in small molecule binding have been assessed for curated pairs of human to rat orthologs and also for recently diverged human paralogs. Our analysis shows that in general, small molecule binding is conserved for pairs of human to rat orthologs. Using statistical tests, we identified a small number of cases where small molecule binding is different between human and rat, some of which had previously been reported in the literature. Knowledge of species specific pharmacology can be advantageous for drug discovery, where rats are frequently used as a model system. For human paralogs, we demonstrate a global correlation between sequence identity and the binding of small molecules with equivalent affinity. Our findings provide an initial general model relating small molecule binding and sequence divergence, containing the foundations for a general model to anticipate and predict within-target-family selectivity.

Novel CNS drug discovery and development approach: model-based integration to predict neuro-pharmacokinetics and pharmacodynamics.

Science.gov (United States)

de Lange, Elizabeth C M; van den Brink, Willem; Yamamoto, Yumi; de Witte, Wilhelmus E A; Wong, Yin Cheong

2017-12-01

CNS drug development has been hampered by inadequate consideration of CNS pharmacokinetic (PK), pharmacodynamics (PD) and disease complexity (reductionist approach). Improvement is required via integrative model-based approaches. Areas covered: The authors summarize factors that have played a role in the high attrition rate of CNS compounds. Recent advances in CNS research and drug discovery are presented, especially with regard to assessment of relevant neuro-PK parameters. Suggestions for further improvements are also discussed. Expert opinion: Understanding time- and condition dependent interrelationships between neuro-PK and neuro-PD processes is key to predictions in different conditions. As a first screen, it is suggested to use in silico/in vitro derived molecular properties of candidate compounds and predict concentration-time profiles of compounds in multiple compartments of the human CNS, using time-course based physiology-based (PB) PK models. Then, for selected compounds, one can include in vitro drug-target binding kinetics to predict target occupancy (TO)-time profiles in humans. This will improve neuro-PD prediction. Furthermore, a pharmaco-omics approach is suggested, providing multilevel and paralleled data on systems processes from individuals in a systems-wide manner. Thus, clinical trials will be better informed, using fewer animals, while also, needing fewer individuals and samples per individual for proof of concept in humans.

Protein (Viridiplantae): 41039 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available s mume MSKSKGRFQLPSSSSVISCMFSLSKQKQEESLDDDTQTQKDEWKKTLIGKLGNVHQREYLSHYGRGRKGKIRGE...403 3745:2403 ... 171637:3833 721805:8 ... 3754:8 ... 102107:3050 ... PREDICTED: UPF0481 protein At3g47200-like Prunu

Integration of Attributes from Non-Linear Characterization of Cardiovascular Time-Series for Prediction of Defibrillation Outcomes.

Directory of Open Access Journals (Sweden)

Sharad Shandilya

Full Text Available The timing of defibrillation is mostly at arbitrary intervals during cardio-pulmonary resuscitation (CPR, rather than during intervals when the out-of-hospital cardiac arrest (OOH-CA patient is physiologically primed for successful countershock. Interruptions to CPR may negatively impact defibrillation success. Multiple defibrillations can be associated with decreased post-resuscitation myocardial function. We hypothesize that a more complete picture of the cardiovascular system can be gained through non-linear dynamics and integration of multiple physiologic measures from biomedical signals.Retrospective analysis of 153 anonymized OOH-CA patients who received at least one defibrillation for ventricular fibrillation (VF was undertaken. A machine learning model, termed Multiple Domain Integrative (MDI model, was developed to predict defibrillation success. We explore the rationale for non-linear dynamics and statistically validate heuristics involved in feature extraction for model development. Performance of MDI is then compared to the amplitude spectrum area (AMSA technique.358 defibrillations were evaluated (218 unsuccessful and 140 successful. Non-linear properties (Lyapunov exponent > 0 of the ECG signals indicate a chaotic nature and validate the use of novel non-linear dynamic methods for feature extraction. Classification using MDI yielded ROC-AUC of 83.2% and accuracy of 78.8%, for the model built with ECG data only. Utilizing 10-fold cross-validation, at 80% specificity level, MDI (74% sensitivity outperformed AMSA (53.6% sensitivity. At 90% specificity level, MDI had 68.4% sensitivity while AMSA had 43.3% sensitivity. Integrating available end-tidal carbon dioxide features into MDI, for the available 48 defibrillations, boosted ROC-AUC to 93.8% and accuracy to 83.3% at 80% sensitivity.At clinically relevant sensitivity thresholds, the MDI provides improved performance as compared to AMSA, yielding fewer unsuccessful defibrillations

Integrated genetic and epigenetic prediction of coronary heart disease in the Framingham Heart Study.

Directory of Open Access Journals (Sweden)

Meeshanthini V Dogan

Full Text Available An improved method for detecting coronary heart disease (CHD could have substantial clinical impact. Building on the idea that systemic effects of CHD risk factors are a conglomeration of genetic and environmental factors, we use machine learning techniques and integrate genetic, epigenetic and phenotype data from the Framingham Heart Study to build and test a Random Forest classification model for symptomatic CHD. Our classifier was trained on n = 1,545 individuals and consisted of four DNA methylation sites, two SNPs, age and gender. The methylation sites and SNPs were selected during the training phase. The final trained model was then tested on n = 142 individuals. The test data comprised of individuals removed based on relatedness to those in the training dataset. This integrated classifier was capable of classifying symptomatic CHD status of those in the test set with an accuracy, sensitivity and specificity of 78%, 0.75 and 0.80, respectively. In contrast, a model using only conventional CHD risk factors as predictors had an accuracy and sensitivity of only 65% and 0.42, respectively, but with a specificity of 0.89 in the test set. Regression analyses of the methylation signatures illustrate our ability to map these signatures to known risk factors in CHD pathogenesis. These results demonstrate the capability of an integrated approach to effectively model symptomatic CHD status. These results also suggest that future studies of biomaterial collected from longitudinally informative cohorts that are specifically characterized for cardiac disease at follow-up could lead to the introduction of sensitive, readily employable integrated genetic-epigenetic algorithms for predicting onset of future symptomatic CHD.

More Gamma More Predictions: Gamma-Synchronization as a Key Mechanism for Efficient Integration of Classical Receptive Field Inputs with Surround Predictions

Science.gov (United States)

Vinck, Martin; Bosman, Conrado A.

2016-01-01

During visual stimulation, neurons in visual cortex often exhibit rhythmic and synchronous firing in the gamma-frequency (30–90 Hz) band. Whether this phenomenon plays a functional role during visual processing is not fully clear and remains heavily debated. In this article, we explore the function of gamma-synchronization in the context of predictive and efficient coding theories. These theories hold that sensory neurons utilize the statistical regularities in the natural world in order to improve the efficiency of the neural code, and to optimize the inference of the stimulus causes of the sensory data. In visual cortex, this relies on the integration of classical receptive field (CRF) data with predictions from the surround. Here we outline two main hypotheses about gamma-synchronization in visual cortex. First, we hypothesize that the precision of gamma-synchronization reflects the extent to which CRF data can be accurately predicted by the surround. Second, we hypothesize that different cortical columns synchronize to the extent that they accurately predict each other’s CRF visual input. We argue that these two hypotheses can account for a large number of empirical observations made on the stimulus dependencies of gamma-synchronization. Furthermore, we show that they are consistent with the known laminar dependencies of gamma-synchronization and the spatial profile of intercolumnar gamma-synchronization, as well as the dependence of gamma-synchronization on experience and development. Based on our two main hypotheses, we outline two additional hypotheses. First, we hypothesize that the precision of gamma-synchronization shows, in general, a negative dependence on RF size. In support, we review evidence showing that gamma-synchronization decreases in strength along the visual hierarchy, and tends to be more prominent in species with small V1 RFs. Second, we hypothesize that gamma-synchronized network dynamics facilitate the emergence of spiking output that

Context mining and integration into predictive web analytics

NARCIS (Netherlands)

Kiseleva, Y.

2013-01-01

Predictive Web Analytics is aimed at understanding behavioural patterns of users of various web-based applications: e-commerce, ubiquitous and mobile computing, and computational advertising. Within these applications business decisions often rely on two types of predictions: an overall or

Ortholog Alleles at Xa3/Xa26 Locus Confer Conserved Race-Specific Resistance against Xanthomonas oryzae in Rice

Institute of Scientific and Technical Information of China (English)

Hong-Jing Li; Xiang-Hua Li; Jing-Hua Xiao; Rod A. Wing; Shi-Ping Wang

2012-01-01

The rice disease resistance (R) gene Xa3/Xa26 (having also been named Xa3 and Xa26) against Xanthomonas oryzae pv.oryzae (Xoo),which causes bacterial blight disease,belongs to a multiple gene family clustered in chromosome 11 and is from an AA genome rice cultivar (Oryza sativa L.).This family encodes leucine-rich repeat (LRR) receptor kinasetype proteins.Here,we show that the orthologs (alleles) of Xa3/Xa26,Xa3/Xa26-2,and Xa3/Xa26-3,from wild Oryza species O.officinalis (CC genome) and O.minuta (BBCC genome),respectively,were also R genes against Xoo.Xa3/Xa26-2 and Xa3/Xa26-3 conferred resistance to 16 of the 18 Xoo strains examined.Comparative sequence analysis of the Xa3/Xa26 families in the two wild Oryza species showed that Xa3/Xa26-3 appeared to have originated from the CC genome of O.minuta.The predicted proteins encoded by Xa3/Xa26,Xa3/Xa26-2,and Xa3/Xa26-3 share 91-99％ sequence identity and 94-99％ sequence similarity.Transgenic plants carrying a single copy of Xa3/Xa26,Xa3/Xa26-2,or Xa3/Xa26-3,in the same genetic background,showed a similar resistance spectrum to a set of Xoo strains,although plants carrying Xa3/Xa26-2 or Xa3/Xa26-3 showed lower resistance levels than the plants carrying Xa3/Xa26.These results suggest that the Xa3/Xa26 locus predates the speciation of A and C genome,which is approximately 7.5 million years ago.Thus,the resistance specificity of this locus has been conserved for a long time.

The use of semantic similarity measures for optimally integrating heterogeneous Gene Ontology data from large scale annotation pipelines

Directory of Open Access Journals (Sweden)

Gaston K Mazandu

2014-08-01

Full Text Available With the advancement of new high throughput sequencing technologies, there has been an increase in the number of genome sequencing projects worldwide, which has yielded complete genome sequences of human, animals and plants. Subsequently, several labs have focused on genome annotation, consisting of assigning functions to gene products, mostly using Gene Ontology (GO terms. As a consequence, there is an increased heterogeneity in annotations across genomes due to different approaches used by different pipelines to infer these annotations and also due to the nature of the GO structure itself. This makes a curator's task difficult, even if they adhere to the established guidelines for assessing these protein annotations. Here we develop a genome-scale approach for integrating GO annotations from different pipelines using semantic similarity measures. We used this approach to identify inconsistencies and similarities in functional annotations between orthologs of human and Drosophila melanogaster, to assess the quality of GO annotations derived from InterPro2GO mappings compared to manually annotated GO annotations for the Drosophila melanogaster proteome from a FlyBase dataset and human, and to filter GO annotation data for these proteomes. Results obtained indicate that an efficient integration of GO annotations eliminates redundancy up to 27.08 and 22.32% in the Drosophila melanogaster and human GO annotation datasets, respectively. Furthermore, we identified lack of and missing annotations for some orthologs, and annotation mismatches between InterPro2GO and manual pipelines in these two proteomes, thus requiring further curation. This simplifies and facilitates tasks of curators in assessing protein annotations, reduces redundancy and eliminates inconsistencies in large annotation datasets for ease of comparative functional genomics.

Following a drop of water from the cloud, throughout the sewer system, into the receiving water - Model predictive control of integrated sewer-wastewater treatment systems

DEFF Research Database (Denmark)

Mikkelsen, Peter Steen; Vezzaro, Luca; Sharma, Anitha Kumari

This article presents selected examples of model-based prediction and control of integrated sewer-wastewater treatment systems, developed within the framework of the Storm- and Wastewater Informatics project (SWI). By exploiting all the available on-line information (e.g. radar based rainfall...... of pollutants discharged from treatment plants, etc.). The tools developed in the SWI project include (but are not limited to (i) rainfall nowcasting based on radar measurements, (ii) probabilistic flow forecasting based on data assimilation and stochastic models, (iii) prediction and optimization of wet......-weather performance of wastewater treatment plants, and (iv) integrated control of the different elements of the integrated wastewater systems. Full-scale testing of these tools in different catchment located in Denmark ensure that the developed tools can represent an important step forwards for on-line operation...

Expression conservation within the circadian clock of a monocot: natural variation at barley Ppd-H1 affects circadian expression of flowering time genes, but not clock orthologs.

Science.gov (United States)

Campoli, Chiara; Shtaya, Munqez; Davis, Seth J; von Korff, Maria

2012-06-21

The circadian clock is an endogenous mechanism that coordinates biological processes with daily changes in the environment. In plants, circadian rhythms contribute to both agricultural productivity and evolutionary fitness. In barley, the photoperiod response regulator and flowering-time gene Ppd-H1 is orthologous to the Arabidopsis core-clock gene PRR7. However, relatively little is known about the role of Ppd-H1 and other components of the circadian clock in temperate crop species. In this study, we identified barley clock orthologs and tested the effects of natural genetic variation at Ppd-H1 on diurnal and circadian expression of clock and output genes from the photoperiod-response pathway. Barley clock orthologs HvCCA1, HvGI, HvPRR1, HvPRR37 (Ppd-H1), HvPRR73, HvPRR59 and HvPRR95 showed a high level of sequence similarity and conservation of diurnal and circadian expression patterns, when compared to Arabidopsis. The natural mutation at Ppd-H1 did not affect diurnal or circadian cycling of barley clock genes. However, the Ppd-H1 mutant was found to be arrhythmic under free-running conditions for the photoperiod-response genes HvCO1, HvCO2, and the MADS-box transcription factor and vernalization responsive gene Vrn-H1. We suggest that the described eudicot clock is largely conserved in the monocot barley. However, genetic differentiation within gene families and differences in the function of Ppd-H1 suggest evolutionary modification in the angiosperm clock. Our data indicates that natural variation at Ppd-H1 does not affect the expression level of clock genes, but controls photoperiodic output genes. Circadian control of Vrn-H1 in barley suggests that this vernalization responsive gene is also controlled by the photoperiod-response pathway. Structural and functional characterization of the barley circadian clock will set the basis for future studies of the adaptive significance of the circadian clock in Triticeae species.

Integrating the ICF with positive psychology: Factors predicting role participation for mothers with multiple sclerosis.

Science.gov (United States)

Farber, Ruth S; Kern, Margaret L; Brusilovsky, Eugene

2015-05-01

Being a mother has become a realizable life role for women with disabilities and chronic illnesses, including multiple sclerosis (MS). Identifying psychosocial factors that facilitate participation in important life roles-including motherhood-is essential to help women have fuller lives despite the challenge of their illness. By integrating the International Classification of Functioning, Disability, and Health (ICF) and a positive psychology perspective, this study examined how environmental social factors and positive personal factors contribute to daily role participation and satisfaction with parental participation. One hundred and 11 community-dwelling mothers with MS completed Ryff's Psychological Well-Being Scales, the Medical Outcome Study Social Support Survey, the Short Form-36, and the Parental Participation Scale. Hierarchical regression analyses examined associations between social support and positive personal factors (environmental mastery, self-acceptance, purpose in life) with daily role participation (physical and emotional) and satisfaction with parental participation. One-way ANOVAs tested synergistic combinations of social support and positive personal factors. Social support predicted daily role participation (fewer limitations) and greater satisfaction with parental participation. Positive personal factors contributed additional unique variance. Positive personal factors and social support synergistically predicted better function and greater satisfaction than either alone. Integrating components of the ICF and positive psychology provides a useful model for understanding how mothers with MS can thrive despite challenge or impairment. Both positive personal factors and environmental social factors were important contributors to positive role functioning. Incorporating these paradigms into treatment may help mothers with MS participate more fully in meaningful life roles. (c) 2015 APA, all rights reserved).

Prediction of leisure-time walking: an integration of social cognitive, perceived environmental, and personality factors

Directory of Open Access Journals (Sweden)

Blanchard Chris M

2007-10-01

Full Text Available Abstract Background Walking is the primary focus of population-based physical activity initiatives but a theoretical understanding of this behaviour is still elusive. The purpose of this study was to integrate personality, the perceived environment, and planning into a theory of planned behaviour (TPB framework to predict leisure-time walking. Methods Participants were a random sample (N = 358 of Canadian adults who completed measures of the TPB, planning, perceived neighbourhood environment, and personality at Time 1 and self-reported walking behaviour two months later. Results Analyses using structural equation modelling provided evidence that leisure-time walking is largely predicted by intention (standardized effect = .42 with an additional independent contribution from proximity to neighbourhood retail shops (standardized effect = .18. Intention, in turn, was predicted by attitudes toward walking and perceived behavioural control. Effects of perceived neighbourhood aesthetics and walking infrastructure on walking were mediated through attitudes and intention. Moderated regression analysis showed that the intention-walking relationship was moderated by conscientiousness and proximity to neighbourhood recreation facilities but not planning. Conclusion Overall, walking behaviour is theoretically complex but may best be addressed at a population level by facilitating strong intentions in a receptive environment even though individual differences may persist.

An ortholog of farA of Aspergillus nidulans is implicated in the transcriptional activation of genes involved in fatty acid utilization in the yeast Yarrowia lipolytica

International Nuclear Information System (INIS)

Poopanitpan, Napapol; Kobayashi, Satoshi; Fukuda, Ryouichi; Horiuchi, Hiroyuki; Ohta, Akinori

2010-01-01

Research highlights: → POR1 is a Yarrowia lipolytica ortholog of farA involved in fatty acid response in A. nidulans. → Deletion of POR1 caused growth defects on fatty acids. → Δpor1 strain exhibited defects in the induction of genes involved in fatty acid utilization. -- Abstract: The yeast Yarrowia lipolytica effectively utilizes hydrophobic substrates such as fatty acids and n-alkanes. To identify a gene(s) regulating fatty acid utilization in Y. lipolytica, we first studied homologous genes to OAF1 and PIP2 of Saccharomyces cerevisiae, but their disruption did not change growth on oleic acid at all. We next characterized a Y. lipolytica gene, POR1 (primary oleate regulator 1), an ortholog of farA encoding a transcriptional activator that regulates fatty acid utilization in Aspergillus nidulans. The deletion mutant of POR1 was defective in the growth on various fatty acids, but not on glucose, glycerol, or n-hexadecane. It exhibited slight defect on n-decane. The transcriptional induction of genes involved in β-oxidation and peroxisome proliferation by oleate was distinctly diminished in the Δpor1 strains. These data suggest that POR1 encodes a transcriptional activator widely regulating fatty acid metabolism in Y. lipolytica.

From a single encapsulated detector to the spectrometer for INTEGRAL satellite: predicting the peak-to-total ratio at high gamma-energies

OpenAIRE

Kshetri, Ritesh

2012-01-01

In two recent papers (R. Kshetri, JINST 2012 7 P04008; ibid., P07006), a probabilistic formalism was introduced to predict the response of encapsulated type composite germanium detectors like the SPI (spectrometer for INTEGRAL satellite). Predictions for the peak-to-total and peak-to-background ratios are given at 1.3 MeV for the addback mode of operation. The application of the formalism to clover germanium detector is discussed in two separate papers (R. Kshetri, JINST 2012 7 P07008; ibid.,...

Protein (Viridiplantae): 356536840 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 24:2780 3398:2780 71240:414 91827:414 71275:1623 91835:562 72025:981 3803:981 3814:981 163735:1026 3846:1026 3847:1026 PREDICTED: pat...ellin-4-like Glycine max MNNTNECCCNDENGKIVVGVPLVFNFFDKNTNNIEKSLKVQLEKKNQLEDHDCDQEDD

Protein (Viridiplantae): 356543245 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 24:2780 3398:2780 71240:414 91827:414 71275:1623 91835:562 72025:981 3803:981 3814:981 163735:1026 3846:1026 3847:1026 PREDICTED: pat...ellin-3-like Glycine max MAQNDSNPTPPPEPHVAAEPITEDLVQDKEEEDDSSKIVIPVPESESLSLKEDSNRVS

Protein (Viridiplantae): 356506815 [PGDBj - Ortholog DB

Lifescience Database Archive (English)

Full Text Available 24:2780 3398:2780 71240:414 91827:414 71275:1623 91835:562 72025:981 3803:981 3814:981 163735:1026 3846:1026 3847:1026 PREDICTED: pat...ellin-6-like Glycine max MMDTTSSPLSLQTQKTTFQELPEASPKPYKKGIVATLMGGGLFKEDNYFVSLLRSSEK

X-ray crystallographic studies of the extracellular domain of the first plant ATP receptor, DORN1, and the orthologous protein from Camelina sativa

Energy Technology Data Exchange (ETDEWEB)

Li, Zhijie; Chakraborty, Sayan; Xu, Guozhou (NCSU)

2016-10-26

Does not respond to nucleotides 1 (DORN1) has recently been identified as the first membrane-integral plant ATP receptor, which is required for ATP-induced calcium response, mitogen-activated protein kinase activation and defense responses inArabidopsis thaliana. In order to understand DORN1-mediated ATP sensing and signal transduction, crystallization and preliminary X-ray studies were conducted on the extracellular domain of DORN1 (atDORN1-ECD) and that of an orthologous protein,Camelina sativalectin receptor kinase I.9 (csLecRK-I.9-ECD or csI.9-ECD). A variety of deglycosylation strategies were employed to optimize the glycosylated recombinant atDORN1-ECD for crystallization. In addition, the glycosylated csI.9-ECD protein was crystallized at 291 K. X-ray diffraction data were collected at 4.6 Å resolution from a single crystal. The crystal belonged to space groupC222 orC222₁, with unit-cell parametersa= 94.7,b= 191.5,c= 302.8 Å. These preliminary studies have laid the foundation for structural determination of the DORN1 and I.9 receptor proteins, which will lead to a better understanding of the perception and function of extracellular ATP in plants.

