A genetic ensemble approach for gene-gene interaction identification

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Ho Joshua WK

2010-10-01

Full Text Available Abstract Background It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases. Though a considerable effort has been put into developing statistical models and algorithmic strategies for identifying such interactions, the accurate identification of those genetic interactions has been proven to be very challenging. Methods In this paper, we propose a new approach for identifying such gene-gene and gene-environment interactions underlying complex diseases. This is a hybrid algorithm and it combines genetic algorithm (GA and an ensemble of classifiers (called genetic ensemble. Using this approach, the original problem of SNP interaction identification is converted into a data mining problem of combinatorial feature selection. By collecting various single nucleotide polymorphisms (SNP subsets as well as environmental factors generated in multiple GA runs, patterns of gene-gene and gene-environment interactions can be extracted using a simple combinatorial ranking method. Also considered in this study is the idea of combining identification results obtained from multiple algorithms. A novel formula based on pairwise double fault is designed to quantify the degree of complementarity. Conclusions Our simulation study demonstrates that the proposed genetic ensemble algorithm has comparable identification power to Multifactor Dimensionality Reduction (MDR and is slightly better than Polymorphism Interaction Analysis (PIA, which are the two most popular methods for gene-gene interaction identification. More importantly, the identification results generated by using our genetic ensemble algorithm are highly complementary to those obtained by PIA and MDR. Experimental results from our simulation studies and real world data application also confirm the effectiveness of the proposed genetic ensemble algorithm, as well as the potential benefits of

A Network Approach to Analyzing Highly Recombinant Malaria Parasite Genes

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Larremore, Daniel B.; Clauset, Aaron; Buckee, Caroline O.

2013-01-01

The var genes of the human malaria parasite Plasmodium falciparum present a challenge to population geneticists due to their extreme diversity, which is generated by high rates of recombination. These genes encode a primary antigen protein called PfEMP1, which is expressed on the surface of infected red blood cells and elicits protective immune responses. Var gene sequences are characterized by pronounced mosaicism, precluding the use of traditional phylogenetic tools that require bifurcating tree-like evolutionary relationships. We present a new method that identifies highly variable regions (HVRs), and then maps each HVR to a complex network in which each sequence is a node and two nodes are linked if they share an exact match of significant length. Here, networks of var genes that recombine freely are expected to have a uniformly random structure, but constraints on recombination will produce network communities that we identify using a stochastic block model. We validate this method on synthetic data, showing that it correctly recovers populations of constrained recombination, before applying it to the Duffy Binding Like-α (DBLα) domain of var genes. We find nine HVRs whose network communities map in distinctive ways to known DBLα classifications and clinical phenotypes. We show that the recombinational constraints of some HVRs are correlated, while others are independent. These findings suggest that this micromodular structuring facilitates independent evolutionary trajectories of neighboring mosaic regions, allowing the parasite to retain protein function while generating enormous sequence diversity. Our approach therefore offers a rigorous method for analyzing evolutionary constraints in var genes, and is also flexible enough to be easily applied more generally to any highly recombinant sequences. PMID:24130474

A network approach to analyzing highly recombinant malaria parasite genes.

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Larremore, Daniel B; Clauset, Aaron; Buckee, Caroline O

2013-01-01

The var genes of the human malaria parasite Plasmodium falciparum present a challenge to population geneticists due to their extreme diversity, which is generated by high rates of recombination. These genes encode a primary antigen protein called PfEMP1, which is expressed on the surface of infected red blood cells and elicits protective immune responses. Var gene sequences are characterized by pronounced mosaicism, precluding the use of traditional phylogenetic tools that require bifurcating tree-like evolutionary relationships. We present a new method that identifies highly variable regions (HVRs), and then maps each HVR to a complex network in which each sequence is a node and two nodes are linked if they share an exact match of significant length. Here, networks of var genes that recombine freely are expected to have a uniformly random structure, but constraints on recombination will produce network communities that we identify using a stochastic block model. We validate this method on synthetic data, showing that it correctly recovers populations of constrained recombination, before applying it to the Duffy Binding Like-α (DBLα) domain of var genes. We find nine HVRs whose network communities map in distinctive ways to known DBLα classifications and clinical phenotypes. We show that the recombinational constraints of some HVRs are correlated, while others are independent. These findings suggest that this micromodular structuring facilitates independent evolutionary trajectories of neighboring mosaic regions, allowing the parasite to retain protein function while generating enormous sequence diversity. Our approach therefore offers a rigorous method for analyzing evolutionary constraints in var genes, and is also flexible enough to be easily applied more generally to any highly recombinant sequences.

A network approach to analyzing highly recombinant malaria parasite genes.

Directory of Open Access Journals (Sweden)

Daniel B Larremore

Full Text Available The var genes of the human malaria parasite Plasmodium falciparum present a challenge to population geneticists due to their extreme diversity, which is generated by high rates of recombination. These genes encode a primary antigen protein called PfEMP1, which is expressed on the surface of infected red blood cells and elicits protective immune responses. Var gene sequences are characterized by pronounced mosaicism, precluding the use of traditional phylogenetic tools that require bifurcating tree-like evolutionary relationships. We present a new method that identifies highly variable regions (HVRs, and then maps each HVR to a complex network in which each sequence is a node and two nodes are linked if they share an exact match of significant length. Here, networks of var genes that recombine freely are expected to have a uniformly random structure, but constraints on recombination will produce network communities that we identify using a stochastic block model. We validate this method on synthetic data, showing that it correctly recovers populations of constrained recombination, before applying it to the Duffy Binding Like-α (DBLα domain of var genes. We find nine HVRs whose network communities map in distinctive ways to known DBLα classifications and clinical phenotypes. We show that the recombinational constraints of some HVRs are correlated, while others are independent. These findings suggest that this micromodular structuring facilitates independent evolutionary trajectories of neighboring mosaic regions, allowing the parasite to retain protein function while generating enormous sequence diversity. Our approach therefore offers a rigorous method for analyzing evolutionary constraints in var genes, and is also flexible enough to be easily applied more generally to any highly recombinant sequences.

Face recognition using elastic grid matching through photoshop: A new approach

Directory of Open Access Journals (Sweden)

Manavpreet Kaur

2015-12-01

Full Text Available Computing grids propose to be a very efficacious, economic and ascendable way of image identification. In this paper, we propose a grid based face recognition overture employing a general template matching method to solve the timeconsuming face recognition problem. A new approach has been employed in which the grid was prepared for a specific individual over his photograph using Adobe Photoshop CS5 software. The background was later removed and the grid prepared by merging layers was used as a template for image matching or comparison. This overture is computationally efficient, has high recognition rates and is able to identify a person with minimal efforts and in short time even from photographs taken at different magnifications and from different distances.

Indonesian name matching using machine learning supervised approach

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Alifikri, Mohamad; Arif Bijaksana, Moch.

2018-03-01

Most existing name matching methods are developed for English language and so they cover the characteristics of this language. Up to this moment, there is no specific one has been designed and implemented for Indonesian names. The purpose of this thesis is to develop Indonesian name matching dataset as a contribution to academic research and to propose suitable feature set by utilizing combination of context of name strings and its permute-winkler score. Machine learning classification algorithms is taken as the method for performing name matching. Based on the experiments, by using tuned Random Forest algorithm and proposed features, there is an improvement of matching performance by approximately 1.7% and it is able to reduce until 70% misclassification result of the state of the arts methods. This improving performance makes the matching system more effective and reduces the risk of misclassified matches.

A robust data-driven approach for gene ontology annotation.

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Li, Yanpeng; Yu, Hong

2014-01-01

Gene ontology (GO) and GO annotation are important resources for biological information management and knowledge discovery, but the speed of manual annotation became a major bottleneck of database curation. BioCreative IV GO annotation task aims to evaluate the performance of system that automatically assigns GO terms to genes based on the narrative sentences in biomedical literature. This article presents our work in this task as well as the experimental results after the competition. For the evidence sentence extraction subtask, we built a binary classifier to identify evidence sentences using reference distance estimator (RDE), a recently proposed semi-supervised learning method that learns new features from around 10 million unlabeled sentences, achieving an F1 of 19.3% in exact match and 32.5% in relaxed match. In the post-submission experiment, we obtained 22.1% and 35.7% F1 performance by incorporating bigram features in RDE learning. In both development and test sets, RDE-based method achieved over 20% relative improvement on F1 and AUC performance against classical supervised learning methods, e.g. support vector machine and logistic regression. For the GO term prediction subtask, we developed an information retrieval-based method to retrieve the GO term most relevant to each evidence sentence using a ranking function that combined cosine similarity and the frequency of GO terms in documents, and a filtering method based on high-level GO classes. The best performance of our submitted runs was 7.8% F1 and 22.2% hierarchy F1. We found that the incorporation of frequency information and hierarchy filtering substantially improved the performance. In the post-submission evaluation, we obtained a 10.6% F1 using a simpler setting. Overall, the experimental analysis showed our approaches were robust in both the two tasks. © The Author(s) 2014. Published by Oxford University Press.

A Generalized Approach for Measuring Relationships Among Genes.

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Wang, Lijun; Ahsan, Md Asif; Chen, Ming

2017-07-21

Several methods for identifying relationships among pairs of genes have been developed. In this article, we present a generalized approach for measuring relationships between any pairs of genes, which is based on statistical prediction. We derive two particular versions of the generalized approach, least squares estimation (LSE) and nearest neighbors prediction (NNP). According to mathematical proof, LSE is equivalent to the methods based on correlation; and NNP is approximate to one popular method called the maximal information coefficient (MIC) according to the performances in simulations and real dataset. Moreover, the approach based on statistical prediction can be extended from two-genes relationships to multi-genes relationships. This application would help to identify relationships among multi-genes.

Preimplantation genetic diagnosis with HLA matching.

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Rechitsky, Svetlana; Kuliev, Anver; Tur-Kaspa, Illan; Morris, Randy; Verlinsky, Yury

2004-08-01

Preimplantation genetic diagnosis (PGD) has recently been offered in combination with HLA typing, which allowed a successful haematopoietic reconstitution in affected siblings with Fanconi anaemia by transplantation of stem cells obtained from the HLA-matched offspring resulting from PGD. This study presents the results of the first PGD practical experience performed in a group of couples at risk for producing children with genetic disorders. These parents also requested preimplantation HLA typing for treating the affected children in the family, who required HLA-matched stem cell transplantation. Using a standard IVF procedure, oocytes or embryos were tested for causative gene mutations simultaneously with HLA alleles, selecting and transferring only those unaffected embryos, which were HLA matched to the affected siblings. The procedure was performed for patients with children affected by Fanconi anaemia (FANC) A and C, different thalassaemia mutations, Wiscott-Aldrich syndrome, X-linked adrenoleukodystrophy, X-linked hyperimmunoglobulin M syndrome and X-linked hypohidrotic ectodermal displasia with immune deficiency. Overall, 46 PGD cycles were performed for 26 couples, resulting in selection and transfer of 50 unaffected HLA-matched embryos in 33 cycles, yielding six HLA-matched clinical pregnancies and the birth of five unaffected HLA-matched children. Despite the controversy of PGD use for HLA typing, the data demonstrate the usefulness of this approach for at-risk couples, not only to avoid the birth of affected children with an inherited disease, but also for having unaffected children who may also be potential HLA-matched donors of stem cells for treatment of affected siblings.

An approach to improve the match-on-card fingerprint authentication system security

CSIR Research Space (South Africa)

Nair, Kishor Krishnan

2016-07-01

Full Text Available -on-Card (TOC), Match-on- Card (MOC), Work-Sharing On-Card (WSOC), and System-on-Card (SOC). Out of these four approaches, the SOC is considered as the most secure and expensive, whereas the TOC is considered as the least secure and least expensive. The MOC...

An Approach to Improve the Match-on-Card ngerprint Authentication System Security

CSIR Research Space (South Africa)

Nair, Kishor Krishnan

2016-08-18

Full Text Available -on-Card (TOC), Match-on-Card (MOC), Work-Sharing On-Card (WSOC), and System-on-Card (SOC). Out of these four approaches, the SOC is considered as the most secure and expensive, whereas the TOC is considered as the least secure and least expensive. The MOC...

Horsetail matching: a flexible approach to optimization under uncertainty

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Cook, L. W.; Jarrett, J. P.

2018-04-01

It is important to design engineering systems to be robust with respect to uncertainties in the design process. Often, this is done by considering statistical moments, but over-reliance on statistical moments when formulating a robust optimization can produce designs that are stochastically dominated by other feasible designs. This article instead proposes a formulation for optimization under uncertainty that minimizes the difference between a design's cumulative distribution function and a target. A standard target is proposed that produces stochastically non-dominated designs, but the formulation also offers enough flexibility to recover existing approaches for robust optimization. A numerical implementation is developed that employs kernels to give a differentiable objective function. The method is applied to algebraic test problems and a robust transonic airfoil design problem where it is compared to multi-objective, weighted-sum and density matching approaches to robust optimization; several advantages over these existing methods are demonstrated.

A kernel regression approach to gene-gene interaction detection for case-control studies.

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Larson, Nicholas B; Schaid, Daniel J

2013-11-01

Gene-gene interactions are increasingly being addressed as a potentially important contributor to the variability of complex traits. Consequently, attentions have moved beyond single locus analysis of association to more complex genetic models. Although several single-marker approaches toward interaction analysis have been developed, such methods suffer from very high testing dimensionality and do not take advantage of existing information, notably the definition of genes as functional units. Here, we propose a comprehensive family of gene-level score tests for identifying genetic elements of disease risk, in particular pairwise gene-gene interactions. Using kernel machine methods, we devise score-based variance component tests under a generalized linear mixed model framework. We conducted simulations based upon coalescent genetic models to evaluate the performance of our approach under a variety of disease models. These simulations indicate that our methods are generally higher powered than alternative gene-level approaches and at worst competitive with exhaustive SNP-level (where SNP is single-nucleotide polymorphism) analyses. Furthermore, we observe that simulated epistatic effects resulted in significant marginal testing results for the involved genes regardless of whether or not true main effects were present. We detail the benefits of our methods and discuss potential genome-wide analysis strategies for gene-gene interaction analysis in a case-control study design. © 2013 WILEY PERIODICALS, INC.

A Partial Least Square Approach for Modeling Gene-gene and Gene-environment Interactions When Multiple Markers Are Genotyped

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Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C.

2008-01-01

Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense SNPs in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches: the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey’s 1-df model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women’s Health Initiative (WHI), this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with BMI. PMID:18615621

A partial least-square approach for modeling gene-gene and gene-environment interactions when multiple markers are genotyped.

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Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C

2009-01-01

Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense single nucleotype polymorphisms (SNPs) in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches, the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey's one-degree-of-freedom model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women's Health Initiative, this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with body mass index.

NCI-MATCH Trial Links Targeted Drugs to Mutations

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Investigators for the nationwide trial, NCI-MATCH: Molecular Analysis for Therapy Choice, announced that the trial will seek to determine whether targeted therapies for people whose tumors have specific gene mutations will be effective regardless of their cancer type. NCI-MATCH will incorporate more than 20 different study drugs or drug combinations, each targeting a specific gene mutation, in order to match each patient in the trial with a therapy that targets a molecular abnormality in their tumor.

A Polygon and Point-Based Approach to Matching Geospatial Features

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Juan J. Ruiz-Lendínez

2017-12-01

Full Text Available A methodology for matching bidimensional entities is presented in this paper. The matching is proposed for both area and point features extracted from geographical databases. The procedure used to obtain homologous entities is achieved in a two-step process: The first matching, polygon to polygon matching (inter-element matching, is obtained by means of a genetic algorithm that allows the classifying of area features from two geographical databases. After this, we apply a point to point matching (intra-element matching based on the comparison of changes in their turning functions. This study shows that genetic algorithms are suitable for matching polygon features even if these features are quite different. Our results show up to 40% of matched polygons with differences in geometrical attributes. With regards to point matching, the vertex from homologous polygons, the function and threshold values proposed in this paper show a useful method for obtaining precise vertex matching.

HANDBOOK OF SOCCER MATCH ANALYSIS: A SYSTEMATIC APPROACH TO IMPROVING PERFORMANCE

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Christopher Carling

2006-03-01

Analysis Tells Us about Successful Strategy and Tactics in Soccer, 8. From Technical and Tactical Performance Analysis to Training Drills, 9. The Future of Soccer Match Analysis. ASSESSMENT The authors have assembled an essential reading for all who are interested in understanding and doing better coaching and improving the performance in soccer. To this purpose, there is a strong practical approach in the book by giving plenty of examples along with a satisfactory scientific analysis of the subject area. It is concise and well organized in its presentation, creating an effective textbook. I believe, therefore, the book will serve as a first-rate teaching tool and reference for coaches, athletes and professionals in the human performance sciences.

Gene Therapy Approaches to Hemoglobinopathies.

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Ferrari, Giuliana; Cavazzana, Marina; Mavilio, Fulvio

2017-10-01

Gene therapy for hemoglobinopathies is currently based on transplantation of autologous hematopoietic stem cells genetically modified with a lentiviral vector expressing a globin gene under the control of globin transcriptional regulatory elements. Preclinical and early clinical studies showed the safety and potential efficacy of this therapeutic approach as well as the hurdles still limiting its general application. In addition, for both beta-thalassemia and sickle cell disease, an altered bone marrow microenvironment reduces the efficiency of stem cell harvesting as well as engraftment. These hurdles need be addressed for gene therapy for hemoglobinopathies to become a clinical reality. Copyright © 2017 Elsevier Inc. All rights reserved.

Efficient line matching with homography

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Shen, Yan; Dai, Yuxing; Zhu, Zhiliang

2018-03-01

In this paper, we propose a novel approach to line matching based on homography. The basic idea is to use cheaply obtainable matched points to boost the similarity between two images. Two types of homography method, which are estimated by direct linear transformation, transform images and extract their similar parts, laying a foundation for the use of optical flow tracking. The merit of the similarity is that rapid matching can be achieved by regionalizing line segments and local searching. For multiple homography estimation that can perform better than one global homography, we introduced the rank-one modification method of singular value decomposition to reduce the computation cost. The proposed approach results in point-to-point matches, which can be utilized with state-of-the-art point-match-based structures from motion (SfM) frameworks seamlessly. The outstanding performance and feasible robustness of our approach are demonstrated in this paper.

A Meta-Analysis of Multiple Matched Copy Number and Transcriptomics Data Sets for Inferring Gene Regulatory Relationships

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Newton, Richard; Wernisch, Lorenz

2014-01-01

Inferring gene regulatory relationships from observational data is challenging. Manipulation and intervention is often required to unravel causal relationships unambiguously. However, gene copy number changes, as they frequently occur in cancer cells, might be considered natural manipulation experiments on gene expression. An increasing number of data sets on matched array comparative genomic hybridisation and transcriptomics experiments from a variety of cancer pathologies are becoming publicly available. Here we explore the potential of a meta-analysis of thirty such data sets. The aim of our analysis was to assess the potential of in silico inference of trans-acting gene regulatory relationships from this type of data. We found sufficient correlation signal in the data to infer gene regulatory relationships, with interesting similarities between data sets. A number of genes had highly correlated copy number and expression changes in many of the data sets and we present predicted potential trans-acted regulatory relationships for each of these genes. The study also investigates to what extent heterogeneity between cell types and between pathologies determines the number of statistically significant predictions available from a meta-analysis of experiments. PMID:25148247

AN INTEGRATED RANSAC AND GRAPH BASED MISMATCH ELIMINATION APPROACH FOR WIDE-BASELINE IMAGE MATCHING

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M. Hasheminasab

2015-12-01

Full Text Available In this paper we propose an integrated approach in order to increase the precision of feature point matching. Many different algorithms have been developed as to optimizing the short-baseline image matching while because of illumination differences and viewpoints changes, wide-baseline image matching is so difficult to handle. Fortunately, the recent developments in the automatic extraction of local invariant features make wide-baseline image matching possible. The matching algorithms which are based on local feature similarity principle, using feature descriptor as to establish correspondence between feature point sets. To date, the most remarkable descriptor is the scale-invariant feature transform (SIFT descriptor , which is invariant to image rotation and scale, and it remains robust across a substantial range of affine distortion, presence of noise, and changes in illumination. The epipolar constraint based on RANSAC (random sample consensus method is a conventional model for mismatch elimination, particularly in computer vision. Because only the distance from the epipolar line is considered, there are a few false matches in the selected matching results based on epipolar geometry and RANSAC. Aguilariu et al. proposed Graph Transformation Matching (GTM algorithm to remove outliers which has some difficulties when the mismatched points surrounded by the same local neighbor structure. In this study to overcome these limitations, which mentioned above, a new three step matching scheme is presented where the SIFT algorithm is used to obtain initial corresponding point sets. In the second step, in order to reduce the outliers, RANSAC algorithm is applied. Finally, to remove the remained mismatches, based on the adjacent K-NN graph, the GTM is implemented. Four different close range image datasets with changes in viewpoint are utilized to evaluate the performance of the proposed method and the experimental results indicate its robustness and

Discovering gene annotations in biomedical text databases

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Ozsoyoglu Gultekin

2008-03-01

Full Text Available Abstract Background Genes and gene products are frequently annotated with Gene Ontology concepts based on the evidence provided in genomics articles. Manually locating and curating information about a genomic entity from the biomedical literature requires vast amounts of human effort. Hence, there is clearly a need forautomated computational tools to annotate the genes and gene products with Gene Ontology concepts by computationally capturing the related knowledge embedded in textual data. Results In this article, we present an automated genomic entity annotation system, GEANN, which extracts information about the characteristics of genes and gene products in article abstracts from PubMed, and translates the discoveredknowledge into Gene Ontology (GO concepts, a widely-used standardized vocabulary of genomic traits. GEANN utilizes textual "extraction patterns", and a semantic matching framework to locate phrases matching to a pattern and produce Gene Ontology annotations for genes and gene products. In our experiments, GEANN has reached to the precision level of 78% at therecall level of 61%. On a select set of Gene Ontology concepts, GEANN either outperforms or is comparable to two other automated annotation studies. Use of WordNet for semantic pattern matching improves the precision and recall by 24% and 15%, respectively, and the improvement due to semantic pattern matching becomes more apparent as the Gene Ontology terms become more general. Conclusion GEANN is useful for two distinct purposes: (i automating the annotation of genomic entities with Gene Ontology concepts, and (ii providing existing annotations with additional "evidence articles" from the literature. The use of textual extraction patterns that are constructed based on the existing annotations achieve high precision. The semantic pattern matching framework provides a more flexible pattern matching scheme with respect to "exactmatching" with the advantage of locating approximate

Assessing the short term impact of air pollution on mortality: a matching approach.

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Baccini, Michela; Mattei, Alessandra; Mealli, Fabrizia; Bertazzi, Pier Alberto; Carugno, Michele

2017-02-10

The opportunity to assess short term impact of air pollution relies on the causal interpretation of the exposure-response association. However, up to now few studies explicitly faced this issue within a causal inference framework. In this paper, we reformulated the problem of assessing the short term impact of air pollution on health using the potential outcome approach to causal inference. We considered the impact of high daily levels of particulate matter ≤10 μm in diameter (PM 10 ) on mortality within two days from the exposure in the metropolitan area of Milan (Italy), during the period 2003-2006. Our research focus was the causal impact of a hypothetical intervention setting daily air pollution levels under a pre-fixed threshold. We applied a matching procedure based on propensity score to estimate the total number of attributable deaths (AD) during the study period. After defining the number of attributable deaths in terms of difference between potential outcomes, we used the estimated propensity score to match each high exposure day, namely each day with a level of exposure higher than 40 μg/m 3 , with a day with similar background characteristics but a level of exposure lower than 40 μg/m 3 . Then, we estimated the impact by comparing mortality between matched days. During the study period daily exposures larger than 40 μg/m 3 were responsible for 1079 deaths (90% CI: 116; 2042). The impact was more evident among the elderly than in the younger age classes. Exposures ≥ 40 μg/m 3 were responsible, among the elderly, for 1102 deaths (90% CI: 388, 1816), of which 797 from cardiovascular causes and 243 from respiratory causes. Clear evidence of an impact on respiratory mortality was found also in the age class 65-74, with 87 AD (90% CI: 11, 163). The propensity score matching turned out to be an appealing method to assess historical impacts in this field, which guarantees that the estimated total number of AD can be derived directly as sum

Matching Two-dimensional Gel Electrophoresis' Spots

DEFF Research Database (Denmark)

Dos Anjos, António; AL-Tam, Faroq; Shahbazkia, Hamid Reza

2012-01-01

This paper describes an approach for matching Two-Dimensional Electrophoresis (2-DE) gels' spots, involving the use of image registration. The number of false positive matches produced by the proposed approach is small, when compared to academic and commercial state-of-the-art approaches. This ar...

Statistical approach for selection of biologically informative genes.

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Das, Samarendra; Rai, Anil; Mishra, D C; Rai, Shesh N

2018-05-20

Selection of informative genes from high dimensional gene expression data has emerged as an important research area in genomics. Many gene selection techniques have been proposed so far are either based on relevancy or redundancy measure. Further, the performance of these techniques has been adjudged through post selection classification accuracy computed through a classifier using the selected genes. This performance metric may be statistically sound but may not be biologically relevant. A statistical approach, i.e. Boot-MRMR, was proposed based on a composite measure of maximum relevance and minimum redundancy, which is both statistically sound and biologically relevant for informative gene selection. For comparative evaluation of the proposed approach, we developed two biological sufficient criteria, i.e. Gene Set Enrichment with QTL (GSEQ) and biological similarity score based on Gene Ontology (GO). Further, a systematic and rigorous evaluation of the proposed technique with 12 existing gene selection techniques was carried out using five gene expression datasets. This evaluation was based on a broad spectrum of statistically sound (e.g. subject classification) and biological relevant (based on QTL and GO) criteria under a multiple criteria decision-making framework. The performance analysis showed that the proposed technique selects informative genes which are more biologically relevant. The proposed technique is also found to be quite competitive with the existing techniques with respect to subject classification and computational time. Our results also showed that under the multiple criteria decision-making setup, the proposed technique is best for informative gene selection over the available alternatives. Based on the proposed approach, an R Package, i.e. BootMRMR has been developed and available at https://cran.r-project.org/web/packages/BootMRMR. This study will provide a practical guide to select statistical techniques for selecting informative genes

Functional Associations by Response Overlap (FARO), a functional genomics approach matching gene expression phenotypes

DEFF Research Database (Denmark)

Nielsen, Henrik Bjørn; Mundy, J.; Willenbrock, Hanni

2007-01-01

The systematic comparison of transcriptional responses of organisms is a powerful tool in functional genomics. For example, mutants may be characterized by comparing their transcript profiles to those obtained in other experiments querying the effects on gene expression of many experimental facto...

Current approaches to gene regulatory network modelling

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Brazma Alvis

2007-09-01

Full Text Available Abstract Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.

Identification and Analysis of Jasmonate Pathway Genes in Coffea canephora (Robusta Coffee) by In Silico Approach.

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Bharathi, Kosaraju; Sreenath, H L

2017-07-01

Coffea canephora is the commonly cultivated coffee species in the world along with Coffea arabica . Different pests and pathogens affect the production and quality of the coffee. Jasmonic acid (JA) is a plant hormone which plays an important role in plants growth, development, and defense mechanisms, particularly against insect pests. The key enzymes involved in the production of JA are lipoxygenase, allene oxide synthase, allene oxide cyclase, and 12-oxo-phytodienoic reductase. There is no report on the genes involved in JA pathway in coffee plants. We made an attempt to identify and analyze the genes coding for these enzymes in C. canephora . First, protein sequences of jasmonate pathway genes from model plant Arabidopsis thaliana were identified in the National Center for Biotechnology Information (NCBI) database. These protein sequences were used to search the web-based database Coffee Genome Hub to identify homologous protein sequences in C. canephora genome using Basic Local Alignment Search Tool (BLAST). Homologous protein sequences for key genes were identified in the C. canephora genome database. Protein sequences of the top matches were in turn used to search in NCBI database using BLAST tool to confirm the identity of the selected proteins and to identify closely related genes in species. The protein sequences from C. canephora database and the top matches in NCBI were aligned, and phylogenetic trees were constructed using MEGA6 software and identified the genetic distance of the respective genes. The study identified the four key genes of JA pathway in C. canephora , confirming the conserved nature of the pathway in coffee. The study expected to be useful to further explore the defense mechanisms of coffee plants. JA is a plant hormone that plays an important role in plant defense against insect pests. Genes coding for the 4 key enzymes involved in the production of JA viz., LOX, AOS, AOC, and OPR are identified in C. canephora (robusta coffee) by

Individual match approach to Bowling performance measures in ...

African Journals Online (AJOL)

Match conditions can play a significant role in player performances in a cricket match. If the pitch is in a good condition, the batsmen can achieve good scores, making it difficult for the bowlers. In the case of an uneven pitch or adverse weather conditions, the bowlers may have the upper hand. In order to measure bowlers' ...

A Review on Block Matching Motion Estimation and Automata Theory based Approaches for Fractal Coding

Directory of Open Access Journals (Sweden)

Shailesh Kamble

2016-12-01

Full Text Available Fractal compression is the lossy compression technique in the field of gray/color image and video compression. It gives high compression ratio, better image quality with fast decoding time but improvement in encoding time is a challenge. This review paper/article presents the analysis of most significant existing approaches in the field of fractal based gray/color images and video compression, different block matching motion estimation approaches for finding out the motion vectors in a frame based on inter-frame coding and intra-frame coding i.e. individual frame coding and automata theory based coding approaches to represent an image/sequence of images. Though different review papers exist related to fractal coding, this paper is different in many sense. One can develop the new shape pattern for motion estimation and modify the existing block matching motion estimation with automata coding to explore the fractal compression technique with specific focus on reducing the encoding time and achieving better image/video reconstruction quality. This paper is useful for the beginners in the domain of video compression.

Word-level recognition of multifont Arabic text using a feature vector matching approach

Science.gov (United States)

Erlandson, Erik J.; Trenkle, John M.; Vogt, Robert C., III

1996-03-01

Many text recognition systems recognize text imagery at the character level and assemble words from the recognized characters. An alternative approach is to recognize text imagery at the word level, without analyzing individual characters. This approach avoids the problem of individual character segmentation, and can overcome local errors in character recognition. A word-level recognition system for machine-printed Arabic text has been implemented. Arabic is a script language, and is therefore difficult to segment at the character level. Character segmentation has been avoided by recognizing text imagery of complete words. The Arabic recognition system computes a vector of image-morphological features on a query word image. This vector is matched against a precomputed database of vectors from a lexicon of Arabic words. Vectors from the database with the highest match score are returned as hypotheses for the unknown image. Several feature vectors may be stored for each word in the database. Database feature vectors generated using multiple fonts and noise models allow the system to be tuned to its input stream. Used in conjunction with database pruning techniques, this Arabic recognition system has obtained promising word recognition rates on low-quality multifont text imagery.

A quasi-dense matching approach and its calibration application with Internet photos.

Science.gov (United States)

Wan, Yanli; Miao, Zhenjiang; Wu, Q M Jonathan; Wang, Xifu; Tang, Zhen; Wang, Zhifei

2015-03-01

This paper proposes a quasi-dense matching approach to the automatic acquisition of camera parameters, which is required for recovering 3-D information from 2-D images. An affine transformation-based optimization model and a new matching cost function are used to acquire quasi-dense correspondences with high accuracy in each pair of views. These correspondences can be effectively detected and tracked at the sub-pixel level in multiviews with our neighboring view selection strategy. A two-layer iteration algorithm is proposed to optimize 3-D quasi-dense points and camera parameters. In the inner layer, different optimization strategies based on local photometric consistency and a global objective function are employed to optimize the 3-D quasi-dense points and camera parameters, respectively. In the outer layer, quasi-dense correspondences are resampled to guide a new estimation and optimization process of the camera parameters. We demonstrate the effectiveness of our algorithm with several experiments.

System Biology Approach: Gene Network Analysis for Muscular Dystrophy.

Science.gov (United States)

Censi, Federica; Calcagnini, Giovanni; Mattei, Eugenio; Giuliani, Alessandro

2018-01-01

Phenotypic changes at different organization levels from cell to entire organism are associated to changes in the pattern of gene expression. These changes involve the entire genome expression pattern and heavily rely upon correlation patterns among genes. The classical approach used to analyze gene expression data builds upon the application of supervised statistical techniques to detect genes differentially expressed among two or more phenotypes (e.g., normal vs. disease). The use of an a posteriori, unsupervised approach based on principal component analysis (PCA) and the subsequent construction of gene correlation networks can shed a light on unexpected behaviour of gene regulation system while maintaining a more naturalistic view on the studied system.In this chapter we applied an unsupervised method to discriminate DMD patient and controls. The genes having the highest absolute scores in the discrimination between the groups were then analyzed in terms of gene expression networks, on the basis of their mutual correlation in the two groups. The correlation network structures suggest two different modes of gene regulation in the two groups, reminiscent of important aspects of DMD pathogenesis.

Human gene therapy: novel approaches to improve the current gene delivery systems.

Science.gov (United States)

Cucchiarini, Magali

2016-06-01

Even though gene therapy made its way through the clinics to treat a number of human pathologies since the early years of experimental research and despite the recent approval of the first gene-based product (Glybera) in Europe, the safe and effective use of gene transfer vectors remains a challenge in human gene therapy due to the existence of barriers in the host organism. While work is under active investigation to improve the gene transfer systems themselves, the use of controlled release approaches may offer alternative, convenient tools of vector delivery to achieve a performant gene transfer in vivo while overcoming the various physiological barriers that preclude its wide use in patients. This article provides an overview of the most significant contributions showing how the principles of controlled release strategies may be adapted for human gene therapy.

A stochastic approach to multi-gene expression dynamics

International Nuclear Information System (INIS)

Ochiai, T.; Nacher, J.C.; Akutsu, T.

2005-01-01

In the last years, tens of thousands gene expression profiles for cells of several organisms have been monitored. Gene expression is a complex transcriptional process where mRNA molecules are translated into proteins, which control most of the cell functions. In this process, the correlation among genes is crucial to determine the specific functions of genes. Here, we propose a novel multi-dimensional stochastic approach to deal with the gene correlation phenomena. Interestingly, our stochastic framework suggests that the study of the gene correlation requires only one theoretical assumption-Markov property-and the experimental transition probability, which characterizes the gene correlation system. Finally, a gene expression experiment is proposed for future applications of the model

Equation level matching: An extension of the method of matched asymptotic expansion for problems of wave propagation

Science.gov (United States)

Faria, Luiz; Rosales, Rodolfo

2017-11-01

We introduce an alternative to the method of matched asymptotic expansions. In the ``traditional'' implementation, approximate solutions, valid in different (but overlapping) regions are matched by using ``intermediate'' variables. Here we propose to match at the level of the equations involved, via a ``uniform expansion'' whose equations enfold those of the approximations to be matched. This has the advantage that one does not need to explicitly solve the asymptotic equations to do the matching, which can be quite impossible for some problems. In addition, it allows matching to proceed in certain wave situations where the traditional approach fails because the time behaviors differ (e.g., one of the expansions does not include dissipation). On the other hand, this approach does not provide the fairly explicit approximations resulting from standard matching. In fact, this is not even its aim, which to produce the ``simplest'' set of equations that capture the behavior. Ruben Rosales work was partially supported by NSF Grants DMS-1614043 and DMS-1719637.

Histogram Curve Matching Approaches for Object-based Image Classification of Land Cover and Land Use

Science.gov (United States)

Toure, Sory I.; Stow, Douglas A.; Weeks, John R.; Kumar, Sunil

2013-01-01

The classification of image-objects is usually done using parametric statistical measures of central tendency and/or dispersion (e.g., mean or standard deviation). The objectives of this study were to analyze digital number histograms of image objects and evaluate classifications measures exploiting characteristic signatures of such histograms. Two histograms matching classifiers were evaluated and compared to the standard nearest neighbor to mean classifier. An ADS40 airborne multispectral image of San Diego, California was used for assessing the utility of curve matching classifiers in a geographic object-based image analysis (GEOBIA) approach. The classifications were performed with data sets having 0.5 m, 2.5 m, and 5 m spatial resolutions. Results show that histograms are reliable features for characterizing classes. Also, both histogram matching classifiers consistently performed better than the one based on the standard nearest neighbor to mean rule. The highest classification accuracies were produced with images having 2.5 m spatial resolution. PMID:24403648

Empirically Examining the Performance of Approaches to Multi-Level Matching to Study the Effect of School-Level Interventions

Science.gov (United States)

Hallberg, Kelly; Cook, Thomas D.; Figlio, David

2013-01-01

The goal of this paper is to provide guidance for applied education researchers in using multi-level data to study the effects of interventions implemented at the school level. Two primary approaches are currently employed in observational studies of the effect of school-level interventions. One approach employs intact school matching: matching…

A computational approach to distinguish somatic vs. germline origin of genomic alterations from deep sequencing of cancer specimens without a matched normal.

Directory of Open Access Journals (Sweden)

James X Sun

2018-02-01

Full Text Available A key constraint in genomic testing in oncology is that matched normal specimens are not commonly obtained in clinical practice. Thus, while well-characterized genomic alterations do not require normal tissue for interpretation, a significant number of alterations will be unknown in whether they are germline or somatic, in the absence of a matched normal control. We introduce SGZ (somatic-germline-zygosity, a computational method for predicting somatic vs. germline origin and homozygous vs. heterozygous or sub-clonal state of variants identified from deep massively parallel sequencing (MPS of cancer specimens. The method does not require a patient matched normal control, enabling broad application in clinical research. SGZ predicts the somatic vs. germline status of each alteration identified by modeling the alteration's allele frequency (AF, taking into account the tumor content, tumor ploidy, and the local copy number. Accuracy of the prediction depends on the depth of sequencing and copy number model fit, which are achieved in our clinical assay by sequencing to high depth (>500x using MPS, covering 394 cancer-related genes and over 3,500 genome-wide single nucleotide polymorphisms (SNPs. Calls are made using a statistic based on read depth and local variability of SNP AF. To validate the method, we first evaluated performance on samples from 30 lung and colon cancer patients, where we sequenced tumors and matched normal tissue. We examined predictions for 17 somatic hotspot mutations and 20 common germline SNPs in 20,182 clinical cancer specimens. To assess the impact of stromal admixture, we examined three cell lines, which were titrated with their matched normal to six levels (10-75%. Overall, predictions were made in 85% of cases, with 95-99% of variants predicted correctly, a significantly superior performance compared to a basic approach based on AF alone. We then applied the SGZ method to the COSMIC database of known somatic variants

An integrative approach to inferring biologically meaningful gene modules

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Wang Kai

2011-07-01

Full Text Available Abstract Background The ability to construct biologically meaningful gene networks and modules is critical for contemporary systems biology. Though recent studies have demonstrated the power of using gene modules to shed light on the functioning of complex biological systems, most modules in these networks have shown little association with meaningful biological function. We have devised a method which directly incorporates gene ontology (GO annotation in construction of gene modules in order to gain better functional association. Results We have devised a method, Semantic Similarity-Integrated approach for Modularization (SSIM that integrates various gene-gene pairwise similarity values, including information obtained from gene expression, protein-protein interactions and GO annotations, in the construction of modules using affinity propagation clustering. We demonstrated the performance of the proposed method using data from two complex biological responses: 1. the osmotic shock response in Saccharomyces cerevisiae, and 2. the prion-induced pathogenic mouse model. In comparison with two previously reported algorithms, modules identified by SSIM showed significantly stronger association with biological functions. Conclusions The incorporation of semantic similarity based on GO annotation with gene expression and protein-protein interaction data can greatly enhance the functional relevance of inferred gene modules. In addition, the SSIM approach can also reveal the hierarchical structure of gene modules to gain a broader functional view of the biological system. Hence, the proposed method can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level.

Modeling gene expression measurement error: a quasi-likelihood approach

Directory of Open Access Journals (Sweden)

Strimmer Korbinian

2003-03-01

Full Text Available Abstract Background Using suitable error models for gene expression measurements is essential in the statistical analysis of microarray data. However, the true probabilistic model underlying gene expression intensity readings is generally not known. Instead, in currently used approaches some simple parametric model is assumed (usually a transformed normal distribution or the empirical distribution is estimated. However, both these strategies may not be optimal for gene expression data, as the non-parametric approach ignores known structural information whereas the fully parametric models run the risk of misspecification. A further related problem is the choice of a suitable scale for the model (e.g. observed vs. log-scale. Results Here a simple semi-parametric model for gene expression measurement error is presented. In this approach inference is based an approximate likelihood function (the extended quasi-likelihood. Only partial knowledge about the unknown true distribution is required to construct this function. In case of gene expression this information is available in the form of the postulated (e.g. quadratic variance structure of the data. As the quasi-likelihood behaves (almost like a proper likelihood, it allows for the estimation of calibration and variance parameters, and it is also straightforward to obtain corresponding approximate confidence intervals. Unlike most other frameworks, it also allows analysis on any preferred scale, i.e. both on the original linear scale as well as on a transformed scale. It can also be employed in regression approaches to model systematic (e.g. array or dye effects. Conclusions The quasi-likelihood framework provides a simple and versatile approach to analyze gene expression data that does not make any strong distributional assumptions about the underlying error model. For several simulated as well as real data sets it provides a better fit to the data than competing models. In an example it also

A robust approach to optimal matched filter design in ultrasonic non-destructive evaluation (NDE)

Science.gov (United States)

Li, Minghui; Hayward, Gordon

2017-02-01

The matched filter was demonstrated to be a powerful yet efficient technique to enhance defect detection and imaging in ultrasonic non-destructive evaluation (NDE) of coarse grain materials, provided that the filter was properly designed and optimized. In the literature, in order to accurately approximate the defect echoes, the design utilized the real excitation signals, which made it time consuming and less straightforward to implement in practice. In this paper, we present a more robust and flexible approach to optimal matched filter design using the simulated excitation signals, and the control parameters are chosen and optimized based on the real scenario of array transducer, transmitter-receiver system response, and the test sample, as a result, the filter response is optimized and depends on the material characteristics. Experiments on industrial samples are conducted and the results confirm the great benefits of the method.

SNPsnap: a Web-based tool for identification and annotation of matched SNPs

DEFF Research Database (Denmark)

Pers, Tune Hannes; Timshel, Pascal; Hirschhorn, Joel N.

2015-01-01

-localization of GWAS signals to gene-dense and high linkage disequilibrium (LD) regions, and correlations of gene size, location and function. The SNPsnap Web server enables SNP-based enrichment analysis by providing matched sets of SNPs that can be used to calibrate background expectations. Specifically, SNPsnap...... efficiently identifies sets of randomly drawn SNPs that are matched to a set of query SNPs based on allele frequency, number of SNPs in LD, distance to nearest gene and gene density. Availability and implementation : SNPsnap server is available at http://www.broadinstitute.org/mpg/snpsnap/. Contact: joelh...

History Matching in Parallel Computational Environments

Energy Technology Data Exchange (ETDEWEB)

Steven Bryant; Sanjay Srinivasan; Alvaro Barrera; Sharad Yadav

2004-08-31

In the probabilistic approach for history matching, the information from the dynamic data is merged with the prior geologic information in order to generate permeability models consistent with the observed dynamic data as well as the prior geology. The relationship between dynamic response data and reservoir attributes may vary in different regions of the reservoir due to spatial variations in reservoir attributes, fluid properties, well configuration, flow constrains on wells etc. This implies probabilistic approach should then update different regions of the reservoir in different ways. This necessitates delineation of multiple reservoir domains in order to increase the accuracy of the approach. The research focuses on a probabilistic approach to integrate dynamic data that ensures consistency between reservoir models developed from one stage to the next. The algorithm relies on efficient parameterization of the dynamic data integration problem and permits rapid assessment of the updated reservoir model at each stage. The report also outlines various domain decomposition schemes from the perspective of increasing the accuracy of probabilistic approach of history matching. Research progress in three important areas of the project are discussed: {lg_bullet}Validation and testing the probabilistic approach to incorporating production data in reservoir models. {lg_bullet}Development of a robust scheme for identifying reservoir regions that will result in a more robust parameterization of the history matching process. {lg_bullet}Testing commercial simulators for parallel capability and development of a parallel algorithm for history matching.

The prediction of candidate genes for cervix related cancer through gene ontology and graph theoretical approach.

Science.gov (United States)

Hindumathi, V; Kranthi, T; Rao, S B; Manimaran, P

2014-06-01

With rapidly changing technology, prediction of candidate genes has become an indispensable task in recent years mainly in the field of biological research. The empirical methods for candidate gene prioritization that succors to explore the potential pathway between genetic determinants and complex diseases are highly cumbersome and labor intensive. In such a scenario predicting potential targets for a disease state through in silico approaches are of researcher's interest. The prodigious availability of protein interaction data coupled with gene annotation renders an ease in the accurate determination of disease specific candidate genes. In our work we have prioritized the cervix related cancer candidate genes by employing Csaba Ortutay and his co-workers approach of identifying the candidate genes through graph theoretical centrality measures and gene ontology. With the advantage of the human protein interaction data, cervical cancer gene sets and the ontological terms, we were able to predict 15 novel candidates for cervical carcinogenesis. The disease relevance of the anticipated candidate genes was corroborated through a literature survey. Also the presence of the drugs for these candidates was detected through Therapeutic Target Database (TTD) and DrugMap Central (DMC) which affirms that they may be endowed as potential drug targets for cervical cancer.

Online tuning of impedance matching circuit for long pulse inductively coupled plasma source operation—An alternate approach

International Nuclear Information System (INIS)

Sudhir, Dass; Bandyopadhyay, M.; Chakraborty, A.; Kraus, W.; Gahlaut, A.; Bansal, G.

2014-01-01

Impedance matching circuit between radio frequency (RF) generator and the plasma load, placed between them, determines the RF power transfer from RF generator to the plasma load. The impedance of plasma load depends on the plasma parameters through skin depth and plasma conductivity or resistivity. Therefore, for long pulse operation of inductively coupled plasmas, particularly for high power (∼100 kW or more) where plasma load condition may vary due to different reasons (e.g., pressure, power, and thermal), online tuning of impedance matching circuit is necessary through feedback. In fusion grade ion source operation, such online methodology through feedback is not present but offline remote tuning by adjusting the matching circuit capacitors and tuning the driving frequency of the RF generator between the ion source operation pulses is envisaged. The present model is an approach for remote impedance tuning methodology for long pulse operation and corresponding online impedance matching algorithm based on RF coil antenna current measurement or coil antenna calorimetric measurement may be useful in this regard

Gene variants associated with antisocial behaviour: a latent variable approach.

Science.gov (United States)

Bentley, Mary Jane; Lin, Haiqun; Fernandez, Thomas V; Lee, Maria; Yrigollen, Carolyn M; Pakstis, Andrew J; Katsovich, Liliya; Olds, David L; Grigorenko, Elena L; Leckman, James F

2013-10-01

The aim of this study was to determine if a latent variable approach might be useful in identifying shared variance across genetic risk alleles that is associated with antisocial behaviour at age 15 years. Using a conventional latent variable approach, we derived an antisocial phenotype in 328 adolescents utilizing data from a 15-year follow-up of a randomized trial of a prenatal and infancy nurse-home visitation programme in Elmira, New York. We then investigated, via a novel latent variable approach, 450 informative genetic polymorphisms in 71 genes previously associated with antisocial behaviour, drug use, affiliative behaviours and stress response in 241 consenting individuals for whom DNA was available. Haplotype and Pathway analyses were also performed. Eight single-nucleotide polymorphisms (SNPs) from eight genes contributed to the latent genetic variable that in turn accounted for 16.0% of the variance within the latent antisocial phenotype. The number of risk alleles was linearly related to the latent antisocial variable scores. Haplotypes that included the putative risk alleles for all eight genes were also associated with higher latent antisocial variable scores. In addition, 33 SNPs from 63 of the remaining genes were also significant when added to the final model. Many of these genes interact on a molecular level, forming molecular networks. The results support a role for genes related to dopamine, norepinephrine, serotonin, glutamate, opioid and cholinergic signalling as well as stress response pathways in mediating susceptibility to antisocial behaviour. This preliminary study supports use of relevant behavioural indicators and latent variable approaches to study the potential 'co-action' of gene variants associated with antisocial behaviour. It also underscores the cumulative relevance of common genetic variants for understanding the aetiology of complex behaviour. If replicated in future studies, this approach may allow the identification of a

In silico approach to identification of a novel gene responsive to ...

African Journals Online (AJOL)

Submergence is one of the major constraints to rice production. Bioinformatics approach has been widely used to identify candidate genes on many biological aspects. In the present study, a novel gene involved in submergence stress in rice, Os07g47670 was identified by in silico approach. The amino acid sequence of ...

Mapping topographic plant location properties using a dense matching approach

Science.gov (United States)

Niederheiser, Robert; Rutzinger, Martin; Lamprecht, Andrea; Bardy-Durchhalter, Manfred; Pauli, Harald; Winkler, Manuela

2017-04-01

Within the project MEDIALPS (Disentangling anthropogenic drivers of climate change impacts on alpine plant species: Alps vs. Mediterranean mountains) six regions in Alpine and in Mediterranean mountain regions are investigated to assess how plant species respond to climate change. The project is embedded in the Global Observation Research Initiative in Alpine Environments (GLORIA), which is a well-established global monitoring initiative for systematic observation of changes in the plant species composition and soil temperature on mountain summits worldwide to discern accelerating climate change pressures on these fragile alpine ecosystems. Close-range sensing techniques such as terrestrial photogrammetry are well suited for mapping terrain topography of small areas with high resolution. Lightweight equipment, flexible positioning for image acquisition in the field, and independence on weather conditions (i.e. wind) make this a feasible method for in-situ data collection. New developments of dense matching approaches allow high quality 3D terrain mapping with less requirements for field set-up. However, challenges occur in post-processing and required data storage if many sites have to be mapped. Within MEDIALPS dense matching is used for mapping high resolution topography for 284 3x3 meter plots deriving information on vegetation coverage, roughness, slope, aspect and modelled solar radiation. This information helps identifying types of topography-dependent ecological growing conditions and evaluating the potential for existing refugial locations for specific plant species under climate change. This research is conducted within the project MEDIALPS - Disentangling anthropogenic drivers of climate change impacts on alpine plant species: Alps vs. Mediterranean mountains funded by the Earth System Sciences Programme of the Austrian Academy of Sciences.

GO-Bayes: Gene Ontology-based overrepresentation analysis using a Bayesian approach.

Science.gov (United States)

Zhang, Song; Cao, Jing; Kong, Y Megan; Scheuermann, Richard H

2010-04-01

A typical approach for the interpretation of high-throughput experiments, such as gene expression microarrays, is to produce groups of genes based on certain criteria (e.g. genes that are differentially expressed). To gain more mechanistic insights into the underlying biology, overrepresentation analysis (ORA) is often conducted to investigate whether gene sets associated with particular biological functions, for example, as represented by Gene Ontology (GO) annotations, are statistically overrepresented in the identified gene groups. However, the standard ORA, which is based on the hypergeometric test, analyzes each GO term in isolation and does not take into account the dependence structure of the GO-term hierarchy. We have developed a Bayesian approach (GO-Bayes) to measure overrepresentation of GO terms that incorporates the GO dependence structure by taking into account evidence not only from individual GO terms, but also from their related terms (i.e. parents, children, siblings, etc.). The Bayesian framework borrows information across related GO terms to strengthen the detection of overrepresentation signals. As a result, this method tends to identify sets of closely related GO terms rather than individual isolated GO terms. The advantage of the GO-Bayes approach is demonstrated with a simulation study and an application example.

A quantitative experimental paradigm to optimize construction of rank order lists in the National Resident Matching Program: the ROSS-MOORE approach.

Science.gov (United States)

Ross, David A; Moore, Edward Z

2013-09-01

As part of the National Resident Matching Program, programs must submit a rank order list of desired applicants. Despite the importance of this process and the numerous manifest limitations with traditional approaches, minimal research has been conducted to examine the accuracy of different ranking strategies. The authors developed the Moore Optimized Ordinal Rank Estimator (MOORE), a novel algorithm for ranking applicants that is based on college sports ranking systems. Because it is not possible to study the Match in vivo, the authors then designed the Recruitment Outcomes Simulation System (ROSS). This program was used to simulate a series of interview seasons and to compare MOORE and traditional approaches under different conditions. The accuracy of traditional ranking and the MOORE approach are equally and adversely affected with higher levels of intrarater variability. However, compared with traditional ranking methods, MOORE produces a more accurate rank order list as interrater variability increases. The present data demonstrate three key findings. First, they provide proof of concept that it is possible to scientifically test the accuracy of different rank methods used in the Match. Second, they show that small amounts of variability can have a significant adverse impact on the accuracy of rank order lists. Finally, they demonstrate that an ordinal approach may lead to a more accurate rank order list in the presence of interviewer bias. The ROSS-MOORE approach offers programs a novel way to optimize the recruitment process and, potentially, to construct a more accurate rank order list.

Bioinformatic approach in the identification of arabidopsis gene homologous in amaranthus

Directory of Open Access Journals (Sweden)

Jana Žiarovská

2015-05-01

Full Text Available Bioinfomatics offers an efficient tool for molecular genetics applications and sequence homology search algorithms became an inevitable part for many different research strategies. Appropriate managing of known data that are stored in public available databases can be used in many ways in the research. Here, we report the identification of RmlC-like cupins superfamily protein DNA sequence than is known in Arabidopsis genome for the Amaranthus - plant specie where this sequence was still not sequenced. A BLAST based approach was used to identify the homologous sequences in the nucleotide database and to find suitable parts of the Arabidopsis sequence were primers can be designed. In total, 64 hits were found in nucleotide database for Arabidopsis RmlC-like cupins sequence. A query cover ranged from 10% up to the 100% among RmlC-like cupins nucleotides and its homologues that are actually stored in public nucleotide databases. The most conserved region was identified for matches that posses nucleotides in the range of 1506 up to the 1925 bp of RmlC-like cupins DNA sequence stored in the database. The in silico approach was subsequently used in PCR analysis where the specifity of designed primers was approved. A unique, 250 bp long fragment was obtained for Amaranthus cruentus and a hybride Amaranthus hypochondriacus x hybridus in our analysis. Bioinformatic based analysis of unknown parts of the plant genomes as showed in this study is a very good additional tool in PCR based analysis of plant variability. This approach is suitable in the case for plants, where concrete genomic data are still missing for the appropriate genes, as was demonstrated for Amaranthus. 

Gene doping detection: evaluation of approach for direct detection of gene transfer using erythropoietin as a model system.

Science.gov (United States)

Baoutina, A; Coldham, T; Bains, G S; Emslie, K R

2010-08-01

As clinical gene therapy has progressed toward realizing its potential, concern over misuse of the technology to enhance performance in athletes is growing. Although 'gene doping' is banned by the World Anti-Doping Agency, its detection remains a major challenge. In this study, we developed a methodology for direct detection of the transferred genetic material and evaluated its feasibility for gene doping detection in blood samples from athletes. Using erythropoietin (EPO) as a model gene and a simple in vitro system, we developed real-time PCR assays that target sequences within the transgene complementary DNA corresponding to exon/exon junctions. As these junctions are absent in the endogenous gene due to their interruption by introns, the approach allows detection of trace amounts of a transgene in a large background of the endogenous gene. Two developed assays and one commercial gene expression assay for EPO were validated. On the basis of ability of these assays to selectively amplify transgenic DNA and analysis of literature on testing of gene transfer in preclinical and clinical gene therapy, it is concluded that the developed approach would potentially be suitable to detect gene doping through gene transfer by analysis of small volumes of blood using regular out-of-competition testing.

Approaching the axiomatic enrichment of the Gene Ontology from a lexical perspective.

Science.gov (United States)

Quesada-Martínez, Manuel; Mikroyannidi, Eleni; Fernández-Breis, Jesualdo Tomás; Stevens, Robert

2015-09-01

The main goal of this work is to measure how lexical regularities in biomedical ontology labels can be used for the automatic creation of formal relationships between classes, and to evaluate the results of applying our approach to the Gene Ontology (GO). In recent years, we have developed a method for the lexical analysis of regularities in biomedical ontology labels, and we showed that the labels can present a high degree of regularity. In this work, we extend our method with a cross-products extension (CPE) metric, which estimates the potential interest of a specific regularity for axiomatic enrichment in the lexical analysis, using information on exact matches in external ontologies. The GO consortium recently enriched the GO by using so-called cross-product extensions. Cross-products are generated by establishing axioms that relate a given GO class with classes from the GO or other biomedical ontologies. We apply our method to the GO and study how its lexical analysis can identify and reconstruct the cross-products that are defined by the GO consortium. The label of the classes of the GO are highly regular in lexical terms, and the exact matches with labels of external ontologies affect 80% of the GO classes. The CPE metric reveals that 31.48% of the classes that exhibit regularities have fragments that are classes into two external ontologies that are selected for our experiment, namely, the Cell Ontology and the Chemical Entities of Biological Interest ontology, and 18.90% of them are fully decomposable into smaller parts. Our results show that the CPE metric permits our method to detect GO cross-product extensions with a mean recall of 62% and a mean precision of 28%. The study is completed with an analysis of false positives to explain this precision value. We think that our results support the claim that our lexical approach can contribute to the axiomatic enrichment of biomedical ontologies and that it can provide new insights into the engineering of

Exploiting Best-Match Equations for Efficient Reinforcement Learning

NARCIS (Netherlands)

van Seijen, Harm; Whiteson, Shimon; van Hasselt, Hado; Wiering, Marco

This article presents and evaluates best-match learning, a new approach to reinforcement learning that trades off the sample efficiency of model-based methods with the space efficiency of model-free methods. Best-match learning works by approximating the solution to a set of best-match equations,

Coarse-to-fine region selection and matching

KAUST Repository

Yang, Yanchao

2015-10-15

We present a new approach to wide baseline matching. We propose to use a hierarchical decomposition of the image domain and coarse-to-fine selection of regions to match. In contrast to interest point matching methods, which sample salient regions to reduce the cost of comparing all regions in two images, our method eliminates regions systematically to achieve efficiency. One advantage of our approach is that it is not restricted to covariant salient regions, which is too restrictive under large viewpoint and leads to few corresponding regions. Affine invariant matching of regions in the hierarchy is achieved efficiently by a coarse-to-fine search of the affine space. Experiments on two benchmark datasets shows that our method finds more correct correspondence of the image (with fewer false alarms) than other wide baseline methods on large viewpoint change. © 2015 IEEE.

The benefits of a laparoscopic approach in ileal pouch anal anastomosis formation: a single institutional retrospective case-matched experience.

LENUS (Irish Health Repository)

Kelly, J

2010-06-01

A laparoscopic approach to ileoanal pouch formation is novel. By using prospectively gathered data, laparoscopic and open restorative proctocolectomy procedures in mucosal ulcerative colitis (UC) and familial adenomatous polyposis (FAP) patients were compared using a case-matched design.

A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

Science.gov (United States)

Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

Transgenerational effects persist down the maternal line in marine sticklebacks: gene expression matches physiology in a warming ocean.

Science.gov (United States)

Shama, Lisa N S; Mark, Felix C; Strobel, Anneli; Lokmer, Ana; John, Uwe; Mathias Wegner, K

2016-10-01

Transgenerational effects can buffer populations against environmental change, yet little is known about underlying mechanisms, their persistence or the influence of environmental cue timing. We investigated mitochondrial respiratory capacity (MRC) and gene expression of marine sticklebacks that experienced acute or developmental acclimation to simulated ocean warming (21°C) across three generations. Previous work showed that acute acclimation of grandmothers to 21°C led to lower (optimized) offspring MRCs. Here, developmental acclimation of mothers to 21°C led to higher, but more efficient offspring MRCs. Offspring with a 21°C × 17°C grandmother-mother environment mismatch showed metabolic compensation: their MRCs were as low as offspring with a 17°C thermal history across generations. Transcriptional analyses showed primarily maternal but also grandmaternal environment effects: genes involved in metabolism and mitochondrial protein biosynthesis were differentially expressed when mothers developed at 21°C, whereas 21°C grandmothers influenced genes involved in hemostasis and apoptosis. Genes involved in mitochondrial respiration all showed higher expression when mothers developed at 21° and lower expression in the 21°C × 17°C group, matching the phenotypic pattern for MRCs. Our study links transcriptomics to physiology under climate change, and demonstrates that mechanisms underlying transgenerational effects persist across multiple generations with specific outcomes depending on acclimation type and environmental mismatch between generations.

Interpreting physical performance in professional soccer match-play: should we be more pragmatic in our approach?

Science.gov (United States)

Carling, Christopher

2013-08-01

Academic and practitioner interest in the physical performance of male professional soccer players in the competition setting determined via time-motion analyses has grown substantially over the last four decades leading to a substantial body of published research and aiding development of a more systematic evidence-based framework for physical conditioning. Findings have forcibly shaped contemporary opinions in the sport with researchers and practitioners frequently emphasising the important role that physical performance plays in match outcomes. Time-motion analyses have also influenced practice as player conditioning programmes can be tailored according to the different physical demands identified across individual playing positions. Yet despite a more systematic approach to physical conditioning, data indicate that even at the very highest standards of competition, the contemporary player is still susceptible to transient and end-game fatigue. Over the course of this article, the author suggests that a more pragmatic approach to interpreting the current body of time-motion analysis data and its application in the practical setting is nevertheless required. Examples of this are addressed using findings in the literature to examine (a) the association between competitive physical performance and 'success' in professional soccer, (b) current approaches to interpreting differences in time-motion analysis data across playing positions, and (c) whether data can realistically be used to demonstrate the occurrence of fatigue in match-play. Gaps in the current literature and directions for future research are also identified.

Security and matching of partial fingerprint recognition systems

Science.gov (United States)

Jea, Tsai-Yang; Chavan, Viraj S.; Govindaraju, Venu; Schneider, John K.

2004-08-01

Despite advances in fingerprint identification techniques, matching incomplete or partial fingerprints still poses a difficult challenge. While the introduction of compact silicon chip-based sensors that capture only a part of the fingerprint area have made this problem important from a commercial perspective, there is also considerable interest on the topic for processing partial and latent fingerprints obtained at crime scenes. Attempts to match partial fingerprints using singular ridge structures-based alignment techniques fail when the partial print does not include such structures (e.g., core or delta). We present a multi-path fingerprint matching approach that utilizes localized secondary features derived using only the relative information of minutiae. Since the minutia-based fingerprint representation, is an ANSI-NIST standard, our approach has the advantage of being directly applicable to already existing databases. We also analyze the vulnerability of partial fingerprint identification systems to brute force attacks. The described matching approach has been tested on one of FVC2002"s DB1 database11. The experimental results show that our approach achieves an equal error rate of 1.25% and a total error rate of 1.8% (with FAR at 0.2% and FRR at 1.6%).

Pattern recognition and string matching

CERN Document Server

Cheng, Xiuzhen

2002-01-01

The research and development of pattern recognition have proven to be of importance in science, technology, and human activity. Many useful concepts and tools from different disciplines have been employed in pattern recognition. Among them is string matching, which receives much theoretical and practical attention. String matching is also an important topic in combinatorial optimization. This book is devoted to recent advances in pattern recognition and string matching. It consists of twenty eight chapters written by different authors, addressing a broad range of topics such as those from classifica­ tion, matching, mining, feature selection, and applications. Each chapter is self-contained, and presents either novel methodological approaches or applications of existing theories and techniques. The aim, intent, and motivation for publishing this book is to pro­ vide a reference tool for the increasing number of readers who depend upon pattern recognition or string matching in some way. This includes student...

Rapid approach for cloning bacterial single-genes directly from soils ...

African Journals Online (AJOL)

Obtaining functional genes of bacteria from environmental samples usually depends on library-based approach which is not favored as its large amount of work with small possibility of positive clones. A kind of bacterial single-gene encoding glutamine synthetase (GS) was selected as example to detect the efficiency of ...

Enhanced gene ranking approaches using modified trace ratio algorithm for gene expression data

Directory of Open Access Journals (Sweden)

Shruti Mishra

Full Text Available Microarray technology enables the understanding and investigation of gene expression levels by analyzing high dimensional datasets that contain few samples. Over time, microarray expression data have been collected for studying the underlying biological mechanisms of disease. One such application for understanding the mechanism is by constructing a gene regulatory network (GRN. One of the foremost key criteria for GRN discovery is gene selection. Choosing a generous set of genes for the structure of the network is highly desirable. For this role, two suitable methods were proposed for selection of appropriate genes. The first approach comprises a gene selection method called Information gain, where the dataset is reformed and fused with another distinct algorithm called Trace Ratio (TR. Our second method is the implementation of our projected modified TR algorithm, where the scoring base for finding weight matrices has been re-designed. Both the methods' efficiency was shown with different classifiers that include variants of the Artificial Neural Network classifier, such as Resilient Propagation, Quick Propagation, Back Propagation, Manhattan Propagation and Radial Basis Function Neural Network and also the Support Vector Machine (SVM classifier. In the study, it was confirmed that both of the proposed methods worked well and offered high accuracy with a lesser number of iterations as compared to the original Trace Ratio algorithm. Keywords: Gene regulatory network, Gene selection, Information gain, Trace ratio, Canonical correlation analysis, Classification

Ranking candidate disease genes from gene expression and protein interaction: a Katz-centrality based approach.

Directory of Open Access Journals (Sweden)

Jing Zhao

Full Text Available Many diseases have complex genetic causes, where a set of alleles can affect the propensity of getting the disease. The identification of such disease genes is important to understand the mechanistic and evolutionary aspects of pathogenesis, improve diagnosis and treatment of the disease, and aid in drug discovery. Current genetic studies typically identify chromosomal regions associated specific diseases. But picking out an unknown disease gene from hundreds of candidates located on the same genomic interval is still challenging. In this study, we propose an approach to prioritize candidate genes by integrating data of gene expression level, protein-protein interaction strength and known disease genes. Our method is based only on two, simple, biologically motivated assumptions--that a gene is a good disease-gene candidate if it is differentially expressed in cases and controls, or that it is close to other disease-gene candidates in its protein interaction network. We tested our method on 40 diseases in 58 gene expression datasets of the NCBI Gene Expression Omnibus database. On these datasets our method is able to predict unknown disease genes as well as identifying pleiotropic genes involved in the physiological cellular processes of many diseases. Our study not only provides an effective algorithm for prioritizing candidate disease genes but is also a way to discover phenotypic interdependency, cooccurrence and shared pathophysiology between different disorders.

PREDICTING THE MATCH OUTCOME IN ONE DAY INTERNATIONAL CRICKET MATCHES, WHILE THE GAME IS IN PROGRESS

Directory of Open Access Journals (Sweden)

Michael Bailey

2006-12-01

Full Text Available Millions of dollars are wagered on the outcome of one day international (ODI cricket matches, with a large percentage of bets occurring after the game has commenced. Using match information gathered from all 2200 ODI matches played prior to January 2005, a range of variables that could independently explain statistically significant proportions of variation associated with the predicted run totals and match outcomes were created. Such variables include home ground advantage, past performances, match experience, performance at the specific venue, performance against the specific opposition, experience at the specific venue and current form. Using a multiple linear regression model, prediction variables were numerically weighted according to statistical significance and used to predict the match outcome. With the use of the Duckworth-Lewis method to determine resources remaining, at the end of each completed over, the predicted run total of the batting team could be updated to provide a more accurate prediction of the match outcome. By applying this prediction approach to a holdout sample of matches, the efficiency of the "in the run" wagering market could be assessed. Preliminary results suggest that the market is prone to overreact to events occurring throughout the course of the match, thus creating brief inefficiencies in the wagering market

Anterior Versus Posterior Approach for Multilevel Degenerative Cervical Disease: A Retrospective Propensity Score-Matched Study of the MarketScan Database.

Science.gov (United States)

Cole, Tyler; Veeravagu, Anand; Zhang, Michael; Azad, Tej D; Desai, Atman; Ratliff, John K

2015-07-01

Retrospective 2:1 propensity score-matched analysis on a national longitudinal database between 2006 and 2010. To compare rates of adverse events, revisions procedure rates, and payment differences in anterior cervical fusion procedures compared with posterior laminectomy and fusion procedures with at least 3 levels of instrumentation. The comparative benefits of anterior versus posterior approach to multilevel degenerative cervical disease remain controversial. Recent systematic reviews have reached conflicting conclusions. We demonstrate the comparative economic and clinical outcomes of anterior and posterior approaches for multilevel cervical degenerative disk disease. We identified 13,662 patients in a national billing claims database who underwent anterior or posterior cervical fusion procedures with 3 or more levels of instrumentation. Cohorts were balanced using 2:1 propensity score matching and outcomes were compared using bivariate analysis. With the exception of dysphagia (6.4% in anterior and 1.4% in posterior), overall 30-day complication rates were lower in the anterior approach group. The rate of any complication excluding dysphagia with anterior approaches was 12.3%, significantly lower (P disease provide clinical advantages over posterior approaches, including lower overall complication rates, revision procedure rates, and decreased length of stay. Anterior approach procedures are also associated with decreased overall payments. These findings must be interpreted in light of limitations inherent to retrospective longitudinal studies including absence of subjective and radiographical outcomes. 3.

Impedance matching through a single passive fractional element

KAUST Repository

Radwan, Ahmed Gomaa

2012-07-01

For the first time, a generalized admittance Smith chart theory is introduced to represent fractional order circuit elements. The principles of fractional order matching circuits are described. We show that for fractional order α < 1, a single parallel fractional element can match a wider range of load impedances as compared to its series counterpart. Several matching examples demonstrate the versatility of fractional order series and parallel element matching as compared to the conventional approach. © 2012 IEEE.

Broadband electrical impedance matching for piezoelectric ultrasound transducers.

Science.gov (United States)

Huang, Haiying; Paramo, Daniel

2011-12-01

This paper presents a systematic method for designing broadband electrical impedance matching networks for piezoelectric ultrasound transducers. The design process involves three steps: 1) determine the equivalent circuit of the unmatched piezoelectric transducer based on its measured admittance; 2) design a set of impedance matching networks using a computerized Smith chart; and 3) establish the simulation model of the matched transducer to evaluate the gain and bandwidth of the impedance matching networks. The effectiveness of the presented approach is demonstrated through the design, implementation, and characterization of impedance matching networks for a broadband acoustic emission sensor. The impedance matching network improved the power of the acquired signal by 9 times.

Clustering gene expression regulators: new approach to disease subtyping.

Directory of Open Access Journals (Sweden)

Mikhail Pyatnitskiy

Full Text Available One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms, that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient.

Photon signature analysis using template matching

Energy Technology Data Exchange (ETDEWEB)

Bradley, D.A., E-mail: d.a.bradley@surrey.ac.uk [Department of Physics, University of Surrey, Guildford GU2 7XH (United Kingdom); Hashim, S., E-mail: suhairul@utm.my [Department of Physics, Universiti Teknologi Malaysia, 81310 Skudai, Johor (Malaysia); Saripan, M.I. [Faculty of Engineering, Universiti Putra Malaysia, 43400 Serdang, Selangor (Malaysia); Wells, K. [Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford GU2 7XH (United Kingdom); Dunn, W.L. [Department of Mechanical and Nuclear Engineering, Kansas State University, 3002 Rathbone Hall, Manhattan, KS 66506 (United States)

2011-10-01

We describe an approach to detect improvised explosive devices (IEDs) by using a template matching procedure. This approach relies on the signature due to backstreaming {gamma} photons from various targets. In this work we have simulated cylindrical targets of aluminum, iron, copper, water and ammonium nitrate (nitrogen-rich fertilizer). We simulate 3.5 MeV source photons distributed on a plane inside a shielded area using Monte Carlo N-Particle (MCNP{sup TM}) code version 5 (V5). The 3.5 MeV source gamma rays yield 511 keV peaks due to pair production and scattered gamma rays. In this work, we simulate capture of those photons that backstream, after impinging on the target element, toward a NaI detector. The captured backstreamed photons are expected to produce a unique spectrum that will become part of a simple signal processing recognition system based on the template matching method. Different elements were simulated using different sets of random numbers in the Monte Carlo simulation. To date, the sum of absolute differences (SAD) method has been used to match the template. In the examples investigated, template matching was found to detect all elements correctly.

Robust Point Matching for Non-Rigid Shapes: A Relaxation Labeling Based Approach

National Research Council Canada - National Science Library

Zheng, Yefeng; Doermann, David S

2004-01-01

.... Based on this observation, we formulate point matching as a graph matching problem. Each point is a node in the graph, and two nodes are connected by an edge if their Euclidean distance is less...

MATCHING ALTERNATIVE ADDRESSES: A SEMANTIC WEB APPROACH

Directory of Open Access Journals (Sweden)

S. Ariannamazi

2015-12-01

Full Text Available Rapid development of crowd-sourcing or volunteered geographic information (VGI provides opportunities for authoritatives that deal with geospatial information. Heterogeneity of multiple data sources and inconsistency of data types is a key characteristics of VGI datasets. The expansion of cities resulted in the growing number of POIs in the OpenStreetMap, a well-known VGI source, which causes the datasets to outdate in short periods of time. These changes made to spatial and aspatial attributes of features such as names and addresses might cause confusion or ambiguity in the processes that require feature’s literal information like addressing and geocoding. VGI sources neither will conform specific vocabularies nor will remain in a specific schema for a long period of time. As a result, the integration of VGI sources is crucial and inevitable in order to avoid duplication and the waste of resources. Information integration can be used to match features and qualify different annotation alternatives for disambiguation. This study enhances the search capabilities of geospatial tools with applications able to understand user terminology to pursuit an efficient way for finding desired results. Semantic web is a capable tool for developing technologies that deal with lexical and numerical calculations and estimations. There are a vast amount of literal-spatial data representing the capability of linguistic information in knowledge modeling, but these resources need to be harmonized based on Semantic Web standards. The process of making addresses homogenous generates a helpful tool based on spatial data integration and lexical annotation matching and disambiguating.

Template match using local feature with view invariance

Science.gov (United States)

Lu, Cen; Zhou, Gang

2013-10-01

Matching the template image in the target image is the fundamental task in the field of computer vision. Aiming at the deficiency in the traditional image matching methods and inaccurate matching in scene image with rotation, illumination and view changing, a novel matching algorithm using local features are proposed in this paper. The local histograms of the edge pixels (LHoE) are extracted as the invariable feature to resist view and brightness changing. The merits of the LHoE is that the edge points have been little affected with view changing, and the LHoE can resist not only illumination variance but also the polution of noise. For the process of matching are excuded only on the edge points, the computation burden are highly reduced. Additionally, our approach is conceptually simple, easy to implement and do not need the training phase. The view changing can be considered as the combination of rotation, illumination and shear transformation. Experimental results on simulated and real data demonstrated that the proposed approach is superior to NCC(Normalized cross-correlation) and Histogram-based methods with view changing.

An effective approach for iris recognition using phase-based image matching.

Science.gov (United States)

Miyazawa, Kazuyuki; Ito, Koichi; Aoki, Takafumi; Kobayashi, Koji; Nakajima, Hiroshi

2008-10-01

This paper presents an efficient algorithm for iris recognition using phase-based image matching--an image matching technique using phase components in 2D Discrete Fourier Transforms (DFTs) of given images. Experimental evaluation using CASIA iris image databases (versions 1.0 and 2.0) and Iris Challenge Evaluation (ICE) 2005 database clearly demonstrates that the use of phase components of iris images makes possible to achieve highly accurate iris recognition with a simple matching algorithm. This paper also discusses major implementation issues of our algorithm. In order to reduce the size of iris data and to prevent the visibility of iris images, we introduce the idea of 2D Fourier Phase Code (FPC) for representing iris information. The 2D FPC is particularly useful for implementing compact iris recognition devices using state-of-the-art Digital Signal Processing (DSP) technology.

A multicenter matched case-control analysis on seven polymorphisms from HMGB1 and RAGE genes in predicting hepatocellular carcinoma risk.

Science.gov (United States)

Wang, Dan; Qi, Xiaoying; Liu, Fang; Yang, Chuanhua; Jiang, Wenguo; Wei, Xiaodan; Li, Xuri; Mi, Jia; Tian, Geng

2017-07-25

Based on 540 hepatocellular carcinoma patients and 540 age- and gender-matched controls, we tested the hypothesis that high mobility group protein box1 (HMGB1) and the receptor for advanced glycation end products (RAGE) genes are two potential candidate susceptibility genes for hepatocellular carcinoma in a multicenter hospital-based case-control analysis. The genotypes of seven widely-studied polymorphisms were determined, and their distributions respected the Hardy-Weinberg equilibrium. The mutant alleles of two polymorphisms, rs1045411 in HMGB1 gene and rs2070600 in RAGE gene, had significantly higher frequencies in patients than in controls (P hepatocellular carcinoma significantly, particularly for rs2070600 under the additive (odds ratio [OR] = 1.77; 95% confidence interval [CI]: 1.34-2.32; P hepatocellular carcinoma compared with the commonest C-C-T haplotype after adjustment. In RAGE gene, the T-T-A-G (rs1800625-rs1800624-rs2070600-rs184003) (adjusted OR; 95% CI; P: 1.75; 1.02-3.03; 0.045) and T-T-A-T (adjusted OR; 95% CI; P: 1.95; 1.01-3.76; 0.048) haplotypes were associated with a marginally increased risk of hepatocellular carcinoma compared with the commonest T-T-G-G haplotype. In summary, we identified two risk-associated polymorphisms (rs1045411 and rs2070600), and more importantly a joint impact of seven polymorphisms from the HMGB1/RAGE axis in susceptibility to hepatocellular carcinoma.