Integrating water exclusion theory into βcontacts to predict binding free energy changes and binding hot spots

Science.gov (United States)

2014-01-01

Background Binding free energy and binding hot spots at protein-protein interfaces are two important research areas for understanding protein interactions. Computational methods have been developed previously for accurate prediction of binding free energy change upon mutation for interfacial residues. However, a large number of interrupted and unimportant atomic contacts are used in the training phase which caused accuracy loss. Results This work proposes a new method, βACV ASA , to predict the change of binding free energy after alanine mutations. βACV ASA integrates accessible surface area (ASA) and our newly defined β contacts together into an atomic contact vector (ACV). A β contact between two atoms is a direct contact without being interrupted by any other atom between them. A β contact’s potential contribution to protein binding is also supposed to be inversely proportional to its ASA to follow the water exclusion hypothesis of binding hot spots. Tested on a dataset of 396 alanine mutations, our method is found to be superior in classification performance to many other methods, including Robetta, FoldX, HotPOINT, an ACV method of β contacts without ASA integration, and ACV ASA methods (similar to βACV ASA but based on distance-cutoff contacts). Based on our data analysis and results, we can draw conclusions that: (i) our method is powerful in the prediction of binding free energy change after alanine mutation; (ii) β contacts are better than distance-cutoff contacts for modeling the well-organized protein-binding interfaces; (iii) β contacts usually are only a small fraction number of the distance-based contacts; and (iv) water exclusion is a necessary condition for a residue to become a binding hot spot. Conclusions βACV ASA is designed using the advantages of both β contacts and water exclusion. It is an excellent tool to predict binding free energy changes and binding hot spots after alanine mutation. PMID:24568581

Prediction of time-integrated activity coefficients in PRRT using simulated dynamic PET and a pharmacokinetic model.

Science.gov (United States)

Hardiansyah, Deni; Attarwala, Ali Asgar; Kletting, Peter; Mottaghy, Felix M; Glatting, Gerhard

2017-10-01

To investigate the accuracy of predicted time-integrated activity coefficients (TIACs) in peptide-receptor radionuclide therapy (PRRT) using simulated dynamic PET data and a physiologically based pharmacokinetic (PBPK) model. PBPK parameters were estimated using biokinetic data of 15 patients after injection of (152±15)MBq of 111 In-DTPAOC (total peptide amount (5.78±0.25)nmol). True mathematical phantoms of patients (MPPs) were the PBPK model with the estimated parameters. Dynamic PET measurements were simulated as being done after bolus injection of 150MBq 68 Ga-DOTATATE using the true MPPs. Dynamic PET scans around 35min p.i. (P 1 ), 4h p.i. (P 2 ) and the combination of P 1 and P 2 (P 3 ) were simulated. Each measurement was simulated with four frames of 5min each and 2 bed positions. PBPK parameters were fitted to the PET data to derive the PET-predicted MPPs. Therapy was simulated assuming an infusion of 5.1GBq of 90 Y-DOTATATE over 30min in both true and PET-predicted MPPs. TIACs of simulated therapy were calculated, true MPPs (true TIACs) and predicted MPPs (predicted TIACs) followed by the calculation of variabilities v. For P 1 and P 2 the population variabilities of kidneys, liver and spleen were acceptable (v10%). Treatment planning of PRRT based on dynamic PET data seems possible for the kidneys, liver and spleen using a PBPK model and patient specific information. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Prediction of the flooding process at the Ronneburg site - results of an integrated approach

International Nuclear Information System (INIS)

Paul, M.; Saenger, H.-J.; Snagowski, S.; Maerten, H.; Eckart, M.

1998-01-01

The flooding process of the Ronneburg uranium mine (WISMUT) was initiated at the turn of the year 1997 to 1998. In order to prepare the flooding process and to derive and optimize technological measures an integrated modelling approach was chosen which includes several coupled modules. The most important issues to be answered are: (1) prediction of the flooding time (2) prediction of the groundwater level at the post-flooding stage, assessment of amount, location and quality of flooding waters entering the receiving streams at the final stage (3) water quality prediction within the mine during the flooding process (4) definition of technological measures and assessment of their efficiency A box model which includes the three-dimensional distribution of the cavity volume in the mine represents the model core. The model considers the various types of dewatered cavity volumes for each mine level / mining field and the degree of vertical and horizontal connection between the mining fields. Different types of open mine space as well as the dewatered geological pore and joint volume are considered taking into account the contour of the depression cone prior to flooding and the characteristics of the different rock types. Based on the mine water balance and the flooding technology the model predicts the rise of the water table over time during the flooding process for each mine field separately. In order to predict the mine water quality and the efficiency of in-situ water treatment the box model was linked to a geochemical model (PHREEQC). A three-dimensional flow model is used to evaluate the post-flooding situation at the Ronneburg site. This model is coupled to the box model. The modelling results of various flooding scenarios show that a prediction of the post-flooding geohydraulic situation is possible despite of uncertainties concerning the input parameters which still exist. The post-flooding water table in the central part of the Ronneburg mine will be 270 m

Arabidopsis thaliana gonidialess A/Zuotin related factors (GlsA/ZRF) are essential for maintenance of meristem integrity.

Science.gov (United States)

Guzmán-López, José Alfredo; Abraham-Juárez, María Jazmín; Lozano-Sotomayor, Paulina; de Folter, Stefan; Simpson, June

2016-05-01

Observation of a differential expression pattern, including strong expression in meristematic tissue of an Agave tequilana GlsA/ZRF ortholog suggested an important role for this gene during bulbil formation and developmental changes in this species. In order to better understand this role, the two GlsA/ZFR orthologs present in the genome of Arabidopsis thaliana were functionally characterized by analyzing expression patterns, double mutant phenotypes, promoter-GUS fusions and expression of hormone related or meristem marker genes. Patterns of expression for A. thaliana show that GlsA/ZFR genes are strongly expressed in SAMs and RAMs in mature plants and developing embryos and double mutants showed multiple changes in morphology related to both SAM and RAM tissues. Typical double mutants showed stunted growth of aerial and root tissue, formation of multiple ectopic meristems and effects on cotyledons, leaves and flowers. The KNOX genes STM and BP were overexpressed in double mutants whereas CLV3, WUSCHEL and AS1 were repressed and lack of AtGlsA expression was also associated with changes in localization of auxin and cytokinin. These results suggest that GlsA/ZFR is an essential component of the machinery that maintains the integrity of SAM and RAM tissue and underline the potential to identify new genes or gene functions based on observations in non-model plants.

Evaluating the Determinants of Sugary Beverage Consumption among Overweight and Obese Adults: An Application of the Integrative Model of Behavioural Prediction

Science.gov (United States)

Collado-Rivera, Maria; Branscum, Paul; Larson, Daniel; Gao, Haijuan

2018-01-01

Objective: The objective of this study was to evaluate the determinants of sugary drink consumption among overweight and obese adults attempting to lose weight using the Integrative Model of Behavioural Prediction (IMB). Design: Cross-sectional design. Method: Determinants of behavioural intentions (attitudes, perceived norms and perceived…

The value of integrating pre-clinical data to predict nausea and vomiting risk in humans as illustrated by AZD3514, a novel androgen receptor modulator

Energy Technology Data Exchange (ETDEWEB)

Grant, Claire, E-mail: claire.grant@astrazeneca.com [Drug Safety and Metabolism, AstraZeneca, Alderley Park, Macclesfield SK10 4TG (United Kingdom); Ewart, Lorna [Drug Safety and Metabolism, AstraZeneca, Da Vinci Building, Melbourn Science Park, Cambridge Road, Melbourn, Royston SG8 6HB (United Kingdom); Muthas, Daniel [Respiratory, Inflammation and Autoimmunity iMED, AstraZeneca, Pepparedsleden 1, 431 83 Mölndal (Sweden); Deavall, Damian [Drug Safety and Metabolism, AstraZeneca, Alderley Park, Macclesfield SK10 4TG (United Kingdom); Smith, Simon A. [Oncology Translational Medicine Unit, Early Clinical Development, AstraZeneca, Da Vinci Building, Melbourn Science Park, Melbourn, Royston SG8 6HB (United Kingdom); Clack, Glen [Translational Medicine Unit, Early Clinical Development, AstraZeneca, Alderley Park, Macclesfield SK10 4TG (United Kingdom); Newham, Pete [Drug Safety and Metabolism, AstraZeneca, Darwin Building, Cambridge Science Park, Milton Road, Cambridge CB4 0WG (United Kingdom)

2016-04-01

Nausea and vomiting are components of a complex mechanism that signals food avoidance and protection of the body against the absorption of ingested toxins. This response can also be triggered by pharmaceuticals. Predicting clinical nausea and vomiting liability for pharmaceutical agents based on pre-clinical data can be problematic as no single animal model is a universal predictor. Moreover, efforts to improve models are hampered by the lack of translational animal and human data in the public domain. AZD3514 is a novel, orally-administered compound that inhibits androgen receptor signaling and down-regulates androgen receptor expression. Here we have explored the utility of integrating data from several pre-clinical models to predict nausea and vomiting in the clinic. Single and repeat doses of AZD3514 resulted in emesis, salivation and gastrointestinal disturbances in the dog, and inhibited gastric emptying in rats after a single dose. AZD3514, at clinically relevant exposures, induced dose-responsive “pica” behaviour in rats after single and multiple daily doses, and induced retching and vomiting behaviour in ferrets after a single dose. We compare these data with the clinical manifestation of nausea and vomiting encountered in patients with castration-resistant prostate cancer receiving AZD3514. Our data reveal a striking relationship between the pre-clinical observations described and the experience of nausea and vomiting in the clinic. In conclusion, the emetic nature of AZD3514 was predicted across a range of pre-clinical models, and the approach presented provides a valuable framework for predicition of clinical nausea and vomiting. - Highlights: • Integrated pre-clinical data can be used to predict clinical nausea and vomiting. • Data integrated from standard toxicology studies is sufficient to make a prediction. • The use of the nausea algorithm developed by Parkinson (2012) aids the prediction. • Additional pre-clinical studies can be used

Towards understanding the first genome sequence of a crenarchaeon by genome annotation using clusters of orthologous groups of proteins (COGs).

Science.gov (United States)

Natale, D A; Shankavaram, U T; Galperin, M Y; Wolf, Y I; Aravind, L; Koonin, E V

2000-01-01

Standard archival sequence databases have not been designed as tools for genome annotation and are far from being optimal for this purpose. We used the database of Clusters of Orthologous Groups of proteins (COGs) to reannotate the genomes of two archaea, Aeropyrum pernix, the first member of the Crenarchaea to be sequenced, and Pyrococcus abyssi. A. pernix and P. abyssi proteins were assigned to COGs using the COGNITOR program; the results were verified on a case-by-case basis and augmented by additional database searches using the PSI-BLAST and TBLASTN programs. Functions were predicted for over 300 proteins from A. pernix, which could not be assigned a function using conventional methods with a conservative sequence similarity threshold, an approximately 50% increase compared to the original annotation. A. pernix shares most of the conserved core of proteins that were previously identified in the Euryarchaeota. Cluster analysis or distance matrix tree construction based on the co-occurrence of genomes in COGs showed that A. pernix forms a distinct group within the archaea, although grouping with the two species of Pyrococci, indicative of similar repertoires of conserved genes, was observed. No indication of a specific relationship between Crenarchaeota and eukaryotes was obtained in these analyses. Several proteins that are conserved in Euryarchaeota and most bacteria are unexpectedly missing in A. pernix, including the entire set of de novo purine biosynthesis enzymes, the GTPase FtsZ (a key component of the bacterial and euryarchaeal cell-division machinery), and the tRNA-specific pseudouridine synthase, previously considered universal. A. pernix is represented in 48 COGs that do not contain any euryarchaeal members. Many of these proteins are TCA cycle and electron transport chain enzymes, reflecting the aerobic lifestyle of A. pernix. Special-purpose databases organized on the basis of phylogenetic analysis and carefully curated with respect to known and

Medium term municipal solid waste generation prediction by autoregressive integrated moving average

International Nuclear Information System (INIS)

Younes, Mohammad K.; Nopiah, Z. M.; Basri, Noor Ezlin A.; Basri, Hassan

2014-01-01

Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressive Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval

Medium term municipal solid waste generation prediction by autoregressive integrated moving average

Science.gov (United States)

Younes, Mohammad K.; Nopiah, Z. M.; Basri, Noor Ezlin A.; Basri, Hassan

2014-09-01

Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressive Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval.

Medium term municipal solid waste generation prediction by autoregressive integrated moving average

Energy Technology Data Exchange (ETDEWEB)

Younes, Mohammad K.; Nopiah, Z. M.; Basri, Noor Ezlin A.; Basri, Hassan [Department of Civil and Structural Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor (Malaysia)

2014-09-12

Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressive Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval.

Behaviors of impurity in ITER and DEMOs using BALDUR integrated predictive modeling code

International Nuclear Information System (INIS)

Onjun, Thawatchai; Buangam, Wannapa; Wisitsorasak, Apiwat

2015-01-01

The behaviors of impurity are investigated using self-consistent modeling of 1.5D BALDUR integrated predictive modeling code, in which theory-based models are used for both core and edge region. In these simulations, a combination of NCLASS neoclassical transport and Multi-mode (MMM95) anomalous transport model is used to compute a core transport. The boundary is taken to be at the top of the pedestal, where the pedestal values are described using a theory-based pedestal model. This pedestal temperature model is based on a combination of magnetic and flow shear stabilization pedestal width scaling and an infinite-n ballooning pressure gradient model. The time evolution of plasma current, temperature and density profiles is carried out for ITER and DEMOs plasmas. As a result, the impurity behaviors such as impurity accumulation and impurity transport can be investigated. (author)

Model predictive control system and method for integrated gasification combined cycle power generation

Science.gov (United States)

Kumar, Aditya; Shi, Ruijie; Kumar, Rajeeva; Dokucu, Mustafa

2013-04-09

Control system and method for controlling an integrated gasification combined cycle (IGCC) plant are provided. The system may include a controller coupled to a dynamic model of the plant to process a prediction of plant performance and determine a control strategy for the IGCC plant over a time horizon subject to plant constraints. The control strategy may include control functionality to meet a tracking objective and control functionality to meet an optimization objective. The control strategy may be configured to prioritize the tracking objective over the optimization objective based on a coordinate transformation, such as an orthogonal or quasi-orthogonal projection. A plurality of plant control knobs may be set in accordance with the control strategy to generate a sequence of coordinated multivariable control inputs to meet the tracking objective and the optimization objective subject to the prioritization resulting from the coordinate transformation.

Boolean Dynamic Modeling Approaches to Study Plant Gene Regulatory Networks: Integration, Validation, and Prediction.

Science.gov (United States)

Velderraín, José Dávila; Martínez-García, Juan Carlos; Álvarez-Buylla, Elena R

2017-01-01

Mathematical models based on dynamical systems theory are well-suited tools for the integration of available molecular experimental data into coherent frameworks in order to propose hypotheses about the cooperative regulatory mechanisms driving developmental processes. Computational analysis of the proposed models using well-established methods enables testing the hypotheses by contrasting predictions with observations. Within such framework, Boolean gene regulatory network dynamical models have been extensively used in modeling plant development. Boolean models are simple and intuitively appealing, ideal tools for collaborative efforts between theorists and experimentalists. In this chapter we present protocols used in our group for the study of diverse plant developmental processes. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature.

Global Integration of the Hot-State Brain Network of Appetite Predicts Short Term Weight Loss in Older Adult

Directory of Open Access Journals (Sweden)

Brielle M Paolini

2015-05-01

Full Text Available Obesity is a public health crisis in North America. While lifestyle interventions for weight loss (WL remain popular, the rate of success is highly variable. Clearly, self-regulation of eating behavior is a challenge and patterns of activity across the brain may be an important determinant of success. The current study prospectively examined whether integration across the Hot-State Brain Network of Appetite (HBN-A predicts WL after 6-months of treatment in older adults. Our metric for network integration was global efficiency (GE. The present work is a sub-study (n = 56 of an ongoing randomized clinical trial involving WL. Imaging involved a baseline food-cue visualization functional MRI (fMRI scan following an overnight fast. Using graph theory to build functional brain networks, we demonstrated that regions of the HBN-A (insula, anterior cingulate cortex (ACC, superior temporal pole, amygdala and the parahippocampal gyrus were highly integrated as evidenced by the results of a principal component analysis. After accounting for known correlates of WL (baseline weight, age, sex, and self-regulatory efficacy and treatment condition, which together contributed 36.9% of the variance in WL, greater GE in the HBN-A was associated with an additional 19% of the variance. The ACC of the HBN-A was the primary driver of this effect, accounting for 14.5% of the variance in WL when entered in a stepwise regression following the covariates, p = 0.0001. The HBN-A is comprised of limbic regions important in the processing of emotions and visceral sensations and the ACC is key for translating such processing into behavioral consequences. The improved integration of these regions may enhance awareness of body and emotional states leading to more successful self-regulation and to greater WL. This is the first study among older adults to prospectively demonstrate that, following an overnight fast, GE of the HBN-A during a food visualization task is predictive of

Reliability of nine programs of topological predictions and their application to integral membrane channel and carrier proteins.

Science.gov (United States)

Reddy, Abhinay; Cho, Jaehoon; Ling, Sam; Reddy, Vamsee; Shlykov, Maksim; Saier, Milton H

2014-01-01

We evaluated topological predictions for nine different programs, HMMTOP, TMHMM, SVMTOP, DAS, SOSUI, TOPCONS, PHOBIUS, MEMSAT-SVM (hereinafter referred to as MEMSAT), and SPOCTOPUS. These programs were first evaluated using four large topologically well-defined families of secondary transporters, and the three best programs were further evaluated using topologically more diverse families of channels and carriers. In the initial studies, the order of accuracy was: SPOCTOPUS > MEMSAT > HMMTOP > TOPCONS > PHOBIUS > TMHMM > SVMTOP > DAS > SOSUI. Some families, such as the Sugar Porter Family (2.A.1.1) of the Major Facilitator Superfamily (MFS; TC #2.A.1) and the Amino Acid/Polyamine/Organocation (APC) Family (TC #2.A.3), were correctly predicted with high accuracy while others, such as the Mitochondrial Carrier (MC) (TC #2.A.29) and the K(+) transporter (Trk) families (TC #2.A.38), were predicted with much lower accuracy. For small, topologically homogeneous families, SPOCTOPUS and MEMSAT were generally most reliable, while with large, more diverse superfamilies, HMMTOP often proved to have the greatest prediction accuracy. We next developed a novel program, TM-STATS, that tabulates HMMTOP, SPOCTOPUS or MEMSAT-based topological predictions for any subdivision (class, subclass, superfamily, family, subfamily, or any combination of these) of the Transporter Classification Database (TCDB; www.tcdb.org) and examined the following subclasses: α-type channel proteins (TC subclasses 1.A and 1.E), secreted pore-forming toxins (TC subclass 1.C) and secondary carriers (subclass 2.A). Histograms were generated for each of these subclasses, and the results were analyzed according to subclass, family and protein. The results provide an update of topological predictions for integral membrane transport proteins as well as guides for the development of more reliable topological prediction programs, taking family-specific characteristics into account. © 2014 S. Karger AG, Basel.

Target and Tissue Selectivity Prediction by Integrated Mechanistic Pharmacokinetic-Target Binding and Quantitative Structure Activity Modeling.

Science.gov (United States)

Vlot, Anna H C; de Witte, Wilhelmus E A; Danhof, Meindert; van der Graaf, Piet H; van Westen, Gerard J P; de Lange, Elizabeth C M

2017-12-04

Selectivity is an important attribute of effective and safe drugs, and prediction of in vivo target and tissue selectivity would likely improve drug development success rates. However, a lack of understanding of the underlying (pharmacological) mechanisms and availability of directly applicable predictive methods complicates the prediction of selectivity. We explore the value of combining physiologically based pharmacokinetic (PBPK) modeling with quantitative structure-activity relationship (QSAR) modeling to predict the influence of the target dissociation constant (K D ) and the target dissociation rate constant on target and tissue selectivity. The K D values of CB1 ligands in the ChEMBL database are predicted by QSAR random forest (RF) modeling for the CB1 receptor and known off-targets (TRPV1, mGlu5, 5-HT1a). Of these CB1 ligands, rimonabant, CP-55940, and Δ 8 -tetrahydrocanabinol, one of the active ingredients of cannabis, were selected for simulations of target occupancy for CB1, TRPV1, mGlu5, and 5-HT1a in three brain regions, to illustrate the principles of the combined PBPK-QSAR modeling. Our combined PBPK and target binding modeling demonstrated that the optimal values of the K D and k off for target and tissue selectivity were dependent on target concentration and tissue distribution kinetics. Interestingly, if the target concentration is high and the perfusion of the target site is low, the optimal K D value is often not the lowest K D value, suggesting that optimization towards high drug-target affinity can decrease the benefit-risk ratio. The presented integrative structure-pharmacokinetic-pharmacodynamic modeling provides an improved understanding of tissue and target selectivity.

Integrated Wind Power Planning Tool

DEFF Research Database (Denmark)

Rosgaard, M. H.; Giebel, Gregor; Nielsen, T. S.

2012-01-01

model to be developed in collaboration with ENFOR A/S; a danish company that specialises in forecasting and optimisation for the energy sector. This integrated prediction model will allow for the description of the expected variability in wind power production in the coming hours to days, accounting......This poster presents the current state of the public service obligation (PSO) funded project PSO 10464, with the working title "Integrated Wind Power Planning Tool". The project commenced October 1, 2011, and the goal is to integrate a numerical weather prediction (NWP) model with purely...

Predicting Teacher Participation in a Classroom-Based, Integrated Preventive Intervention for Preschoolers.

Science.gov (United States)

Baker, Courtney N; Kupersmidt, Janis B; Voegler-Lee, Mary Ellen; Arnold, David H; Willoughby, Michael T

2010-01-01

Preschools provide a promising setting in which to conduct preventive interventions for childhood problems, but classroom programs can only be effective if teachers are willing and able to implement them. This study is one of the first to investigate predictors of the frequency of teacher participation in a classroom-based, randomized controlled trial of an integrated prevention program for preschoolers. The intervention was designed to promote school readiness with an integrated social and academic program, to be implemented by teachers with the support of classroom consultants. The current study is part of a larger project conducted with Head Start and community child care centers that serve primarily economically disadvantaged families; 49 teachers from 30 centers participated in this study. Overall, teachers conducted approximately 70% of the program activities. Participation decreased significantly over time from the first to the final week of the intervention, and also decreased within each week of the intervention, from the first to the final weekly activity. Teachers working at community child care centers implemented more intervention activities than did Head Start teachers. Teacher concerns about the intervention, assessed prior to training, predicted less participation. In addition, teachers' participation was positively related to their perception that their centers and directors were supportive, collegial, efficient, and fair, as well as their job satisfaction and commitment. Teacher experience, education, ethnicity, and self-efficacy were not significantly related to participation. In multi-level models that considered center as a level of analysis, substantial variance was accounted for by centers, pointing to the importance of considering center-level predictors in future research.

Integrating Unified Gravity Wave Physics into the NOAA Next Generation Global Prediction System

Science.gov (United States)

Alpert, J. C.; Yudin, V.; Fuller-Rowell, T. J.; Akmaev, R. A.

2017-12-01

The Unified Gravity Wave Physics (UGWP) project for the Next Generation Global Prediction System (NGGPS) is a NOAA collaborative effort between the National Centers for Environmental Prediction (NCEP), Environemntal Modeling Center (EMC) and the University of Colorado, Cooperative Institute for Research in Environmental Sciences (CU-CIRES) to support upgrades and improvements of GW dynamics (resolved scales) and physics (sub-grid scales) in the NOAA Environmental Modeling System (NEMS)†. As envisioned the global climate, weather and space weather models of NEMS will substantially improve their predictions and forecasts with the resolution-sensitive (scale-aware) formulations planned under the UGWP framework for both orographic and non-stationary waves. In particular, the planned improvements for the Global Forecast System (GFS) model of NEMS are: calibration of model physics for higher vertical and horizontal resolution and an extended vertical range of simulations, upgrades to GW schemes, including the turbulent heating and eddy mixing due to wave dissipation and breaking, and representation of the internally-generated QBO. The main priority of the UGWP project is unified parameterization of orographic and non-orographic GW effects including momentum deposition in the middle atmosphere and turbulent heating and eddies due to wave dissipation and breaking. The latter effects are not currently represented in NOAA atmosphere models. The team has tested and evaluated four candidate GW solvers integrating the selected GW schemes into the NGGPS model. Our current work and planned activity is to implement the UGWP schemes in the first available GFS/FV3 (open FV3) configuration including adapted GFDL modification for sub-grid orography in GFS. Initial global model results will be shown for the operational and research GFS configuration for spectral and FV3 dynamical cores. †http://www.emc.ncep.noaa.gov/index.php?branch=NEMS

Cross-species prophylactic efficacy of Sm-p80-based vaccine and intracellular localization of Sm-p80/Sm-p80 ortholog proteins during development in Schistosoma mansoni, Schistosoma japonicum, and Schistosoma haematobium.

Science.gov (United States)

Molehin, Adebayo J; Sennoune, Souad R; Zhang, Weidong; Rojo, Juan U; Siddiqui, Arif J; Herrera, Karlie A; Johnson, Laura; Sudduth, Justin; May, Jordan; Siddiqui, Afzal A

2017-11-01

Schistosomiasis remains a major global health problem. Despite large-scale schistosomiasis control efforts, clear limitations such as possible emergence of drug resistance and reinfection rates highlight the need for an effective schistosomiasis vaccine. Schistosoma mansoni large subunit of calpain (Sm-p80)-based vaccine formulations have shown remarkable efficacy in protecting against S. mansoni challenge infections in mice and baboons. In this study, we evaluated the cross-species protective efficacy of Sm-p80 vaccine against S. japonicum and S. haematobium challenge infections in rodent models. We also elucidated the expression of Sm-p80 and Sm-p80 ortholog proteins in different developmental stages of S. mansoni, S. haematobium, and S. japonicum. Immunization with Sm-p80 vaccine reduced worm burden by 46.75% against S. japonicum challenge infection in mice. DNA prime/protein boost (1 + 1 dose administered on a single day) resulted in 26.95% reduction in worm burden in S. haematobium-hamster infection/challenge model. A balanced Th1 (IFN-γ, TNF-α, IL-2, and IL-12) and Th2 (IL-4, IgG1) type of responses were observed following vaccination in both S. japonicum and S. haematobium challenge trials and these are associated with the prophylactic efficacy of Sm-p80 vaccine. Immunohistochemistry demonstrated that Sm-p80/Sm-p80 ortholog proteins are expressed in different life cycle stages of the three major human species of schistosomes studied. The data presented in this study reinforce the potential of Sm-p80-based vaccine for both hepatic/intestinal and urogenital schistosomiasis occurring in different geographical areas of the world. Differential expression of Sm-p80/Sm-p80 protein orthologs in different life cycle makes this vaccine potentially useful in targeting different levels of infection, disease, and transmission.

Community integration after burn injuries.

Science.gov (United States)

Esselman, P C; Ptacek, J T; Kowalske, K; Cromes, G F; deLateur, B J; Engrav, L H

2001-01-01

Evaluation of community integration is a meaningful outcome criterion after major burn injury. The Community Integration Questionnaire (CIQ) was administered to 463 individuals with major burn injuries. The CIQ results in Total, Home Integration, Social Integration, and Productivity scores. The purposes of this study were to determine change in CIQ scores over time and what burn injury and demographic factors predict CIQ scores. The CIQ scores did not change significantly from 6 to 12 to 24 months postburn injury. Home integration scores were best predicted by sex and living situation; Social Integration scores by marital status; and Productivity scores by functional outcome, burn severity, age, and preburn work factors. The data demonstrate that individuals with burn injuries have significant difficulties with community integration due to burn and nonburn related factors. CIQ scores did not improve over time but improvement may have occurred before the initial 6-month postburn injury follow-up in this study.

Structural implications of mutations in the pea SYM8 symbiosis gene, the DMI1 ortholog, encoding a predicted ion channel

DEFF Research Database (Denmark)

Edwards, Anne; Heckmann, Anne Birgitte Lau; Yousafzai, Faridoon

2007-01-01

the aspartate to valine and identified a missense mutation (changing alanine to valine adjacent to the aspartate residues) in this predicted filter region; both mutations caused a loss of function. We also identified a loss-of-function missense mutation (changing arginine to isoleucine) in a domain proposed...

ATX-2, the C. elegans Ortholog of Human Ataxin-2, Regulates Centrosome Size and Microtubule Dynamics.

Directory of Open Access Journals (Sweden)

Michael D Stubenvoll

2016-09-01

Full Text Available Centrosomes are critical sites for orchestrating microtubule dynamics, and exhibit dynamic changes in size during the cell cycle. As cells progress to mitosis, centrosomes recruit more microtubules (MT to form mitotic bipolar spindles that ensure proper chromosome segregation. We report a new role for ATX-2, a C. elegans ortholog of Human Ataxin-2, in regulating centrosome size and MT dynamics. ATX-2, an RNA-binding protein, forms a complex with SZY-20 in an RNA-independent fashion. Depleting ATX-2 results in embryonic lethality and cytokinesis failure, and restores centrosome duplication to zyg-1 mutants. In this pathway, SZY-20 promotes ATX-2 abundance, which inversely correlates with centrosome size. Centrosomes depleted of ATX-2 exhibit elevated levels of centrosome factors (ZYG-1, SPD-5, γ-Tubulin, increasing MT nucleating activity but impeding MT growth. We show that ATX-2 influences MT behavior through γ-Tubulin at the centrosome. Our data suggest that RNA-binding proteins play an active role in controlling MT dynamics and provide insight into the control of proper centrosome size and MT dynamics.

Personalizing oncology treatments by predicting drug efficacy, side-effects, and improved therapy: mathematics, statistics, and their integration.

Science.gov (United States)

Agur, Zvia; Elishmereni, Moran; Kheifetz, Yuri

2014-01-01

Despite its great promise, personalized oncology still faces many hurdles, and it is increasingly clear that targeted drugs and molecular biomarkers alone yield only modest clinical benefit. One reason is the complex relationships between biomarkers and the patient's response to drugs, obscuring the true weight of the biomarkers in the overall patient's response. This complexity can be disentangled by computational models that integrate the effects of personal biomarkers into a simulator of drug-patient dynamic interactions, for predicting the clinical outcomes. Several computational tools have been developed for personalized oncology, notably evidence-based tools for simulating pharmacokinetics, Bayesian-estimated tools for predicting survival, etc. We describe representative statistical and mathematical tools, and discuss their merits, shortcomings and preliminary clinical validation attesting to their potential. Yet, the individualization power of mathematical models alone, or statistical models alone, is limited. More accurate and versatile personalization tools can be constructed by a new application of the statistical/mathematical nonlinear mixed effects modeling (NLMEM) approach, which until recently has been used only in drug development. Using these advanced tools, clinical data from patient populations can be integrated with mechanistic models of disease and physiology, for generating personal mathematical models. Upon a more substantial validation in the clinic, this approach will hopefully be applied in personalized clinical trials, P-trials, hence aiding the establishment of personalized medicine within the main stream of clinical oncology. © 2014 Wiley Periodicals, Inc.

An ortholog of LEAFY in Jatropha curcas regulates flowering time and floral organ development.

Science.gov (United States)

Tang, Mingyong; Tao, Yan-Bin; Fu, Qiantang; Song, Yaling; Niu, Longjian; Xu, Zeng-Fu

2016-11-21

Jatropha curcas seeds are an excellent biofuel feedstock, but seed yields of Jatropha are limited by its poor flowering and fruiting ability. Thus, identifying genes controlling flowering is critical for genetic improvement of seed yield. We isolated the JcLFY, a Jatropha ortholog of Arabidopsis thaliana LEAFY (LFY), and identified JcLFY function by overexpressing it in Arabidopsis and Jatropha. JcLFY is expressed in Jatropha inflorescence buds, flower buds, and carpels, with highest expression in the early developmental stage of flower buds. JcLFY overexpression induced early flowering, solitary flowers, and terminal flowers in Arabidopsis, and also rescued the delayed flowering phenotype of lfy-15, a LFY loss-of-function Arabidopsis mutant. Microarray and qPCR analysis revealed several flower identity and flower organ development genes were upregulated in JcLFY-overexpressing Arabidopsis. JcLFY overexpression in Jatropha also induced early flowering. Significant changes in inflorescence structure, floral organs, and fruit shape occurred in JcLFY co-suppressed plants in which expression of several flower identity and floral organ development genes were changed. This suggests JcLFY is involved in regulating flower identity, floral organ patterns, and fruit shape, although JcLFY function in Jatropha floral meristem determination is not as strong as that of Arabidopsis.

Use of structure-activity landscape index curves and curve integrals to evaluate the performance of multiple machine learning prediction models.

Science.gov (United States)

Ledonne, Norman C; Rissolo, Kevin; Bulgarelli, James; Tini, Leonard

2011-02-07

Standard approaches to address the performance of predictive models that used common statistical measurements for the entire data set provide an overview of the average performance of the models across the entire predictive space, but give little insight into applicability of the model across the prediction space. Guha and Van Drie recently proposed the use of structure-activity landscape index (SALI) curves via the SALI curve integral (SCI) as a means to map the predictive power of computational models within the predictive space. This approach evaluates model performance by assessing the accuracy of pairwise predictions, comparing compound pairs in a manner similar to that done by medicinal chemists. The SALI approach was used to evaluate the performance of continuous prediction models for MDR1-MDCK in vitro efflux potential. Efflux models were built with ADMET Predictor neural net, support vector machine, kernel partial least squares, and multiple linear regression engines, as well as SIMCA-P+ partial least squares, and random forest from Pipeline Pilot as implemented by AstraZeneca, using molecular descriptors from SimulationsPlus and AstraZeneca. The results indicate that the choice of training sets used to build the prediction models is of great importance in the resulting model quality and that the SCI values calculated for these models were very similar to their Kendall τ values, leading to our suggestion of an approach to use this SALI/SCI paradigm to evaluate predictive model performance that will allow more informed decisions regarding model utility. The use of SALI graphs and curves provides an additional level of quality assessment for predictive models.

Advancing coastal ocean modelling, analysis, and prediction for the US Integrated Ocean Observing System

Science.gov (United States)

Wilkin, John L.; Rosenfeld, Leslie; Allen, Arthur; Baltes, Rebecca; Baptista, Antonio; He, Ruoying; Hogan, Patrick; Kurapov, Alexander; Mehra, Avichal; Quintrell, Josie; Schwab, David; Signell, Richard; Smith, Jane

2017-01-01

This paper outlines strategies that would advance coastal ocean modelling, analysis and prediction as a complement to the observing and data management activities of the coastal components of the US Integrated Ocean Observing System (IOOS®) and the Global Ocean Observing System (GOOS). The views presented are the consensus of a group of US-based researchers with a cross-section of coastal oceanography and ocean modelling expertise and community representation drawn from Regional and US Federal partners in IOOS. Priorities for research and development are suggested that would enhance the value of IOOS observations through model-based synthesis, deliver better model-based information products, and assist the design, evaluation, and operation of the observing system itself. The proposed priorities are: model coupling, data assimilation, nearshore processes, cyberinfrastructure and model skill assessment, modelling for observing system design, evaluation and operation, ensemble prediction, and fast predictors. Approaches are suggested to accomplish substantial progress in a 3–8-year timeframe. In addition, the group proposes steps to promote collaboration between research and operations groups in Regional Associations, US Federal Agencies, and the international ocean research community in general that would foster coordination on scientific and technical issues, and strengthen federal–academic partnerships benefiting IOOS stakeholders and end users.

A statistical framework to predict functional non-coding regions in the human genome through integrated analysis of annotation data.

Science.gov (United States)

Lu, Qiongshi; Hu, Yiming; Sun, Jiehuan; Cheng, Yuwei; Cheung, Kei-Hoi; Zhao, Hongyu

2015-05-27

Identifying functional regions in the human genome is a major goal in human genetics. Great efforts have been made to functionally annotate the human genome either through computational predictions, such as genomic conservation, or high-throughput experiments, such as the ENCODE project. These efforts have resulted in a rich collection of functional annotation data of diverse types that need to be jointly analyzed for integrated interpretation and annotation. Here we present GenoCanyon, a whole-genome annotation method that performs unsupervised statistical learning using 22 computational and experimental annotations thereby inferring the functional potential of each position in the human genome. With GenoCanyon, we are able to predict many of the known functional regions. The ability of predicting functional regions as well as its generalizable statistical framework makes GenoCanyon a unique and powerful tool for whole-genome annotation. The GenoCanyon web server is available at http://genocanyon.med.yale.edu.

Integrated and Total HIV-1 DNA Predict Ex Vivo Viral Outgrowth.

Directory of Open Access Journals (Sweden)

Maja Kiselinova

2016-03-01

Full Text Available The persistence of a reservoir of latently infected CD4 T cells remains one of the major obstacles to cure HIV. Numerous strategies are being explored to eliminate this reservoir. To translate these efforts into clinical trials, there is a strong need for validated biomarkers that can monitor the reservoir over time in vivo. A comprehensive study was designed to evaluate and compare potential HIV-1 reservoir biomarkers. A cohort of 25 patients, treated with suppressive antiretroviral therapy was sampled at three time points, with median of 2.5 years (IQR: 2.4-2.6 between time point 1 and 2; and median of 31 days (IQR: 28-36 between time point 2 and 3. Patients were median of 6 years (IQR: 3-12 on ART, and plasma viral load (<50 copies/ml was suppressed for median of 4 years (IQR: 2-8. Total HIV-1 DNA, unspliced (us and multiply spliced HIV-1 RNA, and 2LTR circles were quantified by digital PCR in peripheral blood, at 3 time points. At the second time point, a viral outgrowth assay (VOA was performed, and integrated HIV-1 DNA and relative mRNA expression levels of HIV-1 restriction factors were quantified. No significant change was found for long- and short-term dynamics of all HIV-1 markers tested in peripheral blood. Integrated HIV-1 DNA was associated with total HIV-1 DNA (p<0.001, R² = 0.85, us HIV-1 RNA (p = 0.029, R² = 0.40, and VOA (p = 0.041, R2 = 0.44. Replication-competent virus was detected in 80% of patients by the VOA and it correlated with total HIV-1 DNA (p = 0.039, R² = 0.54. The mean quantification difference between Alu-PCR and VOA was 2.88 log10, and 2.23 log10 between total HIV-1 DNA and VOA. The levels of usHIV-1 RNA were inversely correlated with mRNA levels of several HIV-1 restriction factors (TRIM5α, SAMHD1, MX2, SLFN11, pSIP1. Our study reveals important correlations between the viral outgrowth and total and integrated HIV-1 DNA measures, suggesting that the total pool of HIV-1 DNA may predict the size of the

Combining modularity, conservation, and interactions of proteins significantly increases precision and coverage of protein function prediction

Directory of Open Access Journals (Sweden)

Sers Christine T

2010-12-01

Full Text Available Abstract Background While the number of newly sequenced genomes and genes is constantly increasing, elucidation of their function still is a laborious and time-consuming task. This has led to the development of a wide range of methods for predicting protein functions in silico. We report on a new method that predicts function based on a combination of information about protein interactions, orthology, and the conservation of protein networks in different species. Results We show that aggregation of these independent sources of evidence leads to a drastic increase in number and quality of predictions when compared to baselines and other methods reported in the literature. For instance, our method generates more than 12,000 novel protein functions for human with an estimated precision of ~76%, among which are 7,500 new functional annotations for 1,973 human proteins that previously had zero or only one function annotated. We also verified our predictions on a set of genes that play an important role in colorectal cancer (MLH1, PMS2, EPHB4 and could confirm more than 73% of them based on evidence in the literature. Conclusions The combination of different methods into a single, comprehensive prediction method infers thousands of protein functions for every species included in the analysis at varying, yet always high levels of precision and very good coverage.

Individualized prediction of perineural invasion in colorectal cancer: development and validation of a radiomics prediction model.

Science.gov (United States)

Huang, Yanqi; He, Lan; Dong, Di; Yang, Caiyun; Liang, Cuishan; Chen, Xin; Ma, Zelan; Huang, Xiaomei; Yao, Su; Liang, Changhong; Tian, Jie; Liu, Zaiyi

2018-02-01

To develop and validate a radiomics prediction model for individualized prediction of perineural invasion (PNI) in colorectal cancer (CRC). After computed tomography (CT) radiomics features extraction, a radiomics signature was constructed in derivation cohort (346 CRC patients). A prediction model was developed to integrate the radiomics signature and clinical candidate predictors [age, sex, tumor location, and carcinoembryonic antigen (CEA) level]. Apparent prediction performance was assessed. After internal validation, independent temporal validation (separate from the cohort used to build the model) was then conducted in 217 CRC patients. The final model was converted to an easy-to-use nomogram. The developed radiomics nomogram that integrated the radiomics signature and CEA level showed good calibration and discrimination performance [Harrell's concordance index (c-index): 0.817; 95% confidence interval (95% CI): 0.811-0.823]. Application of the nomogram in validation cohort gave a comparable calibration and discrimination (c-index: 0.803; 95% CI: 0.794-0.812). Integrating the radiomics signature and CEA level into a radiomics prediction model enables easy and effective risk assessment of PNI in CRC. This stratification of patients according to their PNI status may provide a basis for individualized auxiliary treatment.

Rigorous assessment and integration of the sequence and structure based features to predict hot spots

Directory of Open Access Journals (Sweden)

Wang Yong

2011-07-01

classifiers are quite effective in predicting hot spots based on sequence features. Hot spots cannot be fully predicted through simple analysis based on physicochemical characteristics, but there is reason to believe that integration of features and machine learning methods can remarkably improve the predictive performance for hot spots.

Rigorous assessment and integration of the sequence and structure based features to predict hot spots

Science.gov (United States)

2011-01-01

effective in predicting hot spots based on sequence features. Hot spots cannot be fully predicted through simple analysis based on physicochemical characteristics, but there is reason to believe that integration of features and machine learning methods can remarkably improve the predictive performance for hot spots. PMID:21798070

The trehalose utilization gene thuA ortholog in Mesorhizobium loti does not influence competitiveness for nodulation on Lotus spp.

Science.gov (United States)

Ampomah, Osei Yaw; Jensen, John Beck

2014-03-01

Competitiveness for nodulation is a desirable trait in rhizobia strains used as inoculant. In Sinorhizobium meliloti 1021 mutation in either of the trehalose utilization genes thuA or thuB influences its competitiveness for root colonization and nodule occupancy depending on the interacting host. We have therefore investigated whether mutation in the thuA ortholog in Mesorhizobium loti MAFF303099 also leads to a similar competitive phenotype on its hosts. The results show that M. loti thuA mutant Ml7023 was symbiotically effective and was as competitive as the wild type in colonization and nodule occupancy on Lotus corniculatus and Lotus japonicus. The thuA gene in M. loti was not induced during root colonization or in the infection threads unlike in S. meliloti, despite its induction by trehalose and high osmolarity in in vitro assays.

Predictive Analytics in Information Systems Research

NARCIS (Netherlands)

G. Shmueli (Galit); O.R. Koppius (Otto)

2011-01-01

textabstractThis research essay highlights the need to integrate predictive analytics into information systems research and shows several concrete ways in which this goal can be accomplished. Predictive analytics include empirical methods (statistical and other) that generate data predictions as

Genomic evolution of 11 type strains within family Planctomycetaceae.

Directory of Open Access Journals (Sweden)

Min Guo

Full Text Available The species in family Planctomycetaceae are ideal groups for investigating the origin of eukaryotes. Their cells are divided by a lipidic intracytoplasmic membrane and they share a number of eukaryote-like molecular characteristics. However, their genomic structures, potential abilities, and evolutionary status are still unknown. In this study, we searched for common protein families and a core genome/pan genome based on 11 sequenced species in family Planctomycetaceae. Then, we constructed phylogenetic tree based on their 832 common protein families. We also annotated the 11 genomes using the Clusters of Orthologous Groups database. Moreover, we predicted and reconstructed their core/pan metabolic pathways using the KEGG (Kyoto Encyclopedia of Genes and Genomes orthology system. Subsequently, we identified genomic islands (GIs and structural variations (SVs among the five complete genomes and we specifically investigated the integration of two Planctomycetaceae plasmids in all 11 genomes. The results indicate that Planctomycetaceae species share diverse genomic variations and unique genomic characteristics, as well as have huge potential for human applications.

Proteomic analysis of isolated chlamydomonas centrioles reveals orthologs of ciliary-disease genes.