Systems Pharmacology-Based Approach of Connecting Disease Genes in Genome-Wide Association Studies with Traditional Chinese Medicine.

Science.gov (United States)

Kim, Jihye; Yoo, Minjae; Shin, Jimin; Kim, Hyunmin; Kang, Jaewoo; Tan, Aik Choon

2018-01-01

Traditional Chinese medicine (TCM) originated in ancient China has been practiced over thousands of years for treating various symptoms and diseases. However, the molecular mechanisms of TCM in treating these diseases remain unknown. In this study, we employ a systems pharmacology-based approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. We studied 102 TCM components and their target genes by analyzing microarray gene expression experiments. We constructed disease-gene networks from 2558 GWAS studies. We applied a systems pharmacology approach to prioritize disease-target genes. Using this bioinformatics approach, we analyzed 14,713 GWAS disease-TCM-target gene pairs and identified 115 disease-gene pairs with q value < 0.2. We validated several of these GWAS disease-TCM-target gene pairs with literature evidence, demonstrating that this computational approach could reveal novel indications for TCM. We also develop TCM-Disease web application to facilitate the traditional Chinese medicine drug repurposing efforts. Systems pharmacology is a promising approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. The computational approaches described in this study could be easily expandable to other disease-gene network analysis.

Are Current Physical Match Performance Metrics in Elite Soccer Fit for Purpose or is the Adoption of an Integrated Approach Needed?

Science.gov (United States)

Bradley, Paul S; Ade, Jack D

2018-01-18

Time-motion analysis is a valuable data-collection technique used to quantify the physical match performance of elite soccer players. For over 40 years researchers have adopted a 'traditional' approach when evaluating match demands by simply reporting the distance covered or time spent along a motion continuum of walking through to sprinting. This methodology quantifies physical metrics in isolation without integrating other factors and this ultimately leads to a one-dimensional insight into match performance. Thus, this commentary proposes a novel 'integrated' approach that focuses on a sensitive physical metric such as high-intensity running but contextualizes this in relation to key tactical activities for each position and collectively for the team. In the example presented, the 'integrated' model clearly unveils the unique high-intensity profile that exists due to distinct tactical roles, rather than one-dimensional 'blind' distances produced by 'traditional' models. Intuitively this innovative concept may aid the coaches understanding of the physical performance in relation to the tactical roles and instructions given to the players. Additionally, it will enable practitioners to more effectively translate match metrics into training and testing protocols. This innovative model may well aid advances in other team sports that incorporate similar intermittent movements with tactical purpose. Evidence of the merits and application of this new concept are needed before the scientific community accepts this model as it may well add complexity to an area that conceivably needs simplicity.

Matched pairs approach to set theoretic solutions of the Yang-Baxter equation

International Nuclear Information System (INIS)

Gateva-Ivanova, T.; Majid, S.

2005-08-01

We study set-theoretic solutions (X,r) of the Yang-Baxter equations on a set X in terms of the induced left and right actions of X on itself. We give a characterization of involutive square-free solutions in terms of cyclicity conditions. We characterise general solutions in terms of an induced matched pair of unital semigroups S(X,r) and construct (S,r S ) from the matched pair. Finally, we study extensions of solutions in terms of matched pairs of their associated semigroups. We also prove several general results about matched pairs of unital semigroups of the required type, including iterated products S bowtie S bowtie S underlying the proof that r S is a solution, and extensions (S bowtie T, r Sb owtie T ). Examples include a general 'double' construction (S bowtie S,r Sb owtie S ) and some concrete extensions, their actions and graphs based on small sets. (author)

Mix-and-match holography

KAUST Repository

Peng, Yifan

2017-11-22

Computational caustics and light steering displays offer a wide range of interesting applications, ranging from art works and architectural installations to energy efficient HDR projection. In this work we expand on this concept by encoding several target images into pairs of front and rear phase-distorting surfaces. Different target holograms can be decoded by mixing and matching different front and rear surfaces under specific geometric alignments. Our approach, which we call mix-and-match holography, is made possible by moving from a refractive caustic image formation process to a diffractive, holographic one. This provides the extra bandwidth that is required to multiplex several images into pairing surfaces.

A comparative study between matched and mis-matched projection/back projection pairs used with ASIRT reconstruction method

International Nuclear Information System (INIS)

Guedouar, R.; Zarrad, B.

2010-01-01

For algebraic reconstruction techniques both forward and back projection operators are needed. The ability to perform accurate reconstruction relies fundamentally on the forward projection and back projection methods which are usually, the transpose of each other. Even though the mis-matched pairs may introduce additional errors during the iterative process, the usefulness of mis-matched projector/back projector pairs has been proved in image reconstruction. This work investigates the performance of matched and mis-matched reconstruction pairs using popular forward projectors and their transposes when used in reconstruction tasks with additive simultaneous iterative reconstruction techniques (ASIRT) in a parallel beam approach. Simulated noiseless phantoms are used to compare the performance of the investigated pairs in terms of the root mean squared errors (RMSE) which are calculated between reconstructed slices and the reference in different regions. Results show that mis-matched projection/back projection pairs can promise more accuracy of reconstructed images than matched ones. The forward projection operator performance seems independent of the choice of the back projection operator and vice versa.

A comparative study between matched and mis-matched projection/back projection pairs used with ASIRT reconstruction method

Energy Technology Data Exchange (ETDEWEB)

Guedouar, R., E-mail: raja_guedouar@yahoo.f [Higher School of Health Sciences and Techniques of Monastir, Av. Avicenne, 5060 Monastir, B.P. 128 (Tunisia); Zarrad, B., E-mail: boubakerzarrad@yahoo.f [Higher School of Health Sciences and Techniques of Monastir, Av. Avicenne, 5060 Monastir, B.P. 128 (Tunisia)

2010-07-21

For algebraic reconstruction techniques both forward and back projection operators are needed. The ability to perform accurate reconstruction relies fundamentally on the forward projection and back projection methods which are usually, the transpose of each other. Even though the mis-matched pairs may introduce additional errors during the iterative process, the usefulness of mis-matched projector/back projector pairs has been proved in image reconstruction. This work investigates the performance of matched and mis-matched reconstruction pairs using popular forward projectors and their transposes when used in reconstruction tasks with additive simultaneous iterative reconstruction techniques (ASIRT) in a parallel beam approach. Simulated noiseless phantoms are used to compare the performance of the investigated pairs in terms of the root mean squared errors (RMSE) which are calculated between reconstructed slices and the reference in different regions. Results show that mis-matched projection/back projection pairs can promise more accuracy of reconstructed images than matched ones. The forward projection operator performance seems independent of the choice of the back projection operator and vice versa.

Mixing and matching siderophore clusters: structure and biosynthesis of serratiochelins from Serratia sp. V4.

Science.gov (United States)

Seyedsayamdost, Mohammad R; Cleto, Sara; Carr, Gavin; Vlamakis, Hera; João Vieira, Maria; Kolter, Roberto; Clardy, Jon

2012-08-22

Interrogation of the evolutionary history underlying the remarkable structures and biological activities of natural products has been complicated by not knowing the functions they have evolved to fulfill. Siderophores-soluble, low molecular weight compounds-have an easily understood and measured function: acquiring iron from the environment. Bacteria engage in a fierce competition to acquire iron, which rewards the production of siderophores that bind iron tightly and cannot be used or pirated by competitors. The structures and biosyntheses of "odd" siderophores can reveal the evolutionary strategy that led to their creation. We report a new Serratia strain that produces serratiochelin and an analog of serratiochelin. A genetic approach located the serratiochelin gene cluster, and targeted mutations in several genes implicated in serratiochelin biosynthesis were generated. Bioinformatic analyses and mutagenesis results demonstrate that genes from two well-known siderophore clusters, the Escherichia coli enterobactin cluster and the Vibrio cholera vibriobactin cluster, were shuffled to produce a new siderophore biosynthetic pathway. These results highlight how modular siderophore gene clusters can be mixed and matched during evolution to generate structural diversity in siderophores.

Serious limitations of the QTL/Microarray approach for QTL gene discovery

Directory of Open Access Journals (Sweden)

Warden Craig H

2010-07-01

Full Text Available Abstract Background It has been proposed that the use of gene expression microarrays in nonrecombinant parental or congenic strains can accelerate the process of isolating individual genes underlying quantitative trait loci (QTL. However, the effectiveness of this approach has not been assessed. Results Thirty-seven studies that have implemented the QTL/microarray approach in rodents were reviewed. About 30% of studies showed enrichment for QTL candidates, mostly in comparisons between congenic and background strains. Three studies led to the identification of an underlying QTL gene. To complement the literature results, a microarray experiment was performed using three mouse congenic strains isolating the effects of at least 25 biometric QTL. Results show that genes in the congenic donor regions were preferentially selected. However, within donor regions, the distribution of differentially expressed genes was homogeneous once gene density was accounted for. Genes within identical-by-descent (IBD regions were less likely to be differentially expressed in chromosome 2, but not in chromosomes 11 and 17. Furthermore, expression of QTL regulated in cis (cis eQTL showed higher expression in the background genotype, which was partially explained by the presence of single nucleotide polymorphisms (SNP. Conclusions The literature shows limited successes from the QTL/microarray approach to identify QTL genes. Our own results from microarray profiling of three congenic strains revealed a strong tendency to select cis-eQTL over trans-eQTL. IBD regions had little effect on rate of differential expression, and we provide several reasons why IBD should not be used to discard eQTL candidates. In addition, mismatch probes produced false cis-eQTL that could not be completely removed with the current strains genotypes and low probe density microarrays. The reviewed studies did not account for lack of coverage from the platforms used and therefore removed genes

The match-to-match variation of match-running in elite female soccer.

Science.gov (United States)

Trewin, Joshua; Meylan, César; Varley, Matthew C; Cronin, John

2018-02-01

The purpose of this study was to examine the match-to-match variation of match-running in elite female soccer players utilising GPS, using full-match and rolling period analyses. Longitudinal study. Elite female soccer players (n=45) from the same national team were observed during 55 international fixtures across 5 years (2012-2016). Data was analysed using a custom built MS Excel spreadsheet as full-matches and using a rolling 5-min analysis period, for all players who played 90-min matches (files=172). Variation was examined using co-efficient of variation and 90% confidence limits, calculated following log transformation. Total distance per minute exhibited the smallest variation when both the full-match and peak 5-min running periods were examined (CV=6.8-7.2%). Sprint-efforts were the most variable during a full-match (CV=53%), whilst high-speed running per minute exhibited the greatest variation in the post-peak 5-min period (CV=143%). Peak running periods were observed as slightly more variable than full-match analyses, with the post-peak period very-highly variable. Variability of accelerations (CV=17%) and Player Load (CV=14%) was lower than that of high-speed actions. Positional differences were also present, with centre backs exhibiting the greatest variation in high-speed movements (CV=41-65%). Practitioners and researchers should account for within player variability when examining match performances. Identification of peak running periods should be used to assist worst case scenarios. Whilst micro-sensor technology should be further examined as to its viable use within match-analyses. Copyright © 2017 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Theory of fractional order elements based impedance matching networks

KAUST Repository

Radwan, Ahmed G.

2011-03-01

Fractional order circuit elements (inductors and capacitors) based impedance matching networks are introduced for the first time. In comparison to the conventional integer based L-type matching networks, fractional matching networks are much simpler and versatile. Any complex load can be matched utilizing a single series fractional element, which generally requires two elements for matching in the conventional approach. It is shown that all the Smith chart circles (resistance and reactance) are actually pairs of completely identical circles. They appear to be single for the conventional integer order case, where the identical circles completely overlap each other. The concept is supported by design equations and impedance matching examples. © 2010 IEEE.

Gene selection for the reconstruction of stem cell differentiation trees: a linear programming approach.

Science.gov (United States)

Ghadie, Mohamed A; Japkowicz, Nathalie; Perkins, Theodore J

2015-08-15

Stem cell differentiation is largely guided by master transcriptional regulators, but it also depends on the expression of other types of genes, such as cell cycle genes, signaling genes, metabolic genes, trafficking genes, etc. Traditional approaches to understanding gene expression patterns across multiple conditions, such as principal components analysis or K-means clustering, can group cell types based on gene expression, but they do so without knowledge of the differentiation hierarchy. Hierarchical clustering can organize cell types into a tree, but in general this tree is different from the differentiation hierarchy itself. Given the differentiation hierarchy and gene expression data at each node, we construct a weighted Euclidean distance metric such that the minimum spanning tree with respect to that metric is precisely the given differentiation hierarchy. We provide a set of linear constraints that are provably sufficient for the desired construction and a linear programming approach to identify sparse sets of weights, effectively identifying genes that are most relevant for discriminating different parts of the tree. We apply our method to microarray gene expression data describing 38 cell types in the hematopoiesis hierarchy, constructing a weighted Euclidean metric that uses just 175 genes. However, we find that there are many alternative sets of weights that satisfy the linear constraints. Thus, in the style of random-forest training, we also construct metrics based on random subsets of the genes and compare them to the metric of 175 genes. We then report on the selected genes and their biological functions. Our approach offers a new way to identify genes that may have important roles in stem cell differentiation. tperkins@ohri.ca Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Theoretical investigation into negative differential resistance characteristics of resonant tunneling diodes based on lattice-matched and polarization-matched AlInN/GaN heterostructures

Science.gov (United States)

Rong, Taotao; Yang, Lin-An; Yang, Lin; Hao, Yue

2018-01-01

In this work, we report an investigation of resonant tunneling diodes (RTDs) with lattice-matched and polarization-matched AlInN/GaN heterostructures using the numerical simulation. Compared with the lattice-matched AlInN/GaN RTDs, the RTDs based on polarization-matched AlInN/GaN hetero-structures exhibit symmetrical conduction band profiles due to eliminating the polarization charge discontinuity, which achieve the equivalence of double barrier transmission coefficients, thereby the relatively high driving current, the high symmetry of current density, and the high peak-to-valley current ratio (PVCR) under the condition of the positive and the negative sweeping voltages. Simulations show that the peak current density approaches 1.2 × 107 A/cm2 at the bias voltage of 0.72 V and the PVCR approaches 1.37 at both sweeping voltages. It also shows that under the condition of the same shallow energy level, when the trap density reaches 1 × 1019 cm-3, the polarization-matched RTDs still have acceptable negative differential resistance (NDR) characteristics, while the NDR characteristics of lattice-matched RTDs become irregular. After introducing the deeper energy level of 1 eV into the polarization-matched and lattice-matched RTDs, 60 scans are performed under the same trap density. Simulation results show that the degradation of the polarization-matched RTDs is 22%, while lattice-matched RTDs have a degradation of 55%. It can be found that the polarization-matched RTDs have a greater defect tolerance than the lattice-matched RTDs, which is beneficial to the available manufacture of actual terahertz RTD devices.

Gene therapy: a lipofection approach for gene transfer into primary endothelial cells.

Science.gov (United States)

Young, A T L; Lakey, J R T; Murray, A G; Moore, R B

2002-01-01

Despite the great potential of gene therapy to become a new treatment modality in future medicine, there are still many limitations to overcome before this gene approach can pass to the stage of human trial. The foremost obstacle is the development of a safe, efficient, and efficacious vector system for in vivo gene application. This study evaluated the efficacy of lipofection as a gene delivery vehicle into primary endothelial cells. Transfection efficiency of several lipid-based reagents (Effectene, Fugene 6, DOTAP) was examined at experimental temperatures of 37 degrees C, 24 degrees C, and 6 degrees C. Human umbilical vein endothelial cells (HUVECs) were transfected with the enhanced green fluorescent protein (EGFP) using precise amounts of DNA (Effectene, 0.2 microg; Fugene 6, 0.5 microg; DOTAP, 2.5 microg) and lipids (Effectene, 10 microl; Fugene 6, 6 microl; DOTAP, 15 microl) optimized in our laboratory. Duration of incubation in the DNA/lipid transfection mixture varied for each lipid transfectant as follows: 5 h for both Fugene 6 and DOTAP and 3 h for Effectene. Efficiency of transfection was quantified by microscopic evaluation of EFGP expression in a minimum of 100 cells per group. Transfection efficiencies achieved with these lipofection agents were 34 +/- 1.3% (mean +/- SEM), 33 +/- 1.4%, and 18 +/- 1.5% for Effectene, Fugene 6, and DOTAP, respectively, at 37 degrees C. Transfection results were lower at 24 degrees C with mean efficiencies of 26 +/- 2.4% for Effectene, 14 +/- 2.9% for Fugene 6, and 15 +/- 3.2% for DOTAP. Furthermore, mean efficiencies at 6 degrees C were 6 +/- 0.5%, 8 +/- 1.5%, and 6 +/- 0.0% for Effectene, Fugene 6, and DOTAP, respectively. Efficiency of transfection appeared to be temperature dependent (ANOVA; p lipofection a potential gene delivery strategy for in vivo gene therapy.

A synbio approach for selection of highly expressed gene variants in Gram-positive bacteria

DEFF Research Database (Denmark)

Ferro, Roberto; Rennig, Maja; Hernández Rollán, Cristina

2018-01-01

with a long history in food fermentation. We have developed a synbio approach for increasing gene expression in two Gram-positive bacteria. First of all, the gene of interest was coupled to an antibiotic resistance gene to create a growth-based selection system. We then randomised the translation initiation...... region (TIR) preceding the gene of interest and selected clones that produced high protein titres, as judged by their ability to survive on high concentrations of antibiotic. Using this approach, we were able to significantly increase production of two industrially relevant proteins; sialidase in B....... subtilis and tyrosine ammonia lyase in L. lactis. Gram-positive bacteria are widely used to produce industrial enzymes. High titres are necessary to make the production economically feasible. The synbio approach presented here is a simple and inexpensive way to increase protein titres, which can be carried...

Discovering implicit entity relation with the gene-citation-gene network.

Directory of Open Access Journals (Sweden)

Min Song

Full Text Available In this paper, we apply the entitymetrics model to our constructed Gene-Citation-Gene (GCG network. Based on the premise there is a hidden, but plausible, relationship between an entity in one article and an entity in its citing article, we constructed a GCG network of gene pairs implicitly connected through citation. We compare the performance of this GCG network to a gene-gene (GG network constructed over the same corpus but which uses gene pairs explicitly connected through traditional co-occurrence. Using 331,411 MEDLINE abstracts collected from 18,323 seed articles and their references, we identify 25 gene pairs. A comparison of these pairs with interactions found in BioGRID reveal that 96% of the gene pairs in the GCG network have known interactions. We measure network performance using degree, weighted degree, closeness, betweenness centrality and PageRank. Combining all measures, we find the GCG network has more gene pairs, but a lower matching rate than the GG network. However, combining top ranked genes in both networks produces a matching rate of 35.53%. By visualizing both the GG and GCG networks, we find that cancer is the most dominant disease associated with the genes in both networks. Overall, the study indicates that the GCG network can be useful for detecting gene interaction in an implicit manner.

Fast and accurate phylogeny reconstruction using filtered spaced-word matches

Science.gov (United States)

Sohrabi-Jahromi, Salma; Morgenstern, Burkhard

2017-01-01

Abstract Motivation: Word-based or ‘alignment-free’ algorithms are increasingly used for phylogeny reconstruction and genome comparison, since they are much faster than traditional approaches that are based on full sequence alignments. Existing alignment-free programs, however, are less accurate than alignment-based methods. Results: We propose Filtered Spaced Word Matches (FSWM), a fast alignment-free approach to estimate phylogenetic distances between large genomic sequences. For a pre-defined binary pattern of match and don’t-care positions, FSWM rapidly identifies spaced word-matches between input sequences, i.e. gap-free local alignments with matching nucleotides at the match positions and with mismatches allowed at the don’t-care positions. We then estimate the number of nucleotide substitutions per site by considering the nucleotides aligned at the don’t-care positions of the identified spaced-word matches. To reduce the noise from spurious random matches, we use a filtering procedure where we discard all spaced-word matches for which the overall similarity between the aligned segments is below a threshold. We show that our approach can accurately estimate substitution frequencies even for distantly related sequences that cannot be analyzed with existing alignment-free methods; phylogenetic trees constructed with FSWM distances are of high quality. A program run on a pair of eukaryotic genomes of a few hundred Mb each takes a few minutes. Availability and Implementation: The program source code for FSWM including a documentation, as well as the software that we used to generate artificial genome sequences are freely available at http://fswm.gobics.de/ Contact: chris.leimeister@stud.uni-goettingen.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28073754

Fiber cavities with integrated mode matching optics.

Science.gov (United States)

Gulati, Gurpreet Kaur; Takahashi, Hiroki; Podoliak, Nina; Horak, Peter; Keller, Matthias

2017-07-17

In fiber based Fabry-Pérot Cavities (FFPCs), limited spatial mode matching between the cavity mode and input/output modes has been the main hindrance for many applications. We have demonstrated a versatile mode matching method for FFPCs. Our novel design employs an assembly of a graded-index and large core multimode fiber directly spliced to a single mode fiber. This all-fiber assembly transforms the propagating mode of the single mode fiber to match with the mode of a FFPC. As a result, we have measured a mode matching of 90% for a cavity length of ~400 μm. This is a significant improvement compared to conventional FFPCs coupled with just a single mode fiber, especially at long cavity lengths. Adjusting the parameters of the assembly, the fundamental cavity mode can be matched with the mode of almost any single mode fiber, making this approach highly versatile and integrable.

Bioinformatics approach of salt tolerance gene in mangrove plant Rhizophora stylosa

Science.gov (United States)

Basyuni, M.; Sumardi

2017-01-01

This study descibes bioinformatics approach on the analyze of the salt tolerance genes in mangrove plant, Rhizophora stylosa on DDBJ/EMBL/GenBank as well as similarity, phylogenetic, potential peptide, and subcellular localization. The DNA sequence between salt tolerance gene from R. stylosa exhibited 42-11% between themselves The target peptide value of mitochondria varied from 0.163 to 0.430, indicated it was possible to exist. These results suggested the importance of understanding the diversity and functional of properties of the different amino acids in mangrove OSC genes. To clarify the relationship among the salt-tolerant genes in R. stylosa, a phylogenetic tree was constructed. The phylogenetic tree shows that there are three clusters, first branch of Cu/Zn SOD and reverse transcriptase genes, the second branch consists of the majority genes and the last group was MAP3K alpha protein kinase only. The present study, therefore, suggested that salt tolerance genes form distinct clusters in the tree.

Multimodal Personal Verification Using Likelihood Ratio for the Match Score Fusion

Directory of Open Access Journals (Sweden)

Long Binh Tran

2017-01-01

Full Text Available In this paper, the authors present a novel personal verification system based on the likelihood ratio test for fusion of match scores from multiple biometric matchers (face, fingerprint, hand shape, and palm print. In the proposed system, multimodal features are extracted by Zernike Moment (ZM. After matching, the match scores from multiple biometric matchers are fused based on the likelihood ratio test. A finite Gaussian mixture model (GMM is used for estimating the genuine and impostor densities of match scores for personal verification. Our approach is also compared to some different famous approaches such as the support vector machine and the sum rule with min-max. The experimental results have confirmed that the proposed system can achieve excellent identification performance for its higher level in accuracy than different famous approaches and thus can be utilized for more application related to person verification.

History Matching in Parallel Computational Environments

Energy Technology Data Exchange (ETDEWEB)

Steven Bryant; Sanjay Srinivasan; Alvaro Barrera; Sharad Yadav

2005-10-01

A novel methodology for delineating multiple reservoir domains for the purpose of history matching in a distributed computing environment has been proposed. A fully probabilistic approach to perturb permeability within the delineated zones is implemented. The combination of robust schemes for identifying reservoir zones and distributed computing significantly increase the accuracy and efficiency of the probabilistic approach. The information pertaining to the permeability variations in the reservoir that is contained in dynamic data is calibrated in terms of a deformation parameter rD. This information is merged with the prior geologic information in order to generate permeability models consistent with the observed dynamic data as well as the prior geology. The relationship between dynamic response data and reservoir attributes may vary in different regions of the reservoir due to spatial variations in reservoir attributes, well configuration, flow constrains etc. The probabilistic approach then has to account for multiple r{sub D} values in different regions of the reservoir. In order to delineate reservoir domains that can be characterized with different rD parameters, principal component analysis (PCA) of the Hessian matrix has been done. The Hessian matrix summarizes the sensitivity of the objective function at a given step of the history matching to model parameters. It also measures the interaction of the parameters in affecting the objective function. The basic premise of PC analysis is to isolate the most sensitive and least correlated regions. The eigenvectors obtained during the PCA are suitably scaled and appropriate grid block volume cut-offs are defined such that the resultant domains are neither too large (which increases interactions between domains) nor too small (implying ineffective history matching). The delineation of domains requires calculation of Hessian, which could be computationally costly and as well as restricts the current approach to

Gene expression profiling via LongSAGE in a non-model plant species: a case study in seeds of Brassica napus

Directory of Open Access Journals (Sweden)

Friedt Wolfgang

2009-07-01

Full Text Available Abstract Background Serial analysis of gene expression (LongSAGE was applied for gene expression profiling in seeds of oilseed rape (Brassica napus ssp. napus. The usefulness of this technique for detailed expression profiling in a non-model organism was demonstrated for the highly complex, neither fully sequenced nor annotated genome of B. napus by applying a tag-to-gene matching strategy based on Brassica ESTs and the annotated proteome of the closely related model crucifer A. thaliana. Results Transcripts from 3,094 genes were detected at two time-points of seed development, 23 days and 35 days after pollination (DAP. Differential expression showed a shift from gene expression involved in diverse developmental processes including cell proliferation and seed coat formation at 23 DAP to more focussed metabolic processes including storage protein accumulation and lipid deposition at 35 DAP. The most abundant transcripts at 23 DAP were coding for diverse protease inhibitor proteins and proteases, including cysteine proteases involved in seed coat formation and a number of lipid transfer proteins involved in embryo pattern formation. At 35 DAP, transcripts encoding napin, cruciferin and oleosin storage proteins were most abundant. Over both time-points, 18.6% of the detected genes were matched by Brassica ESTs identified by LongSAGE tags in antisense orientation. This suggests a strong involvement of antisense transcript expression in regulatory processes during B. napus seed development. Conclusion This study underlines the potential of transcript tagging approaches for gene expression profiling in Brassica crop species via EST matching to annotated A. thaliana genes. Limits of tag detection for low-abundance transcripts can today be overcome by ultra-high throughput sequencing approaches, so that tag-based gene expression profiling may soon become the method of choice for global expression profiling in non-model species.

Multi-image Matching of Airborne SAR Imagery by SANCC

Directory of Open Access Journals (Sweden)

DING Hao

2015-03-01

Full Text Available In order to improve accuracy of SAR matching, a multi-image matching method based on sum of adaptive normalized cross-correlation (SANCC is proposed. It utilizes geometrical and radiometric information of multi-baselinesynthetic aperture radar (SARimages effectively. Firstly, imaging parameters, platform parameters and approximate digital surface model (DSM are used to predict matching line. Secondly, similarity and proximity in Gestalt theory are introduced to SANCC, and SANCC measures of potential matching points along the matching line are calculated. Thirdly, multi-image matching results and object coordinates of matching points are obtained by winner-take-all (WTA optimization strategy. The approach has been demonstrated with airborne SAR images acquired by a Chinese airborne SAR system (CASMSAR system. The experimental results indicate that the proposed algorithm is effective for providing dense and accuracy matching points, reducing the number of mismatches caused by repeated textures, and offering a better solution to match in poor textured areas.

Using machine learning to assess covariate balance in matching studies.

Science.gov (United States)

Linden, Ariel; Yarnold, Paul R

2016-12-01

In order to assess the effectiveness of matching approaches in observational studies, investigators typically present summary statistics for each observed pre-intervention covariate, with the objective of showing that matching reduces the difference in means (or proportions) between groups to as close to zero as possible. In this paper, we introduce a new approach to distinguish between study groups based on their distributions of the covariates using a machine-learning algorithm called optimal discriminant analysis (ODA). Assessing covariate balance using ODA as compared with the conventional method has several key advantages: the ability to ascertain how individuals self-select based on optimal (maximum-accuracy) cut-points on the covariates; the application to any variable metric and number of groups; its insensitivity to skewed data or outliers; and the use of accuracy measures that can be widely applied to all analyses. Moreover, ODA accepts analytic weights, thereby extending the assessment of covariate balance to any study design where weights are used for covariate adjustment. By comparing the two approaches using empirical data, we are able to demonstrate that using measures of classification accuracy as balance diagnostics produces highly consistent results to those obtained via the conventional approach (in our matched-pairs example, ODA revealed a weak statistically significant relationship not detected by the conventional approach). Thus, investigators should consider ODA as a robust complement, or perhaps alternative, to the conventional approach for assessing covariate balance in matching studies. © 2016 John Wiley & Sons, Ltd.

Rethinking the Match: A Proposal for Modern Matchmaking.

Science.gov (United States)

Ray, Chris; Bishop, Steven E; Dow, Alan W

2018-01-01

Since the 1950s, the National Resident Matching Program, or "the Match," has governed the placement of medical students into residencies. The Match was created to protect students in an era when residency positions outnumbered applicants and hospitals pressured students early in their academic careers to commit to a residency position. Now, however, applicants outnumber positions, applicants are applying to increasing numbers of programs, and the costs of the Match for applicants and programs are high. Meanwhile, medical education is evolving toward a competency-based approach, a U.S. physician shortage is predicted, and some researchers describe a "July effect"-worse clinical outcomes correlated with the mass entry of new residents.Against this background, the authors argue for adopting a more modern, free-market approach to residency matchmaking that might better suit the needs of applicants, programs, and the public. They propose allowing students who have been identified by their medical schools as having achieved graduation-level competency to apply to residency programs at any point during the year. Residency programs would set their own application timetables and extend offers in an ongoing fashion. Students, counseled by their schools, would accept or decline offers as desired. The authors argue this approach would better support competency-based education while allowing applicants and programs more choice regarding how they engage and adapt within the selection process. The approach's staggered start times for new residents might attenuate the July effect and improve outcomes for patients. Medical students might also enter and thereby complete residency earlier, increasing the physician workforce.

Asymptotic Properties of the Number of Matching Coalescent Histories for Caterpillar-Like Families of Species Trees.

Science.gov (United States)

Disanto, Filippo; Rosenberg, Noah A

2016-01-01

Coalescent histories provide lists of species tree branches on which gene tree coalescences can take place, and their enumerative properties assist in understanding the computational complexity of calculations central in the study of gene trees and species trees. Here, we solve an enumerative problem left open by Rosenberg (IEEE/ACM Transactions on Computational Biology and Bioinformatics 10: 1253-1262, 2013) concerning the number of coalescent histories for gene trees and species trees with a matching labeled topology that belongs to a generic caterpillar-like family. By bringing a generating function approach to the study of coalescent histories, we prove that for any caterpillar-like family with seed tree t , the sequence (h n ) n ≥ 0 describing the number of matching coalescent histories of the n th tree of the family grows asymptotically as a constant multiple of the Catalan numbers. Thus, h n  ∼ β t c n , where the asymptotic constant β t > 0 depends on the shape of the seed tree t. The result extends a claim demonstrated only for seed trees with at most eight taxa to arbitrary seed trees, expanding the set of cases for which detailed enumerative properties of coalescent histories can be determined. We introduce a procedure that computes from t the constant β t as well as the algebraic expression for the generating function of the sequence (h n ) n ≥ 0 .

Gene prediction in metagenomic fragments: A large scale machine learning approach

Directory of Open Access Journals (Sweden)

Morgenstern Burkhard

2008-04-01

Full Text Available Abstract Background Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. The amount of metagenomic sequence data is growing fast while computational methods for metagenome analysis are still in their infancy. In contrast to genomic sequences of single species, which can usually be assembled and analyzed by many available methods, a large proportion of metagenome data remains as unassembled anonymous sequencing reads. One of the aims of all metagenomic sequencing projects is the identification of novel genes. Short length, for example, Sanger sequencing yields on average 700 bp fragments, and unknown phylogenetic origin of most fragments require approaches to gene prediction that are different from the currently available methods for genomes of single species. In particular, the large size of metagenomic samples requires fast and accurate methods with small numbers of false positive predictions. Results We introduce a novel gene prediction algorithm for metagenomic fragments based on a two-stage machine learning approach. In the first stage, we use linear discriminants for monocodon usage, dicodon usage and translation initiation sites to extract features from DNA sequences. In the second stage, an artificial neural network combines these features with open reading frame length and fragment GC-content to compute the probability that this open reading frame encodes a protein. This probability is used for the classification and scoring of gene candidates. With large scale training, our method provides fast single fragment predictions with good sensitivity and specificity on artificially fragmented genomic DNA. Additionally, this method is able to predict translation initiation sites accurately and distinguishes complete from incomplete genes with high reliability. Conclusion Large scale machine learning methods are well-suited for gene

Predicting Football Matches Results using Bayesian Networks for English Premier League (EPL)

Science.gov (United States)

Razali, Nazim; Mustapha, Aida; Yatim, Faiz Ahmad; Aziz, Ruhaya Ab

2017-08-01

The issues of modeling asscoiation football prediction model has become increasingly popular in the last few years and many different approaches of prediction models have been proposed with the point of evaluating the attributes that lead a football team to lose, draw or win the match. There are three types of approaches has been considered for predicting football matches results which include statistical approaches, machine learning approaches and Bayesian approaches. Lately, many studies regarding football prediction models has been produced using Bayesian approaches. This paper proposes a Bayesian Networks (BNs) to predict the results of football matches in term of home win (H), away win (A) and draw (D). The English Premier League (EPL) for three seasons of 2010-2011, 2011-2012 and 2012-2013 has been selected and reviewed. K-fold cross validation has been used for testing the accuracy of prediction model. The required information about the football data is sourced from a legitimate site at http://www.football-data.co.uk. BNs achieved predictive accuracy of 75.09% in average across three seasons. It is hoped that the results could be used as the benchmark output for future research in predicting football matches results.

Efficient Topological Localization Using Global and Local Feature Matching

Directory of Open Access Journals (Sweden)

Junqiu Wang

2013-03-01

Full Text Available We present an efficient vision-based global topological localization approach in which different image features are used in a coarse-to-fine matching framework. Orientation Adjacency Coherence Histogram (OACH, a novel image feature, is proposed to improve the coarse localization. The coarse localization results are taken as inputs for the fine localization which is carried out by matching Harris-Laplace interest points characterized by the SIFT descriptor. The computation of OACHs and interest points is efficient due to the fact that these features are computed in an integrated process. The matching of local features is improved by using approximate nearest neighbor searching technique. We have implemented and tested the localization system in real environments. The experimental results demonstrate that our approach is efficient and reliable in both indoor and outdoor environments. This work has also been compared with previous works. The comparison results show that our approach has better performance with higher correct ratio and lower computational complexity.

Stochastic Boolean networks: An efficient approach to modeling gene regulatory networks

Directory of Open Access Journals (Sweden)

Liang Jinghang

2012-08-01

network inferred from a T cell immune response dataset. An SBN can also implement the function of an asynchronous PBN and is potentially useful in a hybrid approach in combination with a continuous or single-molecule level stochastic model. Conclusions Stochastic Boolean networks (SBNs are proposed as an efficient approach to modelling gene regulatory networks (GRNs. The SBN approach is able to recover biologically-proven regulatory behaviours, such as the oscillatory dynamics of the p53-Mdm2 network and the dynamic attractors in a T cell immune response network. The proposed approach can further predict the network dynamics when the genes are under perturbation, thus providing biologically meaningful insights for a better understanding of the dynamics of GRNs. The algorithms and methods described in this paper have been implemented in Matlab packages, which are attached as Additional files.

Transgene traceability in transgenic mice: a bioanalytical approach for potential gene-doping analysis.

Science.gov (United States)

Bogani, Patrizia; Spiriti, Maria Michela; Lazzarano, Stefano; Arcangeli, Annarosa; Buiatti, Marcello; Minunni, Maria

2011-11-01

The World Anti-Doping Agency fears the use of gene doping to enhance athletic performances. Thus, a bioanalytical approach based on end point PCR for detecting markers' of transgenesis traceability was developed. A few sequences from two different vectors using an animal model were selected and traced in different tissues and at different times. In particular, enhanced green fluorescent protein gene and a construct-specific new marker were targeted in the analysis. To make the developed detection approach open to future routine doping analysis, matrices such as urine and tears as well blood were also tested. This study will have impact in evaluating the vector transgenes traceability for the detection of a gene doping event by non-invasive sampling.

Secondhand smoke exposure and other correlates of susceptibility to smoking: a propensity score matching approach.

Science.gov (United States)

McIntire, Russell K; Nelson, Ashlyn A; Macy, Jonathan T; Seo, Dong-Chul; Kolbe, Lloyd J

2015-09-01

Secondhand smoke (SHS) exposure is responsible for numerous diseases of the lungs and other bodily systems among children. In addition to the adverse health effects of SHS exposure, studies show that children exposed to SHS are more likely to smoke in adolescence. Susceptibility to smoking is a measure used to identify adolescent never-smokers who are at risk for smoking. Limited research has been conducted on the influence of SHS on susceptibility to smoking. The purpose of this study was to determine a robust measure of the strength of correlation between SHS exposure and susceptibility to smoking among never-smoking U.S. adolescents. This study used data from the 2009 National Youth Tobacco Survey to identify predictors of susceptibility to smoking in the full (pre-match) sample of adolescents and a smaller (post-match) sample created by propensity score matching. Results showed a significant association between SHS exposure and susceptibility to smoking among never-smoking adolescents in the pre-match (OR=1.47) and post-match (OR=1.52) samples. The odds ratio increase after matching suggests that the strength of the relationship was underestimated in the pre-match sample. Other significant correlates of susceptibility to smoking identified include: gender, race/ethnicity, personal income, smoke-free home rules, number of smoking friends, perception of SHS harm, perceived benefits of smoking, and exposure to pro-tobacco media messages. The use of propensity score matching procedures reduced bias in the post-match sample, and provided a more robust estimate of the influence of SHS exposure on susceptibility to smoking, compared to the pre-match sample estimates. Copyright © 2015 Elsevier Ltd. All rights reserved.