Science.gov (United States)

Keller, Lani C; Romijn, Edwin P; Zamora, Ivan; Yates, John R; Marshall, Wallace F

2005-06-21

The centriole is one of the most enigmatic organelles in the cell. Centrioles are cylindrical, microtubule-based barrels found in the core of the centrosome. Centrioles also act as basal bodies during interphase to nucleate the assembly of cilia and flagella. There are currently only a handful of known centriole proteins. We used mass-spectrometry-based MudPIT (multidimensional protein identification technology) to identify the protein composition of basal bodies (centrioles) isolated from the green alga Chlamydomonas reinhardtii. This analysis detected the majority of known centriole proteins, including centrin, epsilon tubulin, and the cartwheel protein BLD10p. By combining proteomic data with information about gene expression and comparative genomics, we identified 45 cross-validated centriole candidate proteins in two classes. Members of the first class of proteins (BUG1-BUG27) are encoded by genes whose expression correlates with flagellar assembly and which therefore may play a role in ciliogenesis-related functions of basal bodies. Members of the second class (POC1-POC18) are implicated by comparative-genomics and -proteomics studies to be conserved components of the centriole. We confirmed centriolar localization for the human homologs of four candidate proteins. Three of the cross-validated centriole candidate proteins are encoded by orthologs of genes (OFD1, NPHP-4, and PACRG) implicated in mammalian ciliary function and disease, suggesting that oral-facial-digital syndrome and nephronophthisis may involve a dysfunction of centrioles and/or basal bodies. By analyzing isolated Chlamydomonas basal bodies, we have been able to obtain the first reported proteomic analysis of the centriole.

A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy.

Science.gov (United States)

Ji, Zhiwei; Wang, Bing; Yan, Ke; Dong, Ligang; Meng, Guanmin; Shi, Lei

2017-12-21

In recent years, the integration of 'omics' technologies, high performance computation, and mathematical modeling of biological processes marks that the systems biology has started to fundamentally impact the way of approaching drug discovery. The LINCS public data warehouse provides detailed information about cell responses with various genetic and environmental stressors. It can be greatly helpful in developing new drugs and therapeutics, as well as improving the situations of lacking effective drugs, drug resistance and relapse in cancer therapies, etc. In this study, we developed a Ternary status based Integer Linear Programming (TILP) method to infer cell-specific signaling pathway network and predict compounds' treatment efficacy. The novelty of our study is that phosphor-proteomic data and prior knowledge are combined for modeling and optimizing the signaling network. To test the power of our approach, a generic pathway network was constructed for a human breast cancer cell line MCF7; and the TILP model was used to infer MCF7-specific pathways with a set of phosphor-proteomic data collected from ten representative small molecule chemical compounds (most of them were studied in breast cancer treatment). Cross-validation indicated that the MCF7-specific pathway network inferred by TILP were reliable predicting a compound's efficacy. Finally, we applied TILP to re-optimize the inferred cell-specific pathways and predict the outcomes of five small compounds (carmustine, doxorubicin, GW-8510, daunorubicin, and verapamil), which were rarely used in clinic for breast cancer. In the simulation, the proposed approach facilitates us to identify a compound's treatment efficacy qualitatively and quantitatively, and the cross validation analysis indicated good accuracy in predicting effects of five compounds. In summary, the TILP model is useful for discovering new drugs for clinic use, and also elucidating the potential mechanisms of a compound to targets.

Decision Support for Flood Event Prediction and Monitoring

DEFF Research Database (Denmark)

Mioc, Darka; Anton, François; Liang, Gengsheng

2007-01-01

In this paper the development of Web GIS based decision support system for flood events is presented. To improve flood prediction we developed the decision support system for flood prediction and monitoring that integrates hydrological modelling and CARIS GIS. We present the methodology for data...... integration, floodplain delineation, and online map interfaces. Our Web-based GIS model can dynamically display observed and predicted flood extents for decision makers and the general public. The users can access Web-based GIS that models current flood events and displays satellite imagery and digital...... elevation model integrated with flood plain area. The system can show how the flooding prediction based on the output from hydrological modeling for the next 48 hours along the lower Saint John River Valley....

Use of structure-activity landscape index curves and curve integrals to evaluate the performance of multiple machine learning prediction models

Directory of Open Access Journals (Sweden)

LeDonne Norman C

2011-02-01

Full Text Available Abstract Background Standard approaches to address the performance of predictive models that used common statistical measurements for the entire data set provide an overview of the average performance of the models across the entire predictive space, but give little insight into applicability of the model across the prediction space. Guha and Van Drie recently proposed the use of structure-activity landscape index (SALI curves via the SALI curve integral (SCI as a means to map the predictive power of computational models within the predictive space. This approach evaluates model performance by assessing the accuracy of pairwise predictions, comparing compound pairs in a manner similar to that done by medicinal chemists. Results The SALI approach was used to evaluate the performance of continuous prediction models for MDR1-MDCK in vitro efflux potential. Efflux models were built with ADMET Predictor neural net, support vector machine, kernel partial least squares, and multiple linear regression engines, as well as SIMCA-P+ partial least squares, and random forest from Pipeline Pilot as implemented by AstraZeneca, using molecular descriptors from SimulationsPlus and AstraZeneca. Conclusion The results indicate that the choice of training sets used to build the prediction models is of great importance in the resulting model quality and that the SCI values calculated for these models were very similar to their Kendall τ values, leading to our suggestion of an approach to use this SALI/SCI paradigm to evaluate predictive model performance that will allow more informed decisions regarding model utility. The use of SALI graphs and curves provides an additional level of quality assessment for predictive models.

Gene expression prediction by soft integration and the elastic net-best performance of the DREAM3 gene expression challenge.

Directory of Open Access Journals (Sweden)

Mika Gustafsson

Full Text Available BACKGROUND: To predict gene expressions is an important endeavour within computational systems biology. It can both be a way to explore how drugs affect the system, as well as providing a framework for finding which genes are interrelated in a certain process. A practical problem, however, is how to assess and discriminate among the various algorithms which have been developed for this purpose. Therefore, the DREAM project invited the year 2008 to a challenge for predicting gene expression values, and here we present the algorithm with best performance. METHODOLOGY/PRINCIPAL FINDINGS: We develop an algorithm by exploring various regression schemes with different model selection procedures. It turns out that the most effective scheme is based on least squares, with a penalty term of a recently developed form called the "elastic net". Key components in the algorithm are the integration of expression data from other experimental conditions than those presented for the challenge and the utilization of transcription factor binding data for guiding the inference process towards known interactions. Of importance is also a cross-validation procedure where each form of external data is used only to the extent it increases the expected performance. CONCLUSIONS/SIGNIFICANCE: Our algorithm proves both the possibility to extract information from large-scale expression data concerning prediction of gene levels, as well as the benefits of integrating different data sources for improving the inference. We believe the former is an important message to those still hesitating on the possibilities for computational approaches, while the latter is part of an important way forward for the future development of the field of computational systems biology.

A model of integration among prediction tools: applied study to road freight transportation

Directory of Open Access Journals (Sweden)

Henrique Dias Blois

Full Text Available Abstract This study has developed a scenery analysis model which has integrated decision-making tools on investments: prospective scenarios (Grumbach Method and systems dynamics (hard modeling, with the innovated multivariate analysis of experts. It was designed through analysis and simulation scenarios and showed which are the most striking events in the study object as well as highlighted the actions could redirect the future of the analyzed system. Moreover, predictions are likely to be developed through the generated scenarios. The model has been validated empirically with road freight transport data from state of Rio Grande do Sul, Brazil. The results showed that the model contributes to the analysis of investment because it identifies probabilities of events that impact on decision making, and identifies priorities for action, reducing uncertainties in the future. Moreover, it allows an interdisciplinary discussion that correlates different areas of knowledge, fundamental when you wish more consistency in creating scenarios.

A viral microRNA functions as an ortholog of cellular miR-155

Science.gov (United States)

Gottwein, Eva; Mukherjee, Neelanjan; Sachse, Christoph; Frenzel, Corina; Majoros, William H.; Chi, Jen-Tsan A.; Braich, Ravi; Manoharan, Muthiah; Soutschek, Jürgen; Ohler, Uwe; Cullen, Bryan R.

2008-01-01

All metazoan eukaryotes express microRNAs (miRNAs), ∼22 nt regulatory RNAs that can repress the expression of mRNAs bearing complementary sequences1. Several DNA viruses also express miRNAs in infected cells, suggesting a role in viral replication and pathogenesis2. While specific viral miRNAs have been shown to autoregulate viral mRNAs3,4 or downregulate cellular mRNAs5,6, the function of the majority of viral miRNAs remains unknown. Here, we report that the miR-K12−11 miRNA encoded by Kaposi's Sarcoma Associated Herpesvirus (KSHV) shows significant homology to cellular miR-155, including the entire miRNA “seed” region7. Using a range of assays, we demonstrate that expression of physiological levels of miR-K12−11 or miR-155 results in the downregulation of an extensive set of common mRNA targets, including genes with known roles in cell growth regulation. Our findings indicate that viral miR-K12−11 functions as an ortholog of cellular miR-155 and has likely evolved to exploit a pre-existing gene regulatory pathway in B-cells. Moreover, the known etiological role of miR-155 in B-cell transformation8-10 suggests that miR-K12−11 may contribute to the induction of KSHV-positive B-cell tumors in infected patients. PMID:18075594

Structural and functional characterization of a novel molluskan ortholog of TRAF and TNF receptor-associated protein from disk abalone (Haliotis discus discus).

Science.gov (United States)

Lee, Youngdeuk; Elvitigala, Don Anushka Sandaruwan; Whang, Ilson; Lee, Sukkyoung; Kim, Hyowon; Zoysa, Mahanama De; Oh, Chulhong; Kang, Do-Hyung; Lee, Jehee

2014-09-01

Immune signaling cascades have an indispensable role in the host defense of almost all the organisms. Tumor necrosis factor (TNF) signaling is considered as a prominent signaling pathway in vertebrate as well as invertebrate species. Within the signaling cascade, TNF receptor-associated factor (TRAF) and TNF receptor-associated protein (TTRAP) has been shown to have a crucial role in the modulation of immune signaling in animals. Here, we attempted to characterize a novel molluskan ortholog of TTRAP (AbTTRAP) from disk abalone (Haliotis discus discus) and analyzed its expression levels under pathogenic stress. The complete coding sequence of AbTTRAP consisted of 1071 nucleotides, coding for a 357 amino acid peptide, with a predicted molecular mass of 40 kDa. According to our in-silico analysis, AbTTRAP resembled the typical TTRAP domain architecture, including a 5'-tyrosyl DNA phosphodiesterase domain. Moreover, phylogenetic analysis revealed its common ancestral invertebrate origin, where AbTTRAP was clustered with molluskan counterparts. Quantitative real time PCR showed universally distributed expression of AbTTRAP in selected tissues of abalone, from which more prominent expression was detected in hemocytes. Upon stimulation with two pathogen-derived mitogens, lipopolysaccharide (LPS) and polyinosinic:polycytidylic acid (poly I:C), transcript levels of AbTTRAP in hemocytes and gill tissues were differentially modulated with time. In addition, the recombinant protein of AbTTRAP exhibited prominent endonuclease activity against abalone genomic DNA, which was enhanced by the presence of Mg(2+) in the medium. Collectively, these results reinforce the existence of the TNF signaling cascade in mollusks like disk abalone, further implicating the putative regulatory behavior of TTRAP in invertebrate host pathology. Copyright © 2014 Elsevier Ltd. All rights reserved.

Integrated Decision Tools for Sustainable Watershed/Ground Water and Crop Health using Predictive Weather, Remote Sensing, and Irrigation Decision Tools

Science.gov (United States)

Jones, A. S.; Andales, A.; McGovern, C.; Smith, G. E. B.; David, O.; Fletcher, S. J.

2017-12-01

US agricultural and Govt. lands have a unique co-dependent relationship, particularly in the Western US. More than 30% of all irrigated US agricultural output comes from lands sustained by the Ogallala Aquifer in the western Great Plains. Six US Forest Service National Grasslands reside within the aquifer region, consisting of over 375,000 ha (3,759 km2) of USFS managed lands. Likewise, National Forest lands are the headwaters to many intensive agricultural regions. Our Ogallala Aquifer team is enhancing crop irrigation decision tools with predictive weather and remote sensing data to better manage water for irrigated crops within these regions. An integrated multi-model software framework is used to link irrigation decision tools, resulting in positive management benefits on natural water resources. Teams and teams-of-teams can build upon these multi-disciplinary multi-faceted modeling capabilities. For example, the CSU Catalyst for Innovative Partnerships program has formed a new multidisciplinary team that will address "Rural Wealth Creation" focusing on the many integrated links between economic, agricultural production and management, natural resource availabilities, and key social aspects of govt. policy recommendations. By enhancing tools like these with predictive weather and other related data (like in situ measurements, hydrologic models, remotely sensed data sets, and (in the near future) linking to agro-economic and life cycle assessment models) this work demonstrates an integrated data-driven future vision of inter-meshed dynamic systems that can address challenging multi-system problems. We will present the present state of the work and opportunities for future involvement.

Accurate Holdup Calculations with Predictive Modeling & Data Integration

Energy Technology Data Exchange (ETDEWEB)

Azmy, Yousry [North Carolina State Univ., Raleigh, NC (United States). Dept. of Nuclear Engineering; Cacuci, Dan [Univ. of South Carolina, Columbia, SC (United States). Dept. of Mechanical Engineering

2017-04-03

Bayes’ Theorem, one must have a model y(x) that maps the state variables x (the solution in this case) to the measurements y. In this case, the unknown state variables are the configuration and composition of the heldup SNM. The measurements are the detector readings. Thus, the natural model is neutral-particle radiation transport where a wealth of computational tools exists for performing these simulations accurately and efficiently. The combination of predictive model and Bayesian inference forms the Data Integration with Modeled Predictions (DIMP) method that serves as foundation for this project. The cost functional describing the model-to-data misfit is computed via a norm created by the inverse of the covariance matrix of the model parameters and responses. Since the model y(x) for the holdup problem is nonlinear, a nonlinear optimization on Q is conducted via Newton-type iterative methods to find the optimal values of the model parameters x. This project comprised a collaboration between NC State University (NCSU), the University of South Carolina (USC), and Oak Ridge National Laboratory (ORNL). The project was originally proposed in seven main tasks with an eighth contingency task to be performed if time and funding permitted; in fact time did not permit commencement of the contingency task and it was not performed. The remaining tasks involved holdup analysis with gamma detection strategies and separately with neutrons based on coincidence counting. Early in the project, and upon consultation with experts in coincidence counting it became evident that this approach is not viable for holdup applications and this task was replaced with an alternative, but valuable investigation that was carried out by the USC partner. Nevertheless, the experimental 4 measurements at ORNL of both gamma and neutron sources for the purpose of constructing Detector Response Functions (DRFs) with the associated uncertainties were indeed completed.

Prediction of degradation and fracture of structural materials

International Nuclear Information System (INIS)

Tomkins, B.

1992-01-01

Prediction of materials performance in an engineering integrity context requires the underpinning of predictive modelling tuned by inputs from design, fabrication, operating experience, and laboratory testing. In this regard, in addition to fracture resistance four important areas of time dependent degradation are considered - mechanical, environmental, irradiation and thermal. The status of prediction of materials performance is discussed in relation to a number of important components such as LWR reactor pressure vessels and steam generators, and Fast Reactor high temperature structures. In each case the role of materials modelling is examined and the balance of factors which contribute to the overall prediction of component integrity/reliability noted. Structural integrity arguments must follow a clear strategy if the required level of confidence is to be established. Various strategies and their evolution are discussed. (author)

Integration of curated databases to identify genotype-phenotype associations

Directory of Open Access Journals (Sweden)

Li Jianrong

2006-10-01

Full Text Available Abstract Background The ability to rapidly characterize an unknown microorganism is critical in both responding to infectious disease and biodefense. To do this, we need some way of anticipating an organism's phenotype based on the molecules encoded by its genome. However, the link between molecular composition (i.e. genotype and phenotype for microbes is not obvious. While there have been several studies that address this challenge, none have yet proposed a large-scale method integrating curated biological information. Here we utilize a systematic approach to discover genotype-phenotype associations that combines phenotypic information from a biomedical informatics database, GIDEON, with the molecular information contained in National Center for Biotechnology Information's Clusters of Orthologous Groups database (NCBI COGs. Results Integrating the information in the two databases, we are able to correlate the presence or absence of a given protein in a microbe with its phenotype as measured by certain morphological characteristics or survival in a particular growth media. With a 0.8 correlation score threshold, 66% of the associations found were confirmed by the literature and at a 0.9 correlation threshold, 86% were positively verified. Conclusion Our results suggest possible phenotypic manifestations for proteins biochemically associated with sugar metabolism and electron transport. Moreover, we believe our approach can be extended to linking pathogenic phenotypes with functionally related proteins.

Fast and General Method To Predict the Physicochemical Properties of Druglike Molecules Using the Integral Equation Theory of Molecular Liquids.

Science.gov (United States)

Palmer, David S; Mišin, Maksim; Fedorov, Maxim V; Llinas, Antonio

2015-09-08

We report a method to predict physicochemical properties of druglike molecules using a classical statistical mechanics based solvent model combined with machine learning. The RISM-MOL-INF method introduced here provides an accurate technique to characterize solvation and desolvation processes based on solute-solvent correlation functions computed by the 1D reference interaction site model of the integral equation theory of molecular liquids. These functions can be obtained in a matter of minutes for most small organic and druglike molecules using existing software (RISM-MOL) (Sergiievskyi, V. P.; Hackbusch, W.; Fedorov, M. V. J. Comput. Chem. 2011, 32, 1982-1992). Predictions of caco-2 cell permeability and hydration free energy obtained using the RISM-MOL-INF method are shown to be more accurate than the state-of-the-art tools for benchmark data sets. Due to the importance of solvation and desolvation effects in biological systems, it is anticipated that the RISM-MOL-INF approach will find many applications in biophysical and biomedical property prediction.

Integrating genomics and proteomics data to predict drug effects using binary linear programming.

Science.gov (United States)

Ji, Zhiwei; Su, Jing; Liu, Chenglin; Wang, Hongyan; Huang, Deshuang; Zhou, Xiaobo

2014-01-01

The Library of Integrated Network-Based Cellular Signatures (LINCS) project aims to create a network-based understanding of biology by cataloging changes in gene expression and signal transduction that occur when cells are exposed to a variety of perturbations. It is helpful for understanding cell pathways and facilitating drug discovery. Here, we developed a novel approach to infer cell-specific pathways and identify a compound's effects using gene expression and phosphoproteomics data under treatments with different compounds. Gene expression data were employed to infer potential targets of compounds and create a generic pathway map. Binary linear programming (BLP) was then developed to optimize the generic pathway topology based on the mid-stage signaling response of phosphorylation. To demonstrate effectiveness of this approach, we built a generic pathway map for the MCF7 breast cancer cell line and inferred the cell-specific pathways by BLP. The first group of 11 compounds was utilized to optimize the generic pathways, and then 4 compounds were used to identify effects based on the inferred cell-specific pathways. Cross-validation indicated that the cell-specific pathways reliably predicted a compound's effects. Finally, we applied BLP to re-optimize the cell-specific pathways to predict the effects of 4 compounds (trichostatin A, MS-275, staurosporine, and digoxigenin) according to compound-induced topological alterations. Trichostatin A and MS-275 (both HDAC inhibitors) inhibited the downstream pathway of HDAC1 and caused cell growth arrest via activation of p53 and p21; the effects of digoxigenin were totally opposite. Staurosporine blocked the cell cycle via p53 and p21, but also promoted cell growth via activated HDAC1 and its downstream pathway. Our approach was also applied to the PC3 prostate cancer cell line, and the cross-validation analysis showed very good accuracy in predicting effects of 4 compounds. In summary, our computational model can be

Integration of QSAR models for bioconcentration suitable for REACH

Energy Technology Data Exchange (ETDEWEB)

Gissi, Andrea [Laboratory of Chemistry and Environmental Toxicology, IRCCS - Istituto di Ricerche Farmacologiche “Mario Negri”, via Giuseppe La Masa 19, 20156 Milan (Italy); Dipartimento di Farmacia — Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, via Orabona 4, I-70125 Bari (Italy); Nicolotti, Orazio; Carotti, Angelo; Gadaleta, Domenico [Dipartimento di Farmacia — Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, via Orabona 4, I-70125 Bari (Italy); Lombardo, Anna [Laboratory of Chemistry and Environmental Toxicology, IRCCS - Istituto di Ricerche Farmacologiche “Mario Negri”, via Giuseppe La Masa 19, 20156 Milan (Italy); Benfenati, Emilio, E-mail: benfenati@marionegri.it [Laboratory of Chemistry and Environmental Toxicology, IRCCS - Istituto di Ricerche Farmacologiche “Mario Negri”, via Giuseppe La Masa 19, 20156 Milan (Italy)

2013-07-01

QSAR (Quantitative Structure Activity Relationship) models can be a valuable alternative method to replace or reduce animal test required by REACH. In particular, some endpoints such as bioconcentration factor (BCF) are easier to predict and many useful models have been already developed. In this paper we describe how to integrate two popular BCF models to obtain more reliable predictions. In particular, the herein presented integrated model relies on the predictions of two among the most used BCF models (CAESAR and Meylan), together with the Applicability Domain Index (ADI) provided by the software VEGA. Using a set of simple rules, the integrated model selects the most reliable and conservative predictions and discards possible outliers. In this way, for the prediction of the 851 compounds included in the ANTARES BCF dataset, the integrated model discloses a R{sup 2} (coefficient of determination) of 0.80, a RMSE (Root Mean Square Error) of 0.61 log units and a sensitivity of 76%, with a considerable improvement in respect to the CAESAR (R{sup 2} = 0.63; RMSE = 0.84 log units; sensitivity 55%) and Meylan (R{sup 2} = 0.66; RMSE = 0.77 log units; sensitivity 65%) without discarding too many predictions (118 out of 851). Importantly, considering solely the compounds within the new integrated ADI, the R{sup 2} increased to 0.92, and the sensitivity to 85%, with a RMSE of 0.44 log units. Finally, the use of properly set safety thresholds applied for monitoring the so called “suspicious” compounds, which are those chemicals predicted in proximity of the border normally accepted to discern non-bioaccumulative from bioaccumulative substances, permitted to obtain an integrated model with sensitivity equal to 100%. - Highlights: • Applying two independent QSAR models for bioconcentration factor increases the prediction. • The concordance of the models is an important component of the integration. • The measurement of the applicability domain improves the

Integration of QSAR models for bioconcentration suitable for REACH

International Nuclear Information System (INIS)

Gissi, Andrea; Nicolotti, Orazio; Carotti, Angelo; Gadaleta, Domenico; Lombardo, Anna; Benfenati, Emilio

2013-01-01

QSAR (Quantitative Structure Activity Relationship) models can be a valuable alternative method to replace or reduce animal test required by REACH. In particular, some endpoints such as bioconcentration factor (BCF) are easier to predict and many useful models have been already developed. In this paper we describe how to integrate two popular BCF models to obtain more reliable predictions. In particular, the herein presented integrated model relies on the predictions of two among the most used BCF models (CAESAR and Meylan), together with the Applicability Domain Index (ADI) provided by the software VEGA. Using a set of simple rules, the integrated model selects the most reliable and conservative predictions and discards possible outliers. In this way, for the prediction of the 851 compounds included in the ANTARES BCF dataset, the integrated model discloses a R 2 (coefficient of determination) of 0.80, a RMSE (Root Mean Square Error) of 0.61 log units and a sensitivity of 76%, with a considerable improvement in respect to the CAESAR (R 2 = 0.63; RMSE = 0.84 log units; sensitivity 55%) and Meylan (R 2 = 0.66; RMSE = 0.77 log units; sensitivity 65%) without discarding too many predictions (118 out of 851). Importantly, considering solely the compounds within the new integrated ADI, the R 2 increased to 0.92, and the sensitivity to 85%, with a RMSE of 0.44 log units. Finally, the use of properly set safety thresholds applied for monitoring the so called “suspicious” compounds, which are those chemicals predicted in proximity of the border normally accepted to discern non-bioaccumulative from bioaccumulative substances, permitted to obtain an integrated model with sensitivity equal to 100%. - Highlights: • Applying two independent QSAR models for bioconcentration factor increases the prediction. • The concordance of the models is an important component of the integration. • The measurement of the applicability domain improves the prediction. • The use of a

An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes.