'Omics' approaches in tomato aimed at identifying candidate genes ...

African Journals Online (AJOL)

adriana

2013-12-04

Dec 4, 2013 ... approaches could be combined in order to identify candidate genes for the genetic control of ascorbic ..... applied to other traits under the complex control of many ... Engineering increased vitamin C levels in ... Chem. Biol. 13:532–538. Giovannucci E, Rimm EB, Liu Y, Stampfer MJ, Willett WC (2002). A.

Self-Similar Spin Images for Point Cloud Matching

Science.gov (United States)

Pulido, Daniel

based on the concept of self-similarity to aid in the scale and feature matching steps. An open problem in fusion is how best to extract features from two point clouds and then perform feature-based matching. The proposed approach for this matching step is the use of local self-similarity as an invariant measure to match features. In particular, the proposed approach is to combine the concept of local self-similarity with a well-known feature descriptor, Spin Images, and thereby define "Self-Similar Spin Images". This approach is then extended to the case of matching two points clouds in very different coordinate systems (e.g., a geo-referenced Lidar point cloud and stereo-image derived point cloud without geo-referencing). The use of Self-Similar Spin Images is again applied to address this problem by introducing a "Self-Similar Keyscale" that matches the spatial scales of two point clouds. Another open problem is how best to detect changes in content between two point clouds. A method is proposed to find changes between two point clouds by analyzing the order statistics of the nearest neighbors between the two clouds, and thereby define the "Nearest Neighbor Order Statistic" method. Note that the well-known Hausdorff distance is a special case as being just the maximum order statistic. Therefore, by studying the entire histogram of these nearest neighbors it is expected to yield a more robust method to detect points that are present in one cloud but not the other. This approach is applied at multiple resolutions. Therefore, changes detected at the coarsest level will yield large missing targets and at finer levels will yield smaller targets.

Towards 3D Face Recognition in the Real: A Registration-Free Approach Using Fine-Grained Matching of 3D Keypoint Descriptors

KAUST Repository

Li, Huibin

2014-11-12

Registration algorithms performed on point clouds or range images of face scans have been successfully used for automatic 3D face recognition under expression variations, but have rarely been investigated to solve pose changes and occlusions mainly since that the basic landmarks to initialize coarse alignment are not always available. Recently, local feature-based SIFT-like matching proves competent to handle all such variations without registration. In this paper, towards 3D face recognition for real-life biometric applications, we significantly extend the SIFT-like matching framework to mesh data and propose a novel approach using fine-grained matching of 3D keypoint descriptors. First, two principal curvature-based 3D keypoint detectors are provided, which can repeatedly identify complementary locations on a face scan where local curvatures are high. Then, a robust 3D local coordinate system is built at each keypoint, which allows extraction of pose-invariant features. Three keypoint descriptors, corresponding to three surface differential quantities, are designed, and their feature-level fusion is employed to comprehensively describe local shapes of detected keypoints. Finally, we propose a multi-task sparse representation based fine-grained matching algorithm, which accounts for the average reconstruction error of probe face descriptors sparsely represented by a large dictionary of gallery descriptors in identification. Our approach is evaluated on the Bosphorus database and achieves rank-one recognition rates of 96.56, 98.82, 91.14, and 99.21 % on the entire database, and the expression, pose, and occlusion subsets, respectively. To the best of our knowledge, these are the best results reported so far on this database. Additionally, good generalization ability is also exhibited by the experiments on the FRGC v2.0 database.

FEATURE MATCHING OF HISTORICAL IMAGES BASED ON GEOMETRY OF QUADRILATERALS

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F. Maiwald

2018-05-01

Full Text Available This contribution shows an approach to match historical images from the photo library of the Saxon State and University Library Dresden (SLUB in the context of a historical three-dimensional city model of Dresden. In comparison to recent images, historical photography provides diverse factors which make an automatical image analysis (feature detection, feature matching and relative orientation of images difficult. Due to e.g. film grain, dust particles or the digitalization process, historical images are often covered by noise interfering with the image signal needed for a robust feature matching. The presented approach uses quadrilaterals in image space as these are commonly available in man-made structures and façade images (windows, stones, claddings. It is explained how to generally detect quadrilaterals in images. Consequently, the properties of the quadrilaterals as well as the relationship to neighbouring quadrilaterals are used for the description and matching of feature points. The results show that most of the matches are robust and correct but still small in numbers.

Interaction between the Opioid Receptor OPRM1 Gene and Mother-Child Language Style Matching Prospectively Predicts Children's Separation Anxiety Disorder Symptoms.

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Boparai, Sameen; Borelli, Jessica L; Partington, Lindsey; Smiley, Patricia; Jarvik, Ella; Rasmussen, Hannah F; Seaman, Lauren C; Nurmi, Erika L

2018-03-22

Recent research suggests that lower mother-child language style matching (LSM) is associated with greater physiological reactivity and insecure attachment in school-aged children, but to date no studies have explored this measure of parent-child behavioral matching for its association with children's anxiety symptoms, a well-known correlate of attachment insecurity and heightened physiological reactivity. There is also considerable evidence of genetic risk for anxiety, including possession of the OPRM1 minor allele, 118G. In the current study (N = 44), we expand upon what is known about children's genetic and environmental risk for anxiety by examining the unique and interactive effects of mother-child LSM and the OPRM1 polymorphism A118G on school-aged children's separation anxiety disorder (SAD) symptoms. SAD symptoms were measured both concurrently with LSM and OPRM1 genotype and two years later through self-report. No significant associations emerged between LSM or OPRM1 and concurrent Time 1 SAD symptoms. However, lower LSM and 118G minor allele possession were both associated with greater SAD symptoms at Time 2; further, the interaction between LSM and OPRM1 genotype significantly predicted SAD symptoms beyond the main effects of the two variables. Possession of the minor allele was only associated with greater SAD symptoms among children in low LSM dyads, whereas children with the minor allele in high LSM dyads showed non-significantly lower SAD symptoms. These findings and a proportion affected analysis provide support for a differential susceptibility model of gene by environment interactions for the OPRM1 gene. We discuss the implications for predicting children's separation anxiety across development. Copyright © 2018 Elsevier Ltd. All rights reserved.

Prostate cancer metastasis-driving genes: hurdles and potential approaches in their identification

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Yan Ting Chiang

2014-08-01

Full Text Available Metastatic prostate cancer is currently incurable. Metastasis is thought to result from changes in the expression of specific metastasis-driving genes in nonmetastatic prostate cancer tissue, leading to a cascade of activated downstream genes that set the metastatic process in motion. Such genes could potentially serve as effective therapeutic targets for improved management of the disease. They could be identified by comparative analysis of gene expression profiles of patient-derived metastatic and nonmetastatic prostate cancer tissues to pinpoint genes showing altered expression, followed by determining whether silencing of such genes can lead to inhibition of metastatic properties. Various hurdles encountered in this approach are discussed, including (i the need for clinically relevant, nonmetastatic and metastatic prostate cancer tissues such as xenografts of patients' prostate cancers developed via subrenal capsule grafting technology and (ii limitations in the currently available methodology for identification of master regulatory genes.

IMPROVED REAL-TIME SCAN MATCHING USING CORNER FEATURES

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H. A. Mohamed

2016-06-01

Full Text Available The automation of unmanned vehicle operation has gained a lot of research attention, in the last few years, because of its numerous applications. The vehicle localization is more challenging in indoor environments where absolute positioning measurements (e.g. GPS are typically unavailable. Laser range finders are among the most widely used sensors that help the unmanned vehicles to localize themselves in indoor environments. Typically, automatic real-time matching of the successive scans is performed either explicitly or implicitly by any localization approach that utilizes laser range finders. Many accustomed approaches such as Iterative Closest Point (ICP, Iterative Matching Range Point (IMRP, Iterative Dual Correspondence (IDC, and Polar Scan Matching (PSM handles the scan matching problem in an iterative fashion which significantly affects the time consumption. Furthermore, the solution convergence is not guaranteed especially in cases of sharp maneuvers or fast movement. This paper proposes an automated real-time scan matching algorithm where the matching process is initialized using the detected corners. This initialization step aims to increase the convergence probability and to limit the number of iterations needed to reach convergence. The corner detection is preceded by line extraction from the laser scans. To evaluate the probability of line availability in indoor environments, various data sets, offered by different research groups, have been tested and the mean numbers of extracted lines per scan for these data sets are ranging from 4.10 to 8.86 lines of more than 7 points. The set of all intersections between extracted lines are detected as corners regardless of the physical intersection of these line segments in the scan. To account for the uncertainties of the detected corners, the covariance of the corners is estimated using the extracted lines variances. The detected corners are used to estimate the transformation parameters

Combining machine learning and matching techniques to improve causal inference in program evaluation.

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Linden, Ariel; Yarnold, Paul R

2016-12-01

Program evaluations often utilize various matching approaches to emulate the randomization process for group assignment in experimental studies. Typically, the matching strategy is implemented, and then covariate balance is assessed before estimating treatment effects. This paper introduces a novel analytic framework utilizing a machine learning algorithm called optimal discriminant analysis (ODA) for assessing covariate balance and estimating treatment effects, once the matching strategy has been implemented. This framework holds several key advantages over the conventional approach: application to any variable metric and number of groups; insensitivity to skewed data or outliers; and use of accuracy measures applicable to all prognostic analyses. Moreover, ODA accepts analytic weights, thereby extending the methodology to any study design where weights are used for covariate adjustment or more precise (differential) outcome measurement. One-to-one matching on the propensity score was used as the matching strategy. Covariate balance was assessed using standardized difference in means (conventional approach) and measures of classification accuracy (ODA). Treatment effects were estimated using ordinary least squares regression and ODA. Using empirical data, ODA produced results highly consistent with those obtained via the conventional methodology for assessing covariate balance and estimating treatment effects. When ODA is combined with matching techniques within a treatment effects framework, the results are consistent with conventional approaches. However, given that it provides additional dimensions and robustness to the analysis versus what can currently be achieved using conventional approaches, ODA offers an appealing alternative. © 2016 John Wiley & Sons, Ltd.

Evaluating whole transcriptome amplification for gene profiling experiments using RNA-Seq.

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Faherty, Sheena L; Campbell, C Ryan; Larsen, Peter A; Yoder, Anne D

2015-07-30

RNA-Seq has enabled high-throughput gene expression profiling to provide insight into the functional link between genotype and phenotype. Low quantities of starting RNA can be a severe hindrance for studies that aim to utilize RNA-Seq. To mitigate this bottleneck, whole transcriptome amplification (WTA) technologies have been developed to generate sufficient sequencing targets from minute amounts of RNA. Successful WTA requires accurate replication of transcript abundance without the loss or distortion of specific mRNAs. Here, we test the efficacy of NuGEN's Ovation RNA-Seq V2 system, which uses linear isothermal amplification with a unique chimeric primer for amplification, using white adipose tissue from standard laboratory rats (Rattus norvegicus). Our goal was to investigate potential biological artifacts introduced through WTA approaches by establishing comparisons between matched raw and amplified RNA libraries derived from biological replicates. We found that 93% of expressed genes were identical between all unamplified versus matched amplified comparisons, also finding that gene density is similar across all comparisons. Our sequencing experiment and downstream bioinformatic analyses using the Tuxedo analysis pipeline resulted in the assembly of 25,543 high-quality transcripts. Libraries constructed from raw RNA and WTA samples averaged 15,298 and 15,253 expressed genes, respectively. Although significant differentially expressed genes (P < 0.05) were identified in all matched samples, each of these represents less than 0.15% of all shared genes for each comparison. Transcriptome amplification is efficient at maintaining relative transcript frequencies with no significant bias when using this NuGEN linear isothermal amplification kit under ideal laboratory conditions as presented in this study. This methodology has broad applications, from clinical and diagnostic, to field-based studies when sample acquisition, or sample preservation, methods prove

A review of the Match technique as applied to AASE-2/EASOE and SOLVE/THESEO 2000

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G. A. Morris

2005-01-01

Full Text Available We apply the NASA Goddard Trajectory Model to data from a series of ozonesondes to derive ozone loss rates in the lower stratosphere for the AASE-2/EASOE mission (January-March 1992 and for the SOLVE/THESEO 2000 mission (January-March 2000 in an approach similar to Match. Ozone loss rates are computed by comparing the ozone concentrations provided by ozonesondes launched at the beginning and end of the trajectories connecting the launches. We investigate the sensitivity of the Match results to the various parameters used to reject potential matches in the original Match technique. While these filters effectively eliminate from consideration 80% of the matched sonde pairs and >99% of matched observations in our study, we conclude that only a filter based on potential vorticity changes along the calculated back trajectories seems warranted. Our study also demonstrates that the ozone loss rates estimated in Match can vary by up to a factor of two depending upon the precise trajectory paths calculated for each trajectory. As a result, the statistical uncertainties published with previous Match results might need to be augmented by an additional systematic error. The sensitivity to the trajectory path is particularly pronounced in the month of January, for which the largest ozone loss rate discrepancies between photochemical models and Match are found. For most of the two study periods, our ozone loss rates agree with those previously published. Notable exceptions are found for January 1992 at 475K and late February/early March 2000 at 450K, both periods during which we generally find smaller loss rates than the previous Match studies. Integrated ozone loss rates estimated by Match in both of those years compare well with those found in numerous other studies and in a potential vorticity/potential temperature approach shown previously and in this paper. Finally, we suggest an alternate approach to Match using trajectory mapping. This approach uses

A network approach to predict pathogenic genes for Fusarium graminearum.

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Liu, Xiaoping; Tang, Wei-Hua; Zhao, Xing-Ming; Chen, Luonan

2010-10-04

Fusarium graminearum is the pathogenic agent of Fusarium head blight (FHB), which is a destructive disease on wheat and barley, thereby causing huge economic loss and health problems to human by contaminating foods. Identifying pathogenic genes can shed light on pathogenesis underlying the interaction between F. graminearum and its plant host. However, it is difficult to detect pathogenic genes for this destructive pathogen by time-consuming and expensive molecular biological experiments in lab. On the other hand, computational methods provide an alternative way to solve this problem. Since pathogenesis is a complicated procedure that involves complex regulations and interactions, the molecular interaction network of F. graminearum can give clues to potential pathogenic genes. Furthermore, the gene expression data of F. graminearum before and after its invasion into plant host can also provide useful information. In this paper, a novel systems biology approach is presented to predict pathogenic genes of F. graminearum based on molecular interaction network and gene expression data. With a small number of known pathogenic genes as seed genes, a subnetwork that consists of potential pathogenic genes is identified from the protein-protein interaction network (PPIN) of F. graminearum, where the genes in the subnetwork are further required to be differentially expressed before and after the invasion of the pathogenic fungus. Therefore, the candidate genes in the subnetwork are expected to be involved in the same biological processes as seed genes, which imply that they are potential pathogenic genes. The prediction results show that most of the pathogenic genes of F. graminearum are enriched in two important signal transduction pathways, including G protein coupled receptor pathway and MAPK signaling pathway, which are known related to pathogenesis in other fungi. In addition, several pathogenic genes predicted by our method are verified in other pathogenic fungi, which

A network approach to predict pathogenic genes for Fusarium graminearum.

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Xiaoping Liu

Full Text Available Fusarium graminearum is the pathogenic agent of Fusarium head blight (FHB, which is a destructive disease on wheat and barley, thereby causing huge economic loss and health problems to human by contaminating foods. Identifying pathogenic genes can shed light on pathogenesis underlying the interaction between F. graminearum and its plant host. However, it is difficult to detect pathogenic genes for this destructive pathogen by time-consuming and expensive molecular biological experiments in lab. On the other hand, computational methods provide an alternative way to solve this problem. Since pathogenesis is a complicated procedure that involves complex regulations and interactions, the molecular interaction network of F. graminearum can give clues to potential pathogenic genes. Furthermore, the gene expression data of F. graminearum before and after its invasion into plant host can also provide useful information. In this paper, a novel systems biology approach is presented to predict pathogenic genes of F. graminearum based on molecular interaction network and gene expression data. With a small number of known pathogenic genes as seed genes, a subnetwork that consists of potential pathogenic genes is identified from the protein-protein interaction network (PPIN of F. graminearum, where the genes in the subnetwork are further required to be differentially expressed before and after the invasion of the pathogenic fungus. Therefore, the candidate genes in the subnetwork are expected to be involved in the same biological processes as seed genes, which imply that they are potential pathogenic genes. The prediction results show that most of the pathogenic genes of F. graminearum are enriched in two important signal transduction pathways, including G protein coupled receptor pathway and MAPK signaling pathway, which are known related to pathogenesis in other fungi. In addition, several pathogenic genes predicted by our method are verified in other

A Novel Real-Time Reference Key Frame Scan Matching Method

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Haytham Mohamed

2017-05-01

Full Text Available Unmanned aerial vehicles represent an effective technology for indoor search and rescue operations. Typically, most indoor missions’ environments would be unknown, unstructured, and/or dynamic. Navigation of UAVs in such environments is addressed by simultaneous localization and mapping approach using either local or global approaches. Both approaches suffer from accumulated errors and high processing time due to the iterative nature of the scan matching method. Moreover, point-to-point scan matching is prone to outlier association processes. This paper proposes a low-cost novel method for 2D real-time scan matching based on a reference key frame (RKF. RKF is a hybrid scan matching technique comprised of feature-to-feature and point-to-point approaches. This algorithm aims at mitigating errors accumulation using the key frame technique, which is inspired from video streaming broadcast process. The algorithm depends on the iterative closest point algorithm during the lack of linear features which is typically exhibited in unstructured environments. The algorithm switches back to the RKF once linear features are detected. To validate and evaluate the algorithm, the mapping performance and time consumption are compared with various algorithms in static and dynamic environments. The performance of the algorithm exhibits promising navigational, mapping results and very short computational time, that indicates the potential use of the new algorithm with real-time systems.

Unsupervised image matching based on manifold alignment.

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Pei, Yuru; Huang, Fengchun; Shi, Fuhao; Zha, Hongbin

2012-08-01

This paper challenges the issue of automatic matching between two image sets with similar intrinsic structures and different appearances, especially when there is no prior correspondence. An unsupervised manifold alignment framework is proposed to establish correspondence between data sets by a mapping function in the mutual embedding space. We introduce a local similarity metric based on parameterized distance curves to represent the connection of one point with the rest of the manifold. A small set of valid feature pairs can be found without manual interactions by matching the distance curve of one manifold with the curve cluster of the other manifold. To avoid potential confusions in image matching, we propose an extended affine transformation to solve the nonrigid alignment in the embedding space. The comparatively tight alignments and the structure preservation can be obtained simultaneously. The point pairs with the minimum distance after alignment are viewed as the matchings. We apply manifold alignment to image set matching problems. The correspondence between image sets of different poses, illuminations, and identities can be established effectively by our approach.

A Multiomics Approach to Identify Genes Associated with Childhood Asthma Risk and Morbidity.

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Forno, Erick; Wang, Ting; Yan, Qi; Brehm, John; Acosta-Perez, Edna; Colon-Semidey, Angel; Alvarez, Maria; Boutaoui, Nadia; Cloutier, Michelle M; Alcorn, John F; Canino, Glorisa; Chen, Wei; Celedón, Juan C

2017-10-01

Childhood asthma is a complex disease. In this study, we aim to identify genes associated with childhood asthma through a multiomics "vertical" approach that integrates multiple analytical steps using linear and logistic regression models. In a case-control study of childhood asthma in Puerto Ricans (n = 1,127), we used adjusted linear or logistic regression models to evaluate associations between several analytical steps of omics data, including genome-wide (GW) genotype data, GW methylation, GW expression profiling, cytokine levels, asthma-intermediate phenotypes, and asthma status. At each point, only the top genes/single-nucleotide polymorphisms/probes/cytokines were carried forward for subsequent analysis. In step 1, asthma modified the gene expression-protein level association for 1,645 genes; pathway analysis showed an enrichment of these genes in the cytokine signaling system (n = 269 genes). In steps 2-3, expression levels of 40 genes were associated with intermediate phenotypes (asthma onset age, forced expiratory volume in 1 second, exacerbations, eosinophil counts, and skin test reactivity); of those, methylation of seven genes was also associated with asthma. Of these seven candidate genes, IL5RA was also significant in analytical steps 4-8. We then measured plasma IL-5 receptor α levels, which were associated with asthma age of onset and moderate-severe exacerbations. In addition, in silico database analysis showed that several of our identified IL5RA single-nucleotide polymorphisms are associated with transcription factors related to asthma and atopy. This approach integrates several analytical steps and is able to identify biologically relevant asthma-related genes, such as IL5RA. It differs from other methods that rely on complex statistical models with various assumptions.

Probabilistic seismic history matching using binary images

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Davolio, Alessandra; Schiozer, Denis Jose

2018-02-01

Currently, the goal of history-matching procedures is not only to provide a model matching any observed data but also to generate multiple matched models to properly handle uncertainties. One such approach is a probabilistic history-matching methodology based on the discrete Latin Hypercube sampling algorithm, proposed in previous works, which was particularly efficient for matching well data (production rates and pressure). 4D seismic (4DS) data have been increasingly included into history-matching procedures. A key issue in seismic history matching (SHM) is to transfer data into a common domain: impedance, amplitude or pressure, and saturation. In any case, seismic inversions and/or modeling are required, which can be time consuming. An alternative to avoid these procedures is using binary images in SHM as they allow the shape, rather than the physical values, of observed anomalies to be matched. This work presents the incorporation of binary images in SHM within the aforementioned probabilistic history matching. The application was performed with real data from a segment of the Norne benchmark case that presents strong 4D anomalies, including softening signals due to pressure build up. The binary images are used to match the pressurized zones observed in time-lapse data. Three history matchings were conducted using: only well data, well and 4DS data, and only 4DS. The methodology is very flexible and successfully utilized the addition of binary images for seismic objective functions. Results proved the good convergence of the method in few iterations for all three cases. The matched models of the first two cases provided the best results, with similar well matching quality. The second case provided models presenting pore pressure changes according to the expected dynamic behavior (pressurized zones) observed on 4DS data. The use of binary images in SHM is relatively new with few examples in the literature. This work enriches this discussion by presenting a new

Matching with transfer matrices

International Nuclear Information System (INIS)

Perez-Alvarez, R.; Velasco, V.R.; Garcia-Moliner, F.; Rodriguez-Coppola, H.

1987-10-01

An ABC configuration - which corresponds to various systems of physical interest, such as a barrier or a quantum well - is studied by combining a surface Green function matching analysis of the entire system with a description of the intermediate (B) region in terms of a transfer matrix in the sense of Mora et al. (1985). This hybrid approach proves very useful when it is very difficult to construct the corresponding Green function G B . An application is made to the calculation of quantised subband levels in a parabolic quantum well. Further possibilities of extension of this approach are pointed out. (author). 27 refs, 1 tab

No difference in the frequency of locus-specific methylation in the peripheral blood DNA of women diagnosed with breast cancer and age-matched controls

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Wojdacz, Tomasz K; Thestrup, Britta Boserup; Cold, Søren

2011-01-01

with no signs of breast cancer. No significant differences in the frequency of methylation of the above genes were found between cases and controls in our study. Hence, testing for the presence of methylation of cancer-related genes in PBL DNA from women diagnosed with sporadic breast cancer and classified...... might predispose for cancer development. Here, we have used the methlyation-sensitive high-resolution melting approach to examine the methylation status of the BRCA1, BRCA2, APC, RASSF1A and RARβ2 genes in PBLs of a group of women diagnosed with breast cancer, and an age-matched control group......, to the pathology of different diseases, remains open. Recently, a number of studies addressed the question of the prevalence of aberrant methylation of cancer-related genes in peripheral blood leukocyte (PBL) DNA and indicated a strong possibility that the presence of constitutional methylation of different genes...

Positron emission tomography and gene therapy: basic concepts and experimental approaches for in vivo gene expression imaging.

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Peñuelas, Iván; Boán, JoséF; Martí-Climent, Josep M; Sangro, Bruno; Mazzolini, Guillermo; Prieto, Jesús; Richter, José A

2004-01-01

More than two decades of intense research have allowed gene therapy to move from the laboratory to the clinical setting, where its use for the treatment of human pathologies has been considerably increased in the last years. However, many crucial questions remain to be solved in this challenging field. In vivo imaging with positron emission tomography (PET) by combination of the appropriate PET reporter gene and PET reporter probe could provide invaluable qualitative and quantitative information to answer multiple unsolved questions about gene therapy. PET imaging could be used to define parameters not available by other techniques that are of substantial interest not only for the proper understanding of the gene therapy process, but also for its future development and clinical application in humans. This review focuses on the molecular biology basis of gene therapy and molecular imaging, describing the fundamentals of in vivo gene expression imaging by PET, and the application of PET to gene therapy, as a technology that can be used in many different ways. It could be applied to avoid invasive procedures for gene therapy monitoring; accurately diagnose the pathology for better planning of the most adequate therapeutic approach; as treatment evaluation to image the functional effects of gene therapy at the biochemical level; as a quantitative noninvasive way to monitor the location, magnitude and persistence of gene expression over time; and would also help to a better understanding of vector biology and pharmacology devoted to the development of safer and more efficient vectors.

Expression profiles of selected genes in tumors and matched surgical margins in oral cavity cancer: Do we have to pay attention to the molecular analysis of the surgical margins?

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Strzelczyk, Joanna K; Krakowczyk, Łukasz; Gołąbek, Karolina; Owczarek, Aleksander J

2018-04-24

Head and neck squamous cell carcinomas (HNSCCs) are associated with an interplay between genetics and the environment; they account for 3% of all diagnosed malignant tumors in men and 2% of those in women. The aim of the study was to analyze the significance of TIMP3, SFRP1, SFRP2, CDH1, RASSF1, RORA, and DAPK1 gene expression in head and neck squamous cell carcinoma tumors, and in matching surgical margin samples. We also analyzed the association between clinical parameters and the expression of the selected genes. Following surgical resection, 56 primary HNSCC tumors and matching surgical margin samples were collected from patients at the Clinic of Oncological and Reconstructive Surgery of Maria Skłodowska-Curie Memorial Cancer Center and the Institute of Oncology in Gliwice, Poland. The gene expression levels were analyzed by quantitative reverse transcription (qRT)-PCR. SFRP1 gene expression was statistically significantly lower in the tumor samples than in the surgical margins (0.30 ±0.36 vs 0.62 ±0.36; p < 0.01). No correlation was found between gene expression and clinical parameters, except DAPK1, where low expression correlated with alcohol abuse (0.85 ±1.19 vs 1.97 ±3.22; p = 0.074). Moreover, patients with G3 grade tumors, i.e., poorly differentiated tumors, had significantly higher values of DAPK1 gene expression than the G1 (well-differentiated tumors) and G2 (moderately differentiated) groups. There are many different reasons and concepts for altered gene expression in tumors and surgical margin tissue. Tumor heterogeneity and its microenvironment are undoubtedly linked to the biology of HNSCC. In order to understand specific tumor behavior and the microenvironment, further studies are needed. To find markers connected with cancer development and to provide insight into the earliest stages of cancer development, attention should also be focused on molecular analysis of the surgical margins.

A multi-pattern hash-binary hybrid algorithm for URL matching in the HTTP protocol.

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Ping Zeng

Full Text Available In this paper, based on our previous multi-pattern uniform resource locator (URL binary-matching algorithm called HEM, we propose an improved multi-pattern matching algorithm called MH that is based on hash tables and binary tables. The MH algorithm can be applied to the fields of network security, data analysis, load balancing, cloud robotic communications, and so on-all of which require string matching from a fixed starting position. Our approach effectively solves the performance problems of the classical multi-pattern matching algorithms. This paper explores ways to improve string matching performance under the HTTP protocol by using a hash method combined with a binary method that transforms the symbol-space matching problem into a digital-space numerical-size comparison and hashing problem. The MH approach has a fast matching speed, requires little memory, performs better than both the classical algorithms and HEM for matching fields in an HTTP stream, and it has great promise for use in real-world applications.

Robust and accurate multi-view reconstruction by prioritized matching

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Ylimaki, Markus; Kannala, Juho; Holappa, Jukka

2012-01-01

a prioritized matching method which expands the most promising seeds first. The output of the method is a three-dimensional point cloud. Unlike previous correspondence growing approaches our method allows to use the best-first matching principle in the generic multi-view stereo setting with arbitrary number...... of input images. Our experiments show that matching the most promising seeds first provides very robust point cloud reconstructions efficiently with just a single expansion step. A comparison to the current state-of-the-art shows that our method produces reconstructions of similar quality but significantly...

Fast group matching for MR fingerprinting reconstruction.

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Cauley, Stephen F; Setsompop, Kawin; Ma, Dan; Jiang, Yun; Ye, Huihui; Adalsteinsson, Elfar; Griswold, Mark A; Wald, Lawrence L

2015-08-01

MR fingerprinting (MRF) is a technique for quantitative tissue mapping using pseudorandom measurements. To estimate tissue properties such as T1 , T2 , proton density, and B0 , the rapidly acquired data are compared against a large dictionary of Bloch simulations. This matching process can be a very computationally demanding portion of MRF reconstruction. We introduce a fast group matching algorithm (GRM) that exploits inherent correlation within MRF dictionaries to create highly clustered groupings of the elements. During matching, a group specific signature is first used to remove poor matching possibilities. Group principal component analysis (PCA) is used to evaluate all remaining tissue types. In vivo 3 Tesla brain data were used to validate the accuracy of our approach. For a trueFISP sequence with over 196,000 dictionary elements, 1000 MRF samples, and image matrix of 128 × 128, GRM was able to map MR parameters within 2s using standard vendor computational resources. This is an order of magnitude faster than global PCA and nearly two orders of magnitude faster than direct matching, with comparable accuracy (1-2% relative error). The proposed GRM method is a highly efficient model reduction technique for MRF matching and should enable clinically relevant reconstruction accuracy and time on standard vendor computational resources. © 2014 Wiley Periodicals, Inc.

A surgical approach appropriate for targeted cochlear gene therapy in the mouse.

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Jero, J; Tseng, C J; Mhatre, A N; Lalwani, A K

2001-01-01

Therapeutic manipulations of the mammalian cochlea, including cochlear gene transfer, have been predominantly studied using the guinea pig as the experimental model. With the significant developments in mouse genomics and the availability of mutant strains of mice with well-characterized hearing loss, the mouse justifiably will be the preferred animal model for therapeutic manipulations. However, the potential advantages of the mouse model have not been fully realized due to the surgical difficulty of accessing its small cochlea. This study describes a ventral approach, instead of the routinely used postauricular approach in other rodents, for accessing the mouse middle and inner ear, and its application in cochlear gene transfer. This ventral approach enabled rapid and direct delivery of liposome-transgene complex to the mouse inner ear while avoiding blood loss, facial nerve morbidity, and mortality. Transgene expression at 3 days was detected in Reissner's membrane, spiral limbus, spiral ligament, and spiral ganglion cells, in a pattern similar to that previously described in the guinea pig. The successful access and delivery of material to the mouse cochlea and the replication of gene expression seen in the guinea pig demonstrated in this study should promote the use of the mouse in future studies investigating targeted cochlear therapy.

A synbio approach for selection of highly expressed gene variants in Gram-positive bacteria.

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Ferro, Roberto; Rennig, Maja; Hernández-Rollán, Cristina; Daley, Daniel O; Nørholm, Morten H H

2018-03-08

The market for recombinant proteins is on the rise, and Gram-positive strains are widely exploited for this purpose. Bacillus subtilis is a profitable host for protein production thanks to its ability to secrete large amounts of proteins, and Lactococcus lactis is an attractive production organism with a long history in food fermentation. We have developed a synbio approach for increasing gene expression in two Gram-positive bacteria. First of all, the gene of interest was coupled to an antibiotic resistance gene to create a growth-based selection system. We then randomised the translation initiation region (TIR) preceding the gene of interest and selected clones that produced high protein titres, as judged by their ability to survive on high concentrations of antibiotic. Using this approach, we were able to significantly increase production of two industrially relevant proteins; sialidase in B. subtilis and tyrosine ammonia lyase in L. lactis. Gram-positive bacteria are widely used to produce industrial enzymes. High titres are necessary to make the production economically feasible. The synbio approach presented here is a simple and inexpensive way to increase protein titres, which can be carried out in any laboratory within a few days. It could also be implemented as a tool for applications beyond TIR libraries, such as screening of synthetic, homologous or domain-shuffled genes.

RMP: Reduced-set matching pursuit approach for efficient compressed sensing signal reconstruction

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Michael M. Abdel-Sayed

2016-11-01

Full Text Available Compressed sensing enables the acquisition of sparse signals at a rate that is much lower than the Nyquist rate. Compressed sensing initially adopted ℓ1 minimization for signal reconstruction which is computationally expensive. Several greedy recovery algorithms have been recently proposed for signal reconstruction at a lower computational complexity compared to the optimal ℓ1 minimization, while maintaining a good reconstruction accuracy. In this paper, the Reduced-set Matching Pursuit (RMP greedy recovery algorithm is proposed for compressed sensing. Unlike existing approaches which either select too many or too few values per iteration, RMP aims at selecting the most sufficient number of correlation values per iteration, which improves both the reconstruction time and error. Furthermore, RMP prunes the estimated signal, and hence, excludes the incorrectly selected values. The RMP algorithm achieves a higher reconstruction accuracy at a significantly low computational complexity compared to existing greedy recovery algorithms. It is even superior to ℓ1 minimization in terms of the normalized time-error product, a new metric introduced to measure the trade-off between the reconstruction time and error. RMP superior performance is illustrated with both noiseless and noisy samples.

RMP: Reduced-set matching pursuit approach for efficient compressed sensing signal reconstruction.

Science.gov (United States)

Abdel-Sayed, Michael M; Khattab, Ahmed; Abu-Elyazeed, Mohamed F

2016-11-01

Compressed sensing enables the acquisition of sparse signals at a rate that is much lower than the Nyquist rate. Compressed sensing initially adopted [Formula: see text] minimization for signal reconstruction which is computationally expensive. Several greedy recovery algorithms have been recently proposed for signal reconstruction at a lower computational complexity compared to the optimal [Formula: see text] minimization, while maintaining a good reconstruction accuracy. In this paper, the Reduced-set Matching Pursuit (RMP) greedy recovery algorithm is proposed for compressed sensing. Unlike existing approaches which either select too many or too few values per iteration, RMP aims at selecting the most sufficient number of correlation values per iteration, which improves both the reconstruction time and error. Furthermore, RMP prunes the estimated signal, and hence, excludes the incorrectly selected values. The RMP algorithm achieves a higher reconstruction accuracy at a significantly low computational complexity compared to existing greedy recovery algorithms. It is even superior to [Formula: see text] minimization in terms of the normalized time-error product, a new metric introduced to measure the trade-off between the reconstruction time and error. RMP superior performance is illustrated with both noiseless and noisy samples.

Environment-Gene interaction in common complex diseases: New approaches

Directory of Open Access Journals (Sweden)

William A. Toscano, Jr.

2014-10-01

Full Text Available Approximately 100,000 different environmental chemicals that are in use as high production volume chemicals confront us in our daily lives. Many of the chemicals we encounter are persistent and have long half-lives in the environment and our bodies. These compounds are referred to as Persistent Organic Pollutants, or POPS. The total environment however is broader than just toxic pollutants. It includes social capital, social economic status, and other factors that are not commonly considered in traditional approaches to studying environment-human interactions. The mechanism of action of environmental agents in altering the human phenotype from health to disease is more complex than once thought. The focus in public health has shifted away from the study of single-gene rare diseases and has given way to the study of multifactorial complex diseases that are common in the population. To understand common complex diseases, we need teams of scientists from different fields working together with common aims. We review some approaches for studying the action of the environment by discussing use-inspired research, and transdisciplinary research approaches. The Genomic era has yielded new tools for study of gene-environment interactions, including genomics, epigenomics, and systems biology. We use environmentally-driven diabetes mellitus type two as an example of environmental epigenomics and disease. The aim of this review is to start the conversation of how the application of advances in biomedical science can be used to advance public health.

Efficacious and safe tissue-selective controlled gene therapy approaches for the cornea.

Directory of Open Access Journals (Sweden)

Rajiv R Mohan

2011-04-01

Full Text Available Untargeted and uncontrolled gene delivery is a major cause of gene therapy failure. This study aimed to define efficient and safe tissue-selective targeted gene therapy approaches for delivering genes into keratocytes of the cornea in vivo using a normal or diseased rabbit model. New Zealand White rabbits, adeno-associated virus serotype 5 (AAV5, and a minimally invasive hair-dryer based vector-delivery technique were used. Fifty microliters of AAV5 titer (6.5×10(12 vg/ml expressing green fluorescent protein gene (GFP was topically applied onto normal or diseased (fibrotic or neovascularized rabbit corneas for 2-minutes with a custom vector-delivery technique. Corneal fibrosis and neovascularization in rabbit eyes were induced with photorefractive keratectomy using excimer laser and VEGF (630 ng using micropocket assay, respectively. Slit-lamp biomicroscopy and immunocytochemistry were used to confirm fibrosis and neovascularization in rabbit corneas. The levels, location and duration of delivered-GFP gene expression in the rabbit stroma were measured with immunocytochemistry and/or western blotting. Slot-blot measured delivered-GFP gene copy number. Confocal microscopy performed in whole-mounts of cornea and thick corneal sections determined geometric and spatial localization of delivered-GFP in three-dimensional arrangement. AAV5 toxicity and safety were evaluated with clinical eye exam, stereomicroscopy, slit-lamp biomicroscopy, and H&E staining. A single 2-minute AAV5 topical application via custom delivery-technique efficiently and selectively transduced keratocytes in the anterior stroma of normal and diseased rabbit corneas as evident from immunocytochemistry and confocal microscopy. Transgene expression was first detected at day 3, peaked at day 7, and was maintained up to 16 weeks (longest tested time point. Clinical and slit-lamp eye examination in live rabbits and H&E staining did not reveal any significant changes between AAV5

Covariant diagrams for one-loop matching

International Nuclear Information System (INIS)

Zhang, Zhengkang

2016-10-01

We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gaugecovariant quantities and are thus dubbed ''covariant diagrams.'' The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.