Science.gov (United States)

Shapira, Stav; Novack, Lena; Bar-Dayan, Yaron; Aharonson-Daniel, Limor

2016-01-01

A comprehensive technique for earthquake-related casualty estimation remains an unmet challenge. This study aims to integrate risk factors related to characteristics of the exposed population and to the built environment in order to improve communities' preparedness and response capabilities and to mitigate future consequences. An innovative model was formulated based on a widely used loss estimation model (HAZUS) by integrating four human-related risk factors (age, gender, physical disability and socioeconomic status) that were identified through a systematic review and meta-analysis of epidemiological data. The common effect measures of these factors were calculated and entered to the existing model's algorithm using logistic regression equations. Sensitivity analysis was performed by conducting a casualty estimation simulation in a high-vulnerability risk area in Israel. the integrated model outcomes indicated an increase in the total number of casualties compared with the prediction of the traditional model; with regard to specific injury levels an increase was demonstrated in the number of expected fatalities and in the severely and moderately injured, and a decrease was noted in the lightly injured. Urban areas with higher populations at risk rates were found more vulnerable in this regard. The proposed model offers a novel approach that allows quantification of the combined impact of human-related and structural factors on the results of earthquake casualty modelling. Investing efforts in reducing human vulnerability and increasing resilience prior to an occurrence of an earthquake could lead to a possible decrease in the expected number of casualties.

CTDB: An Integrated Chickpea Transcriptome Database for Functional and Applied Genomics.

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Mohit Verma

Full Text Available Chickpea is an important grain legume used as a rich source of protein in human diet. The narrow genetic diversity and limited availability of genomic resources are the major constraints in implementing breeding strategies and biotechnological interventions for genetic enhancement of chickpea. We developed an integrated Chickpea Transcriptome Database (CTDB, which provides the comprehensive web interface for visualization and easy retrieval of transcriptome data in chickpea. The database features many tools for similarity search, functional annotation (putative function, PFAM domain and gene ontology search and comparative gene expression analysis. The current release of CTDB (v2.0 hosts transcriptome datasets with high quality functional annotation from cultivated (desi and kabuli types and wild chickpea. A catalog of transcription factor families and their expression profiles in chickpea are available in the database. The gene expression data have been integrated to study the expression profiles of chickpea transcripts in major tissues/organs and various stages of flower development. The utilities, such as similarity search, ortholog identification and comparative gene expression have also been implemented in the database to facilitate comparative genomic studies among different legumes and Arabidopsis. Furthermore, the CTDB represents a resource for the discovery of functional molecular markers (microsatellites and single nucleotide polymorphisms between different chickpea types. We anticipate that integrated information content of this database will accelerate the functional and applied genomic research for improvement of chickpea. The CTDB web service is freely available at http://nipgr.res.in/ctdb.html.

Integration of fluvial erosion factors for predicting landslides along meandering rivers

Science.gov (United States)

Chen, Yi-chin; Chang, Kang-tsung; Ho, Jui-yi

2015-04-01

the bank from erosion. Finally, the results also showed that the integration of fluvial erosion factors can improve the performance in predicting landsliding along meandering rivers.

Predicting phenology by integrating ecology, evolution and climate science

Science.gov (United States)

Pau, Stephanie; Wolkovich, Elizabeth M.; Cook, Benjamin I.; Davies, T. Jonathan; Kraft, Nathan J.B.; Bolmgren, Kjell; Betancourt, Julio L.; Cleland, Elsa E.

2011-01-01

Forecasting how species and ecosystems will respond to climate change has been a major aim of ecology in recent years. Much of this research has focused on phenology — the timing of life-history events. Phenology has well-demonstrated links to climate, from genetic to landscape scales; yet our ability to explain and predict variation in phenology across species, habitats and time remains poor. Here, we outline how merging approaches from ecology, climate science and evolutionary biology can advance research on phenological responses to climate variability. Using insight into seasonal and interannual climate variability combined with niche theory and community phylogenetics, we develop a predictive approach for species' reponses to changing climate. Our approach predicts that species occupying higher latitudes or the early growing season should be most sensitive to climate and have the most phylogenetically conserved phenologies. We further predict that temperate species will respond to climate change by shifting in time, while tropical species will respond by shifting space, or by evolving. Although we focus here on plant phenology, our approach is broadly applicable to ecological research of plant responses to climate variability.

Reward and Cognition: Integrating Reinforcement Sensitivity Theory and Social Cognitive Theory to Predict Drinking Behavior.

Science.gov (United States)

Hasking, Penelope; Boyes, Mark; Mullan, Barbara

2015-01-01

Both Reinforcement Sensitivity Theory and Social Cognitive Theory have been applied to understanding drinking behavior. We propose that theoretical relationships between these models support an integrated approach to understanding alcohol use and misuse. We aimed to test an integrated model in which the relationships between reward sensitivity and drinking behavior (alcohol consumption, alcohol-related problems, and symptoms of dependence) were mediated by alcohol expectancies and drinking refusal self-efficacy. Online questionnaires assessing the constructs of interest were completed by 443 Australian adults (M age = 26.40, sd = 1.83) in 2013 and 2014. Path analysis revealed both direct and indirect effects and implicated two pathways to drinking behavior with differential outcomes. Drinking refusal self-efficacy both in social situations and for emotional relief was related to alcohol consumption. Sensitivity to reward was associated with alcohol-related problems, but operated through expectations of increased confidence and personal belief in the ability to limit drinking in social situations. Conversely, sensitivity to punishment operated through negative expectancies and drinking refusal self-efficacy for emotional relief to predict symptoms of dependence. Two pathways relating reward sensitivity, alcohol expectancies, and drinking refusal self-efficacy may underlie social and dependent drinking, which has implications for development of intervention to limit harmful drinking.

Integrated Theory of Planned Behavior with Extrinsic Motivation to Predict Intention Not to Use Illicit Drugs by Fifth-Grade Students in Taiwan

Science.gov (United States)

Liao, Jung-Yu; Chang, Li-Chun; Hsu, Hsiao-Pei; Huang, Chiu-Mieh; Huang, Su-Fei; Guo, Jong-Long

2017-01-01

This study assessed the effects of a model that integrated the theory of planned behavior (TPB) with extrinsic motivation (EM) in predicting the intentions of fifth-grade students to not use illicit drugs. A cluster-sampling design was adopted in a cross-sectional survey (N = 571). The structural equation modeling results showed that the model…

Protein Sorting Prediction

DEFF Research Database (Denmark)

Nielsen, Henrik

2017-01-01

and drawbacks of each of these approaches is described through many examples of methods that predict secretion, integration into membranes, or subcellular locations in general. The aim of this chapter is to provide a user-level introduction to the field with a minimum of computational theory.......Many computational methods are available for predicting protein sorting in bacteria. When comparing them, it is important to know that they can be grouped into three fundamentally different approaches: signal-based, global-property-based and homology-based prediction. In this chapter, the strengths...

Comparative Genomics of Glossina palpalis gambiensis and G. morsitans morsitans to Reveal Gene Orthologs Involved in Infection by Trypanosoma brucei gambiense.

Science.gov (United States)

Hamidou Soumana, Illiassou; Tchicaya, Bernadette; Rialle, Stéphanie; Parrinello, Hugues; Geiger, Anne

2017-01-01

Blood-feeding Glossina palpalis gambiense (Gpg) fly transmits the single-celled eukaryotic parasite Trypanosoma brucei gambiense (Tbg), the second Glossina fly African trypanosome pair being Glossina morsitans / T .brucei rhodesiense. Whatever the T. brucei subspecies, whereas the onset of their developmental program in the zoo-anthropophilic blood feeding flies does unfold in the fly midgut, its completion is taking place in the fly salivary gland where does emerge a low size metacyclic trypomastigote population displaying features that account for its establishment in mammals-human individuals included. Considering that the two Glossina - T. brucei pairs introduced above share similarity with respect to the developmental program of this African parasite, we were curious to map on the Glossina morsitans morsitans (Gmm), the Differentially Expressed Genes (DEGs) we listed in a previous study. Briefly, using the gut samples collected at days 3, 10, and 20 from Gpg that were fed or not at day 0 on Tbg-hosting mice, these DGE lists were obtained from RNA seq-based approaches. Here, post the mapping on the quality controlled DEGs on the Gmm genome, the identified ortholog genes were further annotated, the resulting datasets being compared. Around 50% of the Gpg DEGs were shown to have orthologs in the Gmm genome. Under one of the three Glossina midgut sampling conditions, the number of DEGs was even higher when mapping on the Gmm genome than initially recorded. Many Gmm genes annotated as "Hypothetical" were mapped and annotated on many distinct databases allowing some of them to be properly identified. We identify Glossina fly candidate genes encoding (a) a broad panel of proteases as well as (b) chitin-binding proteins, (c) antimicrobial peptide production-Pro3 protein, transferrin, mucin, atttacin, cecropin, etc-to further select in functional studies, the objectives being to probe and validated fly genome manipulation that prevents the onset of the developmental

Comparison of orthologous cyanobacterial aldehyde deformylating oxygenases in the production of volatile C3-C7 alkanes in engineered E. coli

Directory of Open Access Journals (Sweden)

Pekka Patrikainen

2017-12-01

Full Text Available Aldehyde deformylating oxygenase (ADO is a unique enzyme found exclusively in photosynthetic cyanobacteria, which natively converts acyl aldehyde precursors into hydrocarbon products embedded in cellular lipid bilayers. This capacity has opened doors for potential biotechnological applications aiming at biological production of diesel-range alkanes and alkenes, which are compatible with the nonrenewable petroleum-derived end-products in current use. The development of production platforms, however, has been limited by the relative inefficiency of ADO enzyme, promoting research towards finding new strategies and information to be used for rational design of enhanced pathways for hydrocarbon over-expression. In this work we present an optimized approach to study different ADO orthologs derived from different cyanobacterial species in an in vivo set-up in Escherichia coli. The system enabled comparison of alternative ADOs for the production efficiency of short-chain volatile C3-C7 alkanes, propane, pentane and heptane, and provided insight on the differences in substrate preference, catalytic efficiency and limitations associated with the enzymes. The work concentrated on five ADO orthologs which represent the most extensively studied cyanobacterial species in the field, and revealed distinct differences between the enzymes. In most cases the ADO from Nostoc punctiforme PCC 73102 performed the best in respect to yields and initial rates for the production of the volatile hydrocarbons. At the other extreme, the system harboring the ADO form Synechococcus sp. RS9917 produced very low amounts of the short-chain alkanes, primarily due to poor accumulation of the enzyme in E. coli. The ADOs from Synechocystis sp. PCC 6803 and Prochlorococcus marinus MIT9313, and the corresponding variant A134F displayed less divergence, although variation between chain-length preferences could be observed. The results confirmed the general trend of ADOs having

Predictive Analytics in Information Systems Research

OpenAIRE

Shmueli, Galit; Koppius, Otto

2011-01-01

textabstractThis research essay highlights the need to integrate predictive analytics into information systems research and shows several concrete ways in which this goal can be accomplished. Predictive analytics include empirical methods (statistical and other) that generate data predictions as well as methods for assessing predictive power. Predictive analytics not only assist in creating practically useful models, they also play an important role alongside explanatory modeling in theory bu...

Prediction of total organic carbon content in shale reservoir based on a new integrated hybrid neural network and conventional well logging curves

Science.gov (United States)

Zhu, Linqi; Zhang, Chong; Zhang, Chaomo; Wei, Yang; Zhou, Xueqing; Cheng, Yuan; Huang, Yuyang; Zhang, Le

2018-06-01

There is increasing interest in shale gas reservoirs due to their abundant reserves. As a key evaluation criterion, the total organic carbon content (TOC) of the reservoirs can reflect its hydrocarbon generation potential. The existing TOC calculation model is not very accurate and there is still the possibility for improvement. In this paper, an integrated hybrid neural network (IHNN) model is proposed for predicting the TOC. This is based on the fact that the TOC information on the low TOC reservoir, where the TOC is easy to evaluate, comes from a prediction problem, which is the inherent problem of the existing algorithm. By comparing the prediction models established in 132 rock samples in the shale gas reservoir within the Jiaoshiba area, it can be seen that the accuracy of the proposed IHNN model is much higher than that of the other prediction models. The mean square error of the samples, which were not joined to the established models, was reduced from 0.586 to 0.442. The results show that TOC prediction is easier after logging prediction has been improved. Furthermore, this paper puts forward the next research direction of the prediction model. The IHNN algorithm can help evaluate the TOC of a shale gas reservoir.

The clustering-based case-based reasoning for imbalanced business failure prediction: a hybrid approach through integrating unsupervised process with supervised process

Science.gov (United States)

Li, Hui; Yu, Jun-Ling; Yu, Le-An; Sun, Jie

2014-05-01

Case-based reasoning (CBR) is one of the main forecasting methods in business forecasting, which performs well in prediction and holds the ability of giving explanations for the results. In business failure prediction (BFP), the number of failed enterprises is relatively small, compared with the number of non-failed ones. However, the loss is huge when an enterprise fails. Therefore, it is necessary to develop methods (trained on imbalanced samples) which forecast well for this small proportion of failed enterprises and performs accurately on total accuracy meanwhile. Commonly used methods constructed on the assumption of balanced samples do not perform well in predicting minority samples on imbalanced samples consisting of the minority/failed enterprises and the majority/non-failed ones. This article develops a new method called clustering-based CBR (CBCBR), which integrates clustering analysis, an unsupervised process, with CBR, a supervised process, to enhance the efficiency of retrieving information from both minority and majority in CBR. In CBCBR, various case classes are firstly generated through hierarchical clustering inside stored experienced cases, and class centres are calculated out by integrating cases information in the same clustered class. When predicting the label of a target case, its nearest clustered case class is firstly retrieved by ranking similarities between the target case and each clustered case class centre. Then, nearest neighbours of the target case in the determined clustered case class are retrieved. Finally, labels of the nearest experienced cases are used in prediction. In the empirical experiment with two imbalanced samples from China, the performance of CBCBR was compared with the classical CBR, a support vector machine, a logistic regression and a multi-variant discriminate analysis. The results show that compared with the other four methods, CBCBR performed significantly better in terms of sensitivity for identifying the

Predicting freshwater habitat integrity using land-use surrogates

CSIR Research Space (South Africa)

Amis, MA

2007-04-01

Full Text Available Freshwater biodiversity is globally threatened due to human disturbances, but freshwater ecosystems have been accorded less protection than their terrestrial and marine counterparts. Few criteria exist for assessing the habitat integrity of rivers...

Model predictive control using fuzzy decision functions

NARCIS (Netherlands)

Kaymak, U.; Costa Sousa, da J.M.

2001-01-01

Fuzzy predictive control integrates conventional model predictive control with techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the (fuzzy) goals and the (fuzzy) constraints of the

An approximation to the adaptive exponential integrate-and-fire neuron model allows fast and predictive fitting to physiological data

Directory of Open Access Journals (Sweden)

Loreen eHertäg

2012-09-01

Full Text Available For large-scale network simulations, it is often desirable to have computationally tractable, yet in a defined sense still physiologically valid neuron models. In particular, these models should be able to reproduce physiological measurements, ideally in a predictive sense, and under different input regimes in which neurons may operate in vivo. Here we present an approach to parameter estimation for a simple spiking neuron model mainly based on standard f-I curves obtained from in vitro recordings. Such recordings are routinely obtained in standard protocols and assess a neuron's response under a wide range of mean input currents. Our fitting procedure makes use of closed-form expressions for the firing rate derived from an approximation to the adaptive exponential integrate-and-fire (AdEx model. The resulting fitting process is simple and about two orders of magnitude faster compared to methods based on numerical integration of the differential equations. We probe this method on different cell types recorded from rodent prefrontal cortex. After fitting to the f-I current-clamp data, the model cells are tested on completely different sets of recordings obtained by fluctuating ('in-vivo-like' input currents. For a wide range of different input regimes, cell types, and cortical layers, the model could predict spike times on these test traces quite accurately within the bounds of physiological reliability, although no information from these distinct test sets was used for model fitting. Further analyses delineated some of the empirical factors constraining model fitting and the model's generalization performance. An even simpler adaptive LIF neuron was also examined in this context. Hence, we have developed a 'high-throughput' model fitting procedure which is simple and fast, with good prediction performance, and which relies only on firing rate information and standard physiological data widely and easily available.

Vorticity confinement technique for drag prediction

Science.gov (United States)

Povitsky, Alex; Snyder, Troy

2011-11-01

This work couples wake-integral drag prediction and vorticity confinement technique (VC) for the improved prediction of drag from CFD simulations. Induced drag computations of a thin wing are shown to be more accurate than the more widespread method of surface pressure integration when compared to theoretical lifting-line value. Furthermore, the VC method improves trailing vortex preservation and counteracts the shift from induced drag to numerical entropy drag with increasing distance of Trefftz plane downstream of the wing. Accurate induced drag prediction via the surface integration of pressure barring a sufficiently refined surface grid and increased computation time. Furthermore, the alternative wake-integral technique for drag prediction suffers from numerical dissipation. VC is shown to control the numerical dissipation with very modest computational overhead. The 2-D research code is used to test specific formulations of the VC body force terms and illustrate the computational efficiency of the method compared to a ``brute force'' reduction in spatial step size. For the 3-D wing simulation, ANSYS FLUENT is employed with the VC body force terms added to the solver with user-defined functions (UDFs). VC is successfully implemented to highly unsteady flows typical for Micro Air Vehicles (MAV) producing oscillative drag force either by natural vortex shedding at high angles of attack or by flapping wing motion.

Long-time predictions in nonlinear dynamics

Science.gov (United States)

Szebehely, V.

1980-01-01

It is known that nonintegrable dynamical systems do not allow precise predictions concerning their behavior for arbitrary long times. The available series solutions are not uniformly convergent according to Poincare's theorem and numerical integrations lose their meaningfulness after the elapse of arbitrary long times. Two approaches are the use of existing global integrals and statistical methods. This paper presents a generalized method along the first approach. As examples long-time predictions in the classical gravitational satellite and planetary problems are treated.

An integrated unscented kalman filter and relevance vector regression approach for lithium-ion battery remaining useful life and short-term capacity prediction

International Nuclear Information System (INIS)

Zheng, Xiujuan; Fang, Huajing

2015-01-01

The gradual decreasing capacity of lithium-ion batteries can serve as a health indicator for tracking the degradation of lithium-ion batteries. It is important to predict the capacity of a lithium-ion battery for future cycles to assess its health condition and remaining useful life (RUL). In this paper, a novel method is developed using unscented Kalman filter (UKF) with relevance vector regression (RVR) and applied to RUL and short-term capacity prediction of batteries. A RVR model is employed as a nonlinear time-series prediction model to predict the UKF future residuals which otherwise remain zero during the prediction period. Taking the prediction step into account, the predictive value through the RVR method and the latest real residual value constitute the future evolution of the residuals with a time-varying weighting scheme. Next, the future residuals are utilized by UKF to recursively estimate the battery parameters for predicting RUL and short-term capacity. Finally, the performance of the proposed method is validated and compared to other predictors with the experimental data. According to the experimental and analysis results, the proposed approach has high reliability and prediction accuracy, which can be applied to battery monitoring and prognostics, as well as generalized to other prognostic applications. - Highlights: • An integrated method is proposed for RUL prediction as well as short-term capacity prediction. • Relevance vector regression model is employed as a nonlinear time-series prediction model. • Unscented Kalman filter is used to recursively update the states for battery model parameters during the prediction. • A time-varying weighting scheme is utilized to improve the accuracy of the RUL prediction. • The proposed method demonstrates high reliability and prediction accuracy.

Systems integration.

Science.gov (United States)

Siemieniuch, C E; Sinclair, M A

2006-01-01

The paper presents a view of systems integration, from an ergonomics/human factors perspective, emphasising the process of systems integration as is carried out by humans. The first section discusses some of the fundamental issues in systems integration, such as the significance of systems boundaries, systems lifecycle and systems entropy, issues arising from complexity, the implications of systems immortality, and so on. The next section outlines various generic processes for executing systems integration, to act as guides for practitioners. These address both the design of the system to be integrated and the preparation of the wider system in which the integration will occur. Then the next section outlines some of the human-specific issues that would need to be addressed in such processes; for example, indeterminacy and incompleteness, the prediction of human reliability, workload issues, extended situation awareness, and knowledge lifecycle management. For all of these, suggestions and further readings are proposed. Finally, the conclusions section reiterates in condensed form the major issues arising from the above.

Predictive Systems Toxicology

KAUST Repository

Kiani, Narsis A.; Shang, Ming-Mei; Zenil, Hector; Tegner, Jesper

2018-01-01

In this review we address to what extent computational techniques can augment our ability to predict toxicity. The first section provides a brief history of empirical observations on toxicity dating back to the dawn of Sumerian civilization. Interestingly, the concept of dose emerged very early on, leading up to the modern emphasis on kinetic properties, which in turn encodes the insight that toxicity is not solely a property of a compound but instead depends on the interaction with the host organism. The next logical step is the current conception of evaluating drugs from a personalized medicine point-of-view. We review recent work on integrating what could be referred to as classical pharmacokinetic analysis with emerging systems biology approaches incorporating multiple omics data. These systems approaches employ advanced statistical analytical data processing complemented with machine learning techniques and use both pharmacokinetic and omics data. We find that such integrated approaches not only provide improved predictions of toxicity but also enable mechanistic interpretations of the molecular mechanisms underpinning toxicity and drug resistance. We conclude the chapter by discussing some of the main challenges, such as how to balance the inherent tension between the predictive capacity of models, which in practice amounts to constraining the number of features in the models versus allowing for rich mechanistic interpretability, i.e. equipping models with numerous molecular features. This challenge also requires patient-specific predictions on toxicity, which in turn requires proper stratification of patients as regards how they respond, with or without adverse toxic effects. In summary, the transformation of the ancient concept of dose is currently successfully operationalized using rich integrative data encoded in patient-specific models.

Predictive Systems Toxicology

KAUST Repository

Kiani, Narsis A.

2018-01-15

In this review we address to what extent computational techniques can augment our ability to predict toxicity. The first section provides a brief history of empirical observations on toxicity dating back to the dawn of Sumerian civilization. Interestingly, the concept of dose emerged very early on, leading up to the modern emphasis on kinetic properties, which in turn encodes the insight that toxicity is not solely a property of a compound but instead depends on the interaction with the host organism. The next logical step is the current conception of evaluating drugs from a personalized medicine point-of-view. We review recent work on integrating what could be referred to as classical pharmacokinetic analysis with emerging systems biology approaches incorporating multiple omics data. These systems approaches employ advanced statistical analytical data processing complemented with machine learning techniques and use both pharmacokinetic and omics data. We find that such integrated approaches not only provide improved predictions of toxicity but also enable mechanistic interpretations of the molecular mechanisms underpinning toxicity and drug resistance. We conclude the chapter by discussing some of the main challenges, such as how to balance the inherent tension between the predictive capacity of models, which in practice amounts to constraining the number of features in the models versus allowing for rich mechanistic interpretability, i.e. equipping models with numerous molecular features. This challenge also requires patient-specific predictions on toxicity, which in turn requires proper stratification of patients as regards how they respond, with or without adverse toxic effects. In summary, the transformation of the ancient concept of dose is currently successfully operationalized using rich integrative data encoded in patient-specific models.

Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics.

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István A Kovács

Full Text Available BACKGROUND: Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. METHODOLOGY/PRINCIPAL FINDINGS: Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1 determine persvasively overlapping modules with high resolution; (2 uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3 allow the determination of key network nodes and (4 help to predict network dynamics. CONCLUSIONS/SIGNIFICANCE: The concept opens a wide range of possibilities to develop new approaches and applications including network routing, classification, comparison and prediction.

Improving protein function prediction methods with integrated literature data

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Gabow Aaron P

2008-04-01

Full Text Available Abstract Background Determining the function of uncharacterized proteins is a major challenge in the post-genomic era due to the problem's complexity and scale. Identifying a protein's function contributes to an understanding of its role in the involved pathways, its suitability as a drug target, and its potential for protein modifications. Several graph-theoretic approaches predict unidentified functions of proteins by using the functional annotations of better-characterized proteins in protein-protein interaction networks. We systematically consider the use of literature co-occurrence data, introduce a new method for quantifying the reliability of co-occurrence and test how performance differs across species. We also quantify changes in performance as the prediction algorithms annotate with increased specificity. Results We find that including information on the co-occurrence of proteins within an abstract greatly boosts performance in the Functional Flow graph-theoretic function prediction algorithm in yeast, fly and worm. This increase in performance is not simply due to the presence of additional edges since supplementing protein-protein interactions with co-occurrence data outperforms supplementing with a comparably-sized genetic interaction dataset. Through the combination of protein-protein interactions and co-occurrence data, the neighborhood around unknown proteins is quickly connected to well-characterized nodes which global prediction algorithms can exploit. Our method for quantifying co-occurrence reliability shows superior performance to the other methods, particularly at threshold values around 10% which yield the best trade off between coverage and accuracy. In contrast, the traditional way of asserting co-occurrence when at least one abstract mentions both proteins proves to be the worst method for generating co-occurrence data, introducing too many false positives. Annotating the functions with greater specificity is harder

Quantification of design margins and safety factors based on the prediction uncertainty in tritium production rate from fusion integral experiments of the USDOE/JAERI collaborative program on fusion blanket neutronics

International Nuclear Information System (INIS)

Youssef, M.Z.; Konno, C.; Maekawa, F.; Ikeda, Y.; Kosako, K.; Nakagawa, M.; Mori, T.; Maekawa, H.

1995-01-01

Several fusion integral experiments were performed within a collaboration between the USA and Japan on fusion breeder neutronics aimed at verifying the prediction accuracy of key neutronics parameters in a fusion reactor blanket based on current neutron transport codes and basic nuclear databases. The focus has been on the tritium production rate (TRP) as an important design parameter to resolve the issue of tritium self-sufficiency in a fusion reactor. In this paper, the calculational and experimental uncertainties (errors) in local TPR in each experiment performed i were interpolated and propagated to estimate the prediction uncertainty u i in the line-integrated TPR and its standard deviation σ i . The measured data are based on Li-glass and NE213 detectors. From the quantities u i and σ i , normalized density functions (NDFs) were constructed, considering all the experiments and their associated analyses performed independently by the UCLA and JAERI. Several statistical parameters were derived, including the mean prediction uncertainties u and the possible spread ±σ u around them. Design margins and safety factors were derived from these NDFs. Distinction was made between the results obtained by UCLA and JAERI and between calculational results based on the discrete ordinates and Monte Carlo methods. The prediction uncertainties, their standard deviations and the design margins and safety factors were derived for the line-integrated TPR from Li-6 T 6 , and Li-7 T 7 . These parameters were used to estimate the corresponding uncertainties and safety factor for the line-integrated TPR from natural lithium T n . (orig.)

[Integrity].

Science.gov (United States)

Gómez Rodríguez, Rafael Ángel

2014-01-01

To say that someone possesses integrity is to claim that that person is almost predictable about responses to specific situations, that he or she can prudentially judge and to act correctly. There is a closed interrelationship between integrity and autonomy, and the autonomy rests on the deeper moral claim of all humans to integrity of the person. Integrity has two senses of significance for medical ethic: one sense refers to the integrity of the person in the bodily, psychosocial and intellectual elements; and in the second sense, the integrity is the virtue. Another facet of integrity of the person is la integrity of values we cherish and espouse. The physician must be a person of integrity if the integrity of the patient is to be safeguarded. The autonomy has reduced the violations in the past, but the character and virtues of the physician are the ultimate safeguard of autonomy of patient. A field very important in medicine is the scientific research. It is the character of the investigator that determines the moral quality of research. The problem arises when legitimate self-interests are replaced by selfish, particularly when human subjects are involved. The final safeguard of moral quality of research is the character and conscience of the investigator. Teaching must be relevant in the scientific field, but the most effective way to teach virtue ethics is through the example of the a respected scientist.

Middle and long-term prediction of UT1-UTC based on combination of Gray Model and Autoregressive Integrated Moving Average

Science.gov (United States)

Jia, Song; Xu, Tian-he; Sun, Zhang-zhen; Li, Jia-jing

2017-02-01

UT1-UTC is an important part of the Earth Orientation Parameters (EOP). The high-precision predictions of UT1-UTC play a key role in practical applications of deep space exploration, spacecraft tracking and satellite navigation and positioning. In this paper, a new prediction method with combination of Gray Model (GM(1, 1)) and Autoregressive Integrated Moving Average (ARIMA) is developed. The main idea is as following. Firstly, the UT1-UTC data are preprocessed by removing the leap second and Earth's zonal harmonic tidal to get UT1R-TAI data. Periodic terms are estimated and removed by the least square to get UT2R-TAI. Then the linear terms of UT2R-TAI data are modeled by the GM(1, 1), and the residual terms are modeled by the ARIMA. Finally, the UT2R-TAI prediction can be performed based on the combined model of GM(1, 1) and ARIMA, and the UT1-UTC predictions are obtained by adding the corresponding periodic terms, leap second correction and the Earth's zonal harmonic tidal correction. The results show that the proposed model can be used to predict UT1-UTC effectively with higher middle and long-term (from 32 to 360 days) accuracy than those of LS + AR, LS + MAR and WLS + MAR.

Sina and Sinb genes in triticale do not determine grain hardness contrary to their orthologs Pina and Pinb in wheat.

Science.gov (United States)

Gasparis, Sebastian; Orczyk, Waclaw; Nadolska-Orczyk, Anna

2013-11-26

Secaloindoline a (Sina) and secaloindoline b (Sinb) genes of hexaploid triticale (x Triticosecale Wittmack) are orthologs of puroindoline a (Pina) and puroindoline b (Pinb) in hexaploid wheat (Triticum aestivum L.). It has already been proven that RNA interference (RNAi)-based silencing of Pina and Pinb genes significantly decreased the puroindoline a and puroindoline b proteins in wheat and essentially increased grain hardness (J Exp Bot 62:4025-4036, 2011). The function of Sina and Sinb in triticale was tested by means of RNAi silencing and compared to wheat. Novel Sina and Sinb alleles in wild-type plants of cv. Wanad were identified and their expression profiles characterized. Alignment with wheat Pina-D1a and Pinb-D1a alleles showed 95% and 93.3% homology with Sina and Sinb coding sequences. Twenty transgenic lines transformed with two hpRNA silencing cassettes directed to silence Sina or Sinb were obtained by the Agrobacterium-mediated method. A significant decrease of expression of both Sin genes in segregating progeny of tested T1 lines was observed independent of the silencing cassette used. The silencing was transmitted to the T4 kernel generation. The relative transcript level was reduced by up to 99% in T3 progeny with the mean for the sublines being around 90%. Silencing of the Sin genes resulted in a substantial decrease of secaloindoline a and secaloindoline b content. The identity of SIN peptides was confirmed by mass spectrometry. The hardness index, measured by the SKCS (Single Kernel Characterization System) method, ranged from 22 to 56 in silent lines and from 37 to 49 in the control, and the mean values were insignificantly lower in the silent ones, proving increased softness. Additionally, the mean total seed protein content of silenced lines was about 6% lower compared with control lines. Correlation coefficients between hardness and transcript level were weakly positive. We documented that RNAi-based silencing of Sin genes resulted in

Predicting body appreciation in young women: An integrated model of positive body image.

Science.gov (United States)

Andrew, Rachel; Tiggemann, Marika; Clark, Levina

2016-09-01

This study examined a range of predictors, based on previous theoretical models, of positive body image in young adult women. Participants were 266 women who completed an online questionnaire measuring body appreciation, activity participation, media consumption, perceived body acceptance by others, self-compassion, and autonomy. Potential mechanisms in predicting body appreciation assessed were self-objectification, social appearance comparison, and thin-ideal internalisation. Results indicated that greater perceived body acceptance by others and self-compassion, and lower appearance media consumption, self-objectification, social comparison, and thin-ideal internalisation were related to greater body appreciation. An integrated model showed that appearance media (negatively) and non-appearance media and self-compassion (positively) were associated with lower self-objectification, social comparison, and thin-ideal internalisation, which in turn related to greater body appreciation. Additionally, perceived body acceptance by others was directly associated with body appreciation. The results contribute to an understanding of potential pathways of positive body image development, thereby highlighting possible intervention targets. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identification of four families of yCCR4- and Mg2+-dependent endonuclease-related proteins in higher eukaryotes, and characterization of orthologs of yCCR4 with a conserved leucine-rich repeat essential for hCAF1/hPOP2 binding

Directory of Open Access Journals (Sweden)

Corbo Laura

2001-11-01

Full Text Available Abstract Background The yeast yCCR4 factor belongs to the CCR4-NOT transcriptional regulatory complex, in which it interacts, through its leucine-rich repeat (LRR motif with yPOP2. Recently, yCCR4 was shown to be a component of the major cytoplasmic mRNA deadenylase complex, and to contain a fold related to the Mg2+-dependent endonuclease core. Results Here, we report the identification of nineteen yCCR4-related proteins in eukaryotes (including yeast, plants and animals, which all contain the yCCR4 endonuclease-like fold, with highly conserved CCR4-specific residues. Phylogenetic and genomic analyses show that they form four distinct families, one of which contains the yCCR4 orthologs. The orthologs in animals possess a leucine-rich repeat domain. We show, using two-hybrid and far-Western assays, that the human member binds to the human yPOP2 homologs, i.e. hCAF1 and hPOP2, in a LRR-dependent manner. Conclusions We have identified the mammalian orthologs of yCCR4 and have shown that the human member binds to the human yPOP2 homologs, thus strongly suggesting conservation of the CCR4-NOT complex from yeast to human. All members of the four identified yCCR4-related protein families show stricking conservation of the endonuclease-like catalytic motifs of the yCCR4 C-terminal domain and therefore constitute a new family of potential deadenylases in mammals.

Orthology Analysis and In Vivo Complementation Studies to Elucidate the Role of DIR1 during Systemic Acquired Resistance in Arabidopsis thaliana and Cucumis sativus

Directory of Open Access Journals (Sweden)

Marisa Isaacs

2016-05-01

Full Text Available AtDIR1 (Defective in Induced Resistance1 is an acidic lipid transfer protein essential for systemic acquired resistance (SAR in Arabidopsis thaliana. Upon SAR induction, DIR1 moves from locally infected to distant uninfected leaves to activate defense priming; however, a molecular function for DIR1 has not been elucidated. Bioinformatic analysis and in silico homology modeling identified putative AtDIR1 orthologs in crop species, revealing conserved protein motifs within and outside of DIR1’s central hydrophobic cavity. In vitro assays to compare the capacity of recombinant AtDIR1 and targeted AtDIR1-variant proteins to bind the lipophilic probe TNS (6,P-toluidinylnaphthalene-2-sulfonate provided evidence that conserved leucine 43 and aspartic acid 39 contribute to the size of the DIR1 hydrophobic cavity and possibly hydrophobic ligand binding. An Arabidopsis–cucumber SAR model was developed to investigate the conservation of DIR1 function in cucumber (Cucumis sativus, and we demonstrated that phloem exudates from SAR-induced cucumber rescued the SAR defect in the Arabidopsis dir1-1 mutant. Additionally, an AtDIR1 antibody detected a protein of the same size as AtDIR1 in SAR-induced cucumber phloem exudates, providing evidence that DIR1 function during SAR is conserved in Arabidopsis and cucumber. In vitro TNS displacement assays demonstrated that recombinant AtDIR1 did not bind the SAR signals azelaic acid (AzA, glycerol-3-phosphate or pipecolic acid. However, recombinant CsDIR1 and CsDIR2 interacted weakly with AzA and pipecolic acid. Bioinformatic and functional analyses using the Arabidopsis–cucumber SAR model provide evidence that DIR1 orthologs exist in tobacco, tomato, cucumber, and soybean, and that DIR1-mediated SAR signaling is conserved in Arabidopsis and cucumber.

With a little help from my goals: integrating intergoal facilitation with the theory of planned behaviour to predict physical activity.

Science.gov (United States)

Presseau, Justin; Sniehotta, Falko F; Francis, Jill J; Gebhardt, Winifred A

2010-11-01

Integration of a multiple goal theory approach into the theory of planned behaviour (TPB) to investigate how the perceived facilitating and conflicting relationships in multiple goal pursuit predict performance of a health-related behaviour. Prospective design with 8-week follow-up. At baseline, perceived intergoal facilitation and intergoal conflict were measured using personal projects analysis supplemented with standard TPB measures for physical activity (PA). Self-reported PA was measured at follow-up 8 weeks later. N=137 participants completed measures at both time points (55.4% response rate at follow-up). Hierarchical regression showed that perceived intergoal facilitation, but not intergoal conflict, directly predicted PA beyond intention and perceived behavioural control (PBC), accounting for more than 4% of additional variance in PA. Intergoal facilitation had an indirect effect on intention through attitude and PBC, and intention partially mediated the effect of intergoal facilitation on behaviour. The perceived facilitating effect of pursuing other personal goals predicts the performance of a health-related behaviour over and above single behaviour-focused social cognitions.

Reprogramming the phenylpropanoid metabolism in seeds of oilseed rape by suppressing the orthologs of reduced epidermal fluorescence1.

Science.gov (United States)

Mittasch, Juliane; Böttcher, Christoph; Frolov, Andrej; Strack, Dieter; Milkowski, Carsten

2013-04-01

As a result of the phenylpropanoid pathway, many Brassicaceae produce considerable amounts of soluble hydroxycinnamate conjugates, mainly sinapate esters. From oilseed rape (Brassica napus), we cloned two orthologs of the Arabidopsis (Arabidopsis thaliana) gene reduced epidermal fluorescence1 (REF1) encoding a coniferaldehyde/sinapaldehyde dehydrogenase. The enzyme is involved in the formation of ferulate and sinapate from the corresponding aldehydes, thereby linking lignin and hydroxycinnamate biosynthesis as a potential branch-point enzyme. We used RNA interference to silence REF1 genes in seeds of oilseed rape. Nontargeted metabolite profiling showed that BnREF1-suppressing seeds produced a novel chemotype characterized by reduced levels of sinapate esters, the appearance of conjugated monolignols, dilignols, and trilignols, altered accumulation patterns of kaempferol glycosides, and changes in minor conjugates of caffeate, ferulate, and 5-hydroxyferulate. BnREF1 suppression affected the level of minor sinapate conjugates more severely than that of the major component sinapine. Mapping of the changed metabolites onto the phenylpropanoid metabolic network revealed partial redirection of metabolic sequences as a major impact of BnREF1 suppression.

Integrating data from randomized controlled trials and observational studies to predict the response to pregabalin in patients with painful diabetic peripheral neuropathy

Directory of Open Access Journals (Sweden)

Joe Alexander

2017-07-01

Full Text Available Abstract Background More patient-specific medical care is expected as more is learned about variations in patient responses to medical treatments. Analytical tools enable insights by linking treatment responses from different types of studies, such as randomized controlled trials (RCTs and observational studies. Given the importance of evidence from both types of studies, our goal was to integrate these types of data into a single predictive platform to help predict response to pregabalin in individual patients with painful diabetic peripheral neuropathy (pDPN. Methods We utilized three pivotal RCTs of pregabalin (398 North American patients and the largest observational study of pregabalin (3159 German patients. We implemented a hierarchical cluster analysis to identify patient clusters in the Observational Study to which RCT patients could be matched using the coarsened exact matching (CEM technique, thereby creating a matched dataset. We then developed autoregressive moving average models (ARMAXs to estimate weekly pain scores for pregabalin-treated patients in each cluster in the matched dataset using the maximum likelihood method. Finally, we validated ARMAX models using Observational Study patients who had not matched with RCT patients, using t tests between observed and predicted pain scores. Results Cluster analysis yielded six clusters (287–777 patients each with the following clustering variables: gender, age, pDPN duration, body mass index, depression history, pregabalin monotherapy, prior gabapentin use, baseline pain score, and baseline sleep interference. CEM yielded 1528 unique patients in the matched dataset. The reduction in global imbalance scores for the clusters after adding the RCT patients (ranging from 6 to 63% depending on the cluster demonstrated that the process reduced the bias of covariates in five of the six clusters. ARMAX models of pain score performed well (R 2 : 0.85–0.91; root mean square errors: 0.53–0

Developing a comprehensive training curriculum for integrated predictive maintenance

Science.gov (United States)

Wurzbach, Richard N.

2002-03-01

On-line equipment condition monitoring is a critical component of the world-class production and safety histories of many successful nuclear plant operators. From addressing availability and operability concerns of nuclear safety-related equipment to increasing profitability through support system reliability and reduced maintenance costs, Predictive Maintenance programs have increasingly become a vital contribution to the maintenance and operation decisions of nuclear facilities. In recent years, significant advancements have been made in the quality and portability of many of the instruments being used, and software improvements have been made as well. However, the single most influential component of the success of these programs is the impact of a trained and experienced team of personnel putting this technology to work. Changes in the nature of the power generation industry brought on by competition, mergers, and acquisitions, has taken the historically stable personnel environment of power generation and created a very dynamic situation. As a result, many facilities have seen a significant turnover in personnel in key positions, including predictive maintenance personnel. It has become the challenge for many nuclear operators to maintain the consistent contribution of quality data and information from predictive maintenance that has become important in the overall equipment decision process. These challenges can be met through the implementation of quality training to predictive maintenance personnel and regular updating and re-certification of key technology holders. The use of data management tools and services aid in the sharing of information across sites within an operating company, and with experts who can contribute value-added data management and analysis. The overall effectiveness of predictive maintenance programs can be improved through the incorporation of newly developed comprehensive technology training courses. These courses address the use of

Predicting Flory-Huggins χ from Simulations

Science.gov (United States)

Zhang, Wenlin; Gomez, Enrique D.; Milner, Scott T.

2017-07-01

We introduce a method, based on a novel thermodynamic integration scheme, to extract the Flory-Huggins χ parameter as small as 10-3k T for polymer blends from molecular dynamics (MD) simulations. We obtain χ for the archetypical coarse-grained model of nonpolar polymer blends: flexible bead-spring chains with different Lennard-Jones interactions between A and B monomers. Using these χ values and a lattice version of self-consistent field theory (SCFT), we predict the shape of planar interfaces for phase-separated binary blends. Our SCFT results agree with MD simulations, validating both the predicted χ values and our thermodynamic integration method. Combined with atomistic simulations, our method can be applied to predict χ for new polymers from their chemical structures.

Identification of putative orthologous genes for the phylogenetic reconstruction of temperate woody bamboos (Poaceae: Bambusoideae).

Science.gov (United States)

Zhang, Li-Na; Zhang, Xian-Zhi; Zhang, Yu-Xiao; Zeng, Chun-Xia; Ma, Peng-Fei; Zhao, Lei; Guo, Zhen-Hua; Li, De-Zhu

2014-09-01

The temperate woody bamboos (Arundinarieae) are highly diverse in morphology but lack a substantial amount of genetic variation. The taxonomy of this lineage is intractable, and the relationships within the tribe have not been well resolved. Recent studies indicated that this tribe could have a complex evolutionary history. Although phylogenetic studies of the tribe have been carried out, most of these phylogenetic reconstructions were based on plastid data, which provide lower phylogenetic resolution compared with nuclear data. In this study, we intended to identify a set of desirable nuclear genes for resolving the phylogeny of the temperate woody bamboos. Using two different methodologies, we identified 209 and 916 genes, respectively, as putative single copy orthologous genes. A total of 112 genes was successfully amplified and sequenced by next-generation sequencing technologies in five species sampled from the tribe. As most of the genes exhibited intra-individual allele heterozygotes, we investigated phylogenetic utility by reconstructing the phylogeny based on individual genes. Discordance among gene trees was observed and, to resolve the conflict, we performed a range of analyses using BUCKy and HybTree. While caution should be taken when inferring a phylogeny from multiple conflicting genes, our analysis indicated that 74 of the 112 investigated genes are potential markers for resolving the phylogeny of the temperate woody bamboos. © 2014 John Wiley & Sons Ltd.