Covariant diagrams for one-loop matching

Energy Technology Data Exchange (ETDEWEB)

Zhang, Zhengkang [Michigan Center for Theoretical Physics (MCTP), University of Michigan,450 Church Street, Ann Arbor, MI 48109 (United States); Deutsches Elektronen-Synchrotron (DESY),Notkestraße 85, 22607 Hamburg (Germany)

2017-05-30

We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gauge-covariant quantities and are thus dubbed “covariant diagrams.” The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.

Covariant diagrams for one-loop matching

Energy Technology Data Exchange (ETDEWEB)

Zhang, Zhengkang [Michigan Univ., Ann Arbor, MI (United States). Michigan Center for Theoretical Physics; Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)

2016-10-15

We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gaugecovariant quantities and are thus dubbed ''covariant diagrams.'' The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.

Covariant diagrams for one-loop matching

International Nuclear Information System (INIS)

Zhang, Zhengkang

2017-01-01

We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gauge-covariant quantities and are thus dubbed “covariant diagrams.” The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.

A hybrid gene selection approach for microarray data classification using cellular learning automata and ant colony optimization.

Science.gov (United States)

Vafaee Sharbaf, Fatemeh; Mosafer, Sara; Moattar, Mohammad Hossein

2016-06-01

This paper proposes an approach for gene selection in microarray data. The proposed approach consists of a primary filter approach using Fisher criterion which reduces the initial genes and hence the search space and time complexity. Then, a wrapper approach which is based on cellular learning automata (CLA) optimized with ant colony method (ACO) is used to find the set of features which improve the classification accuracy. CLA is applied due to its capability to learn and model complicated relationships. The selected features from the last phase are evaluated using ROC curve and the most effective while smallest feature subset is determined. The classifiers which are evaluated in the proposed framework are K-nearest neighbor; support vector machine and naïve Bayes. The proposed approach is evaluated on 4 microarray datasets. The evaluations confirm that the proposed approach can find the smallest subset of genes while approaching the maximum accuracy. Copyright © 2016 Elsevier Inc. All rights reserved.

76 FR 5235 - Privacy Act of 1974, as Amended; Computer Matching Program (SSA Internal Match)-Match Number 1014

Science.gov (United States)

2011-01-28

...; Computer Matching Program (SSA Internal Match)--Match Number 1014 AGENCY: Social Security Administration... regarding protections for such persons. The Privacy Act, as amended, regulates the use of computer matching....C. 552a, as amended, and the provisions of the Computer Matching and Privacy Protection Act of 1988...

Evaluation of the Match External Load in Soccer: Methods Comparison.

Science.gov (United States)

Castagna, Carlo; Varley, Matthew; Póvoas, Susana C A; D'Ottavio, Stefano

2017-04-01

To test the interchangeability of 2 match-analysis approaches for external-load detection considering arbitrary selected speeds and metabolic power (MP) thresholds in male top-level soccer. Data analyses were performed considering match physical performance of 60 matches (1200 player cases) of randomly selected Spanish, German, and English first-division championship matches (2013-14 season). Match analysis was performed with a validated semiautomated multicamera system operating at 25 Hz. During a match, players covered 10,673 ± 348 m, of which 1778 ± 208 m and 2759 ± 241 m were performed at high intensity, as measured using speed (≥16 km/h, HI) and metabolic power (≥20 W/kg, MPHI) notations. High-intensity notations were nearly perfectly associated (r = .93, P Player high-intensity decelerations (≥-2 m/s 2 ) were very largely associated with MPHI (r = .73, P physical match-analysis methods can be independently used to track match external load in elite-level players. However, match-analyst decisions must be based on use of a single method to avoid bias in external-load determination.

Candidate gene linkage approach to identify DNA variants that predispose to preterm birth

DEFF Research Database (Denmark)

Bream, Elise N A; Leppellere, Cara R; Cooper, Margaret E

2013-01-01

Background:The aim of this study was to identify genetic variants contributing to preterm birth (PTB) using a linkage candidate gene approach.Methods:We studied 99 single-nucleotide polymorphisms (SNPs) for 33 genes in 257 families with PTBs segregating. Nonparametric and parametric analyses were...... through the infant and/or the mother in the etiology of PTB....

Gene editing in hematopoietic stem cells: a potential therapeutic approach for Fanconi anemia

International Nuclear Information System (INIS)

Diez Cabezas, B.

2015-01-01

Gene therapy nowadays constitutes a safe and efficient treatment for a number of monogenic diseases affecting the hematopoietic system. Risks of insertional mutagenesis derived from the use of integrative vectors cannot, however, be completely excluded. Therefore, gene targeting has been proposed as a safer alternative, since the insertion of the herapeutic gene is driven to a specific locus in the genome. Gene targeting approaches are based on the use of specific nucleases which generate double strand breaks (DSBs) in a specific site of the genome,markedly enhancing the efficacy of homologous recombination (HR) with donor constructs harboring the gene of interest flanked by the corresponding homology arms. In this study we have optimized the conditions to target human lymphoblastic cell lines (LCLs) and also hematopoietic stem cells (HSCs) from healthy donors, with the final aim of correcting by gene editing the hematopoietic progenitor cells from Fanconi anemia subtype A (FA-A) patients. In particular, we have established a robust method to target both LCLs and HSCs in a safe harbor site in the genome, the AAVS1 locus. Our approach is based on the transduction of these cells with integrase-defective lentiviral vectors carrying a donor with the gene of interest, followed by the nucleofection of these cells with zinc finger nucleases used as mRNA. Using a control donor vector carrying the GFP reporter gene we have obtained, on average, 9.43% gene targeting efficiency in cord blood CD34+ cells from healthy donors. Moreover, we confirmed that gene targeting was also efficient in HSCs with long term and multipotent repopulation capacity, as demonstrated by transplants into immunodeficient mice. To improve the gene targeting efficiency, we investigated the feasibility of using gold nanoparticles, which were shown to improve the transduction efficiency of integrase-defective and competent lentiviral vectors in HSCs. This increment, however, did not lead to a higher gene

Gene editing in hematopoietic stem cells: a potential therapeutic approach for Fanconi anemia

Energy Technology Data Exchange (ETDEWEB)

Diez Cabezas, B.

2015-07-01

Gene therapy nowadays constitutes a safe and efficient treatment for a number of monogenic diseases affecting the hematopoietic system. Risks of insertional mutagenesis derived from the use of integrative vectors cannot, however, be completely excluded. Therefore, gene targeting has been proposed as a safer alternative, since the insertion of the herapeutic gene is driven to a specific locus in the genome. Gene targeting approaches are based on the use of specific nucleases which generate double strand breaks (DSBs) in a specific site of the genome,markedly enhancing the efficacy of homologous recombination (HR) with donor constructs harboring the gene of interest flanked by the corresponding homology arms. In this study we have optimized the conditions to target human lymphoblastic cell lines (LCLs) and also hematopoietic stem cells (HSCs) from healthy donors, with the final aim of correcting by gene editing the hematopoietic progenitor cells from Fanconi anemia subtype A (FA-A) patients. In particular, we have established a robust method to target both LCLs and HSCs in a safe harbor site in the genome, the AAVS1 locus. Our approach is based on the transduction of these cells with integrase-defective lentiviral vectors carrying a donor with the gene of interest, followed by the nucleofection of these cells with zinc finger nucleases used as mRNA. Using a control donor vector carrying the GFP reporter gene we have obtained, on average, 9.43% gene targeting efficiency in cord blood CD34+ cells from healthy donors. Moreover, we confirmed that gene targeting was also efficient in HSCs with long term and multipotent repopulation capacity, as demonstrated by transplants into immunodeficient mice. To improve the gene targeting efficiency, we investigated the feasibility of using gold nanoparticles, which were shown to improve the transduction efficiency of integrase-defective and competent lentiviral vectors in HSCs. This increment, however, did not lead to a higher gene

Technical performance and match-to-match variation in elite football teams.

Science.gov (United States)

Liu, Hongyou; Gómez, Miguel-Angel; Gonçalves, Bruno; Sampaio, Jaime

2016-01-01

Recent research suggests that match-to-match variation adds important information to performance descriptors in team sports, as it helps measure how players fine-tune their tactical behaviours and technical actions to the extreme dynamical environments. The current study aims to identify the differences in technical performance of players from strong and weak teams and to explore match-to-match variation of players' technical match performance. Performance data of all the 380 matches of season 2012-2013 in the Spanish First Division Professional Football League were analysed. Twenty-one performance-related match actions and events were chosen as variables in the analyses. Players' technical performance profiles were established by unifying count values of each action or event of each player per match into the same scale. Means of these count values of players from Top3 and Bottom3 teams were compared and plotted into radar charts. Coefficient of variation of each match action or event within a player was calculated to represent his match-to-match variation of technical performance. Differences in the variation of technical performances of players across different match contexts (team and opposition strength, match outcome and match location) were compared. All the comparisons were achieved by the magnitude-based inferences. Results showed that technical performances differed between players of strong and weak teams from different perspectives across different field positions. Furthermore, the variation of the players' technical performance is affected by the match context, with effects from team and opposition strength greater than effects from match location and match outcome.

Small Vocabulary with Saliency Matching for Video Copy Detection

DEFF Research Database (Denmark)

Ren, Huamin; Moeslund, Thomas B.; Tang, Sheng

2013-01-01

The importance of copy detection has led to a substantial amount of research in recent years, among which Bag of visual Words (BoW) plays an important role due to its ability to effectively handling occlusion and some minor transformations. One crucial issue in BoW approaches is the size of vocab......The importance of copy detection has led to a substantial amount of research in recent years, among which Bag of visual Words (BoW) plays an important role due to its ability to effectively handling occlusion and some minor transformations. One crucial issue in BoW approaches is the size...... matching algorithm based on salient visual words selection. More specifically, the variation of visual words across a given video are represented as trajectories and those containing locally asymptotically stable points are selected as salient visual words. Then we attempt to measure the similarity of two...... videos through saliency matching merely based on the selected salient visual words to remove false positives. Our experiments show that a small codebook with saliency matching is quite competitive in video copy detection. With the incorporation of the proposed saliency matching, the precision can...

Bioinformatics approach of three partial polyprenol reductase genes in Kandelia obovata

Science.gov (United States)

Basyuni, M.; Wati, R.; Sagami, H.; Oku, H.; Baba, S.

2018-03-01

This present study describesthe bioinformatics approach to analyze three partial polyprenol reductase genes from mangrove plant, Kandeliaobovataas well aspredictedphysical and chemical properties, potential peptide, subcellular localization, and phylogenetic. The diversity was noted in the physical and chemical properties of three partial polyprenol reductase genes. The values of chloroplast were relatively high, showed that chloroplast transit peptide occurred in mangrove polyprenol reductase. The target peptide value of mitochondria varied from 0.088 to 0.198 indicated it was possible to be present. These results suggested the importance of understanding the diversity of physicochemical properties of the different amino acids in polyprenol reductase. The subcellular localization of two partial genes located in the plasma membrane. To confirm the homology among the polyprenol reductase in the database, a dendrogram was drawn. The phylogenetic tree depicts that there are three clusters, the partial genes of K. obovata joined the largest one: C23157 was close to Ricinus communis polyprenol reductase. Whereas, C23901 and C24171 were grouped with Ipomoea nil polyprenol reductase, suggested that these polyprenol reductase genes form distinct separation into tropical habitat plants.

Clustering approaches to identifying gene expression patterns from DNA microarray data.

Science.gov (United States)

Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

Comparison of endoscopic endonasal and bifrontal craniotomy approaches for olfactory groove meningiomas: A matched pair analysis of outcomes and frontal lobe changes on MRI.

Science.gov (United States)

de Almeida, John R; Carvalho, Felipe; Vaz Guimaraes Filho, Francisco; Kiehl, Tim-Rasmus; Koutourousiou, Maria; Su, Shirley; Vescan, Allan D; Witterick, Ian J; Zadeh, Gelareh; Wang, Eric W; Fernandez-Miranda, Juan C; Gardner, Paul A; Gentili, Fred; Snyderman, Carl H

2015-11-01

We compare the outcomes and postoperative MRI changes of endoscopic endonasal (EEA) and bifrontal craniotomy (BFC) approaches for olfactory groove meningiomas (OGM). All patients who underwent either BFC or EEA for OGM were eligible. Matched pairs were created by matching tumor volumes of an EEA patient with a BFC patient, and matching the timing of the postoperative scans. The tumor dimensions, peritumoral edema, resectability issues, and frontal lobe changes were recorded based on preoperative and postoperative MRI. Postoperative fluid-attenuated inversion recovery (FLAIR) hyperintensity and residual cystic cavity (porencephalic cave) volume were compared using univariable and multivariable analyses. From a total of 70 patients (46 EEA, 24 BFC), 10 matched pairs (20 patients) were created. Three patients (30%) in the EEA group and two (20%) in the BFC had postoperative cerebrospinal fluid leaks (p=0.61). Gross total resections were achieved in seven (70%) of the EEA group and nine (90%) of the BFC group (p=0.26), and one patient from each group developed a recurrence. On postoperative MRI, there was no significant difference in FLAIR signal volumes between EEA and BFC approaches (6.9 versus 13.3 cm(3); p=0.17) or in porencephalic cave volumes (1.7 versus 5.0 cm(3); p=0.11) in univariable analysis. However, in a multivariable analysis, EEA was associated with less postoperative FLAIR change (p=0.02) after adjusting for the volume of preoperative edema. This study provides preliminary evidence that EEA is associated with quantifiable improvements in postoperative frontal lobe imaging. Copyright © 2015 Elsevier Ltd. All rights reserved.

Mix-and-match holography

KAUST Repository

Peng, Yifan; Dun, Xiong; Sun, Qilin; Heidrich, Wolfgang

2017-01-01

target images into pairs of front and rear phase-distorting surfaces. Different target holograms can be decoded by mixing and matching different front and rear surfaces under specific geometric alignments. Our approach, which we call mixWe derive a detailed image formation model for the setting of holographic projection displays, as well as a multiplexing method based on a combination of phase retrieval methods and complex matrix factorization. We demonstrate several application scenarios in both simulation and physical prototypes.

Gene function analysis by artificial microRNAs in Physcomitrella patens.

KAUST Repository

Khraiwesh, Basel

2011-01-01

MicroRNAs (miRNAs) are ~21 nt long small RNAs transcribed from endogenous MIR genes which form precursor RNAs with a characteristic hairpin structure. miRNAs control the expression of cognate target genes by binding to reverse complementary sequences resulting in cleavage or translational inhibition of the target RNA. Artificial miRNAs (amiRNAs) can be generated by exchanging the miRNA/miRNA sequence of endogenous MIR precursor genes, while maintaining the general pattern of matches and mismatches in the foldback. Thus, for functional gene analysis amiRNAs can be designed to target any gene of interest. During the last decade the moss Physcomitrella patens emerged as a model plant for functional gene analysis based on its unique ability to integrate DNA into the nuclear genome by homologous recombination which allows for the generation of targeted gene knockout mutants. In addition to this, we developed a protocol to express amiRNAs in P. patens that has particular advantages over the generation of knockout mutants and might be used to speed up reverse genetics approaches in this model species.

Transcriptional profiling of five isolated size-matched stages of human preantral follicles

DEFF Research Database (Denmark)

Kristensen, Stine Gry; Ebbesen, Pernille; Andersen, Claus Yding

2015-01-01

Little is known of the early stages of human follicular development and the complex processes that regulate follicular growth. To identify genes of potential importance, we analysed follicle-related transcripts in five populations of isolated size-matched human preantral follicles by microarray...... factors of NOTCH signalling, IGF2, orphan nuclear receptor LRH-1, and homeobox gene HOXA7, indicating potentially important regulatory roles for these genes during early human folliculogenesis. We also found that FSHR mRNA and protein were present in the earliest stages of preantral follicles, whereas LHR...

An evaluation of the genetic-matched pair study design using genome-wide SNP data from the European population

DEFF Research Database (Denmark)

Lu, Timothy Tehua; Lao, Oscar; Nothnagel, Michael

2009-01-01

of cases (76.0%), the BOM of a given individual, based on the complete marker set, came from a different recruitment site than the individual itself. A second marker set, specifically selected for ancestry sensitivity using singular value decomposition, performed even more poorly and was no more capable......Genetic matching potentially provides a means to alleviate the effects of incomplete Mendelian randomization in population-based gene-disease association studies. We therefore evaluated the genetic-matched pair study design on the basis of genome-wide SNP data (309,790 markers; Affymetrix Gene......Chip Human Mapping 500K Array) from 2457 individuals, sampled at 23 different recruitment sites across Europe. Using pair-wise identity-by-state (IBS) as a matching criterion, we tried to derive a subset of markers that would allow identification of the best overall matching (BOM) partner for a given...

Linking Genes and Brain Development of Honeybee Workers: A Whole-Transcriptome Approach.

Directory of Open Access Journals (Sweden)

Christina Vleurinck

Full Text Available Honeybees live in complex societies whose capabilities far exceed those of the sum of their single members. This social synergism is achieved mainly by the worker bees, which form a female caste. The worker bees display diverse collaborative behaviors and engage in different behavioral tasks, which are controlled by the central nervous system (CNS. The development of the worker brain is determined by the female sex and the worker caste determination signal. Here, we report on genes that are controlled by sex or by caste during differentiation of the worker's pupal brain. We sequenced and compared transcriptomes from the pupal brains of honeybee workers, queens and drones. We detected 333 genes that are differently expressed and 519 genes that are differentially spliced between the sexes, and 1760 genes that are differentially expressed and 692 genes that are differentially spliced between castes. We further found that 403 genes are differentially regulated by both the sex and caste signals, providing evidence of the integration of both signals through differential gene regulation. In this gene set, we found that the molecular processes of restructuring the cell shape and cell-to-cell signaling are overrepresented. Our approach identified candidate genes that may be involved in brain differentiation that ensures the various social worker behaviors.

Improved Stereo Matching With Boosting Method

Directory of Open Access Journals (Sweden)

Shiny B

2015-06-01

Full Text Available Abstract This paper presents an approach based on classification for improving the accuracy of stereo matching methods. We propose this method for occlusion handling. This work employs classification of pixels for finding the erroneous disparity values. Due to the wide applications of disparity map in 3D television medical imaging etc the accuracy of disparity map has high significance. An initial disparity map is obtained using local or global stereo matching methods from the input stereo image pair. The various features for classification are computed from the input stereo image pair and the obtained disparity map. Then the computed feature vector is used for classification of pixels by using GentleBoost as the classification method. The erroneous disparity values in the disparity map found by classification are corrected through a completion stage or filling stage. A performance evaluation of stereo matching using AdaBoostM1 RUSBoost Neural networks and GentleBoost is performed.

State of otolaryngology match: has competition increased since the "early" match?

Science.gov (United States)

Cabrera-Muffly, Cristina; Sheeder, Jeanelle; Abaza, Mona

2015-05-01

To examine fluctuations in supply and demand of otolaryngology residency positions after the shift from an "early match" coordinated by the San Francisco match to a "conventional" matching process through the National Residency Matching Program (NRMP). To determine whether competition among otolaryngology residency positions have changed during this time frame. Database analysis. Matching statistics from 1998 to 2013 were obtained for all first-year residency positions through the NRMP. Matching statistics from 1998 to 2005 were obtained for otolaryngology residency positions through the San Francisco match. Univariate analysis was performed, with a P value less than .05 determined as significant. The number of otolaryngology positions and applicants remained proportional to the overall number of positions and applicants in the NRMP match. Otolaryngology applicants per position and the matching rate of all applicants did not change between the 2 time periods studied. The overall match rate of US seniors applying to otolaryngology did not change, while the match rate of non-US seniors decreased significantly following initiation of the conventional match. There was no significant change in United States Medical Licensing Exam step 1 scores or percentage of unfilled otolaryngology residency positions between the 2 time periods. When comparing the early versus conventional otolaryngology match time periods, the only major change was the decreased percentage of matching among non-US senior applicants. Despite a significant shift in match timing after 2006, the supply, demand, and competitiveness of otolaryngology residency positions have not changed significantly. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2015.

A zero-one programming approach to Gulliksen's matched random subtests method

NARCIS (Netherlands)

van der Linden, Willem J.; Boekkooi-Timminga, Ellen

1986-01-01

In order to estimate the classical coefficient of test reliability, parallel measurements are needed. H. Gulliksen's matched random subtests method, which is a graphical method for splitting a test into parallel test halves, has practical relevance because it maximizes the alpha coefficient as a

Artificial intelligence (AI)-based relational matching and multimodal medical image fusion: generalized 3D approaches

Science.gov (United States)

Vajdic, Stevan M.; Katz, Henry E.; Downing, Andrew R.; Brooks, Michael J.

1994-09-01

A 3D relational image matching/fusion algorithm is introduced. It is implemented in the domain of medical imaging and is based on Artificial Intelligence paradigms--in particular, knowledge base representation and tree search. The 2D reference and target images are selected from 3D sets and segmented into non-touching and non-overlapping regions, using iterative thresholding and/or knowledge about the anatomical shapes of human organs. Selected image region attributes are calculated. Region matches are obtained using a tree search, and the error is minimized by evaluating a `goodness' of matching function based on similarities of region attributes. Once the matched regions are found and the spline geometric transform is applied to regional centers of gravity, images are ready for fusion and visualization into a single 3D image of higher clarity.

Integration of prior knowledge into dense image matching for video surveillance

Science.gov (United States)

Menze, M.; Heipke, C.

2014-08-01

Three-dimensional information from dense image matching is a valuable input for a broad range of vision applications. While reliable approaches exist for dedicated stereo setups they do not easily generalize to more challenging camera configurations. In the context of video surveillance the typically large spatial extent of the region of interest and repetitive structures in the scene render the application of dense image matching a challenging task. In this paper we present an approach that derives strong prior knowledge from a planar approximation of the scene. This information is integrated into a graph-cut based image matching framework that treats the assignment of optimal disparity values as a labelling task. Introducing the planar prior heavily reduces ambiguities together with the search space and increases computational efficiency. The results provide a proof of concept of the proposed approach. It allows the reconstruction of dense point clouds in more general surveillance camera setups with wider stereo baselines.

Shadow Areas Robust Matching Among Image Sequence in Planetary Landing

Science.gov (United States)

Ruoyan, Wei; Xiaogang, Ruan; Naigong, Yu; Xiaoqing, Zhu; Jia, Lin

2017-01-01

In this paper, an approach for robust matching shadow areas in autonomous visual navigation and planetary landing is proposed. The approach begins with detecting shadow areas, which are extracted by Maximally Stable Extremal Regions (MSER). Then, an affine normalization algorithm is applied to normalize the areas. Thirdly, a descriptor called Multiple Angles-SIFT (MA-SIFT) that coming from SIFT is proposed, the descriptor can extract more features of an area. Finally, for eliminating the influence of outliers, a method of improved RANSAC based on Skinner Operation Condition is proposed to extract inliers. At last, series of experiments are conducted to test the performance of the approach this paper proposed, the results show that the approach can maintain the matching accuracy at a high level even the differences among the images are obvious with no attitude measurements supplied.

A guide to approaching regulatory considerations for lentiviral-mediated gene therapies.

Science.gov (United States)

White, Michael; Whittaker, Roger; Stoll, Elizabeth Ann

2017-06-12

Lentiviral vectors are increasingly the gene transfer tool of choice for gene or cell therapies, with multiple clinical investigations showing promise for this viral vector in terms of both safety and efficacy. The third-generation vector system is well-characterized, effectively delivers genetic material and maintains long-term stable expression in target cells, delivers larger amounts of genetic material than other methods, is non-pathogenic and does not cause an inflammatory response in the recipient. This report aims to help academic scientists and regulatory managers negotiate the governance framework to achieve successful translation of a lentiviral vector-based gene therapy. The focus is on European regulations, and how they are administered in the United Kingdom, although many of the principles will be similar for other regions including the United States. The report justifies the rationale for using third-generation lentiviral vectors to achieve gene delivery for in vivo and ex vivo applications; briefly summarises the extant regulatory guidance for gene therapies, categorised as advanced therapeutic medicinal products (ATMPs); provides guidance on specific regulatory issues regarding gene therapies; presents an overview of the key stakeholders to be approached when pursuing clinical trials authorization for an ATMP; and includes a brief catalogue of the documentation required to submit an application for regulatory approval of a new gene therapy.

So many genes, so little time: A practical approach to divergence-time estimation in the genomic era.

Science.gov (United States)

Smith, Stephen A; Brown, Joseph W; Walker, Joseph F

2018-01-01

Phylogenomic datasets have been successfully used to address questions involving evolutionary relationships, patterns of genome structure, signatures of selection, and gene and genome duplications. However, despite the recent explosion in genomic and transcriptomic data, the utility of these data sources for efficient divergence-time inference remains unexamined. Phylogenomic datasets pose two distinct problems for divergence-time estimation: (i) the volume of data makes inference of the entire dataset intractable, and (ii) the extent of underlying topological and rate heterogeneity across genes makes model mis-specification a real concern. "Gene shopping", wherein a phylogenomic dataset is winnowed to a set of genes with desirable properties, represents an alternative approach that holds promise in alleviating these issues. We implemented an approach for phylogenomic datasets (available in SortaDate) that filters genes by three criteria: (i) clock-likeness, (ii) reasonable tree length (i.e., discernible information content), and (iii) least topological conflict with a focal species tree (presumed to have already been inferred). Such a winnowing procedure ensures that errors associated with model (both clock and topology) mis-specification are minimized, therefore reducing error in divergence-time estimation. We demonstrated the efficacy of this approach through simulation and applied it to published animal (Aves, Diplopoda, and Hymenoptera) and plant (carnivorous Caryophyllales, broad Caryophyllales, and Vitales) phylogenomic datasets. By quantifying rate heterogeneity across both genes and lineages we found that every empirical dataset examined included genes with clock-like, or nearly clock-like, behavior. Moreover, many datasets had genes that were clock-like, exhibited reasonable evolutionary rates, and were mostly compatible with the species tree. We identified overlap in age estimates when analyzing these filtered genes under strict clock and uncorrelated

Hierarchical Matching of Traffic Information Services Using Semantic Similarity

Directory of Open Access Journals (Sweden)

Zongtao Duan

2018-01-01

Full Text Available Service matching aims to find the information similar to a given query, which has numerous applications in web search. Although existing methods yield promising results, they are not applicable for transportation. In this paper, we propose a multilevel matching method based on semantic technology, towards efficiently searching the traffic information requested. Our approach is divided into two stages: service clustering, which prunes candidate services that are not promising, and functional matching. The similarity at function level between services is computed by grouping the connections between the services into inheritance and noninheritance relationships. We also developed a three-layer framework with a semantic similarity measure that requires less time and space cost than existing method since the scale of candidate services is significantly smaller than the whole transportation network. The OWL_TC4 based service set was used to verify the proposed approach. The accuracy of offline service clustering reached 93.80%, and it reduced the response time to 651 ms when the total number of candidate services was 1000. Moreover, given the different thresholds for the semantic similarity measure, the proposed mixed matching model did better in terms of recall and precision (i.e., up to 72.7% and 80%, respectively, for more than 1000 services compared to the compared models based on information theory and taxonomic distance. These experimental results confirmed the effectiveness and validity of service matching for responding quickly and accurately to user queries.

Impedance-matched Marx generators

Directory of Open Access Journals (Sweden)

W. A. Stygar

2017-04-01

Full Text Available We have conceived a new class of prime-power sources for pulsed-power accelerators: impedance-matched Marx generators (IMGs. The fundamental building block of an IMG is a brick, which consists of two capacitors connected electrically in series with a single switch. An IMG comprises a single stage or several stages distributed axially and connected in series. Each stage is powered by a single brick or several bricks distributed azimuthally within the stage and connected in parallel. The stages of a multistage IMG drive an impedance-matched coaxial transmission line with a conical center conductor. When the stages are triggered sequentially to launch a coherent traveling wave along the coaxial line, the IMG achieves electromagnetic-power amplification by triggered emission of radiation. Hence a multistage IMG is a pulsed-power analogue of a laser. To illustrate the IMG approach to prime power, we have developed conceptual designs of two ten-stage IMGs with LC time constants on the order of 100 ns. One design includes 20 bricks per stage, and delivers a peak electrical power of 1.05 TW to a matched-impedance 1.22-Ω load. The design generates 113 kV per stage and has a maximum energy efficiency of 89%. The other design includes a single brick per stage, delivers 68 GW to a matched-impedance 19-Ω load, generates 113 kV per stage, and has a maximum energy efficiency of 90%. For a given electrical-power-output time history, an IMG is less expensive and slightly more efficient than a linear transformer driver, since an IMG does not use ferromagnetic cores.

Impedance-matched Marx generators

Science.gov (United States)

Stygar, W. A.; LeChien, K. R.; Mazarakis, M. G.; Savage, M. E.; Stoltzfus, B. S.; Austin, K. N.; Breden, E. W.; Cuneo, M. E.; Hutsel, B. T.; Lewis, S. A.; McKee, G. R.; Moore, J. K.; Mulville, T. D.; Muron, D. J.; Reisman, D. B.; Sceiford, M. E.; Wisher, M. L.

2017-04-01

We have conceived a new class of prime-power sources for pulsed-power accelerators: impedance-matched Marx generators (IMGs). The fundamental building block of an IMG is a brick, which consists of two capacitors connected electrically in series with a single switch. An IMG comprises a single stage or several stages distributed axially and connected in series. Each stage is powered by a single brick or several bricks distributed azimuthally within the stage and connected in parallel. The stages of a multistage IMG drive an impedance-matched coaxial transmission line with a conical center conductor. When the stages are triggered sequentially to launch a coherent traveling wave along the coaxial line, the IMG achieves electromagnetic-power amplification by triggered emission of radiation. Hence a multistage IMG is a pulsed-power analogue of a laser. To illustrate the IMG approach to prime power, we have developed conceptual designs of two ten-stage IMGs with L C time constants on the order of 100 ns. One design includes 20 bricks per stage, and delivers a peak electrical power of 1.05 TW to a matched-impedance 1.22 -Ω load. The design generates 113 kV per stage and has a maximum energy efficiency of 89%. The other design includes a single brick per stage, delivers 68 GW to a matched-impedance 19 -Ω load, generates 113 kV per stage, and has a maximum energy efficiency of 90%. For a given electrical-power-output time history, an IMG is less expensive and slightly more efficient than a linear transformer driver, since an IMG does not use ferromagnetic cores.

Physics-based shape matching for intraoperative image guidance

Energy Technology Data Exchange (ETDEWEB)

Suwelack, Stefan, E-mail: suwelack@kit.edu; Röhl, Sebastian; Bodenstedt, Sebastian; Reichard, Daniel; Dillmann, Rüdiger; Speidel, Stefanie [Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology, Adenauerring 2, Karlsruhe 76131 (Germany); Santos, Thiago dos; Maier-Hein, Lena [Computer-assisted Interventions, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg 69120 (Germany); Wagner, Martin; Wünscher, Josephine; Kenngott, Hannes; Müller, Beat P. [General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Im Neuenheimer Feld 110, Heidelberg 69120 (Germany)

2014-11-01

Purpose: Soft-tissue deformations can severely degrade the validity of preoperative planning data during computer assisted interventions. Intraoperative imaging such as stereo endoscopic, time-of-flight or, laser range scanner data can be used to compensate these movements. In this context, the intraoperative surface has to be matched to the preoperative model. The shape matching is especially challenging in the intraoperative setting due to noisy sensor data, only partially visible surfaces, ambiguous shape descriptors, and real-time requirements. Methods: A novel physics-based shape matching (PBSM) approach to register intraoperatively acquired surface meshes to preoperative planning data is proposed. The key idea of the method is to describe the nonrigid registration process as an electrostatic–elastic problem, where an elastic body (preoperative model) that is electrically charged slides into an oppositely charged rigid shape (intraoperative surface). It is shown that the corresponding energy functional can be efficiently solved using the finite element (FE) method. It is also demonstrated how PBSM can be combined with rigid registration schemes for robust nonrigid registration of arbitrarily aligned surfaces. Furthermore, it is shown how the approach can be combined with landmark based methods and outline its application to image guidance in laparoscopic interventions. Results: A profound analysis of the PBSM scheme based on in silico and phantom data is presented. Simulation studies on several liver models show that the approach is robust to the initial rigid registration and to parameter variations. The studies also reveal that the method achieves submillimeter registration accuracy (mean error between 0.32 and 0.46 mm). An unoptimized, single core implementation of the approach achieves near real-time performance (2 TPS, 7–19 s total registration time). It outperforms established methods in terms of speed and accuracy. Furthermore, it is shown that the

Labor tax reform and equilibrium unemployment : a search and matching approach

NARCIS (Netherlands)

Heijdra, Ben J.; Ligthart, Jenny E.

2004-01-01

The paper studies simple strategies of labor tax reform in a search and matching model of the labor market featuring endogenous labor supply. Changing the composition of the tax wedge---that is, reducing a payroll tax and increasing a progressive wage tax such that the marginal tax wedge remains

Labor Tax Reform and Equilibrium Unemployment : A Search and Matching Approach

NARCIS (Netherlands)

Heijdra, B.J.; Ligthart, J.E.

2004-01-01

The paper studies simple strategies of labor tax reform in a search and matching model of the labor market featuring endogenous labor supply.Changing the composition of the tax wedge|that is, reducing a payroll tax and increasing a progressive wage tax such that the marginal tax wedge remains

Pigeons ("Columba Livia") Approach Nash Equilibrium in Experimental Matching Pennies Competitions

Science.gov (United States)

Sanabria, Federico; Thrailkill, Eric

2009-01-01

The game of Matching Pennies (MP), a simplified version of the more popular Rock, Papers, Scissors, schematically represents competitions between organisms with incentives to predict each other's behavior. Optimal performance in iterated MP competitions involves the production of random choice patterns and the detection of nonrandomness in the…

Transit Matching for International Safeguards

International Nuclear Information System (INIS)

Gilligan, K.; Whitaker, M.; Oakberg, J.

2015-01-01

In 2013 the U.S. Department of Energy / National Nuclear Security Administration Office of Non-proliferation and International Security (NIS) supported a study of the International Atomic Energy Agency's (IAEA) processes and procedures for ensuring that shipments of nuclear material correspond to (match) their receipts (i.e., transit matching). Under Comprehensive Safeguards Agreements, Member States are obliged to declare such information within certain time frames. Nuclear weapons states voluntarily declare such information under INFCIRC/207. This study was funded by the NIS Next Generation Safeguards Initiative (NGSI) Concepts and Approaches program. Oak Ridge National Laboratory led the research, which included collaboration with the U.S. Nuclear Regulatory Commission, the U.S. Nuclear Material Management and Safeguards System (NMMSS), and the IAEA Section for Declared Information Analysis within the Department of Safeguards. The project studied the current transit matching methodologies, identified current challenges (e.g., level of effort and timeliness), and suggested improvements. This paper presents the recommendations that resulted from the study and discussions with IAEA staff. In particular, it includes a recommendation to collaboratively develop a set of best reporting practices for nuclear weapons states under INFCIRC/207. (author)

From gene networks to drugs: systems pharmacology approaches for AUD.

Science.gov (United States)

Ferguson, Laura B; Harris, R Adron; Mayfield, Roy Dayne

2018-06-01

The alcohol research field has amassed an impressive number of gene expression datasets spanning key brain areas for addiction, species (humans as well as multiple animal models), and stages in the addiction cycle (binge/intoxication, withdrawal/negative effect, and preoccupation/anticipation). These data have improved our understanding of the molecular adaptations that eventually lead to dysregulation of brain function and the chronic, relapsing disorder of addiction. Identification of new medications to treat alcohol use disorder (AUD) will likely benefit from the integration of genetic, genomic, and behavioral information included in these important datasets. Systems pharmacology considers drug effects as the outcome of the complex network of interactions a drug has rather than a single drug-molecule interaction. Computational strategies based on this principle that integrate gene expression signatures of pharmaceuticals and disease states have shown promise for identifying treatments that ameliorate disease symptoms (called in silico gene mapping or connectivity mapping). In this review, we suggest that gene expression profiling for in silico mapping is critical to improve drug repurposing and discovery for AUD and other psychiatric illnesses. We highlight studies that successfully apply gene mapping computational approaches to identify or repurpose pharmaceutical treatments for psychiatric illnesses. Furthermore, we address important challenges that must be overcome to maximize the potential of these strategies to translate to the clinic and improve healthcare outcomes.

Modelling relationships between match events and match outcome in elite football.

Science.gov (United States)

Liu, Hongyou; Hopkins, Will G; Gómez, Miguel-Angel

2016-08-01

Identifying match events that are related to match outcome is an important task in football match analysis. Here we have used generalised mixed linear modelling to determine relationships of 16 football match events and 1 contextual variable (game location: home/away) with the match outcome. Statistics of 320 close matches (goal difference ≤ 2) of season 2012-2013 in the Spanish First Division Professional Football League were analysed. Relationships were evaluated with magnitude-based inferences and were expressed as extra matches won or lost per 10 close matches for an increase of two within-team or between-team standard deviations (SD) of the match event (representing effects of changes in team values from match to match and of differences between average team values, respectively). There was a moderate positive within-team effect from shots on target (3.4 extra wins per 10 matches; 99% confidence limits ±1.0), and a small positive within-team effect from total shots (1.7 extra wins; ±1.0). Effects of most other match events were related to ball possession, which had a small negative within-team effect (1.2 extra losses; ±1.0) but a small positive between-team effect (1.7 extra wins; ±1.4). Game location showed a small positive within-team effect (1.9 extra wins; ±0.9). In analyses of nine combinations of team and opposition end-of-season rank (classified as high, medium, low), almost all between-team effects were unclear, while within-team effects varied depending on the strength of team and opposition. Some of these findings will be useful to coaches and performance analysts when planning training sessions and match tactics.

Job Searchers, Job Matches and the Elasticity of Matching

NARCIS (Netherlands)

Broersma, L.; van Ours, J.C.

1998-01-01

This paper stresses the importance of a specification of the matching function in which the measure of job matches corresponds to the measure of job searchers. In many empirical studies on the matching function this requirement has not been fulfilled because it is difficult to find information about

Recognizing human actions by learning and matching shape-motion prototype trees.

Science.gov (United States)

Jiang, Zhuolin; Lin, Zhe; Davis, Larry S

2012-03-01

A shape-motion prototype-based approach is introduced for action recognition. The approach represents an action as a sequence of prototypes for efficient and flexible action matching in long video sequences. During training, an action prototype tree is learned in a joint shape and motion space via hierarchical K-means clustering and each training sequence is represented as a labeled prototype sequence; then a look-up table of prototype-to-prototype distances is generated. During testing, based on a joint probability model of the actor location and action prototype, the actor is tracked while a frame-to-prototype correspondence is established by maximizing the joint probability, which is efficiently performed by searching the learned prototype tree; then actions are recognized using dynamic prototype sequence matching. Distance measures used for sequence matching are rapidly obtained by look-up table indexing, which is an order of magnitude faster than brute-force computation of frame-to-frame distances. Our approach enables robust action matching in challenging situations (such as moving cameras, dynamic backgrounds) and allows automatic alignment of action sequences. Experimental results demonstrate that our approach achieves recognition rates of 92.86 percent on a large gesture data set (with dynamic backgrounds), 100 percent on the Weizmann action data set, 95.77 percent on the KTH action data set, 88 percent on the UCF sports data set, and 87.27 percent on the CMU action data set.

A zero-one programming approach to Gulliksen's matched random subtests method

NARCIS (Netherlands)

van der Linden, Willem J.; Boekkooi-Timminga, Ellen

1988-01-01

Gulliksen’s matched random subtests method is a graphical method to split a test into parallel test halves. The method has practical relevance because it maximizes coefficient α as a lower bound to the classical test reliability coefficient. In this paper the same problem is formulated as a zero-one

A Systems’ Biology Approach to Study MicroRNA-Mediated Gene Regulatory Networks

Directory of Open Access Journals (Sweden)

Xin Lai

2013-01-01

Full Text Available MicroRNAs (miRNAs are potent effectors in gene regulatory networks where aberrant miRNA expression can contribute to human diseases such as cancer. For a better understanding of the regulatory role of miRNAs in coordinating gene expression, we here present a systems biology approach combining data-driven modeling and model-driven experiments. Such an approach is characterized by an iterative process, including biological data acquisition and integration, network construction, mathematical modeling and experimental validation. To demonstrate the application of this approach, we adopt it to investigate mechanisms of collective repression on p21 by multiple miRNAs. We first construct a p21 regulatory network based on data from the literature and further expand it using algorithms that predict molecular interactions. Based on the network structure, a detailed mechanistic model is established and its parameter values are determined using data. Finally, the calibrated model is used to study the effect of different miRNA expression profiles and cooperative target regulation on p21 expression levels in different biological contexts.

Construction of basic match schedules for sports competitions by using graph theory

NARCIS (Netherlands)

van Weert, Arjan; Schreuder, J.A.M.; Burke, Edmund; Carter, Michael

1997-01-01

Basic Match Schedules are important for constructing sports timetables. Firstly these schedules guarantee the fairness of the sports competitions and secondly they reduce the complexity of the problem. This paper presents an approach to the problem of finding Basic Match Schedules for sports

78 FR 73195 - Privacy Act of 1974: CMS Computer Matching Program Match No. 2013-01; HHS Computer Matching...

Science.gov (United States)

2013-12-05

... 1974: CMS Computer Matching Program Match No. 2013-01; HHS Computer Matching Program Match No. 1312 AGENCY: Centers for Medicare & Medicaid Services (CMS), Department of Health and Human Services (HHS... Privacy Act of 1974 (5 U.S.C. 552a), as amended, this notice announces the renewal of a CMP that CMS plans...

Cross-species genomics matches driver mutations and cell compartments to model ependymoma

Science.gov (United States)

Johnson, Robert A.; Wright, Karen D.; Poppleton, Helen; Mohankumar, Kumarasamypet M.; Finkelstein, David; Pounds, Stanley B.; Rand, Vikki; Leary, Sarah E.S.; White, Elsie; Eden, Christopher; Hogg, Twala; Northcott, Paul; Mack, Stephen; Neale, Geoffrey; Wang, Yong-Dong; Coyle, Beth; Atkinson, Jennifer; DeWire, Mariko; Kranenburg, Tanya A.; Gillespie, Yancey; Allen, Jeffrey C.; Merchant, Thomas; Boop, Fredrick A.; Sanford, Robert. A.; Gajjar, Amar; Ellison, David W.; Taylor, Michael D.; Grundy, Richard G.; Gilbertson, Richard J.

2010-01-01

Understanding the biology that underlies histologically similar but molecularly distinct subgroups of cancer has proven difficult since their defining genetic alterations are often numerous, and the cellular origins of most cancers remain unknown1–3. We sought to decipher this heterogeneity by integrating matched genetic alterations and candidate cells of origin to generate accurate disease models. First, we identified subgroups of human ependymoma, a form of neural tumor that arises throughout the central nervous system (CNS). Subgroup specific alterations included amplifications and homozygous deletions of genes not yet implicated in ependymoma. To select cellular compartments most likely to give rise to subgroups of ependymoma, we matched the transcriptomes of human tumors to those of mouse neural stem cells (NSCs), isolated from different regions of the CNS at different developmental stages, with an intact or deleted Ink4a/Arf locus. The transcriptome of human cerebral ependymomas with amplified EPHB2 and deleted INK4A/ARF matched only that of embryonic cerebral Ink4a/Arf−/− NSCs. Remarkably, activation of Ephb2 signaling in these, but not other NSCs, generated the first mouse model of ependymoma, which is highly penetrant and accurately models the histology and transcriptome of one subgroup of human cerebral tumor. Further comparative analysis of matched mouse and human tumors revealed selective deregulation in the expression and copy number of genes that control synaptogenesis, pinpointing disruption of this pathway as a critical event in the production of this ependymoma subgroup. Our data demonstrate the power of cross-species genomics to meticulously match subgroup specific driver mutations with cellular compartments to model and interrogate cancer subgroups. PMID:20639864

Comparison of shade matching by visual observation and an intraoral dental colorimeter.

Science.gov (United States)

Li, Q; Wang, Y N

2007-11-01

The purpose of this study was to compare the applicability of two shade-matching approaches: Vintage Halo shade guide (visual method) and Shofu ShadeEye NCC colorimeter (instrumental method). Twenty participants' maxillary left central incisors were evaluated. Corresponding metal ceramic crowns were fabricated with each shade-matching approach. The colour distributions (L*, a* and b*) of the middle third region of each tooth and corresponding metal ceramic crowns were spectrophotometrically assessed. The colour difference (DeltaE) and colour distributions (DeltaL*, Deltaa* and Deltab*) between the tooth and the corresponding crowns were calculated. We found that the colour differences of both groups fell within the clinical unacceptable range (DeltaE > 2.75). Regarding DeltaE and the three colour distributions, no significant difference was found, expect for a* (P colorimeter nor the visual approach. However, the colorimeter can achieve better results within easy matching cases.

Real-time UAV trajectory generation using feature points matching between video image sequences

Science.gov (United States)

Byun, Younggi; Song, Jeongheon; Han, Dongyeob

2017-09-01

Unmanned aerial vehicles (UAVs), equipped with navigation systems and video capability, are currently being deployed for intelligence, reconnaissance and surveillance mission. In this paper, we present a systematic approach for the generation of UAV trajectory using a video image matching system based on SURF (Speeded up Robust Feature) and Preemptive RANSAC (Random Sample Consensus). Video image matching to find matching points is one of the most important steps for the accurate generation of UAV trajectory (sequence of poses in 3D space). We used the SURF algorithm to find the matching points between video image sequences, and removed mismatching by using the Preemptive RANSAC which divides all matching points to outliers and inliers. The inliers are only used to determine the epipolar geometry for estimating the relative pose (rotation and translation) between image sequences. Experimental results from simulated video image sequences showed that our approach has a good potential to be applied to the automatic geo-localization of the UAVs system

Differential gene expression in liver and small intestine from lactating rats compared to age-matched virgin controls detects increased mRNA of cholesterol biosynthetic genes

Directory of Open Access Journals (Sweden)

Jungsuwadee Paiboon

2011-02-01

Full Text Available Abstract Background Lactation increases energy demands four- to five-fold, leading to a two- to three-fold increase in food consumption, requiring a proportional adjustment in the ability of the lactating dam to absorb nutrients and to synthesize critical biomolecules, such as cholesterol, to meet the dietary needs of both the offspring and the dam. The size and hydrophobicity of the bile acid pool increases during lactation, implying an increased absorption and disposition of lipids, sterols, nutrients, and xenobiotics. In order to investigate changes at the transcriptomics level, we utilized an exon array and calculated expression levels to investigate changes in gene expression in the liver, duodenum, jejunum, and ileum of lactating dams when compared against age-matched virgin controls. Results A two-way mixed models ANOVA was applied to detect differentially expressed genes. Significance calls were defined as a p Cyp7a1, which catalyzes the rate limiting step in the bile acid biosynthetic pathway, was also significantly increased in liver. In addition, decreased levels of mRNA associated with T-cell signaling were found in the jejunum and ileum. Several members of the Solute Carrier (SLC and Adenosine Triphosphate Binding Cassette (ABC superfamilies of membrane transporters were found to be differentially expressed; these genes may play a role in differences in nutrient and xenobiotic absorption and disposition. mRNA expression of SLC39a4_predicted, a zinc transporter, was increased in all tissues, suggesting that it is involved in increased zinc uptake during lactation. Microarray data are available through GEO under GSE19175. Conclusions We detected differential expression of mRNA from several pathways in lactating dams, including upregulation of the cholesterol biosynthetic pathway in liver and intestine, consistent with Srebp activation. Differential T-Cell signaling in the two most distal regions of the small intestine (ileum and

Clustering based gene expression feature selection method: A computational approach to enrich the classifier efficiency of differentially expressed genes

KAUST Repository

Abusamra, Heba

2016-07-20

The native nature of high dimension low sample size of gene expression data make the classification task more challenging. Therefore, feature (gene) selection become an apparent need. Selecting a meaningful and relevant genes for classifier not only decrease the computational time and cost, but also improve the classification performance. Among different approaches of feature selection methods, however most of them suffer from several problems such as lack of robustness, validation issues etc. Here, we present a new feature selection technique that takes advantage of clustering both samples and genes. Materials and methods We used leukemia gene expression dataset [1]. The effectiveness of the selected features were evaluated by four different classification methods; support vector machines, k-nearest neighbor, random forest, and linear discriminate analysis. The method evaluate the importance and relevance of each gene cluster by summing the expression level for each gene belongs to this cluster. The gene cluster consider important, if it satisfies conditions depend on thresholds and percentage otherwise eliminated. Results Initial analysis identified 7120 differentially expressed genes of leukemia (Fig. 15a), after applying our feature selection methodology we end up with specific 1117 genes discriminating two classes of leukemia (Fig. 15b). Further applying the same method with more stringent higher positive and lower negative threshold condition, number reduced to 58 genes have be tested to evaluate the effectiveness of the method (Fig. 15c). The results of the four classification methods are summarized in Table 11. Conclusions The feature selection method gave good results with minimum classification error. Our heat-map result shows distinct pattern of refines genes discriminating between two classes of leukemia.

Matching Expectations for Successful University Student Volunteering

Science.gov (United States)

Paull, Megan; Omari, Maryam; MacCallum, Judith; Young, Susan; Walker, Gabrielle; Holmes, Kirsten; Haski-Leventha, Debbie; Scott, Rowena

2017-01-01

Purpose: The purpose of this paper is to demonstrate the importance of expectation formation and matching for university student volunteers and their hosts. Design/methodology/approach: This research involved a multi-stage data collection process including interviews with student volunteers, and university and host representatives from six…

Entropy-Weighted Instance Matching Between Different Sourcing Points of Interest

Directory of Open Access Journals (Sweden)

Lin Li

2016-01-01

Full Text Available The crucial problem for integrating geospatial data is finding the corresponding objects (the counterpart from different sources. Most current studies focus on object matching with individual attributes such as spatial, name, or other attributes, which avoids the difficulty of integrating those attributes, but at the cost of an ineffective matching. In this study, we propose an approach for matching instances by integrating heterogeneous attributes with the allocation of suitable attribute weights via information entropy. First, a normalized similarity formula is developed, which can simplify the calculation of spatial attribute similarity. Second, sound-based and word segmentation-based methods are adopted to eliminate the semantic ambiguity when there is a lack of a normative coding standard in geospatial data to express the name attribute. Third, category mapping is established to address the heterogeneity among different classifications. Finally, to address the non-linear characteristic of attribute similarity, the weights of the attributes are calculated by the entropy of the attributes. Experiments demonstrate that the Entropy-Weighted Approach (EWA has good performance both in terms of precision and recall for instance matching from different data sets.

Multi-patch matching for person re-identification

Science.gov (United States)

Labidi, Hocine; Luo, Sen-Lin; Boubekeur, Mohamed B.; Benlefki, Tarek

2015-08-01

Recognizing a target object across non-overlapping distributed cameras is known in the computer vision community as the problem of person re-identification. In this paper, a multi-patch matching method for person reidentification is presented. Starting from the assumption that: the appearance (clothes) of a person does not change during the time of passing in different cameras field of view , which means the regions with the same color in target image will be identical while crossing cameras. First, we extract distinctive features in the training procedure, where each image target is devised into small patches, the SIFT features and LAB color histograms are computed for each patch. Then we use the KNN approach to detect group of patches with high similarity in the target image and then we use a bi-directional weighted group matching mechanism for the re-identification. Experiments on a challenging VIPeR dataset show that the performances of the proposed method outperform several baselines and state of the art approaches.

Source-to-accelerator quadrupole matching section for a compact linear accelerator

Science.gov (United States)

Seidl, P. A.; Persaud, A.; Ghiorso, W.; Ji, Q.; Waldron, W. L.; Lal, A.; Vinayakumar, K. B.; Schenkel, T.

2018-05-01

Recently, we presented a new approach for a compact radio-frequency (RF) accelerator structure and demonstrated the functionality of the individual components: acceleration units and focusing elements. In this paper, we combine these units to form a working accelerator structure: a matching section between the ion source extraction grids and the RF-acceleration unit and electrostatic focusing quadrupoles between successive acceleration units. The matching section consists of six electrostatic quadrupoles (ESQs) fabricated using 3D-printing techniques. The matching section enables us to capture more beam current and to match the beam envelope to conditions for stable transport in an acceleration lattice. We present data from an integrated accelerator consisting of the source, matching section, and an ESQ doublet sandwiched between two RF-acceleration units.

Sequence Matching Analysis for Curriculum Development

Directory of Open Access Journals (Sweden)

Liem Yenny Bendatu

2015-06-01

Full Text Available Many organizations apply information technologies to support their business processes. Using the information technologies, the actual events are recorded and utilized to conform with predefined model. Conformance checking is an approach to measure the fitness and appropriateness between process model and actual events. However, when there are multiple events with the same timestamp, the traditional approach unfit to result such measures. This study attempts to develop a sequence matching analysis. Considering conformance checking as the basis of this approach, this proposed approach utilizes the current control flow technique in process mining domain. A case study in the field of educational process has been conducted. This study also proposes a curriculum analysis framework to test the proposed approach. By considering the learning sequence of students, it results some measurements for curriculum development. Finally, the result of the proposed approach has been verified by relevant instructors for further development.

Myocardium tracking via matching distributions.

Science.gov (United States)

Ben Ayed, Ismail; Li, Shuo; Ross, Ian; Islam, Ali

2009-01-01

The goal of this study is to investigate automatic myocardium tracking in cardiac Magnetic Resonance (MR) sequences using global distribution matching via level-set curve evolution. Rather than relying on the pixelwise information as in existing approaches, distribution matching compares intensity distributions, and consequently, is well-suited to the myocardium tracking problem. Starting from a manual segmentation of the first frame, two curves are evolved in order to recover the endocardium (inner myocardium boundary) and the epicardium (outer myocardium boundary) in all the frames. For each curve, the evolution equation is sought following the maximization of a functional containing two terms: (1) a distribution matching term measuring the similarity between the non-parametric intensity distributions sampled from inside and outside the curve to the model distributions of the corresponding regions estimated from the previous frame; (2) a gradient term for smoothing the curve and biasing it toward high gradient of intensity. The Bhattacharyya coefficient is used as a similarity measure between distributions. The functional maximization is obtained by the Euler-Lagrange ascent equation of curve evolution, and efficiently implemented via level-set. The performance of the proposed distribution matching was quantitatively evaluated by comparisons with independent manual segmentations approved by an experienced cardiologist. The method was applied to ten 2D mid-cavity MR sequences corresponding to ten different subjects. Although neither shape prior knowledge nor curve coupling were used, quantitative evaluation demonstrated that the results were consistent with manual segmentations. The proposed method compares well with existing methods. The algorithm also yields a satisfying reproducibility. Distribution matching leads to a myocardium tracking which is more flexible and applicable than existing methods because the algorithm uses only the current data, i.e., does not

Signature detection and matching for document image retrieval.

Science.gov (United States)

Zhu, Guangyu; Zheng, Yefeng; Doermann, David; Jaeger, Stefan

2009-11-01

As one of the most pervasive methods of individual identification and document authentication, signatures present convincing evidence and provide an important form of indexing for effective document image processing and retrieval in a broad range of applications. However, detection and segmentation of free-form objects such as signatures from clustered background is currently an open document analysis problem. In this paper, we focus on two fundamental problems in signature-based document image retrieval. First, we propose a novel multiscale approach to jointly detecting and segmenting signatures from document images. Rather than focusing on local features that typically have large variations, our approach captures the structural saliency using a signature production model and computes the dynamic curvature of 2D contour fragments over multiple scales. This detection framework is general and computationally tractable. Second, we treat the problem of signature retrieval in the unconstrained setting of translation, scale, and rotation invariant nonrigid shape matching. We propose two novel measures of shape dissimilarity based on anisotropic scaling and registration residual error and present a supervised learning framework for combining complementary shape information from different dissimilarity metrics using LDA. We quantitatively study state-of-the-art shape representations, shape matching algorithms, measures of dissimilarity, and the use of multiple instances as query in document image retrieval. We further demonstrate our matching techniques in offline signature verification. Extensive experiments using large real-world collections of English and Arabic machine-printed and handwritten documents demonstrate the excellent performance of our approaches.

Multi Data Reservoir History Matching using the Ensemble Kalman Filter

KAUST Repository

Katterbauer, Klemens

2015-05-01

Reservoir history matching is becoming increasingly important with the growing demand for higher quality formation characterization and forecasting and the increased complexity and expenses for modern hydrocarbon exploration projects. History matching has long been dominated by adjusting reservoir parameters based solely on well data whose spatial sparse sampling has been a challenge for characterizing the flow properties in areas away from the wells. Geophysical data are widely collected nowadays for reservoir monitoring purposes, but has not yet been fully integrated into history matching and forecasting fluid flow. In this thesis, I present a pioneering approach towards incorporating different time-lapse geophysical data together for enhancing reservoir history matching and uncertainty quantification. The thesis provides several approaches to efficiently integrate multiple geophysical data, analyze the sensitivity of the history matches to observation noise, and examine the framework’s performance in several settings, such as the Norne field in Norway. The results demonstrate the significant improvements in reservoir forecasting and characterization and the synergy effects encountered between the different geophysical data. In particular, the joint use of electromagnetic and seismic data improves the accuracy of forecasting fluid properties, and the usage of electromagnetic data has led to considerably better estimates of hydrocarbon fluid components. For volatile oil and gas reservoirs the joint integration of gravimetric and InSAR data has shown to be beneficial in detecting the influx of water and thereby improving the recovery rate. Summarizing, this thesis makes an important contribution towards integrated reservoir management and multiphysics integration for reservoir history matching.

One-loop effective lagrangians after matching

Energy Technology Data Exchange (ETDEWEB)

Aguila, F. del; Santiago, J. [Universidad de Granada, Departamento de Fisica Teorica y del Cosmos and CAFPE, Granada (Spain); Kunszt, Z. [ETH Zuerich, Institute for Theoretical Physics, Zuerich (Switzerland)

2016-05-15

We discuss the limitations of the covariant derivative expansion prescription advocated to compute the one-loop Standard Model (SM) effective lagrangian when the heavy fields couple linearly to the SM. In particular, one-loop contributions resulting from the exchange of both heavy and light fields must be explicitly taken into account through matching because the proposed functional approach alone does not account for them. We review a simple case with a heavy scalar singlet of charge -1 to illustrate the argument. As two other examples where this matching is needed and this functional method gives a vanishing result, up to renormalization of the heavy sector parameters, we re-evaluate the one-loop corrections to the T-parameter due to a heavy scalar triplet with vanishing hypercharge coupling to the Brout-Englert-Higgs boson and to a heavy vector-like quark singlet of charged 2/3 mixing with the top quark, respectively. In all cases we make use of a new code for matching fundamental and effective theories in models with arbitrary heavy field additions. (orig.)

Improving the Quality of the Supply-Demand-Match in Vocational Education and Training by Anticipation and "Matching Policy"

Science.gov (United States)

Lassnigg, Lorenz

2008-01-01

This article discusses the implications of a framework to improve matching supply and demand in VET by a policy to improve quality by using anticipation and foresight approaches. Analysis of the Austrian anticipation system identified some basic aspects such as policy. The analysis focused on two issues: the observation and measurement of…

GPU Based N-Gram String Matching Algorithm with Score Table Approach for String Searching in Many Documents

Science.gov (United States)

Srinivasa, K. G.; Shree Devi, B. N.

2017-10-01

String searching in documents has become a tedious task with the evolution of Big Data. Generation of large data sets demand for a high performance search algorithm in areas such as text mining, information retrieval and many others. The popularity of GPU's for general purpose computing has been increasing for various applications. Therefore it is of great interest to exploit the thread feature of a GPU to provide a high performance search algorithm. This paper proposes an optimized new approach to N-gram model for string search in a number of lengthy documents and its GPU implementation. The algorithm exploits GPGPUs for searching strings in many documents employing character level N-gram matching with parallel Score Table approach and search using CUDA API. The new approach of Score table used for frequency storage of N-grams in a document, makes the search independent of the document's length and allows faster access to the frequency values, thus decreasing the search complexity. The extensive thread feature in a GPU has been exploited to enable parallel pre-processing of trigrams in a document for Score Table creation and parallel search in huge number of documents, thus speeding up the whole search process even for a large pattern size. Experiments were carried out for many documents of varied length and search strings from the standard Lorem Ipsum text on NVIDIA's GeForce GT 540M GPU with 96 cores. Results prove that the parallel approach for Score Table creation and searching gives a good speed up than the same approach executed serially.

Sparse reconstruction using distribution agnostic bayesian matching pursuit

KAUST Repository

Masood, Mudassir; Al-Naffouri, Tareq Y.

2013-01-01

A fast matching pursuit method using a Bayesian approach is introduced for sparse signal recovery. This method performs Bayesian estimates of sparse signals even when the signal prior is non-Gaussian or unknown. It is agnostic on signal statistics

Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypes

KAUST Repository

AlShahrani, Mona; Hoehndorf, Robert

2018-01-01

In the past years, several methods have been developed to incorporate information about phenotypes into computational disease gene prioritization methods. These methods commonly compute the similarity between a disease's (or patient's) phenotypes and a database of gene-to-phenotype associations to find the phenotypically most similar match. A key limitation of these methods is their reliance on knowledge about phenotypes associated with particular genes which is highly incomplete in humans as well as in many model organisms such as the mouse. Results: We developed SmuDGE, a method that uses feature learning to generate vector-based representations of phenotypes associated with an entity. SmuDGE can be used as a trainable semantic similarity measure to compare two sets of phenotypes (such as between a disease and gene, or a disease and patient). More importantly, SmuDGE can generate phenotype representations for entities that are only indirectly associated with phenotypes through an interaction network; for this purpose, SmuDGE exploits background knowledge in interaction networks comprising of multiple types of interactions. We demonstrate that SmuDGE can match or outperform semantic similarity in phenotype-based disease gene prioritization, and furthermore significantly extends the coverage of phenotype-based methods to all genes in a connected interaction network.

Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypes

KAUST Repository

Alshahrani, Mona

2018-04-30

In the past years, several methods have been developed to incorporate information about phenotypes into computational disease gene prioritization methods. These methods commonly compute the similarity between a disease\\'s (or patient\\'s) phenotypes and a database of gene-to-phenotype associations to find the phenotypically most similar match. A key limitation of these methods is their reliance on knowledge about phenotypes associated with particular genes which is highly incomplete in humans as well as in many model organisms such as the mouse. Results: We developed SmuDGE, a method that uses feature learning to generate vector-based representations of phenotypes associated with an entity. SmuDGE can be used as a trainable semantic similarity measure to compare two sets of phenotypes (such as between a disease and gene, or a disease and patient). More importantly, SmuDGE can generate phenotype representations for entities that are only indirectly associated with phenotypes through an interaction network; for this purpose, SmuDGE exploits background knowledge in interaction networks comprising of multiple types of interactions. We demonstrate that SmuDGE can match or outperform semantic similarity in phenotype-based disease gene prioritization, and furthermore significantly extends the coverage of phenotype-based methods to all genes in a connected interaction network.

A novel approach to simulate gene-environment interactions in complex diseases

Directory of Open Access Journals (Sweden)

Nicodemi Mario

2010-01-01

Full Text Available Abstract Background Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.. Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. Results We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS, a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. Conclusions By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte

Match Analysis in Volleyball: a systematic review

Directory of Open Access Journals (Sweden)

Miguel Silva

2016-03-01

Full Text Available The present article aims to review the available literature on match analysis in adult male Volleyball. Specific key words "performance analysis", "match analysis", "game analysis", "notational analysis", "tactical analysis", "technical analysis", "outcome" and "skills" were used to search relevant databases (PubMed, Web of Science, SportDiscus, Academic Search Complete and the International Journal of Performance Analysis in Sport. The research was conducted according to PRISMA (Preferred Reporting Items for Systematic reviews and Meta analyses guidelines. Of 3407 studies initially identified, only 34 were fully reviewed, and their outcome measures extracted and analyzed. Studies that fit all inclusion criteria were organized into two levels of analysis, according to their research design (comparative or predictive and depending on the type of variables analyzed (skills and their relationship with success, play position and match phase. Results show that from a methodological point of view, comparative studies where currently complemented with some predictive studies. This predictive approach emerged with the aim to identify the relationship between variables, considering their possible interactions and consequently its effect on team performance, contributing to a better understanding of Volleyball game performance through match analysis. Taking into account the limitations of the reviewed studies, future research should provide comprehensive operational definitions for the studied variables, using more recent samples, and consider integrating the player positions and match phase contexts into the analysis of Volleyball.

Convergent functional genomics in addiction research - a translational approach to study candidate genes and gene networks.

Science.gov (United States)

Spanagel, Rainer

2013-01-01

Convergent functional genomics (CFG) is a translational methodology that integrates in a Bayesian fashion multiple lines of evidence from studies in human and animal models to get a better understanding of the genetics of a disease or pathological behavior. Here the integration of data sets that derive from forward genetics in animals and genetic association studies including genome wide association studies (GWAS) in humans is described for addictive behavior. The aim of forward genetics in animals and association studies in humans is to identify mutations (e.g. SNPs) that produce a certain phenotype; i.e. "from phenotype to genotype". Most powerful in terms of forward genetics is combined quantitative trait loci (QTL) analysis and gene expression profiling in recombinant inbreed rodent lines or genetically selected animals for a specific phenotype, e.g. high vs. low drug consumption. By Bayesian scoring genomic information from forward genetics in animals is then combined with human GWAS data on a similar addiction-relevant phenotype. This integrative approach generates a robust candidate gene list that has to be functionally validated by means of reverse genetics in animals; i.e. "from genotype to phenotype". It is proposed that studying addiction relevant phenotypes and endophenotypes by this CFG approach will allow a better determination of the genetics of addictive behavior.

Template matching techniques in computer vision theory and practice

CERN Document Server

Brunelli, Roberto

2009-01-01

The detection and recognition of objects in images is a key research topic in the computer vision community.  Within this area, face recognition and interpretation has attracted increasing attention owing to the possibility of unveiling human perception mechanisms, and for the development of practical biometric systems. This book and the accompanying website, focus on template matching, a subset of object recognition techniques of wide applicability, which has proved to be particularly effective for face recognition applications. Using examples from face processing tasks throughout the book to illustrate more general object recognition approaches, Roberto Brunelli: examines the basics of digital image formation, highlighting points critical to the task of template matching;presents basic and  advanced template matching techniques, targeting grey-level images, shapes and point sets;discusses recent pattern classification paradigms from a template matching perspective;illustrates the development of a real fac...

MULTI-TEMPORAL AND MULTI-SENSOR IMAGE MATCHING BASED ON LOCAL FREQUENCY INFORMATION

Directory of Open Access Journals (Sweden)

X. Liu

2012-08-01

Full Text Available Image Matching is often one of the first tasks in many Photogrammetry and Remote Sensing applications. This paper presents an efficient approach to automated multi-temporal and multi-sensor image matching based on local frequency information. Two new independent image representations, Local Average Phase (LAP and Local Weighted Amplitude (LWA, are presented to emphasize the common scene information, while suppressing the non-common illumination and sensor-dependent information. In order to get the two representations, local frequency information is firstly obtained from Log-Gabor wavelet transformation, which is similar to that of the human visual system; then the outputs of odd and even symmetric filters are used to construct the LAP and LWA. The LAP and LWA emphasize on the phase and amplitude information respectively. As these two representations are both derivative-free and threshold-free, they are robust to noise and can keep as much of the image details as possible. A new Compositional Similarity Measure (CSM is also presented to combine the LAP and LWA with the same weight for measuring the similarity of multi-temporal and multi-sensor images. The CSM can make the LAP and LWA compensate for each other and can make full use of the amplitude and phase of local frequency information. In many image matching applications, the template is usually selected without consideration of its matching robustness and accuracy. In order to overcome this problem, a local best matching point detection is presented to detect the best matching template. In the detection method, we employ self-similarity analysis to identify the template with the highest matching robustness and accuracy. Experimental results using some real images and simulation images demonstrate that the presented approach is effective for matching image pairs with significant scene and illumination changes and that it has advantages over other state-of-the-art approaches, which include: the

Using complementary approaches to identify trans-domain nuclear gene transfers in the extremophile Galdieria sulphuraria (Rhodophyta).

Science.gov (United States)

Pandey, Ravi S; Saxena, Garima; Bhattacharya, Debashish; Qiu, Huan; Azad, Rajeev K

2017-02-01

Identification of horizontal gene transfers (HGTs) has primarily relied on phylogenetic tree based methods, which require a rich sampling of sequenced genomes to ensure a reliable inference. Because the success of phylogenetic approaches depends on the breadth and depth of the database, researchers usually apply stringent filters to detect only the most likely gene transfers in the genomes of interest. One such study focused on a highly conservative estimate of trans-domain gene transfers in the extremophile eukaryote, Galdieria sulphuraria (Galdieri) Merola (Rhodophyta), by applying multiple filters in their phylogenetic pipeline. This led to the identification of 75 inter-domain acquisitions from Bacteria or Archaea. Because of the evolutionary, ecological, and potential biotechnological significance of foreign genes in algae, alternative approaches and pipelines complementing phylogenetics are needed for a more comprehensive assessment of HGT. We present here a novel pipeline that uncovered 17 novel foreign genes of prokaryotic origin in G. sulphuraria, results that are supported by multiple lines of evidence including composition-based, comparative data, and phylogenetics. These genes encode a variety of potentially adaptive functions, from metabolite transport to DNA repair. © 2016 Phycological Society of America.

Improvements in algal lipid production: a systems biology and gene editing approach.

Science.gov (United States)

Banerjee, Avik; Banerjee, Chiranjib; Negi, Sangeeta; Chang, Jo-Shu; Shukla, Pratyoosh

2018-05-01

In the wake of rising energy demands, microalgae have emerged as potential sources of sustainable and renewable carbon-neutral fuels, such as bio-hydrogen and bio-oil. For rational metabolic engineering, the elucidation of metabolic pathways in fine detail and their manipulation according to requirements is the key to exploiting the use of microalgae. Emergence of site-specific nucleases have revolutionized applied research leading to biotechnological gains. Genome engineering as well as modulation of the endogenous genome with high precision using CRISPR systems is being gradually employed in microalgal research. Further, to optimize and produce better algal platforms, use of systems biology network analysis and integration of omics data is required. This review discusses two important approaches: systems biology and gene editing strategies used on microalgal systems with a focus on biofuel production and sustainable solutions. It also emphasizes that the integration of such systems would contribute and compliment applied research on microalgae. Recent advances in microalgae are discussed, including systems biology, gene editing approaches in lipid bio-synthesis, and antenna engineering. Lastly, it has been attempted here to showcase how CRISPR/Cas systems are a better editing tool than existing techniques that can be utilized for gene modulation and engineering during biofuel production.

Ratiometric Gas Reporting: A Nondisruptive Approach To Monitor Gene Expression in Soils.

Science.gov (United States)

Cheng, Hsiao-Ying; Masiello, Caroline A; Del Valle, Ilenne; Gao, Xiaodong; Bennett, George N; Silberg, Jonathan J

2018-03-16

Fluorescent proteins are ubiquitous tools that are used to monitor the dynamic functions of natural and synthetic genetic circuits. However, these visual reporters can only be used in transparent settings, a limitation that complicates nondisruptive measurements of gene expression within many matrices, such as soils and sediments. We describe a new ratiometric gas reporting method for nondisruptively monitoring gene expression within hard-to-image environmental matrices. With this approach, C 2 H 4 is continuously synthesized by ethylene forming enzyme to provide information on viable cell number, and CH 3 Br is conditionally synthesized by placing a methyl halide transferase gene under the control of a conditional promoter. We show that ratiometric gas reporting enables the creation of Escherichia coli biosensors that report on acylhomoserine lactone (AHL) autoinducers used for quorum sensing by Gram-negative bacteria. Using these biosensors, we find that an agricultural soil decreases the bioavailable concentration of a long-chain AHL up to 100-fold. We also demonstrate that these biosensors can be used in soil to nondisruptively monitor AHLs synthesized by Rhizobium leguminosarum and degraded by Bacillus thuringiensis. Finally, we show that this new reporting approach can be used in Shewanella oneidensis, a bacterium that lives in sediments.

Cyclic Matching Pursuits with Multiscale Time-frequency Dictionaries

DEFF Research Database (Denmark)

Sturm, Bob L.; Christensen, Mads Græsbøll

2010-01-01

We generalize cyclic matching pursuit (CMP), propose an orthogonal variant, and examine their performance using multiscale time-frequency dictionaries in the sparse approximation of signals. Overall, we find that the cyclic approach of CMP produces signal models that have a much lower approximation...

A Third Approach to Gene Prediction Suggests Thousands of Additional Human Transcribed Regions

Science.gov (United States)

Glusman, Gustavo; Qin, Shizhen; El-Gewely, M. Raafat; Siegel, Andrew F; Roach, Jared C; Hood, Leroy; Smit, Arian F. A

2006-01-01

The identification and characterization of the complete ensemble of genes is a main goal of deciphering the digital information stored in the human genome. Many algorithms for computational gene prediction have been described, ultimately derived from two basic concepts: (1) modeling gene structure and (2) recognizing sequence similarity. Successful hybrid methods combining these two concepts have also been developed. We present a third orthogonal approach to gene prediction, based on detecting the genomic signatures of transcription, accumulated over evolutionary time. We discuss four algorithms based on this third concept: Greens and CHOWDER, which quantify mutational strand biases caused by transcription-coupled DNA repair, and ROAST and PASTA, which are based on strand-specific selection against polyadenylation signals. We combined these algorithms into an integrated method called FEAST, which we used to predict the location and orientation of thousands of putative transcription units not overlapping known genes. Many of the newly predicted transcriptional units do not appear to code for proteins. The new algorithms are particularly apt at detecting genes with long introns and lacking sequence conservation. They therefore complement existing gene prediction methods and will help identify functional transcripts within many apparent “genomic deserts.” PMID:16543943

Integrating network, sequence and functional features using machine learning approaches towards identification of novel Alzheimer genes.

Science.gov (United States)

Jamal, Salma; Goyal, Sukriti; Shanker, Asheesh; Grover, Abhinav

2016-10-18

Alzheimer's disease (AD) is a complex progressive neurodegenerative disorder commonly characterized by short term memory loss. Presently no effective therapeutic treatments exist that can completely cure this disease. The cause of Alzheimer's is still unclear, however one of the other major factors involved in AD pathogenesis are the genetic factors and around 70 % risk of the disease is assumed to be due to the large number of genes involved. Although genetic association studies have revealed a number of potential AD susceptibility genes, there still exists a need for identification of unidentified AD-associated genes and therapeutic targets to have better understanding of the disease-causing mechanisms of Alzheimer's towards development of effective AD therapeutics. In the present study, we have used machine learning approach to identify candidate AD associated genes by integrating topological properties of the genes from the protein-protein interaction networks, sequence features and functional annotations. We also used molecular docking approach and screened already known anti-Alzheimer drugs against the novel predicted probable targets of AD and observed that an investigational drug, AL-108, had high affinity for majority of the possible therapeutic targets. Furthermore, we performed molecular dynamics simulations and MM/GBSA calculations on the docked complexes to validate our preliminary findings. To the best of our knowledge, this is the first comprehensive study of its kind for identification of putative Alzheimer-associated genes using machine learning approaches and we propose that such computational studies can improve our understanding on the core etiology of AD which could lead to the development of effective anti-Alzheimer drugs.

An oscillopathic approach to developmental dyslexia: From genes to speech processing.

Science.gov (United States)

Jiménez-Bravo, Miguel; Marrero, Victoria; Benítez-Burraco, Antonio

2017-06-30

Developmental dyslexia is a heterogeneous condition entailing problems with reading and spelling. Several genes have been linked or associated to the disease, many of which contribute to the development and function of brain areas important for auditory and phonological processing. Nonetheless, a clear link between genes, the brain, and the symptoms of dyslexia is still pending. The goal of this paper is contributing to bridge this gap. With this aim, we have focused on how the dyslexic brain fails to process speech sounds and reading cues. We have adopted an oscillatory perspective, according to which dyslexia may result from a deficient integration of different brain rhythms during reading/spellings tasks. Moreover, we show that some candidate genes for this condition are related to brain rhythms. This fresh approach is expected to provide a better understanding of the aetiology and the clinical presentation of developmental dyslexia, but also to achieve an earlier and more accurate diagnosis of the disease. Copyright © 2017 Elsevier B.V. All rights reserved.