An integrated approach to the prediction of chemotherapeutic response in patients with breast cancer.

Directory of Open Access Journals (Sweden)

Kelly H Salter

Full Text Available A major challenge in oncology is the selection of the most effective chemotherapeutic agents for individual patients, while the administration of ineffective chemotherapy increases mortality and decreases quality of life in cancer patients. This emphasizes the need to evaluate every patient's probability of responding to each chemotherapeutic agent and limiting the agents used to those most likely to be effective.Using gene expression data on the NCI-60 and corresponding drug sensitivity, mRNA and microRNA profiles were developed representing sensitivity to individual chemotherapeutic agents. The mRNA signatures were tested in an independent cohort of 133 breast cancer patients treated with the TFAC (paclitaxel, 5-fluorouracil, adriamycin, and cyclophosphamide chemotherapy regimen. To further dissect the biology of resistance, we applied signatures of oncogenic pathway activation and performed hierarchical clustering. We then used mRNA signatures of chemotherapy sensitivity to identify alternative therapeutics for patients resistant to TFAC. Profiles from mRNA and microRNA expression data represent distinct biologic mechanisms of resistance to common cytotoxic agents. The individual mRNA signatures were validated in an independent dataset of breast tumors (P = 0.002, NPV = 82%. When the accuracy of the signatures was analyzed based on molecular variables, the predictive ability was found to be greater in basal-like than non basal-like patients (P = 0.03 and P = 0.06. Samples from patients with co-activated Myc and E2F represented the cohort with the lowest percentage (8% of responders. Using mRNA signatures of sensitivity to other cytotoxic agents, we predict that TFAC non-responders are more likely to be sensitive to docetaxel (P = 0.04, representing a viable alternative therapy.Our results suggest that the optimal strategy for chemotherapy sensitivity prediction integrates molecular variables such as ER and HER2 status with corresponding micro

Acute Anxiety Predicts Components of the Cold Shock Response on Cold Water Immersion: Toward an Integrated Psychophysiological Model of Acute Cold Water Survival

Science.gov (United States)

Barwood, Martin J.; Corbett, Jo; Massey, Heather; McMorris, Terry; Tipton, Mike; Wagstaff, Christopher R. D.

2018-01-01

Introduction: Drowning is a leading cause of accidental death. In cold-water, sudden skin cooling triggers the life-threatening cold shock response (CSR). The CSR comprises tachycardia, peripheral vasoconstriction, hypertension, inspiratory gasp, and hyperventilation with the hyperventilatory component inducing hypocapnia and increasing risk of aspirating water to the lungs. Some CSR components can be reduced by habituation (i.e., reduced response to stimulus of same magnitude) induced by 3–5 short cold-water immersions (CWI). However, high levels of acute anxiety, a plausible emotion on CWI: magnifies the CSR in unhabituated participants, reverses habituated components of the CSR and prevents/delays habituation when high levels of anxiety are experienced concurrent to immersions suggesting anxiety is integral to the CSR. Purpose: To examine the predictive relationship that prior ratings of acute anxiety have with the CSR. Secondly, to examine whether anxiety ratings correlated with components of the CSR during immersion before and after induction of habituation. Methods: Forty-eight unhabituated participants completed one (CON1) 7-min immersion in to cold water (15°C). Of that cohort, twenty-five completed four further CWIs that would ordinarily induce CSR habituation. They then completed two counter-balanced immersions where anxiety levels were increased (CWI-ANX) or were not manipulated (CON2). Acute anxiety and the cardiorespiratory responses (cardiac frequency [fc], respiratory frequency [fR], tidal volume [VT], minute ventilation [E]) were measured. Multiple regression was used to identify components of the CSR from the most life-threatening period of immersion (1st minute) predicted by the anxiety rating prior to immersion. Relationships between anxiety rating and CSR components during immersion were assessed by correlation. Results: Anxiety rating predicted the fc component of the CSR in unhabituated participants (CON1; p anxiety rating predicted the f

Authentic Learning Exercises as a Means to Influence Preservice Teachers' Technology Integration Self-Efficacy and Intentions to Integrate Technology

Science.gov (United States)

Banas, Jennifer R.; York, Cindy S.

2014-01-01

This study explored the impact of authentic learning exercises, as an instructional strategy, on preservice teachers' technology integration self-efficacy and intentions to integrate technology. Also explored was the predictive relationship between change in preservice teachers' technology integration self-efficacy and change in intentions to…

The Integrated Medical Model: A Probabilistic Simulation Model Predicting In-Flight Medical Risks

Science.gov (United States)

Keenan, Alexandra; Young, Millennia; Saile, Lynn; Boley, Lynn; Walton, Marlei; Kerstman, Eric; Shah, Ronak; Goodenow, Debra A.; Myers, Jerry G., Jr.

2015-01-01

The Integrated Medical Model (IMM) is a probabilistic model that uses simulation to predict mission medical risk. Given a specific mission and crew scenario, medical events are simulated using Monte Carlo methodology to provide estimates of resource utilization, probability of evacuation, probability of loss of crew, and the amount of mission time lost due to illness. Mission and crew scenarios are defined by mission length, extravehicular activity (EVA) schedule, and crew characteristics including: sex, coronary artery calcium score, contacts, dental crowns, history of abdominal surgery, and EVA eligibility. The Integrated Medical Evidence Database (iMED) houses the model inputs for one hundred medical conditions using in-flight, analog, and terrestrial medical data. Inputs include incidence, event durations, resource utilization, and crew functional impairment. Severity of conditions is addressed by defining statistical distributions on the dichotomized best and worst-case scenarios for each condition. The outcome distributions for conditions are bounded by the treatment extremes of the fully treated scenario in which all required resources are available and the untreated scenario in which no required resources are available. Upon occurrence of a simulated medical event, treatment availability is assessed, and outcomes are generated depending on the status of the affected crewmember at the time of onset, including any pre-existing functional impairments or ongoing treatment of concurrent conditions. The main IMM outcomes, including probability of evacuation and loss of crew life, time lost due to medical events, and resource utilization, are useful in informing mission planning decisions. To date, the IMM has been used to assess mission-specific risks with and without certain crewmember characteristics, to determine the impact of eliminating certain resources from the mission medical kit, and to design medical kits that maximally benefit crew health while meeting

Integrated Wind Power Planning Tool

DEFF Research Database (Denmark)

Rosgaard, M. H.; Hahmann, Andrea N.; Nielsen, T. S.

This poster describes the status as of April 2012 of the Public Service Obligation (PSO) funded project PSO 10464 \\Integrated Wind Power Planning Tool". The project goal is to integrate a meso scale numerical weather prediction (NWP) model with a statistical tool in order to better predict short...... term power variation from off shore wind farms, as well as to conduct forecast error assessment studies in preparation for later implementation of such a feature in an existing simulation model. The addition of a forecast error estimation feature will further increase the value of this tool, as it...

Integrated genomic and immunophenotypic classification of pancreatic cancer reveals three distinct subtypes with prognostic/predictive significance.

Science.gov (United States)

Wartenberg, Martin; Cibin, Silvia; Zlobec, Inti; Vassella, Erik; Eppenberger-Castori, Serenella M M; Terracciano, Luigi; Eichmann, Micha; Worni, Mathias; Gloor, Beat; Perren, Aurel; Karamitopoulou, Eva

2018-04-16

Current clinical classification of pancreatic ductal adenocarcinoma (PDAC) is unable to predict prognosis or response to chemo- or immunotherapy and does not take into account the host reaction to PDAC-cells. Our aim is to classify PDAC according to host- and tumor-related factors into clinically/biologically relevant subtypes by integrating molecular and microenvironmental findings. A well-characterized PDAC-cohort (n=110) underwent next-generation sequencing with a hotspot cancer panel, while Next-generation Tissue-Microarrays were immunostained for CD3, CD4, CD8, CD20, PD-L1, p63, hyaluronan-mediated motility receptor (RHAMM) and DNA mismatch-repair proteins. Previous data on FOXP3 were integrated. Immune-cell counts and protein expression were correlated with tumor-derived driver mutations, clinicopathologic features (TNM 8. 2017), survival and epithelial-mesenchymal-transition (EMT)-like tumor budding.  Results: Three PDAC-subtypes were identified: the "immune-escape" (54%), poor in T- and B-cells and enriched in FOXP3+Tregs, with high-grade budding, frequent CDKN2A- , SMAD4- and PIK3CA-mutations and poor outcome; the "immune-rich" (35%), rich in T- and B-cells and poorer in FOXP3+Tregs, with infrequent budding, lower CDKN2A- and PIK3CA-mutation rate and better outcome and a subpopulation with tertiary lymphoid tissue (TLT), mutations in DNA damage response genes (STK11, ATM) and the best outcome; and the "immune-exhausted" (11%) with immunogenic microenvironment and two subpopulations: one with PD-L1-expression and high PIK3CA-mutation rate and a microsatellite-unstable subpopulation with high prevalence of JAK3-mutations. The combination of low budding, low stromal FOXP3-counts, presence of TLTs and absence of CDKN2A-mutations confers significant survival advantage in PDAC-patients. Immune host responses correlate with tumor characteristics leading to morphologically recognizable PDAC-subtypes with prognostic/predictive significance. Copyright ©2018

Improving sexual health communication between older women and their providers: how the integrative model of behavioral prediction can help.

Science.gov (United States)

Hughes, Anne K; Rostant, Ola S; Curran, Paul G

2014-07-01

Talking about sexual health can be a challenge for some older women. This project was initiated to identify key factors that improve communication between aging women and their primary care providers. A sample of women (aged 60+) completed an online survey regarding their intent to communicate with a provider about sexual health. Using the integrative model of behavioral prediction as a guide, the survey instrument captured data on attitudes, perceived norms, self-efficacy, and intent to communicate with a provider about sexual health. Data were analyzed using structural equation modeling. Self-efficacy and perceived norms were the most important factors predicting intent to communicate for this sample of women. Intent did not vary with race, but mean scores of the predictors of intent varied for African American and White women. Results can guide practice and intervention with ethnically diverse older women who may be struggling to communicate about their sexual health concerns. © The Author(s) 2013.

An integrative approach to predicting the functional effects of small indels in non-coding regions of the human genome.

Science.gov (United States)

Ferlaino, Michael; Rogers, Mark F; Shihab, Hashem A; Mort, Matthew; Cooper, David N; Gaunt, Tom R; Campbell, Colin

2017-10-06

Small insertions and deletions (indels) have a significant influence in human disease and, in terms of frequency, they are second only to single nucleotide variants as pathogenic mutations. As the majority of mutations associated with complex traits are located outside the exome, it is crucial to investigate the potential pathogenic impact of indels in non-coding regions of the human genome. We present FATHMM-indel, an integrative approach to predict the functional effect, pathogenic or neutral, of indels in non-coding regions of the human genome. Our method exploits various genomic annotations in addition to sequence data. When validated on benchmark data, FATHMM-indel significantly outperforms CADD and GAVIN, state of the art models in assessing the pathogenic impact of non-coding variants. FATHMM-indel is available via a web server at indels.biocompute.org.uk. FATHMM-indel can accurately predict the functional impact and prioritise small indels throughout the whole non-coding genome.

Predictive Direct Torque Control Application-Specific Integrated Circuit of an Induction Motor Drive with a Fuzzy Controller

Directory of Open Access Journals (Sweden)

Guo-Ming Sung

2017-06-01

Full Text Available This paper proposes a modified predictive direct torque control (PDTC application-specific integrated circuit (ASIC of a motor drive with a fuzzy controller for eliminating sampling and calculating delay times in hysteresis controllers. These delay times degrade the control quality and increase both torque and flux ripples in a motor drive. The proposed fuzzy PDTC ASIC calculates the stator’s magnetic flux and torque by detecting the three-phase current, three-phase voltage, and rotor speed, and eliminates the ripples in the torque and flux by using a fuzzy controller and predictive scheme. The Verilog hardware description language was used to implement the hardware architecture, and the ASIC was fabricated by the Taiwan Semiconductor Manufacturing Company through a 0.18-μm 1P6M CMOS process that involved a cell-based design method. The measurements revealed that the proposed fuzzy PDTC ASIC of the three-phase induction motor yielded a test coverage of 96.03%, fault coverage of 95.06%, chip area of 1.81 × 1.81 mm2, and power consumption of 296 mW, at an operating frequency of 50 MHz and a supply voltage of 1.8 V.

Energy and carbon emissions analysis and prediction of complex petrochemical systems based on an improved extreme learning machine integrated interpretative structural model

International Nuclear Information System (INIS)

Han, Yongming; Zhu, Qunxiong; Geng, Zhiqiang; Xu, Yuan

2017-01-01

Highlights: • The ELM integrated ISM (ISM-ELM) method is proposed. • The proposed method is more efficient and accurate than the ELM through the UCI data set. • Energy and carbon emissions analysis and prediction of petrochemical industries based ISM-ELM is obtained. • The proposed method is valid in improving energy efficiency and reducing carbon emissions of ethylene plants. - Abstract: Energy saving and carbon emissions reduction of the petrochemical industry are affected by many factors. Thus, it is difficult to analyze and optimize the energy of complex petrochemical systems accurately. This paper proposes an energy and carbon emissions analysis and prediction approach based on an improved extreme learning machine (ELM) integrated interpretative structural model (ISM) (ISM-ELM). ISM based the partial correlation coefficient is utilized to analyze key parameters that affect the energy and carbon emissions of the complex petrochemical system, and can denoise and reduce dimensions of data to decrease the training time and errors of the ELM prediction model. Meanwhile, in terms of the model accuracy and the training time, the robustness and effectiveness of the ISM-ELM model are better than the ELM through standard data sets from the University of California Irvine (UCI) repository. Moreover, a multi-inputs and single-output (MISO) model of energy and carbon emissions of complex ethylene systems is established based on the ISM-ELM. Finally, detailed analyses and simulations using the real ethylene plant data demonstrate the effectiveness of the ISM-ELM and can guide the improvement direction of energy saving and carbon emissions reduction in complex petrochemical systems.

An integrated view of complex landscapes: a big data-model integration approach to trans-disciplinary science

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The Earth is a complex system comprised of many interacting spatial and temporal scales. Understanding, predicting, and managing for these dynamics requires a trans-disciplinary integrated approach. Although there have been calls for this integration, a general approach is needed. We developed a Tra...

Accurate and dynamic predictive model for better prediction in medicine and healthcare.

Science.gov (United States)

Alanazi, H O; Abdullah, A H; Qureshi, K N; Ismail, A S

2018-05-01

Information and communication technologies (ICTs) have changed the trend into new integrated operations and methods in all fields of life. The health sector has also adopted new technologies to improve the systems and provide better services to customers. Predictive models in health care are also influenced from new technologies to predict the different disease outcomes. However, still, existing predictive models have suffered from some limitations in terms of predictive outcomes performance. In order to improve predictive model performance, this paper proposed a predictive model by classifying the disease predictions into different categories. To achieve this model performance, this paper uses traumatic brain injury (TBI) datasets. TBI is one of the serious diseases worldwide and needs more attention due to its seriousness and serious impacts on human life. The proposed predictive model improves the predictive performance of TBI. The TBI data set is developed and approved by neurologists to set its features. The experiment results show that the proposed model has achieved significant results including accuracy, sensitivity, and specificity.

Real-Time Prediction of Observed Action Requires Integrity of the Dorsal Premotor Cortex: Evidence From Repetitive Transcranial Magnetic Stimulation.

Science.gov (United States)

Brich, Louisa F M; Bächle, Christine; Hermsdörfer, Joachim; Stadler, Waltraud

2018-01-01

Studying brain mechanisms underlying the prediction of observed action, the dorsal premotor cortex (PMd) has been suggested a key area. The present study probed this notion using repetitive transcranial magnetic stimulation (rTMS) to test whether interference in this area would affect the accuracy in predicting the time course of object directed actions performed with the right hand. Young and healthy participants observed actions in short videos. These were briefly occluded from view for 600 ms and resumed immediately afterwards. The task was to continue the action mentally and to indicate after each occlusion, whether the action was resumed at the right moment (condition in-time) or shifted. In a first run, single-pulse transcranial magnetic stimulation (sTMS) was delivered over the left primary hand-area during occlusion. In the second run, rTMS over the left PMd was applied during occlusion in half of the participants [experimental group (EG)]. The control group (CG) received sham-rTMS over the same area. Under rTMS, the EG predicted less trials correctly than in the sTMS run. Sham-rTMS in the CG had no effects on prediction. The interference in PMd interacted with the type of manipulation applied to the action's time course occasionally during occlusion. The performance decrease of the EG was most pronounced in conditions in which the continuations after occlusions were too late in the action's course. The present results extend earlier findings suggesting that real-time action prediction requires the integrity of the PMd. Different functional roles of this area are discussed. Alternative interpretations consider either simulation of specific motor programming functions or the involvement of a feature-unspecific predictor.

oPOSSUM: integrated tools for analysis of regulatory motif over-representation

Science.gov (United States)

Ho Sui, Shannan J.; Fulton, Debra L.; Arenillas, David J.; Kwon, Andrew T.; Wasserman, Wyeth W.

2007-01-01

The identification of over-represented transcription factor binding sites from sets of co-expressed genes provides insights into the mechanisms of regulation for diverse biological contexts. oPOSSUM, an internet-based system for such studies of regulation, has been improved and expanded in this new release. New features include a worm-specific version for investigating binding sites conserved between Caenorhabditis elegans and C. briggsae, as well as a yeast-specific version for the analysis of co-expressed sets of Saccharomyces cerevisiae genes. The human and mouse applications feature improvements in ortholog mapping, sequence alignments and the delineation of multiple alternative promoters. oPOSSUM2, introduced for the analysis of over-represented combinations of motifs in human and mouse genes, has been integrated with the original oPOSSUM system. Analysis using user-defined background gene sets is now supported. The transcription factor binding site models have been updated to include new profiles from the JASPAR database. oPOSSUM is available at http://www.cisreg.ca/oPOSSUM/ PMID:17576675

Functional region prediction with a set of appropriate homologous sequences-an index for sequence selection by integrating structure and sequence information with spatial statistics

Science.gov (United States)

2012-01-01

Background The detection of conserved residue clusters on a protein structure is one of the effective strategies for the prediction of functional protein regions. Various methods, such as Evolutionary Trace, have been developed based on this strategy. In such approaches, the conserved residues are identified through comparisons of homologous amino acid sequences. Therefore, the selection of homologous sequences is a critical step. It is empirically known that a certain degree of sequence divergence in the set of homologous sequences is required for the identification of conserved residues. However, the development of a method to select homologous sequences appropriate for the identification of conserved residues has not been sufficiently addressed. An objective and general method to select appropriate homologous sequences is desired for the efficient prediction of functional regions. Results We have developed a novel index to select the sequences appropriate for the identification of conserved residues, and implemented the index within our method to predict the functional regions of a protein. The implementation of the index improved the performance of the functional region prediction. The index represents the degree of conserved residue clustering on the tertiary structure of the protein. For this purpose, the structure and sequence information were integrated within the index by the application of spatial statistics. Spatial statistics is a field of statistics in which not only the attributes but also the geometrical coordinates of the data are considered simultaneously. Higher degrees of clustering generate larger index scores. We adopted the set of homologous sequences with the highest index score, under the assumption that the best prediction accuracy is obtained when the degree of clustering is the maximum. The set of sequences selected by the index led to higher functional region prediction performance than the sets of sequences selected by other sequence

Non-integrable quantum field theories as perturbations of certain integrable models

International Nuclear Information System (INIS)

Delfino, G.; Simonetti, P.

1996-03-01

We approach the study of non-integrable models of two-dimensional quantum field theory as perturbations of the integrable ones. By exploiting the knowledge of the exact S-matrix and Form Factors of the integrable field theories we obtain the first order corrections to the mass ratios, the vacuum energy density and the S-matrix of the non-integrable theories. As interesting applications of the formalism, we study the scaling region of the Ising model in an external magnetic field at T ∼ T c and the scaling region around the minimal model M 2 , τ . For these models, a remarkable agreement is observed between the theoretical predictions and the data extracted by a numerical diagonalization of their Hamiltonian. (author). 41 refs, 9 figs, 1 tab

House Price Prediction Using LSTM

OpenAIRE

Chen, Xiaochen; Wei, Lai; Xu, Jiaxin

2017-01-01

In this paper, we use the house price data ranging from January 2004 to October 2016 to predict the average house price of November and December in 2016 for each district in Beijing, Shanghai, Guangzhou and Shenzhen. We apply Autoregressive Integrated Moving Average model to generate the baseline while LSTM networks to build prediction model. These algorithms are compared in terms of Mean Squared Error. The result shows that the LSTM model has excellent properties with respect to predict time...

Prokaryotic regulatory systems biology: Common principles governing the functional architectures of Bacillus subtilis and Escherichia coli unveiled by the natural decomposition approach.

Science.gov (United States)

Freyre-González, Julio A; Treviño-Quintanilla, Luis G; Valtierra-Gutiérrez, Ilse A; Gutiérrez-Ríos, Rosa María; Alonso-Pavón, José A

2012-10-31

Escherichia coli and Bacillus subtilis are two of the best-studied prokaryotic model organisms. Previous analyses of their transcriptional regulatory networks have shown that they exhibit high plasticity during evolution and suggested that both converge to scale-free-like structures. Nevertheless, beyond this suggestion, no analyses have been carried out to identify the common systems-level components and principles governing these organisms. Here we show that these two phylogenetically distant organisms follow a set of common novel biologically consistent systems principles revealed by the mathematically and biologically founded natural decomposition approach. The discovered common functional architecture is a diamond-shaped, matryoshka-like, three-layer (coordination, processing, and integration) hierarchy exhibiting feedback, which is shaped by four systems-level components: global transcription factors (global TFs), locally autonomous modules, basal machinery and intermodular genes. The first mathematical criterion to identify global TFs, the κ-value, was reassessed on B. subtilis and confirmed its high predictive power by identifying all the previously reported, plus three potential, master regulators and eight sigma factors. The functionally conserved cores of modules, basal cell machinery, and a set of non-orthologous common physiological global responses were identified via both orthologous genes and non-orthologous conserved functions. This study reveals novel common systems principles maintained between two phylogenetically distant organisms and provides a comparison of their lifestyle adaptations. Our results shed new light on the systems-level principles and the fundamental functions required by bacteria to sustain life. Copyright © 2012 Elsevier B.V. All rights reserved.