A robust approach based on Weibull distribution for clustering gene expression data

Directory of Open Access Journals (Sweden)

Gong Binsheng

2011-05-01

Full Text Available Abstract Background Clustering is a widely used technique for analysis of gene expression data. Most clustering methods group genes based on the distances, while few methods group genes according to the similarities of the distributions of the gene expression levels. Furthermore, as the biological annotation resources accumulated, an increasing number of genes have been annotated into functional categories. As a result, evaluating the performance of clustering methods in terms of the functional consistency of the resulting clusters is of great interest. Results In this paper, we proposed the WDCM (Weibull Distribution-based Clustering Method, a robust approach for clustering gene expression data, in which the gene expressions of individual genes are considered as the random variables following unique Weibull distributions. Our WDCM is based on the concept that the genes with similar expression profiles have similar distribution parameters, and thus the genes are clustered via the Weibull distribution parameters. We used the WDCM to cluster three cancer gene expression data sets from the lung cancer, B-cell follicular lymphoma and bladder carcinoma and obtained well-clustered results. We compared the performance of WDCM with k-means and Self Organizing Map (SOM using functional annotation information given by the Gene Ontology (GO. The results showed that the functional annotation ratios of WDCM are higher than those of the other methods. We also utilized the external measure Adjusted Rand Index to validate the performance of the WDCM. The comparative results demonstrate that the WDCM provides the better clustering performance compared to k-means and SOM algorithms. The merit of the proposed WDCM is that it can be applied to cluster incomplete gene expression data without imputing the missing values. Moreover, the robustness of WDCM is also evaluated on the incomplete data sets. Conclusions The results demonstrate that our WDCM produces clusters

Coalitional game theory as a promising approach to identify candidate autism genes.

Science.gov (United States)

Gupta, Anika; Sun, Min Woo; Paskov, Kelley Marie; Stockham, Nate Tyler; Jung, Jae-Yoon; Wall, Dennis Paul

2018-01-01

Despite mounting evidence for the strong role of genetics in the phenotypic manifestation of Autism Spectrum Disorder (ASD), the specific genes responsible for the variable forms of ASD remain undefined. ASD may be best explained by a combinatorial genetic model with varying epistatic interactions across many small effect mutations. Coalitional or cooperative game theory is a technique that studies the combined effects of groups of players, known as coalitions, seeking to identify players who tend to improve the performance--the relationship to a specific disease phenotype--of any coalition they join. This method has been previously shown to boost biologically informative signal in gene expression data but to-date has not been applied to the search for cooperative mutations among putative ASD genes. We describe our approach to highlight genes relevant to ASD using coalitional game theory on alteration data of 1,965 fully sequenced genomes from 756 multiplex families. Alterations were encoded into binary matrices for ASD (case) and unaffected (control) samples, indicating likely gene-disrupting, inherited mutations in altered genes. To determine individual gene contributions given an ASD phenotype, a "player" metric, referred to as the Shapley value, was calculated for each gene in the case and control cohorts. Sixty seven genes were found to have significantly elevated player scores and likely represent significant contributors to the genetic coordination underlying ASD. Using network and cross-study analysis, we found that these genes are involved in biological pathways known to be affected in the autism cases and that a subset directly interact with several genes known to have strong associations to autism. These findings suggest that coalitional game theory can be applied to large-scale genomic data to identify hidden yet influential players in complex polygenic disorders such as autism.

Cellular neural networks for the stereo matching problem

International Nuclear Information System (INIS)

Taraglio, S.; Zanela, A.

1997-03-01

The applicability of the Cellular Neural Network (CNN) paradigm to the problem of recovering information on the tridimensional structure of the environment is investigated. The approach proposed is the stereo matching of video images. The starting point of this work is the Zhou-Chellappa neural network implementation for the same problem. The CNN based system we present here yields the same results as the previous approach, but without the many existing drawbacks

Inflammatory gene regulatory networks in amnion cells following cytokine stimulation: translational systems approach to modeling human parturition.

Directory of Open Access Journals (Sweden)

Ruth Li

Full Text Available A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals.

Tolerating Correlated Failures for Generalized Cartesian Distributions via Bipartite Matching

International Nuclear Information System (INIS)

Ali, Nawab; Krishnamoorthy, Sriram; Halappanavar, Mahantesh; Daily, Jeffrey A.

2011-01-01

Faults are expected to play an increasingly important role in how algorithms and applications are designed to run on future extreme-scale systems. A key ingredient of any approach to fault tolerance is effective support for fault tolerant data storage. A typical application execution consists of phases in which certain data structures are modified while others are read-only. Often, read-only data structures constitute a large fraction of total memory consumed. Fault tolerance for read-only data can be ensured through the use of checksums or parities, without resorting to expensive in-memory duplication or checkpointing to secondary storage. In this paper, we present a graph-matching approach to compute and store parity data for read-only matrices that are compatible with fault tolerant linear algebra (FTLA). Typical approaches only support blocked data distributions with each process holding one block with the parity located on additional processes. The matrices are assumed to be blocked by a cartesian grid with each block assigned to a process. We consider a generalized distribution in which each process can be assigned arbitrary blocks. We also account for the fact that multiple processes might be part of the same failure unit, say an SMP node. The flexibility enabled by our novel application of graph matching extends fault tolerance support to data distributions beyond those supported by prior work. We evaluate the matching implementations and cost to compute the parity and recover lost data, demonstrating the low overhead incurred by our approach.

Reappraising the Impact of Offending on Victimization: A Propensity Score Matching Approach.

Science.gov (United States)

Posick, Chad

2017-05-01

Existing evidence clearly supports an empirical connection between offending and victimization. Often called the "victim-offender overlap," this relationship holds for both sexes, across the life course, and across a wide range of countries and cultural environments. In addition, the relationship is sustained regardless of the study sample and statistical methods applied in the analyses of the sample data. However, there has yet to be a study that examines this relationship for violent and property crime using quasi-experimental methods accounting for a wide range of potential confounders including individual differences and cultural contexts. This study subjects the victim-offender relationship to testing through propensity score matching for both violent and property crimes using an international dataset. The results show that previous violent and theft offending increases the odds of victimization when matching on individual and contextual factors. This finding supports previous literature and suggests that delinquent behavior may act as a "switch" that exposes one to subsequent violent and theft victimization.

Understanding gene expression in coronary artery disease through ...

Indian Academy of Sciences (India)

Understanding gene expression in coronary artery disease through global profiling, network analysis and independent validation of key candidate genes. Prathima ... Table 2. Differentially expressed genes in CAD compared to age and gender matched controls. .... Regulation of nuclear pre-mRNA domain containing 1A.

Targeted biomarker profiling of matched primary and metastatic estrogen receptor positive breast cancers.

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Erica B Schleifman

Full Text Available Patients with newly diagnosed, early stage estrogen receptor positive (ER+ breast cancer often show disease free survival in excess of five years following surgery and systemic adjuvant therapy. An important question is whether diagnostic tumor tissue from the primary lesion offers an accurate molecular portrait of the cancer post recurrence and thus may be used for predictive diagnostic purposes for patients with relapsed, metastatic disease. As the class I phosphatidylinositol 3' kinase (PI3K pathway is frequently activated in ER+ breast cancer and has been linked to acquired resistance to hormonal therapy, we hypothesized pathway status could evolve over time and treatment. Biomarker analyses were conducted on matched, asynchronous primary and metastatic tumors from 77 patients with ER+ breast cancer. We examined whether PIK3CA and AKT1 alterations or PTEN and Ki67 levels showed differences between primary and metastatic samples. We also sought to look more broadly at gene expression markers reflective of proliferation, molecular subtype, and key receptors and signaling pathways using an mRNA analysis platform developed on the Fluidigm BioMark™ microfluidics system to measure the relative expression of 90 breast cancer related genes in formalin-fixed paraffin-embedded (FFPE tissue. Application of this panel of biomarker assays to matched tumor pairs showed a high concordance between primary and metastatic tissue, with generally few changes in mutation status, proliferative markers, or gene expression between matched samples. The collection of assays described here has been optimized for FFPE tissue and may have utility in exploratory analyses to identify patient subsets responsive to targeted therapies.

Preferential Allele Expression Analysis Identifies Shared Germline and Somatic Driver Genes in Advanced Ovarian Cancer

Science.gov (United States)

Halabi, Najeeb M.; Martinez, Alejandra; Al-Farsi, Halema; Mery, Eliane; Puydenus, Laurence; Pujol, Pascal; Khalak, Hanif G.; McLurcan, Cameron; Ferron, Gwenael; Querleu, Denis; Al-Azwani, Iman; Al-Dous, Eman; Mohamoud, Yasmin A.; Malek, Joel A.; Rafii, Arash

2016-01-01

Identifying genes where a variant allele is preferentially expressed in tumors could lead to a better understanding of cancer biology and optimization of targeted therapy. However, tumor sample heterogeneity complicates standard approaches for detecting preferential allele expression. We therefore developed a novel approach combining genome and transcriptome sequencing data from the same sample that corrects for sample heterogeneity and identifies significant preferentially expressed alleles. We applied this analysis to epithelial ovarian cancer samples consisting of matched primary ovary and peritoneum and lymph node metastasis. We find that preferentially expressed variant alleles include germline and somatic variants, are shared at a relatively high frequency between patients, and are in gene networks known to be involved in cancer processes. Analysis at a patient level identifies patient-specific preferentially expressed alleles in genes that are targets for known drugs. Analysis at a site level identifies patterns of site specific preferential allele expression with similar pathways being impacted in the primary and metastasis sites. We conclude that genes with preferentially expressed variant alleles can act as cancer drivers and that targeting those genes could lead to new therapeutic strategies. PMID:26735499

Magnetic safety matches

Science.gov (United States)

Lindén, J.; Lindberg, M.; Greggas, A.; Jylhävuori, N.; Norrgrann, H.; Lill, J. O.

2017-07-01

In addition to the main ingredients; sulfur, potassium chlorate and carbon, ordinary safety matches contain various dyes, glues etc, giving the head of the match an even texture and appealing color. Among the common reddish-brown matches there are several types, which after ignition can be attracted by a strong magnet. Before ignition the match head is generally not attracted by the magnet. An elemental analysis based on proton-induced x-ray emission was performed to single out iron as the element responsible for the observed magnetism. 57Fe Mössbauer spectroscopy was used for identifying the various types of iron-compounds, present before and after ignition, responsible for the macroscopic magnetism: Fe2O3 before and Fe3O4 after. The reaction was verified by mixing the main chemicals in the match-head with Fe2O3 in glue and mounting the mixture on a match stick. The ash residue after igniting the mixture was magnetic.

Image matching as a data source for forest inventory - Comparison of Semi-Global Matching and Next-Generation Automatic Terrain Extraction algorithms in a typical managed boreal forest environment

Science.gov (United States)

Kukkonen, M.; Maltamo, M.; Packalen, P.

2017-08-01

Image matching is emerging as a compelling alternative to airborne laser scanning (ALS) as a data source for forest inventory and management. There is currently an open discussion in the forest inventory community about whether, and to what extent, the new method can be applied to practical inventory campaigns. This paper aims to contribute to this discussion by comparing two different image matching algorithms (Semi-Global Matching [SGM] and Next-Generation Automatic Terrain Extraction [NGATE]) and ALS in a typical managed boreal forest environment in southern Finland. Spectral features from unrectified aerial images were included in the modeling and the potential of image matching in areas without a high resolution digital terrain model (DTM) was also explored. Plot level predictions for total volume, stem number, basal area, height of basal area median tree and diameter of basal area median tree were modeled using an area-based approach. Plot level dominant tree species were predicted using a random forest algorithm, also using an area-based approach. The statistical difference between the error rates from different datasets was evaluated using a bootstrap method. Results showed that ALS outperformed image matching with every forest attribute, even when a high resolution DTM was used for height normalization and spectral information from images was included. Dominant tree species classification with image matching achieved accuracy levels similar to ALS regardless of the resolution of the DTM when spectral metrics were used. Neither of the image matching algorithms consistently outperformed the other, but there were noticeably different error rates depending on the parameter configuration, spectral band, resolution of DTM, or response variable. This study showed that image matching provides reasonable point cloud data for forest inventory purposes, especially when a high resolution DTM is available and information from the understory is redundant.

Uropathogenic Escherichia coli virulence genes: invaluable approaches for designing DNA microarray probes.

Science.gov (United States)

Jahandeh, Nadia; Ranjbar, Reza; Behzadi, Payam; Behzadi, Elham

2015-01-01

The pathotypes of uropathogenic Escherichia coli (UPEC) cause different types of urinary tract infections (UTIs). The presence of a wide range of virulence genes in UPEC enables us to design appropriate DNA microarray probes. These probes, which are used in DNA microarray technology, provide us with an accurate and rapid diagnosis and definitive treatment in association with UTIs caused by UPEC pathotypes. The main goal of this article is to introduce the UPEC virulence genes as invaluable approaches for designing DNA microarray probes. Main search engines such as Google Scholar and databases like NCBI were searched to find and study several original pieces of literature, review articles, and DNA gene sequences. In parallel with in silico studies, the experiences of the authors were helpful for selecting appropriate sources and writing this review article. There is a significant variety of virulence genes among UPEC strains. The DNA sequences of virulence genes are fabulous patterns for designing microarray probes. The location of virulence genes and their sequence lengths influence the quality of probes. The use of selected virulence genes for designing microarray probes gives us a wide range of choices from which the best probe candidates can be chosen. DNA microarray technology provides us with an accurate, rapid, cost-effective, sensitive, and specific molecular diagnostic method which is facilitated by designing microarray probes. Via these tools, we are able to have an accurate diagnosis and a definitive treatment regarding UTIs caused by UPEC pathotypes.

Exact Methods for Solving the Train Departure Matching Problem

DEFF Research Database (Denmark)

Haahr, Jørgen Thorlund; Bull, Simon Henry

In this paper we consider the train departure matching problem which is an important subproblem of the Rolling Stock Unit Management on Railway Sites problem introduced in the ROADEF/EURO Challenge 2014. The subproblem entails matching arriving train units to scheduled departing trains at a railway...... site while respecting multiple physical and operational constraints. In this paper we formally define that subproblem, prove its NP- hardness, and present two exact method approaches for solving the problem. First, we present a compact Mixed Integer Program formulation which we solve using a MIP solver...

Composite Match Index with Application of Interior Deformation Field Measurement from Magnetic Resonance Volumetric Images of Human Tissues

Directory of Open Access Journals (Sweden)

Penglin Zhang

2012-01-01

Full Text Available Whereas a variety of different feature-point matching approaches have been reported in computer vision, few feature-point matching approaches employed in images from nonrigid, nonuniform human tissues have been reported. The present work is concerned with interior deformation field measurement of complex human tissues from three-dimensional magnetic resonance (MR volumetric images. To improve the reliability of matching results, this paper proposes composite match index (CMI as the foundation of multimethod fusion methods to increase the reliability of these various methods. Thereinto, we discuss the definition, components, and weight determination of CMI. To test the validity of the proposed approach, it is applied to actual MR volumetric images obtained from a volunteer’s calf. The main result is consistent with the actual condition.

Fingerprint matching algorithm for poor quality images

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Vedpal Singh

2015-04-01

Full Text Available The main aim of this study is to establish an efficient platform for fingerprint matching for low-quality images. Generally, fingerprint matching approaches use the minutiae points for authentication. However, it is not such a reliable authentication method for low-quality images. To overcome this problem, the current study proposes a fingerprint matching methodology based on normalised cross-correlation, which would improve the performance and reduce the miscalculations during authentication. It would decrease the computational complexities. The error rate of the proposed method is 5.4%, which is less than the two-dimensional (2D dynamic programming (DP error rate of 5.6%, while Lee's method produces 5.9% and the combined method has 6.1% error rate. Genuine accept rate at 1% false accept rate is 89.3% but at 0.1% value it is 96.7%, which is higher. The outcome of this study suggests that the proposed methodology has a low error rate with minimum computational effort as compared with existing methods such as Lee's method and 2D DP and the combined method.

prokaryote genome annotation with GeneScan and GLIMMER

Indian Academy of Sciences (India)

Unknown

The number of false predictions (both positive and negative) is higher for GeneScan as compared to GLIMMER, but in a ... on whether they need to be trained on a set of genes in order to ..... FP has partial matches to the kdpA gene in C. jejuni.

A systems genetics approach identifies CXCL14, ITGAX, and LPCAT2 as novel aggressive prostate cancer susceptibility genes.

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Kendra A Williams

2014-11-01

Full Text Available Although prostate cancer typically runs an indolent course, a subset of men develop aggressive, fatal forms of this disease. We hypothesize that germline variation modulates susceptibility to aggressive prostate cancer. The goal of this work is to identify susceptibility genes using the C57BL/6-Tg(TRAMP8247Ng/J (TRAMP mouse model of neuroendocrine prostate cancer. Quantitative trait locus (QTL mapping was performed in transgene-positive (TRAMPxNOD/ShiLtJ F2 intercross males (n = 228, which facilitated identification of 11 loci associated with aggressive disease development. Microarray data derived from 126 (TRAMPxNOD/ShiLtJ F2 primary tumors were used to prioritize candidate genes within QTLs, with candidate genes deemed as being high priority when possessing both high levels of expression-trait correlation and a proximal expression QTL. This process enabled the identification of 35 aggressive prostate tumorigenesis candidate genes. The role of these genes in aggressive forms of human prostate cancer was investigated using two concurrent approaches. First, logistic regression analysis in two human prostate gene expression datasets revealed that expression levels of five genes (CXCL14, ITGAX, LPCAT2, RNASEH2A, and ZNF322 were positively correlated with aggressive prostate cancer and two genes (CCL19 and HIST1H1A were protective for aggressive prostate cancer. Higher than average levels of expression of the five genes that were positively correlated with aggressive disease were consistently associated with patient outcome in both human prostate cancer tumor gene expression datasets. Second, three of these five genes (CXCL14, ITGAX, and LPCAT2 harbored polymorphisms associated with aggressive disease development in a human GWAS cohort consisting of 1,172 prostate cancer patients. This study is the first example of using a systems genetics approach to successfully identify novel susceptibility genes for aggressive prostate cancer. Such

Matching factorization theorems with an inverse-error weighting

Science.gov (United States)

Echevarria, Miguel G.; Kasemets, Tomas; Lansberg, Jean-Philippe; Pisano, Cristian; Signori, Andrea

2018-06-01

We propose a new fast method to match factorization theorems applicable in different kinematical regions, such as the transverse-momentum-dependent and the collinear factorization theorems in Quantum Chromodynamics. At variance with well-known approaches relying on their simple addition and subsequent subtraction of double-counted contributions, ours simply builds on their weighting using the theory uncertainties deduced from the factorization theorems themselves. This allows us to estimate the unknown complete matched cross section from an inverse-error-weighted average. The method is simple and provides an evaluation of the theoretical uncertainty of the matched cross section associated with the uncertainties from the power corrections to the factorization theorems (additional uncertainties, such as the nonperturbative ones, should be added for a proper comparison with experimental data). Its usage is illustrated with several basic examples, such as Z boson, W boson, H0 boson and Drell-Yan lepton-pair production in hadronic collisions, and compared to the state-of-the-art Collins-Soper-Sterman subtraction scheme. It is also not limited to the transverse-momentum spectrum, and can straightforwardly be extended to match any (un)polarized cross section differential in other variables, including multi-differential measurements.

A New Two-Step Approach for Hands-On Teaching of Gene Technology: Effects on Students' Activities during Experimentation in an Outreach Gene Technology Lab

Science.gov (United States)

Scharfenberg, Franz-Josef; Bogner, Franz X.

2011-01-01

Emphasis on improving higher level biology education continues. A new two-step approach to the experimental phases within an outreach gene technology lab, derived from cognitive load theory, is presented. We compared our approach using a quasi-experimental design with the conventional one-step mode. The difference consisted of additional focused…

Best matching theory & applications

CERN Document Server

Moghaddam, Mohsen

2017-01-01

Mismatch or best match? This book demonstrates that best matching of individual entities to each other is essential to ensure smooth conduct and successful competitiveness in any distributed system, natural and artificial. Interactions must be optimized through best matching in planning and scheduling, enterprise network design, transportation and construction planning, recruitment, problem solving, selective assembly, team formation, sensor network design, and more. Fundamentals of best matching in distributed and collaborative systems are explained by providing: § Methodical analysis of various multidimensional best matching processes § Comprehensive taxonomy, comparing different best matching problems and processes § Systematic identification of systems’ hierarchy, nature of interactions, and distribution of decision-making and control functions § Practical formulation of solutions based on a library of best matching algorithms and protocols, ready for direct applications and apps development. Design...

A suicide gene therapy approach to treat epidermolysis bullosa-associated skin cancer

International Nuclear Information System (INIS)

Gruber, C.

2009-01-01

Recessive dystrophic epidermolysis bullosa (RDEB) is an inherited disease causing extensive blister formation within the basal membrane zone (BMZ) of the skin and mucous membranes. It is caused by premature STOP mutations in the COL7A1 gene, which is indispensable for proper skin assembling. RDEB is associated with the development of a highly malignant skin cancer (squamous cell carcinoma, SCC) in early adulthood that displays a life threatening complication within this patient group. To date, neither chemo- nor radiotherapies showed successful results and due to the high metastatic potential of RDEB SCC wide surgical excision is still favoured. In this study we could reveal a new promising cancer treatment using spliceosome mediated RNA trans-splicing (SMaRT) using a suicide gene therapy approach. First we identified the tumour marker gene MMP-9 expressed by RDEB SCC cells in cell culture which was used to generate various pre-mRNA trans-splicing molecules (PTM). PTMs are able to facilitate trans-splicing between a tumour target gene and a cell death inducing peptide/toxin, encoded by the PTM. As a consequence the toxin is expressed in cancer cells leading to the induction of cell death. This technique offers high specificity in cancer cell targeting compared to other conventional cDNA expression studies. Various trans-splicing molecules were pre-evaluated in a fluorescence screening model for their best trans-splicing efficiency with the target molecule. Herein we identified two potent PTMs (PTM BD0 and PTM BD6), that were further adapted for endogenous suicide studies by inserting the toxin streptolysin O. In two independent in vitro cell culture assays we were able to confirm that the trans-splicing molecules are able to induce expression of the toxin resulting in cell membrane permeabilization and increased cell death induction. The results indicate that SMaRT technology offers a new platform for a suicide gene therapy approach to treat malignant squamous cell

Coincident site lattice-matched InGaN on (111) spinel substrates

International Nuclear Information System (INIS)

Norman, A. G.; Dippo, P. C.; Moutinho, H. R.; Simon, J.; Ptak, A. J.

2012-01-01

Coincident site lattice-matched wurtzite (0001) In 0.31 Ga 0.69 N, emitting in the important green wavelength region, is demonstrated by molecular beam epitaxy on a cubic (111) MgAl 2 O 4 spinel substrate. The coincident site lattice matching condition involves a 30 deg. rotation between the lattice of the InGaN epitaxial layer and the lattice of the spinel. This work describes an alternative approach towards realizing more compositionally homogenous InGaN films with low dislocation density emitting in the ''green gap'' of low efficiency currently observed for semiconductor light emitting diodes (LEDs). This approach could lead to higher efficiency green LEDs presently of great interest for solid-state lighting applications.

Genome-wide local ancestry approach identifies genes and variants associated with chemotherapeutic susceptibility in African Americans.

Directory of Open Access Journals (Sweden)

Heather E Wheeler

Full Text Available Chemotherapeutic agents are used in the treatment of many cancers, yet variable resistance and toxicities among individuals limit successful outcomes. Several studies have indicated outcome differences associated with ancestry among patients with various cancer types. Using both traditional SNP-based and newly developed gene-based genome-wide approaches, we investigated the genetics of chemotherapeutic susceptibility in lymphoblastoid cell lines derived from 83 African Americans, a population for which there is a disparity in the number of genome-wide studies performed. To account for population structure in this admixed population, we incorporated local ancestry information into our association model. We tested over 2 million SNPs and identified 325, 176, 240, and 190 SNPs that were suggestively associated with cytarabine-, 5'-deoxyfluorouridine (5'-DFUR-, carboplatin-, and cisplatin-induced cytotoxicity, respectively (p≤10(-4. Importantly, some of these variants are found only in populations of African descent. We also show that cisplatin-susceptibility SNPs are enriched for carboplatin-susceptibility SNPs. Using a gene-based genome-wide association approach, we identified 26, 11, 20, and 41 suggestive candidate genes for association with cytarabine-, 5'-DFUR-, carboplatin-, and cisplatin-induced cytotoxicity, respectively (p≤10(-3. Fourteen of these genes showed evidence of association with their respective chemotherapeutic phenotypes in the Yoruba from Ibadan, Nigeria (p<0.05, including TP53I11, COPS5 and GAS8, which are known to be involved in tumorigenesis. Although our results require further study, we have identified variants and genes associated with chemotherapeutic susceptibility in African Americans by using an approach that incorporates local ancestry information.

A Link-Based Cluster Ensemble Approach For Improved Gene Expression Data Analysis

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P.Balaji

2015-01-01

Full Text Available Abstract It is difficult from possibilities to select a most suitable effective way of clustering algorithm and its dataset for a defined set of gene expression data because we have a huge number of ways and huge number of gene expressions. At present many researchers are preferring to use hierarchical clustering in different forms this is no more totally optimal. Cluster ensemble research can solve this type of problem by automatically merging multiple data partitions from a wide range of different clusterings of any dimensions to improve both the quality and robustness of the clustering result. But we have many existing ensemble approaches using an association matrix to condense sample-cluster and co-occurrence statistics and relations within the ensemble are encapsulated only at raw level while the existing among clusters are totally discriminated. Finding these missing associations can greatly expand the capability of those ensemble methodologies for microarray data clustering. We propose general K-means cluster ensemble approach for the clustering of general categorical data into required number of partitions.

On Computing Breakpoint Distances for Genomes with Duplicate Genes.

Science.gov (United States)

Shao, Mingfu; Moret, Bernard M E

2017-06-01

A fundamental problem in comparative genomics is to compute the distance between two genomes in terms of its higher level organization (given by genes or syntenic blocks). For two genomes without duplicate genes, we can easily define (and almost always efficiently compute) a variety of distance measures, but the problem is NP-hard under most models when genomes contain duplicate genes. To tackle duplicate genes, three formulations (exemplar, maximum matching, and any matching) have been proposed, all of which aim to build a matching between homologous genes so as to minimize some distance measure. Of the many distance measures, the breakpoint distance (the number of nonconserved adjacencies) was the first one to be studied and remains of significant interest because of its simplicity and model-free property. The three breakpoint distance problems corresponding to the three formulations have been widely studied. Although we provided last year a solution for the exemplar problem that runs very fast on full genomes, computing optimal solutions for the other two problems has remained challenging. In this article, we describe very fast, exact algorithms for these two problems. Our algorithms rely on a compact integer-linear program that we further simplify by developing an algorithm to remove variables, based on new results on the structure of adjacencies and matchings. Through extensive experiments using both simulations and biological data sets, we show that our algorithms run very fast (in seconds) on mammalian genomes and scale well beyond. We also apply these algorithms (as well as the classic orthology tool MSOAR) to create orthology assignment, then compare their quality in terms of both accuracy and coverage. We find that our algorithm for the "any matching" formulation significantly outperforms other methods in terms of accuracy while achieving nearly maximum coverage.

A Semantic Analysis of XML Schema Matching for B2B Systems Integration

Science.gov (United States)

Kim, Jaewook

2011-01-01

One of the most critical steps to integrating heterogeneous e-Business applications using different XML schemas is schema matching, which is known to be costly and error-prone. Many automatic schema matching approaches have been proposed, but the challenge is still daunting because of the complexity of schemas and immaturity of technologies in…

PIV uncertainty quantification by image matching

International Nuclear Information System (INIS)

Sciacchitano, Andrea; Scarano, Fulvio; Wieneke, Bernhard

2013-01-01

A novel method is presented to quantify the uncertainty of PIV data. The approach is a posteriori, i.e. the unknown actual error of the measured velocity field is estimated using the velocity field itself as input along with the original images. The principle of the method relies on the concept of super-resolution: the image pair is matched according to the cross-correlation analysis and the residual distance between matched particle image pairs (particle disparity vector) due to incomplete match between the two exposures is measured. The ensemble of disparity vectors within the interrogation window is analyzed statistically. The dispersion of the disparity vector returns the estimate of the random error, whereas the mean value of the disparity indicates the occurrence of a systematic error. The validity of the working principle is first demonstrated via Monte Carlo simulations. Two different interrogation algorithms are considered, namely the cross-correlation with discrete window offset and the multi-pass with window deformation. In the simulated recordings, the effects of particle image displacement, its gradient, out-of-plane motion, seeding density and particle image diameter are considered. In all cases good agreement is retrieved, indicating that the error estimator is able to follow the trend of the actual error with satisfactory precision. Experiments where time-resolved PIV data are available are used to prove the concept under realistic measurement conditions. In this case the ‘exact’ velocity field is unknown; however a high accuracy estimate is obtained with an advanced interrogation algorithm that exploits the redundant information of highly temporally oversampled data (pyramid correlation, Sciacchitano et al (2012 Exp. Fluids 53 1087–105)). The image-matching estimator returns the instantaneous distribution of the estimated velocity measurement error. The spatial distribution compares very well with that of the actual error with maxima in the

From Genes to Ecosystems in Microbiology: Modeling Approaches and the Importance of Individuality

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Jan-Ulrich Kreft

2017-11-01

Full Text Available Models are important tools in microbial ecology. They can be used to advance understanding by helping to interpret observations and test hypotheses, and to predict the effects of ecosystem management actions or a different climate. Over the past decades, biological knowledge and ecosystem observations have advanced to the molecular and in particular gene level. However, microbial ecology models have changed less and a current challenge is to make them utilize the knowledge and observations at the genetic level. We review published models that explicitly consider genes and make predictions at the population or ecosystem level. The models can be grouped into three general approaches, i.e., metabolic flux, gene-centric and agent-based. We describe and contrast these approaches by applying them to a hypothetical ecosystem and discuss their strengths and weaknesses. An important distinguishing feature is how variation between individual cells (individuality is handled. In microbial ecosystems, individual heterogeneity is generated by a number of mechanisms including stochastic interactions of molecules (e.g., gene expression, stochastic and deterministic cell division asymmetry, small-scale environmental heterogeneity, and differential transport in a heterogeneous environment. This heterogeneity can then be amplified and transferred to other cell properties by several mechanisms, including nutrient uptake, metabolism and growth, cell cycle asynchronicity and the effects of age and damage. For example, stochastic gene expression may lead to heterogeneity in nutrient uptake enzyme levels, which in turn results in heterogeneity in intracellular nutrient levels. Individuality can have important ecological consequences, including division of labor, bet hedging, aging and sub-optimality. Understanding the importance of individuality and the mechanism(s underlying it for the specific microbial system and question investigated is essential for selecting the

Vaccine-induced modulation of gene expression in turbot peritoneal cells. A microarray approach.

Science.gov (United States)

Fontenla, Francisco; Blanco-Abad, Verónica; Pardo, Belén G; Folgueira, Iria; Noia, Manuel; Gómez-Tato, Antonio; Martínez, Paulino; Leiro, José M; Lamas, Jesús

2016-07-01

We used a microarray approach to examine changes in gene expression in turbot peritoneal cells after injection of the fish with vaccines containing the ciliate parasite Philasterides dicentrarchi as antigen and one of the following adjuvants: chitosan-PVMMA microspheres, Freund́s complete adjuvant, aluminium hydroxide gel or Matrix-Q (Isconova, Sweden). We identified 374 genes that were differentially expressed in all groups of fish. Forty-two genes related to tight junctions and focal adhesions and/or actin cytoskeleton were differentially expressed in free peritoneal cells. The profound changes in gene expression related to cell adherence and cytoskeleton may be associated with cell migration and also with the formation of cell-vaccine masses and their attachment to the peritoneal wall. Thirty-five genes related to apoptosis were differentially expressed. Although most of the proteins coded by these genes have a proapoptotic effect, others are antiapoptotic, indicating that both types of signals occur in peritoneal leukocytes of vaccinated fish. Interestingly, many of the genes related to lymphocytes and lymphocyte activity were downregulated in the groups injected with vaccine. We also observed decreased expression of genes related to antigen presentation, suggesting that macrophages (which were abundant in the peritoneal cavity after vaccination) did not express these during the early inflammatory response in the peritoneal cavity. Finally, several genes that participate in the inflammatory response were differentially expressed, and most participated in resolution of inflammation, indicating that an M2 macrophage response is generated in the peritoneal cavity of fish one day post vaccination. Copyright © 2016 Elsevier Ltd. All rights reserved.

Chitinase genes revealed and compared in bacterial isolates, DNA extracts and a metagenomic library from a phytopathogen suppressive soil

Energy Technology Data Exchange (ETDEWEB)

Hjort, K.; Bergstrom, M.; Adesina, M.F.; Jansson, J.K.; Smalla, K.; Sjoling, S.

2009-09-01

Soil that is suppressive to disease caused by fungal pathogens is an interesting source to target for novel chitinases that might be contributing towards disease suppression. In this study we screened for chitinase genes, in a phytopathogen-suppressive soil in three ways: (1) from a metagenomic library constructed from microbial cells extracted from soil, (2) from directly extracted DNA and (3) from bacterial isolates with antifungal and chitinase activities. Terminal-restriction fragment length polymorphism (T-RFLP) of chitinase genes revealed differences in amplified chitinase genes from the metagenomic library and the directly extracted DNA, but approximately 40% of the identified chitinase terminal-restriction fragments (TRFs) were found in both sources. All of the chitinase TRFs from the isolates were matched to TRFs in the directly extracted DNA and the metagenomic library. The most abundant chitinase TRF in the soil DNA and the metagenomic library corresponded to the TRF{sup 103} of the isolate, Streptomyces mutomycini and/or Streptomyces clavifer. There were good matches between T-RFLP profiles of chitinase gene fragments obtained from different sources of DNA. However, there were also differences in both the chitinase and the 16S rRNA gene T-RFLP patterns depending on the source of DNA, emphasizing the lack of complete coverage of the gene diversity by any of the approaches used.

History matching of time-lapse crosswell data using ensemble kalman filtering

KAUST Repository

de Matos Ravanelli, Fabio Miguel; Hoteit, Ibrahim

2015-01-01

results provide quantitative information for history matching purposes using a probabilistic approach to take in account uncertainties in the geological model and reduce uncertainties in reservoir production forecasts.

An accelerated image matching technique for UAV orthoimage registration

Science.gov (United States)

Tsai, Chung-Hsien; Lin, Yu-Ching

2017-06-01

Using an Unmanned Aerial Vehicle (UAV) drone with an attached non-metric camera has become a popular low-cost approach for collecting geospatial data. A well-georeferenced orthoimage is a fundamental product for geomatics professionals. To achieve high positioning accuracy of orthoimages, precise sensor position and orientation data, or a number of ground control points (GCPs), are often required. Alternatively, image registration is a solution for improving the accuracy of a UAV orthoimage, as long as a historical reference image is available. This study proposes a registration scheme, including an Accelerated Binary Robust Invariant Scalable Keypoints (ABRISK) algorithm and spatial analysis of corresponding control points for image registration. To determine a match between two input images, feature descriptors from one image are compared with those from another image. A "Sorting Ring" is used to filter out uncorrected feature pairs as early as possible in the stage of matching feature points, to speed up the matching process. The results demonstrate that the proposed ABRISK approach outperforms the vector-based Scale Invariant Feature Transform (SIFT) approach where radiometric variations exist. ABRISK is 19.2 times and 312 times faster than SIFT for image sizes of 1000 × 1000 pixels and 4000 × 4000 pixels, respectively. ABRISK is 4.7 times faster than Binary Robust Invariant Scalable Keypoints (BRISK). Furthermore, the positional accuracy of the UAV orthoimage after applying the proposed image registration scheme is improved by an average of root mean square error (RMSE) of 2.58 m for six test orthoimages whose spatial resolutions vary from 6.7 cm to 10.7 cm.

Fractured reservoir history matching improved based on artificial intelligent

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Sayyed Hadi Riazi

2016-12-01

Full Text Available In this paper, a new robust approach based on Least Square Support Vector Machine (LSSVM as a proxy model is used for an automatic fractured reservoir history matching. The proxy model is made to model the history match objective function (mismatch values based on the history data of the field. This model is then used to minimize the objective function through Particle Swarm Optimization (PSO and Imperialist Competitive Algorithm (ICA. In automatic history matching, sensitive analysis is often performed on full simulation model. In this work, to get new range of the uncertain parameters (matching parameters in which the objective function has a minimum value, sensitivity analysis is also performed on the proxy model. By applying the modified ranges to the optimization methods, optimization of the objective function will be faster and outputs of the optimization methods (matching parameters are produced in less time and with high precision. This procedure leads to matching of history of the field in which a set of reservoir parameters is used. The final sets of parameters are then applied for the full simulation model to validate the technique. The obtained results show that the present procedure in this work is effective for history matching process due to its robust dependability and fast convergence speed. Due to high speed and need for small data sets, LSSVM is the best tool to build a proxy model. Also the comparison of PSO and ICA shows that PSO is less time-consuming and more effective.

Kangaroo – A pattern-matching program for biological sequences

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Betel Doron

2002-07-01

Full Text Available Abstract Background Biologists are often interested in performing a simple database search to identify proteins or genes that contain a well-defined sequence pattern. Many databases do not provide straightforward or readily available query tools to perform simple searches, such as identifying transcription binding sites, protein motifs, or repetitive DNA sequences. However, in many cases simple pattern-matching searches can reveal a wealth of information. We present in this paper a regular expression pattern-matching tool that was used to identify short repetitive DNA sequences in human coding regions for the purpose of identifying potential mutation sites in mismatch repair deficient cells. Results Kangaroo is a web-based regular expression pattern-matching program that can search for patterns in DNA, protein, or coding region sequences in ten different organisms. The program is implemented to facilitate a wide range of queries with no restriction on the length or complexity of the query expression. The program is accessible on the web at http://bioinfo.mshri.on.ca/kangaroo/ and the source code is freely distributed at http://sourceforge.net/projects/slritools/. Conclusion A low-level simple pattern-matching application can prove to be a useful tool in many research settings. For example, Kangaroo was used to identify potential genetic targets in a human colorectal cancer variant that is characterized by a high frequency of mutations in coding regions containing mononucleotide repeats.

Snapshot of the eukaryotic gene expression in muskoxen rumen--a metatranscriptomic approach.