Reprogramming the Phenylpropanoid Metabolism in Seeds of Oilseed Rape by Suppressing the Orthologs of REDUCED EPIDERMAL FLUORESCENCE11[W

Science.gov (United States)

Mittasch, Juliane; Böttcher, Christoph; Frolov, Andrej; Strack, Dieter; Milkowski, Carsten

2013-01-01

As a result of the phenylpropanoid pathway, many Brassicaceae produce considerable amounts of soluble hydroxycinnamate conjugates, mainly sinapate esters. From oilseed rape (Brassica napus), we cloned two orthologs of the Arabidopsis (Arabidopsis thaliana) gene REDUCED EPIDERMAL FLUORESCENCE1 (REF1) encoding a coniferaldehyde/sinapaldehyde dehydrogenase. The enzyme is involved in the formation of ferulate and sinapate from the corresponding aldehydes, thereby linking lignin and hydroxycinnamate biosynthesis as a potential branch-point enzyme. We used RNA interference to silence REF1 genes in seeds of oilseed rape. Nontargeted metabolite profiling showed that BnREF1-suppressing seeds produced a novel chemotype characterized by reduced levels of sinapate esters, the appearance of conjugated monolignols, dilignols, and trilignols, altered accumulation patterns of kaempferol glycosides, and changes in minor conjugates of caffeate, ferulate, and 5-hydroxyferulate. BnREF1 suppression affected the level of minor sinapate conjugates more severely than that of the major component sinapine. Mapping of the changed metabolites onto the phenylpropanoid metabolic network revealed partial redirection of metabolic sequences as a major impact of BnREF1 suppression. PMID:23424250

Improving Permafrost Hydrology Prediction Through Data-Model Integration

Science.gov (United States)

Wilson, C. J.; Andresen, C. G.; Atchley, A. L.; Bolton, W. R.; Busey, R.; Coon, E.; Charsley-Groffman, L.

2017-12-01

The CMIP5 Earth System Models were unable to adequately predict the fate of the 16GT of permafrost carbon in a warming climate due to poor representation of Arctic ecosystem processes. The DOE Office of Science Next Generation Ecosystem Experiment, NGEE-Arctic project aims to reduce uncertainty in the Arctic carbon cycle and its impact on the Earth's climate system by improved representation of the coupled physical, chemical and biological processes that drive how much buried carbon will be converted to CO2 and CH4, how fast this will happen, which form will dominate, and the degree to which increased plant productivity will offset increased soil carbon emissions. These processes fundamentally depend on permafrost thaw rate and its influence on surface and subsurface hydrology through thermal erosion, land subsidence and changes to groundwater flow pathways as soil, bedrock and alluvial pore ice and massive ground ice melts. LANL and its NGEE colleagues are co-developing data and models to better understand controls on permafrost degradation and improve prediction of the evolution of permafrost and its impact on Arctic hydrology. The LANL Advanced Terrestrial Simulator was built using a state of the art HPC software framework to enable the first fully coupled 3-dimensional surface-subsurface thermal-hydrology and land surface deformation simulations to simulate the evolution of the physical Arctic environment. Here we show how field data including hydrology, snow, vegetation, geochemistry and soil properties, are informing the development and application of the ATS to improve understanding of controls on permafrost stability and permafrost hydrology. The ATS is being used to inform parameterizations of complex coupled physical, ecological and biogeochemical processes for implementation in the DOE ACME land model, to better predict the role of changing Arctic hydrology on the global climate system. LA-UR-17-26566.

A Study of Performance in Low-Power Tokamak Reactor with Integrated Predictive Modeling Code

International Nuclear Information System (INIS)

Pianroj, Y.; Onjun, T.; Suwanna, S.; Picha, R.; Poolyarat, N.

2009-07-01

Full text: A fusion hybrid or a small fusion power output with low power tokamak reactor is presented as another useful application of nuclear fusion. Such tokamak can be used for fuel breeding, high-level waste transmutation, hydrogen production at high temperature, and testing of nuclear fusion technology components. In this work, an investigation of the plasma performance in a small fusion power output design is carried out using the BALDUR predictive integrated modeling code. The simulations of the plasma performance in this design are carried out using the empirical-based Mixed Bohm/gyro Bohm (B/gB) model, whereas the pedestal temperature model is based on magnetic and flow shear (δ α ρ ζ 2 ) stabilization pedestal width scaling. The preliminary results using this core transport model show that the central ion and electron temperatures are rather pessimistic. To improve the performance, the optimization approach are carried out by varying some parameters, such as plasma current and power auxiliary heating, which results in some improvement of plasma performance

Shifts in the evolutionary rate and intensity of purifying selection between two Brassica genomes revealed by analyses of orthologous transposons and relics of a whole genome triplication.

Science.gov (United States)

Zhao, Meixia; Du, Jianchang; Lin, Feng; Tong, Chaobo; Yu, Jingyin; Huang, Shunmou; Wang, Xiaowu; Liu, Shengyi; Ma, Jianxin

2013-10-01

Recent sequencing of the Brassica rapa and Brassica oleracea genomes revealed extremely contrasting genomic features such as the abundance and distribution of transposable elements between the two genomes. However, whether and how these structural differentiations may have influenced the evolutionary rates of the two genomes since their split from a common ancestor are unknown. Here, we investigated and compared the rates of nucleotide substitution between two long terminal repeats (LTRs) of individual orthologous LTR-retrotransposons, the rates of synonymous and non-synonymous substitution among triplicated genes retained in both genomes from a shared whole genome triplication event, and the rates of genetic recombination estimated/deduced by the comparison of physical and genetic distances along chromosomes and ratios of solo LTRs to intact elements. Overall, LTR sequences and genic sequences showed more rapid nucleotide substitution in B. rapa than in B. oleracea. Synonymous substitution of triplicated genes retained from a shared whole genome triplication was detected at higher rates in B. rapa than in B. oleracea. Interestingly, non-synonymous substitution was observed at lower rates in the former than in the latter, indicating shifted densities of purifying selection between the two genomes. In addition to evolutionary asymmetry, orthologous genes differentially regulated and/or disrupted by transposable elements between the two genomes were also characterized. Our analyses suggest that local genomic and epigenomic features, such as recombination rates and chromatin dynamics reshaped by independent proliferation of transposable elements and elimination between the two genomes, are perhaps partially the causes and partially the outcomes of the observed inter-specific asymmetric evolution. © 2013 Purdue University The Plant Journal © 2013 John Wiley & Sons Ltd.

Choosing the Right Systems Integration

Directory of Open Access Journals (Sweden)

Péči Matúš

2014-12-01

Full Text Available The paper examines systems integration and its main levels at higher levels of control. At present, the systems integration is one of the main aspects participating in the consolidation processes and financial flows of a company. Systems Integration is a complicated emotionconsuming process and it is often a problem to choose the right approach and level of integration. The research focused on four levels of integration, while each of them is characterized by specific conditions. At each level, there is a summary of recommendations and practical experience. The paper also discusses systems integration between the information and MES levels. The main part includes user-level integration where we describe an example of such integration. Finally, we list recommendations and also possible predictions of the systems integration as one of the important factors in the future.

Genetic variation in the Solanaceae fruit bearing species lulo and tree tomato revealed by Conserved Ortholog (COSII) markers

Science.gov (United States)

2010-01-01

The Lulo or naranjilla (Solanum quitoense Lam.) and the tree tomato or tamarillo (Solanum betaceum Cav. Sendt.) are both Andean tropical fruit species with high nutritional value and the potential for becoming premium products in local and export markets. Herein, we present a report on the genetic characterization of 62 accessions of lulos (n = 32) and tree tomatoes (n = 30) through the use of PCR-based markers developed from single-copy conserved orthologous genes (COSII) in other Solanaceae (Asterid) species. We successfully PCR amplified a set of these markers for lulos (34 out of 46 initially tested) and tree tomatoes (26 out of 41) for molecular studies. Six polymorphic COSII markers were found in lulo with a total of 47 alleles and five polymorphic markers in tree tomato with a total of 39 alleles in the two populations. Further genetic analyses indicated a high population structure (with FST > 0.90), which may be a result of low migration between populations, adaptation to various niches and the number of markers evaluated. We propose COSII markers as sound tools for molecular studies, conservation and the breeding of these two fruit species. PMID:21637482

Genetic variation in the Solanaceae fruit bearing species lulo and tree tomato revealed by Conserved Ortholog (COSII) markers.

Science.gov (United States)

Enciso-Rodríguez, Felix; Martínez, Rodrigo; Lobo, Mario; Barrero, Luz Stella

2010-04-01

The Lulo or naranjilla (Solanum quitoense Lam.) and the tree tomato or tamarillo (Solanum betaceum Cav. Sendt.) are both Andean tropical fruit species with high nutritional value and the potential for becoming premium products in local and export markets. Herein, we present a report on the genetic characterization of 62 accessions of lulos (n = 32) and tree tomatoes (n = 30) through the use of PCR-based markers developed from single-copy conserved orthologous genes (COSII) in other Solanaceae (Asterid) species. We successfully PCR amplified a set of these markers for lulos (34 out of 46 initially tested) and tree tomatoes (26 out of 41) for molecular studies. Six polymorphic COSII markers were found in lulo with a total of 47 alleles and five polymorphic markers in tree tomato with a total of 39 alleles in the two populations. Further genetic analyses indicated a high population structure (with F(ST) > 0.90), which may be a result of low migration between populations, adaptation to various niches and the number of markers evaluated. We propose COSII markers as sound tools for molecular studies, conservation and the breeding of these two fruit species.

Genetic variation in the Solanaceae fruit bearing species lulo and tree tomato revealed by Conserved Ortholog (COSII markers

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Felix Enciso-Rodríguez

2010-01-01

Full Text Available The Lulo or naranjilla (Solanum quitoense Lam. and the tree tomato or tamarillo (Solanum betaceum Cav. Sendt. are both Andean tropical fruit species with high nutritional value and the potential for becoming premium products in local and export markets. Herein, we present a report on the genetic characterization of 62 accessions of lulos (n = 32 and tree tomatoes (n = 30 through the use of PCR-based markers developed from single-copy conserved orthologous genes (COSII in other Solanaceae (Asterid species. We successfully PCR amplified a set of these markers for lulos (34 out of 46 initially tested and tree tomatoes (26 out of 41 for molecular studies. Six polymorphic COSII markers were found in lulo with a total of 47 alleles and five polymorphic markers in tree tomato with a total of 39 alleles in the two populations. Further genetic analyses indicated a high population structure (with F ST > 0.90, which may be a result of low migration between populations, adaptation to various niches and the number of markers evaluated. We propose COSII markers as sound tools for molecular studies, conservation and the breeding of these two fruit species.

Numerical methods for engine-airframe integration

International Nuclear Information System (INIS)

Murthy, S.N.B.; Paynter, G.C.

1986-01-01

Various papers on numerical methods for engine-airframe integration are presented. The individual topics considered include: scientific computing environment for the 1980s, overview of prediction of complex turbulent flows, numerical solutions of the compressible Navier-Stokes equations, elements of computational engine/airframe integrations, computational requirements for efficient engine installation, application of CAE and CFD techniques to complete tactical missile design, CFD applications to engine/airframe integration, and application of a second-generation low-order panel methods to powerplant installation studies. Also addressed are: three-dimensional flow analysis of turboprop inlet and nacelle configurations, application of computational methods to the design of large turbofan engine nacelles, comparison of full potential and Euler solution algorithms for aeropropulsive flow field computations, subsonic/transonic, supersonic nozzle flows and nozzle integration, subsonic/transonic prediction capabilities for nozzle/afterbody configurations, three-dimensional viscous design methodology of supersonic inlet systems for advanced technology aircraft, and a user's technology assessment

Real-Time Prediction of Observed Action Requires Integrity of the Dorsal Premotor Cortex: Evidence From Repetitive Transcranial Magnetic Stimulation

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Louisa F. M. Brich

2018-03-01

Full Text Available Studying brain mechanisms underlying the prediction of observed action, the dorsal premotor cortex (PMd has been suggested a key area. The present study probed this notion using repetitive transcranial magnetic stimulation (rTMS to test whether interference in this area would affect the accuracy in predicting the time course of object directed actions performed with the right hand. Young and healthy participants observed actions in short videos. These were briefly occluded from view for 600 ms and resumed immediately afterwards. The task was to continue the action mentally and to indicate after each occlusion, whether the action was resumed at the right moment (condition in-time or shifted. In a first run, single-pulse transcranial magnetic stimulation (sTMS was delivered over the left primary hand-area during occlusion. In the second run, rTMS over the left PMd was applied during occlusion in half of the participants [experimental group (EG]. The control group (CG received sham-rTMS over the same area. Under rTMS, the EG predicted less trials correctly than in the sTMS run. Sham-rTMS in the CG had no effects on prediction. The interference in PMd interacted with the type of manipulation applied to the action’s time course occasionally during occlusion. The performance decrease of the EG was most pronounced in conditions in which the continuations after occlusions were too late in the action’s course. The present results extend earlier findings suggesting that real-time action prediction requires the integrity of the PMd. Different functional roles of this area are discussed. Alternative interpretations consider either simulation of specific motor programming functions or the involvement of a feature-unspecific predictor.

Integration of auditory and visual speech information

NARCIS (Netherlands)

Hall, M.; Smeele, P.M.T.; Kuhl, P.K.

1998-01-01

The integration of auditory and visual speech is observed when modes specify different places of articulation. Influences of auditory variation on integration were examined using consonant identifi-cation, plus quality and similarity ratings. Auditory identification predicted auditory-visual

Integrated 18F-FDG PET/MRI in breast cancer. Early prediction of response to neoadjuvant chemotherapy

International Nuclear Information System (INIS)

Cho, Nariya; Im, Seock-Ah; Lee, Kyung-Hun; Kim, Tae-Yong; Cheon, Gi Jeong; Park, In-Ae; Kim, Young Seon; Kwon, Bo Ra; Lee, Jung Min; Suh, Hoon Young; Suh, Koung Jin

2018-01-01

To explore whether integrated 18 F-FDG PET/MRI can be used to predict pathological response to neoadjuvant chemotherapy (NAC) in patients with breast cancer. Between November 2014 and April 2016, 26 patients with breast cancer who had received NAC and subsequent surgery were prospectively enrolled. Each patient underwent 18 F-FDG PET/MRI examination before and after the first cycle of NAC. Qualitative MRI parameters, including morphological descriptors and the presence of peritumoral oedema were assessed. Quantitatively, PET parameters, including maximum standardized uptake value, metabolic tumour volume and total lesion glycolysis (TLG), and MRI parameters, including washout proportion and signal enhancement ratio (SER), were measured. The performance of the imaging parameters singly and in combination in predicting a pathological incomplete response (non-pCR) was assessed. Of the 26 patients, 7 (26.9%) exhibited a pathological complete response (pCR), and 19 (73.1%) exhibited a non-pCR. No significant differences were found between the pCR and non-pCR groups in the qualitative MRI parameters. The mean percentage reductions in TLG 30% on PET and SER on MRI were significantly greater in the pCR group than in the non-pCR group (TLG 30% -64.8 ± 15.5% vs. -25.4 ± 48.7%, P = 0.005; SER -34.6 ± 19.7% vs. -8.7 ± 29.0%, P = 0.040). The area under the receiver operating characteristic curve for the percentage change in TLG 30% (0.789, 95% CI 0.614 to 0.965) was similar to that for the percentage change in SER (0.789, 95% CI 0.552 to 1.000; P = 1.000). The specificity of TLG 30% in predicting pCR was 100% (7/7) and that of SER was 71.4% (5/7). The sensitivity of TLG 30% in predicting non-pCR was 63.2% (12/19) and that of SER was 84.2% (16/19). When the combined TLG 30% and SER criterion was applied, sensitivity was 100% (19/19), and specificity was 71.4% (5/7). 18 F-FDG PET/MRI can be used to predict non-pCR after the first cycle of NAC in patients with breast cancer

The probable effect of integrated reporting on audit quality

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Tamer A. El Nashar

2016-06-01

Full Text Available This paper examines a probable effect of integrated reporting on improving the audit quality of organizations. I correlate the hypothesis of this paper in relation to the current trends of protecting the economies, the financial markets and the societies. I predict an improvement of the audit quality, as a result to an estimated percentage of organizations’ reliance on the integrated reporting in their accountability perspective. I used a decision tree and a Bayes’ theorem approach, to predict the probabilities of the significant effect on improving the auditing quality. I find the overall result of this paper, indicates that the probability of organizations to rely on the integrated reporting by a significant percentage, predicts also a significant improvement in audit quality.

Genome Wide Identification of Orthologous ZIP Genes Associated with Zinc and Iron Translocation in Setaria italica.

Science.gov (United States)

Alagarasan, Ganesh; Dubey, Mahima; Aswathy, Kumar S; Chandel, Girish

2017-01-01

Genes in the ZIP family encode transcripts to store and transport bivalent metal micronutrient, particularly iron (Fe) and or zinc (Zn). These transcripts are important for a variety of functions involved in the developmental and physiological processes in many plant species, including most, if not all, Poaceae plant species and the model species Arabidopsis. Here, we present the report of a genome wide investigation of orthologous ZIP genes in Setaria italica and the identification of 7 single copy genes. RT-PCR shows 4 of them could be used to increase the bio-availability of zinc and iron content in grains. Of 36 ZIP members, 25 genes have traces of signal peptide based sub-cellular localization, as compared to those of plant species studied previously, yet translocation of ions remains unclear. In silico analysis of gene structure and protein nature suggests that these two were preeminent in shaping the functional diversity of the ZIP gene family in S. italica . NAC, bZIP and bHLH are the predominant Fe and Zn responsive transcription factors present in SiZIP genes. Together, our results provide new insights into the signal peptide based/independent iron and zinc translocation in the plant system and allowed identification of ZIP genes that may be involved in the zinc and iron absorption from the soil, and thus transporting it to the cereal grain underlying high micronutrient accumulation.

Prediction of thermo-mechanical integrity of wafer backend processes

NARCIS (Netherlands)

Gonda, V.; Toonder, den J.M.J.; Beijer, J.G.J.; Zhang, G.Q.; Hoofman, R.J.O.M.; Ernst, L.J.; Ernst, L.J.

2003-01-01

More than 65% of IC failures are related to thermal and mechanical problems. For wafer backend processes, thermo-mechanical failure is one of the major bottlenecks. The ongoing technological trends like miniaturization, introduction of new materials, and function/product integration will increase

HERV-W group evolutionary history in non-human primates: characterization of ERV-W orthologs in Catarrhini and related ERV groups in Platyrrhini.

Science.gov (United States)

Grandi, Nicole; Cadeddu, Marta; Blomberg, Jonas; Mayer, Jens; Tramontano, Enzo

2018-01-19

The genomes of all vertebrates harbor remnants of ancient retroviral infections, having affected the germ line cells during the last 100 million years. These sequences, named Endogenous Retroviruses (ERVs), have been transmitted to the offspring in a Mendelian way, being relatively stable components of the host genome even long after their exogenous counterparts went extinct. Among human ERVs (HERVs), the HERV-W group is of particular interest for our physiology and pathology. A HERV-W provirus in locus 7q21.2 has been coopted during evolution to exert an essential role in placenta, and the group expression has been tentatively linked to Multiple Sclerosis and other diseases. Following up on a detailed analysis of 213 HERV-W insertions in the human genome, we now investigated the ERV-W group genomic spread within primate lineages. We analyzed HERV-W orthologous loci in the genome sequences of 12 non-human primate species belonging to Simiiformes (parvorders Catarrhini and Platyrrhini), Tarsiiformes and to the most primitive Prosimians. Analysis of HERV-W orthologous loci in non-human Catarrhini primates revealed species-specific insertions in the genomes of Chimpanzee (3), Gorilla (4), Orangutan (6), Gibbon (2) and especially Rhesus Macaque (66). Such sequences were acquired in a retroviral fashion and, in the majority of cases, by L1-mediated formation of processed pseudogenes. There were also a number of LTR-LTR homologous recombination events that occurred subsequent to separation of Catarrhini sub-lineages. Moreover, we retrieved 130 sequences in Marmoset and Squirrel Monkeys (family Cebidae, Platyrrhini parvorder), identified as ERV1-1_CJa based on RepBase annotations, which appear closely related to the ERV-W group. Such sequences were also identified in Atelidae and Pitheciidae, representative of the other Platyrrhini families. In contrast, no ERV-W-related sequences were found in genome sequence assemblies of Tarsiiformes and Prosimians. Overall, our

Integrating Crop Growth Models with Whole Genome Prediction through Approximate Bayesian Computation.

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Frank Technow

Full Text Available Genomic selection, enabled by whole genome prediction (WGP methods, is revolutionizing plant breeding. Existing WGP methods have been shown to deliver accurate predictions in the most common settings, such as prediction of across environment performance for traits with additive gene effects. However, prediction of traits with non-additive gene effects and prediction of genotype by environment interaction (G×E, continues to be challenging. Previous attempts to increase prediction accuracy for these particularly difficult tasks employed prediction methods that are purely statistical in nature. Augmenting the statistical methods with biological knowledge has been largely overlooked thus far. Crop growth models (CGMs attempt to represent the impact of functional relationships between plant physiology and the environment in the formation of yield and similar output traits of interest. Thus, they can explain the impact of G×E and certain types of non-additive gene effects on the expressed phenotype. Approximate Bayesian computation (ABC, a novel and powerful computational procedure, allows the incorporation of CGMs directly into the estimation of whole genome marker effects in WGP. Here we provide a proof of concept study for this novel approach and demonstrate its use with synthetic data sets. We show that this novel approach can be considerably more accurate than the benchmark WGP method GBLUP in predicting performance in environments represented in the estimation set as well as in previously unobserved environments for traits determined by non-additive gene effects. We conclude that this proof of concept demonstrates that using ABC for incorporating biological knowledge in the form of CGMs into WGP is a very promising and novel approach to improving prediction accuracy for some of the most challenging scenarios in plant breeding and applied genetics.

Brain mechanisms in religion and spirituality: An integrative predictive processing framework.