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Meng Qi

Full Text Available BACKGROUND: Herbivores rely on digestive tract lignocellulolytic microorganisms, including bacteria, fungi and protozoa, to derive energy and carbon from plant cell wall polysaccharides. Culture independent metagenomic studies have been used to reveal the genetic content of the bacterial species within gut microbiomes. However, the nature of the genes encoded by eukaryotic protozoa and fungi within these environments has not been explored using metagenomic or metatranscriptomic approaches. METHODOLOGY/PRINCIPAL FINDINGS: In this study, a metatranscriptomic approach was used to investigate the functional diversity of the eukaryotic microorganisms within the rumen of muskoxen (Ovibos moschatus, with a focus on plant cell wall degrading enzymes. Polyadenylated RNA (mRNA was sequenced on the Illumina Genome Analyzer II system and 2.8 gigabases of sequences were obtained and 59129 contigs assembled. Plant cell wall degrading enzyme modules including glycoside hydrolases, carbohydrate esterases and polysaccharide lyases were identified from over 2500 contigs. These included a number of glycoside hydrolase family 6 (GH6, GH48 and swollenin modules, which have rarely been described in previous gut metagenomic studies. CONCLUSIONS/SIGNIFICANCE: The muskoxen rumen metatranscriptome demonstrates a much higher percentage of cellulase enzyme discovery and an 8.7x higher rate of total carbohydrate active enzyme discovery per gigabase of sequence than previous rumen metagenomes. This study provides a snapshot of eukaryotic gene expression in the muskoxen rumen, and identifies a number of candidate genes coding for potentially valuable lignocellulolytic enzymes.

Snapshot of the Eukaryotic Gene Expression in Muskoxen Rumen—A Metatranscriptomic Approach

Science.gov (United States)

O'Toole, Nicholas; Barboza, Perry S.; Ungerfeld, Emilio; Leigh, Mary Beth; Selinger, L. Brent; Butler, Greg; Tsang, Adrian; McAllister, Tim A.; Forster, Robert J.

2011-01-01

Background Herbivores rely on digestive tract lignocellulolytic microorganisms, including bacteria, fungi and protozoa, to derive energy and carbon from plant cell wall polysaccharides. Culture independent metagenomic studies have been used to reveal the genetic content of the bacterial species within gut microbiomes. However, the nature of the genes encoded by eukaryotic protozoa and fungi within these environments has not been explored using metagenomic or metatranscriptomic approaches. Methodology/Principal Findings In this study, a metatranscriptomic approach was used to investigate the functional diversity of the eukaryotic microorganisms within the rumen of muskoxen (Ovibos moschatus), with a focus on plant cell wall degrading enzymes. Polyadenylated RNA (mRNA) was sequenced on the Illumina Genome Analyzer II system and 2.8 gigabases of sequences were obtained and 59129 contigs assembled. Plant cell wall degrading enzyme modules including glycoside hydrolases, carbohydrate esterases and polysaccharide lyases were identified from over 2500 contigs. These included a number of glycoside hydrolase family 6 (GH6), GH48 and swollenin modules, which have rarely been described in previous gut metagenomic studies. Conclusions/Significance The muskoxen rumen metatranscriptome demonstrates a much higher percentage of cellulase enzyme discovery and an 8.7x higher rate of total carbohydrate active enzyme discovery per gigabase of sequence than previous rumen metagenomes. This study provides a snapshot of eukaryotic gene expression in the muskoxen rumen, and identifies a number of candidate genes coding for potentially valuable lignocellulolytic enzymes. PMID:21655220

Backward-stochastic-differential-equation approach to modeling of gene expression.

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Shamarova, Evelina; Chertovskih, Roman; Ramos, Alexandre F; Aguiar, Paulo

2017-03-01

In this article, we introduce a backward method to model stochastic gene expression and protein-level dynamics. The protein amount is regarded as a diffusion process and is described by a backward stochastic differential equation (BSDE). Unlike many other SDE techniques proposed in the literature, the BSDE method is backward in time; that is, instead of initial conditions it requires the specification of end-point ("final") conditions, in addition to the model parametrization. To validate our approach we employ Gillespie's stochastic simulation algorithm (SSA) to generate (forward) benchmark data, according to predefined gene network models. Numerical simulations show that the BSDE method is able to correctly infer the protein-level distributions that preceded a known final condition, obtained originally from the forward SSA. This makes the BSDE method a powerful systems biology tool for time-reversed simulations, allowing, for example, the assessment of the biological conditions (e.g., protein concentrations) that preceded an experimentally measured event of interest (e.g., mitosis, apoptosis, etc.).

A re-assessment of gene-tag classification approaches for describing var gene expression patterns during human Plasmodium falciparum malaria parasite infections.

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Githinji, George; Bull, Peter C

2017-01-01

PfEMP1 are variant parasite antigens that are inserted on the surface of Plasmodium falciparum infected erythrocytes (IE). Through interactions with various host molecules, PfEMP1 mediate IE sequestration in tissues and play a key role in the pathology of severe malaria. PfEMP1 is encoded by a diverse multi-gene family called var . Previous studies have shown that that expression of specific subsets of var genes are associated with low levels of host immunity and severe malaria. However, in most clinical studies to date, full-length var gene sequences were unavailable and various approaches have been used to make comparisons between var gene expression profiles in different parasite isolates using limited information. Several studies have relied on the classification of a 300 - 500 base-pair "DBLα tag" region in the DBLα domain located at the 5' end of most var genes. We assessed the relationship between various DBLα tag classification methods, and sequence features that are only fully assessable through full-length var gene sequences. We compared these different sequence features in full-length var gene from six fully sequenced laboratory isolates. These comparisons show that despite a long history of recombination,   DBLα sequence tag classification can provide functional information on important features of full-length var genes. Notably, a specific subset of DBLα tags previously defined as "group A-like" is associated with CIDRα1 domains proposed to bind to endothelial protein C receptor. This analysis helps to bring together different sources of data that have been used to assess var gene expression in clinical parasite isolates.

Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping.

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Chang, Meiping; Smith, Sarah; Thorpe, Andrew; Barratt, Michael J; Karim, Farzana

2010-09-16

We have previously used the rat 4 day Complete Freund's Adjuvant (CFA) model to screen compounds with potential to reduce osteoarthritic pain. The aim of this study was to identify genes altered in this model of osteoarthritic pain and use this information to infer analgesic potential of compounds based on their own gene expression profiles using the Connectivity Map approach. Using microarrays, we identified differentially expressed genes in L4 and L5 dorsal root ganglia (DRG) from rats that had received intraplantar CFA for 4 days compared to matched, untreated control animals. Analysis of these data indicated that the two groups were distinguishable by differences in genes important in immune responses, nerve growth and regeneration. This list of differentially expressed genes defined a "CFA signature". We used the Connectivity Map approach to identify pharmacologic agents in the Broad Institute Build02 database that had gene expression signatures that were inversely related ('negatively connected') with our CFA signature. To test the predictive nature of the Connectivity Map methodology, we tested phenoxybenzamine (an alpha adrenergic receptor antagonist) - one of the most negatively connected compounds identified in this database - for analgesic activity in the CFA model. Our results indicate that at 10 mg/kg, phenoxybenzamine demonstrated analgesia comparable to that of Naproxen in this model. Evaluation of phenoxybenzamine-induced analgesia in the current study lends support to the utility of the Connectivity Map approach for identifying compounds with analgesic properties in the CFA model.

Matching fully differential NNLO calculations and parton showers

International Nuclear Information System (INIS)

Alioli, Simone; Bauer, Christian W.; Berggren, Calvin; Walsh, Jonathan R.; Zuberi, Saba

2013-11-01

We present a general method to match fully differential next-to-next-to-leading (NNLO) calculations to parton shower programs. We discuss in detail the perturbative accuracy criteria a complete NNLO+PS matching has to satisfy. Our method is based on consistently improving a given NNLO calculation with the leading-logarithmic (LL) resummation in a chosen jet resolution variable. The resulting NNLO+LL calculation is cast in the form of an event generator for physical events that can be directly interfaced with a parton shower routine, and we give an explicit construction of the input ''Monte Carlo cross sections'' satisfying all required criteria. We also show how other proposed approaches naturally arise as special cases in our method.

Technique to match mantle and para-aortic fields

International Nuclear Information System (INIS)

Lutz, W.R.; Larsen, R.D.

1983-01-01

A technique is described to match the mantle and para-aortic fields used in treatment of Hodgkin's disease, when the patient is treated alternately in supine and prone position. The approach is based on referencing the field edges to a point close to the vertebral column, where uncontrolled motion is minimal and where accurate matching is particularly important. Fiducial surface points are established in the simulation process to accomplish the objective. Dose distributions have been measured to study the combined effect of divergence differences, changes in body angulation and setup errors. Even with the most careful technique, the use of small cord blocks of 50% transmission is an advisable precaution for the posterior fields

[Propensity score matching in SPSS].

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Huang, Fuqiang; DU, Chunlin; Sun, Menghui; Ning, Bing; Luo, Ying; An, Shengli

2015-11-01

To realize propensity score matching in PS Matching module of SPSS and interpret the analysis results. The R software and plug-in that could link with the corresponding versions of SPSS and propensity score matching package were installed. A PS matching module was added in the SPSS interface, and its use was demonstrated with test data. Score estimation and nearest neighbor matching was achieved with the PS matching module, and the results of qualitative and quantitative statistical description and evaluation were presented in the form of a graph matching. Propensity score matching can be accomplished conveniently using SPSS software.

Matching Students to Schools

Directory of Open Access Journals (Sweden)

Dejan Trifunovic

2017-08-01

Full Text Available In this paper, we present the problem of matching students to schools by using different matching mechanisms. This market is specific since public schools are free and the price mechanism cannot be used to determine the optimal allocation of children in schools. Therefore, it is necessary to use different matching algorithms that mimic the market mechanism and enable us to determine the core of the cooperative game. In this paper, we will determine that it is possible to apply cooperative game theory in matching problems. This review paper is based on illustrative examples aiming to compare matching algorithms in terms of the incentive compatibility, stability and efficiency of the matching. In this paper we will present some specific problems that may occur in matching, such as improving the quality of schools, favoring minority students, the limited length of the list of preferences and generating strict priorities from weak priorities.

Mdmap: A Tool for Metadata Collection and Matching

Directory of Open Access Journals (Sweden)

Rico Simke

2014-10-01

Full Text Available This paper describes a front-end for the semi-automatic collection, matching, and generation of bibliographic metadata obtained from different sources for use within a digitization architecture. The Library of a Billion Words project is building an infrastructure for digitizing text that requires high-quality bibliographic metadata, but currently only sparse metadata from digitized editions is available. The project’s approach is to collect metadata for each digitized item from as many sources as possible. An expert user can then use an intuitive front-end tool to choose matching metadata. The collected metadata are centrally displayed in an interactive grid view. The user can choose which metadata they want to assign to a certain edition, and export these data as MARCXML. This paper presents a new approach to bibliographic work and metadata correction. We try to achieve a high quality of the metadata by generating a large amount of metadata to choose from, as well as by giving librarians an intuitive tool to manage their data.

A New Model for a Carpool Matching Service.

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Jizhe Xia

Full Text Available Carpooling is an effective means of reducing traffic. A carpool team shares a vehicle for their commute, which reduces the number of vehicles on the road during rush hour periods. Carpooling is officially sanctioned by most governments, and is supported by the construction of high-occupancy vehicle lanes. A number of carpooling services have been designed in order to match commuters into carpool teams, but it known that the determination of optimal carpool teams is a combinatorially complex problem, and therefore technological solutions are difficult to achieve. In this paper, a model for carpool matching services is proposed, and both optimal and heuristic approaches are tested to find solutions for that model. The results show that different solution approaches are preferred over different ranges of problem instances. Most importantly, it is demonstrated that a new formulation and associated solution procedures can permit the determination of optimal carpool teams and routes. An instantiation of the model is presented (using the street network of Guangzhou city, China to demonstrate how carpool teams can be determined.

Gene expression and gene therapy imaging

International Nuclear Information System (INIS)

Rome, Claire; Couillaud, Franck; Moonen, Chrit T.W.

2007-01-01

The fast growing field of molecular imaging has achieved major advances in imaging gene expression, an important element of gene therapy. Gene expression imaging is based on specific probes or contrast agents that allow either direct or indirect spatio-temporal evaluation of gene expression. Direct evaluation is possible with, for example, contrast agents that bind directly to a specific target (e.g., receptor). Indirect evaluation may be achieved by using specific substrate probes for a target enzyme. The use of marker genes, also called reporter genes, is an essential element of MI approaches for gene expression in gene therapy. The marker gene may not have a therapeutic role itself, but by coupling the marker gene to a therapeutic gene, expression of the marker gene reports on the expression of the therapeutic gene. Nuclear medicine and optical approaches are highly sensitive (detection of probes in the picomolar range), whereas MRI and ultrasound imaging are less sensitive and require amplification techniques and/or accumulation of contrast agents in enlarged contrast particles. Recently developed MI techniques are particularly relevant for gene therapy. Amongst these are the possibility to track gene therapy vectors such as stem cells, and the techniques that allow spatiotemporal control of gene expression by non-invasive heating (with MRI guided focused ultrasound) and the use of temperature sensitive promoters. (orig.)

Integrating Ontological Knowledge and Textual Evidence in Estimating Gene and Gene Product Similarity

Energy Technology Data Exchange (ETDEWEB)

Sanfilippo, Antonio P.; Posse, Christian; Gopalan, Banu; Tratz, Stephen C.; Gregory, Michelle L.

2006-06-08

With the rising influence of the Gene On-tology, new approaches have emerged where the similarity between genes or gene products is obtained by comparing Gene Ontology code annotations associ-ated with them. So far, these approaches have solely relied on the knowledge en-coded in the Gene Ontology and the gene annotations associated with the Gene On-tology database. The goal of this paper is to demonstrate that improvements to these approaches can be obtained by integrating textual evidence extracted from relevant biomedical literature.

Applying Agrep to r-NSA to solve multiple sequences approximate matching.

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Ni, Bing; Wong, Man-Hon; Lam, Chi-Fai David; Leung, Kwong-Sak

2014-01-01

This paper addresses the approximate matching problem in a database consisting of multiple DNA sequences, where the proposed approach applies Agrep to a new truncated suffix array, r-NSA. The construction time of the structure is linear to the database size, and the computations of indexing a substring in the structure are constant. The number of characters processed in applying Agrep is analysed theoretically, and the theoretical upper-bound can approximate closely the empirical number of characters, which is obtained through enumerating the characters in the actual structure built. Experiments are carried out using (synthetic) random DNA sequences, as well as (real) genome sequences including Hepatitis-B Virus and X-chromosome. Experimental results show that, compared to the straight-forward approach that applies Agrep to multiple sequences individually, the proposed approach solves the matching problem in much shorter time. The speed-up of our approach depends on the sequence patterns, and for highly similar homologous genome sequences, which are the common cases in real-life genomes, it can be up to several orders of magnitude.

Coincident site lattice-matched InGaN on (111) spinel substrates

Energy Technology Data Exchange (ETDEWEB)

Norman, A. G.; Dippo, P. C.; Moutinho, H. R.; Simon, J.; Ptak, A. J. [National Renewable Energy Laboratory, Golden, Colorado 80401 (United States)

2012-04-09

Coincident site lattice-matched wurtzite (0001) In{sub 0.31}Ga{sub 0.69}N, emitting in the important green wavelength region, is demonstrated by molecular beam epitaxy on a cubic (111) MgAl{sub 2}O{sub 4} spinel substrate. The coincident site lattice matching condition involves a 30 deg. rotation between the lattice of the InGaN epitaxial layer and the lattice of the spinel. This work describes an alternative approach towards realizing more compositionally homogenous InGaN films with low dislocation density emitting in the ''green gap'' of low efficiency currently observed for semiconductor light emitting diodes (LEDs). This approach could lead to higher efficiency green LEDs presently of great interest for solid-state lighting applications.

The COMT Val158 allele is associated with impaired delayed-match-to-sample performance in ADHD

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Matthews Natasha

2012-05-01

Full Text Available Abstract Background This study explored the association between three measures of working memory ability and genetic variation in a range of catecholamine genes in a sample of children with ADHD. Methods One hundred and eighteen children with ADHD performed three working memory measures taken from the CANTAB battery (Spatial Span, Delayed-match-to-sample, and Spatial Working Memory. Associations between performance on working memory measures and allelic variation in catecholamine genes (including those for the noradrenaline transporter [NET1], the dopamine D4 and D2 receptor genes [DRD4; DRD2], the gene encoding dopamine beta hydroxylase [DBH] and catechol-O-methyl transferase [COMT] were investigated using regression models that controlled for age, IQ, gender and medication status on the day of test. Results Significant associations were found between performance on the delayed-match-to-sample task and COMT genotype. More specifically, val/val homozygotes produced significantly more errors than did children who carried a least one met allele. There were no further associations between allelic variants and performance across the other working memory tasks. Conclusions The working memory measures employed in the present study differed in the degree to which accurate task performance depended upon either the dynamic updating and/or manipulation of items in working memory, as in the spatial span and spatial working memory tasks, or upon the stable maintenance of representations, as in the delay-match–to-sample task. The results are interpreted as evidence of a relationship between tonic dopamine levels associated with the met COMT allele and the maintenance of stable working memory representations required to perform the delayed-match-to-sample-task.

Robust and efficient method for matching features in omnidirectional images

Science.gov (United States)

Zhu, Qinyi; Zhang, Zhijiang; Zeng, Dan

2018-04-01

Binary descriptors have been widely used in many real-time applications due to their efficiency. These descriptors are commonly designed for perspective images but perform poorly on omnidirectional images, which are severely distorted. To address this issue, this paper proposes tangent plane BRIEF (TPBRIEF) and adapted log polar grid-based motion statistics (ALPGMS). TPBRIEF projects keypoints to a unit sphere and applies the fixed test set in BRIEF descriptor on the tangent plane of the unit sphere. The fixed test set is then backprojected onto the original distorted images to construct the distortion invariant descriptor. TPBRIEF directly enables keypoint detecting and feature describing on original distorted images, whereas other approaches correct the distortion through image resampling, which introduces artifacts and adds time cost. With ALPGMS, omnidirectional images are divided into circular arches named adapted log polar grids. Whether a match is true or false is then determined by simply thresholding the match numbers in a grid pair where the two matched points located. Experiments show that TPBRIEF greatly improves the feature matching accuracy and ALPGMS robustly removes wrong matches. Our proposed method outperforms the state-of-the-art methods.

Effective anisotropy through traveltime and amplitude matching

KAUST Repository

Wang, Hui

2014-08-05

Introducing anisotropy to seismic wave propagation reveals more realistic physics of our Earth\\'s subsurface as compared to the isotropic assumption. However wavefield modeling, the engine of seismic inverse problems, in anisotropic media still suffers from computational burdens, in particular with complex anisotropy such as transversely isotropic (TI) and Orthorhombic anisotropy. We develop effective isotropic velocity and density models to package the effects of anisotropy such that the wave propagation behavior using these effective models approximate those of the original anisotropic model. We build these effective models through the high frequency asymptotic approximation based on the eikonal and transport equations. We match the geometrical behavior of the wave-fields, given by traveltimes, from the anisotropic and isotropic eikonal equations. This matching yields the effective isotropic velocity that approximates the kinematics of the anisotropic wavefield. Equivalently, we calculate the effective densities by equating the anisotropic and isotropic transport equations. The effective velocities and densities are then fed into the isotropic acoustic variable density wave equation to obtain cheaper anisotropic wavefields. We justify our approach by testing it on an elliptical anisotropic model. The numerical results demonstrate a good matching of both traveltime and amplitude between anisotropic and effective isotropic wavefields.

Matching Cost Filtering for Dense Stereo Correspondence

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Yimin Lin

2013-01-01

Full Text Available Dense stereo correspondence enabling reconstruction of depth information in a scene is of great importance in the field of computer vision. Recently, some local solutions based on matching cost filtering with an edge-preserving filter have been proved to be capable of achieving more accuracy than global approaches. Unfortunately, the computational complexity of these algorithms is quadratically related to the window size used to aggregate the matching costs. The recent trend has been to pursue higher accuracy with greater efficiency in execution. Therefore, this paper proposes a new cost-aggregation module to compute the matching responses for all the image pixels at a set of sampling points generated by a hierarchical clustering algorithm. The complexity of this implementation is linear both in the number of image pixels and the number of clusters. Experimental results demonstrate that the proposed algorithm outperforms state-of-the-art local methods in terms of both accuracy and speed. Moreover, performance tests indicate that parameters such as the height of the hierarchical binary tree and the spatial and range standard deviations have a significant influence on time consumption and the accuracy of disparity maps.

SAD-Based Stereo Matching Using FPGAs

Science.gov (United States)

Ambrosch, Kristian; Humenberger, Martin; Kubinger, Wilfried; Steininger, Andreas

In this chapter we present a field-programmable gate array (FPGA) based stereo matching architecture. This architecture uses the sum of absolute differences (SAD) algorithm and is targeted at automotive and robotics applications. The disparity maps are calculated using 450×375 input images and a disparity range of up to 150 pixels. We discuss two different implementation approaches for the SAD and analyze their resource usage. Furthermore, block sizes ranging from 3×3 up to 11×11 and their impact on the consumed logic elements as well as on the disparity map quality are discussed. The stereo matching architecture enables a frame rate of up to 600 fps by calculating the data in a highly parallel and pipelined fashion. This way, a software solution optimized by using Intel's Open Source Computer Vision Library running on an Intel Pentium 4 with 3 GHz clock frequency is outperformed by a factor of 400.

PhenoLink - a web-tool for linking phenotype to ~omics data for bacteria: application to gene-trait matching for Lactobacillus plantarum strains

Directory of Open Access Journals (Sweden)

Bayjanov Jumamurat R

2012-05-01

Full Text Available Abstract Background Linking phenotypes to high-throughput molecular biology information generated by ~omics technologies allows revealing cellular mechanisms underlying an organism's phenotype. ~Omics datasets are often very large and noisy with many features (e.g., genes, metabolite abundances. Thus, associating phenotypes to ~omics data requires an approach that is robust to noise and can handle large and diverse data sets. Results We developed a web-tool PhenoLink (http://bamics2.cmbi.ru.nl/websoftware/phenolink/ that links phenotype to ~omics data sets using well-established as well new techniques. PhenoLink imputes missing values and preprocesses input data (i to decrease inherent noise in the data and (ii to counterbalance pitfalls of the Random Forest algorithm, on which feature (e.g., gene selection is based. Preprocessed data is used in feature (e.g., gene selection to identify relations to phenotypes. We applied PhenoLink to identify gene-phenotype relations based on the presence/absence of 2847 genes in 42 Lactobacillus plantarum strains and phenotypic measurements of these strains in several experimental conditions, including growth on sugars and nitrogen-dioxide production. Genes were ranked based on their importance (predictive value to correctly predict the phenotype of a given strain. In addition to known gene to phenotype relations we also found novel relations. Conclusions PhenoLink is an easily accessible web-tool to facilitate identifying relations from large and often noisy phenotype and ~omics datasets. Visualization of links to phenotypes offered in PhenoLink allows prioritizing links, finding relations between features, finding relations between phenotypes, and identifying outliers in phenotype data. PhenoLink can be used to uncover phenotype links to a multitude of ~omics data, e.g., gene presence/absence (determined by e.g.: CGH or next-generation sequencing, gene expression (determined by e.g.: microarrays or RNA

Identification of conserved drought-adaptive genes using a cross-species meta-analysis approach.

Science.gov (United States)

Shaar-Moshe, Lidor; Hübner, Sariel; Peleg, Zvi

2015-05-03

Drought is the major environmental stress threatening crop-plant productivity worldwide. Identification of new genes and metabolic pathways involved in plant adaptation to progressive drought stress at the reproductive stage is of great interest for agricultural research. We developed a novel Cross-Species meta-Analysis of progressive Drought stress at the reproductive stage (CSA:Drought) to identify key drought adaptive genes and mechanisms and to test their evolutionary conservation. Empirically defined filtering criteria were used to facilitate a robust integration of 17 deposited microarray experiments (148 arrays) of Arabidopsis, rice, wheat and barley. By prioritizing consistency over intensity, our approach was able to identify 225 differentially expressed genes shared across studies and taxa. Gene ontology enrichment and pathway analyses classified the shared genes into functional categories involved predominantly in metabolic processes (e.g. amino acid and carbohydrate metabolism), regulatory function (e.g. protein degradation and transcription) and response to stimulus. We further investigated drought related cis-acting elements in the shared gene promoters, and the evolutionary conservation of shared genes. The universal nature of the identified drought-adaptive genes was further validated in a fifth species, Brachypodium distachyon that was not included in the meta-analysis. qPCR analysis of 27, randomly selected, shared orthologs showed similar expression pattern as was found by the CSA:Drought.In accordance, morpho-physiological characterization of progressive drought stress, in B. distachyon, highlighted the key role of osmotic adjustment as evolutionary conserved drought-adaptive mechanism. Our CSA:Drought strategy highlights major drought-adaptive genes and metabolic pathways that were only partially, if at all, reported in the original studies included in the meta-analysis. These genes include a group of unclassified genes that could be involved

UltiMatch-NL: a Web service matchmaker based on multiple semantic filters.

Science.gov (United States)

Mohebbi, Keyvan; Ibrahim, Suhaimi; Zamani, Mazdak; Khezrian, Mojtaba

2014-01-01

In this paper, a Semantic Web service matchmaker called UltiMatch-NL is presented. UltiMatch-NL applies two filters namely Signature-based and Description-based on different abstraction levels of a service profile to achieve more accurate results. More specifically, the proposed filters rely on semantic knowledge to extract the similarity between a given pair of service descriptions. Thus it is a further step towards fully automated Web service discovery via making this process more semantic-aware. In addition, a new technique is proposed to weight and combine the results of different filters of UltiMatch-NL, automatically. Moreover, an innovative approach is introduced to predict the relevance of requests and Web services and eliminate the need for setting a threshold value of similarity. In order to evaluate UltiMatch-NL, the repository of OWLS-TC is used. The performance evaluation based on standard measures from the information retrieval field shows that semantic matching of OWL-S services can be significantly improved by incorporating designed matching filters.

UltiMatch-NL: A Web Service Matchmaker Based on Multiple Semantic Filters

Science.gov (United States)

Mohebbi, Keyvan; Ibrahim, Suhaimi; Zamani, Mazdak; Khezrian, Mojtaba

2014-01-01

In this paper, a Semantic Web service matchmaker called UltiMatch-NL is presented. UltiMatch-NL applies two filters namely Signature-based and Description-based on different abstraction levels of a service profile to achieve more accurate results. More specifically, the proposed filters rely on semantic knowledge to extract the similarity between a given pair of service descriptions. Thus it is a further step towards fully automated Web service discovery via making this process more semantic-aware. In addition, a new technique is proposed to weight and combine the results of different filters of UltiMatch-NL, automatically. Moreover, an innovative approach is introduced to predict the relevance of requests and Web services and eliminate the need for setting a threshold value of similarity. In order to evaluate UltiMatch-NL, the repository of OWLS-TC is used. The performance evaluation based on standard measures from the information retrieval field shows that semantic matching of OWL-S services can be significantly improved by incorporating designed matching filters. PMID:25157872

Impedance matched thin metamaterials make metals absorbing.

Science.gov (United States)

Mattiucci, N; Bloemer, M J; Aközbek, N; D'Aguanno, G

2013-11-13

Metals are generally considered good reflectors over the entire electromagnetic spectrum up to their plasma frequency. Here we demonstrate an approach to tailor their absorbing characteristics based on the effective metamaterial properties of thin, periodic metallo-dielectric multilayers by exploiting a broadband, inherently non-resonant, surface impedance matching mechanism. Based on this mechanism, we design, fabricate and test omnidirectional, thin ( 99%) over a frequency range spanning from the UV to the IR. Our approach opens new venues to design cost effective materials for many applications such as thermo-photovoltaic energy conversion devices, light harvesting for solar cells, flat panel display, infrared detectors, stray light reduction, stealth and others.

Video-assisted thoracic surgery lobectomy does not offer any functional recovery advantage in comparison to the open approach 3 months after the operation: a case matched analysis†.

Science.gov (United States)

Salati, Michele; Brunelli, Alessandro; Xiumè, Francesco; Monteverde, Marco; Sabbatini, Armando; Tiberi, Michela; Pompili, Cecilia; Palloni, Roberto; Refai, Majed

2017-06-01

The objective of the present study was to compare functional loss [forced expiratory volume in one second to forced vital capacity ratio (FEV1), DLCO and VO2max reduction] after VATS versus open lobectomies. We performed a prospective observational study on 195 patients who had a pulmonary lobectomy from June 2010 to November 2014 and who were able to complete a 3-months functional evaluation follow-up program. Since the VATS technique was our first choice for performing lobectomies from January 2012, we divided the patients into two groups: the OPEN group (112 patients) and the VATS group (83 patients). The open approach was intended as a muscle sparing/nerve sparing lateral thoracotomy. Fourteen baseline factors were used to construct a propensity score to match the VATS-group patients with their OPEN-group counterparts. These two matched groups were then compared in terms of reduction of FEV1, DLCO and VO2max (Mann-Whitney test). The propensity score analysis yielded 83 well-matched pairs of OPEN and VATS patients. In both groups, 3 months postoperatively, we found a reduction in FEV1, DLCO and VO2max values (OPEN patients: FEV1-10%, DLCO -11.9%, VO2max - 5.5%; VATS patients: FEV1-7.2%, DLCO-10.6%, VO2max-6.9%). The reductions in FEV1, DLCO and VO2max were similar to those in the two matched groups, with a Cohen effect size offer any advantages in terms of FEV1, DLCO and exercise capacity recovery in comparison to the muscle-sparing thoracotomy approach. © The Author 2017. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Classification of gene expression data: A hubness-aware semi-supervised approach.

Science.gov (United States)

Buza, Krisztian

2016-04-01

Classification of gene expression data is the common denominator of various biomedical recognition tasks. However, obtaining class labels for large training samples may be difficult or even impossible in many cases. Therefore, semi-supervised classification techniques are required as semi-supervised classifiers take advantage of unlabeled data. Gene expression data is high-dimensional which gives rise to the phenomena known under the umbrella of the curse of dimensionality, one of its recently explored aspects being the presence of hubs or hubness for short. Therefore, hubness-aware classifiers have been developed recently, such as Naive Hubness-Bayesian k-Nearest Neighbor (NHBNN). In this paper, we propose a semi-supervised extension of NHBNN which follows the self-training schema. As one of the core components of self-training is the certainty score, we propose a new hubness-aware certainty score. We performed experiments on publicly available gene expression data. These experiments show that the proposed classifier outperforms its competitors. We investigated the impact of each of the components (classification algorithm, semi-supervised technique, hubness-aware certainty score) separately and showed that each of these components are relevant to the performance of the proposed approach. Our results imply that our approach may increase classification accuracy and reduce computational costs (i.e., runtime). Based on the promising results presented in the paper, we envision that hubness-aware techniques will be used in various other biomedical machine learning tasks. In order to accelerate this process, we made an implementation of hubness-aware machine learning techniques publicly available in the PyHubs software package (http://www.biointelligence.hu/pyhubs) implemented in Python, one of the most popular programming languages of data science. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A roadmap of clustering algorithms: finding a match for a biomedical application.

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Andreopoulos, Bill; An, Aijun; Wang, Xiaogang; Schroeder, Michael

2009-05-01

Clustering is ubiquitously applied in bioinformatics with hierarchical clustering and k-means partitioning being the most popular methods. Numerous improvements of these two clustering methods have been introduced, as well as completely different approaches such as grid-based, density-based and model-based clustering. For improved bioinformatics analysis of data, it is important to match clusterings to the requirements of a biomedical application. In this article, we present a set of desirable clustering features that are used as evaluation criteria for clustering algorithms. We review 40 different clustering algorithms of all approaches and datatypes. We compare algorithms on the basis of desirable clustering features, and outline algorithms' benefits and drawbacks as a basis for matching them to biomedical applications.

A robust approach towards unknown transformation, regional adjacency graphs, multigraph matching, segmentation video frames from unnamed aerial vehicles (UAV)

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Gohatre, Umakant Bhaskar; Patil, Venkat P.

2018-04-01

In computer vision application, the multiple object detection and tracking, in real-time operation is one of the important research field, that have gained a lot of attentions, in last few years for finding non stationary entities in the field of image sequence. The detection of object is advance towards following the moving object in video and then representation of object is step to track. The multiple object recognition proof is one of the testing assignment from detection multiple objects from video sequence. The picture enrollment has been for quite some time utilized as a reason for the location the detection of moving multiple objects. The technique of registration to discover correspondence between back to back casing sets in view of picture appearance under inflexible and relative change. The picture enrollment is not appropriate to deal with event occasion that can be result in potential missed objects. In this paper, for address such problems, designs propose novel approach. The divided video outlines utilizing area adjancy diagram of visual appearance and geometric properties. Then it performed between graph sequences by using multi graph matching, then getting matching region labeling by a proposed graph coloring algorithms which assign foreground label to respective region. The plan design is robust to unknown transformation with significant improvement in overall existing work which is related to moving multiple objects detection in real time parameters.

Bayesian assignment of gene ontology terms to gene expression experiments

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Sykacek, P.

2012-01-01

Motivation: Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. Results: This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Availability: Source code under GPL license is available from the author. Contact: peter.sykacek@boku.ac.at PMID:22962488

Bayesian assignment of gene ontology terms to gene expression experiments.

Science.gov (United States)

Sykacek, P

2012-09-15

Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Source code under GPL license is available from the author. peter.sykacek@boku.ac.at.

Matching fully differential NNLO calculations and parton showers

Energy Technology Data Exchange (ETDEWEB)

Alioli, Simone; Bauer, Christian W.; Berggren, Calvin; Walsh, Jonathan R.; Zuberi, Saba [California Univ., Berkeley, CA (United States). Ernest Orlando Lawrence Berkeley National Laboratory; Tackmann, Frank J. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)

2013-11-15

We present a general method to match fully differential next-to-next-to-leading (NNLO) calculations to parton shower programs. We discuss in detail the perturbative accuracy criteria a complete NNLO+PS matching has to satisfy. Our method is based on consistently improving a given NNLO calculation with the leading-logarithmic (LL) resummation in a chosen jet resolution variable. The resulting NNLO+LL calculation is cast in the form of an event generator for physical events that can be directly interfaced with a parton shower routine, and we give an explicit construction of the input ''Monte Carlo cross sections'' satisfying all required criteria. We also show how other proposed approaches naturally arise as special cases in our method.

Whole genome sequencing options for bacterial strain typing and epidemiologic analysis based on single nucleotide polymorphism versus gene-by-gene-based approaches.

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Schürch, A C; Arredondo-Alonso, S; Willems, R J L; Goering, R V

2018-04-01

Whole genome sequence (WGS)-based strain typing finds increasing use in the epidemiologic analysis of bacterial pathogens in both public health as well as more localized infection control settings. This minireview describes methodologic approaches that have been explored for WGS-based epidemiologic analysis and considers the challenges and pitfalls of data interpretation. Personal collection of relevant publications. When applying WGS to study the molecular epidemiology of bacterial pathogens, genomic variability between strains is translated into measures of distance by determining single nucleotide polymorphisms in core genome alignments or by indexing allelic variation in hundreds to thousands of core genes, assigning types to unique allelic profiles. Interpreting isolate relatedness from these distances is highly organism specific, and attempts to establish species-specific cutoffs are unlikely to be generally applicable. In cases where single nucleotide polymorphism or core gene typing do not provide the resolution necessary for accurate assessment of the epidemiology of bacterial pathogens, inclusion of accessory gene or plasmid sequences may provide the additional required discrimination. As with all epidemiologic analysis, realizing the full potential of the revolutionary advances in WGS-based approaches requires understanding and dealing with issues related to the fundamental steps of data generation and interpretation. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

More powerful significant testing for time course gene expression data using functional principal component analysis approaches.

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Wu, Shuang; Wu, Hulin

2013-01-16

One of the fundamental problems in time course gene expression data analysis is to identify genes associated with a biological process or a particular stimulus of interest, like a treatment or virus infection. Most of the existing methods for this problem are designed for data with longitudinal replicates. But in reality, many time course gene experiments have no replicates or only have a small number of independent replicates. We focus on the case without replicates and propose a new method for identifying differentially expressed genes by incorporating the functional principal component analysis (FPCA) into a hypothesis testing framework. The data-driven eigenfunctions allow a flexible and parsimonious representation of time course gene expression trajectories, leaving more degrees of freedom for the inference compared to that using a prespecified basis. Moreover, the information of all genes is borrowed for individual gene inferences. The proposed approach turns out to be more powerful in identifying time course differentially expressed genes compared to the existing methods. The improved performance is demonstrated through simulation studies and a real data application to the Saccharomyces cerevisiae cell cycle data.

GSEH: A Novel Approach to Select Prostate Cancer-Associated Genes Using Gene Expression Heterogeneity.

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Kim, Hyunjin; Choi, Sang-Min; Park, Sanghyun

2018-01-01

When a gene shows varying levels of expression among normal people but similar levels in disease patients or shows similar levels of expression among normal people but different levels in disease patients, we can assume that the gene is associated with the disease. By utilizing this gene expression heterogeneity, we can obtain additional information that abets discovery of disease-associated genes. In this study, we used collaborative filtering to calculate the degree of gene expression heterogeneity between classes and then scored the genes on the basis of the degree of gene expression heterogeneity to find "differentially predicted" genes. Through the proposed method, we discovered more prostate cancer-associated genes than 10 comparable methods. The genes prioritized by the proposed method are potentially significant to biological processes of a disease and can provide insight into them.

Semi-Automatic Anatomical Tree Matching for Landmark-Based Elastic Registration of Liver Volumes

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Klaus Drechsler

2010-01-01

Full Text Available One promising approach to register liver volume acquisitions is based on the branching points of the vessel trees as anatomical landmarks inherently available in the liver. Automated tree matching algorithms were proposed to automatically find pair-wise correspondences between two vessel trees. However, to the best of our knowledge, none of the existing automatic methods are completely error free. After a review of current literature and methodologies on the topic, we propose an efficient interaction method that can be employed to support tree matching algorithms with important pre-selected correspondences or after an automatic matching to manually correct wrongly matched nodes. We used this method in combination with a promising automatic tree matching algorithm also presented in this work. The proposed method was evaluated by 4 participants and a CT dataset that we used to derive multiple artificial datasets.

Shrinkage covariance matrix approach based on robust trimmed mean in gene sets detection

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Karjanto, Suryaefiza; Ramli, Norazan Mohamed; Ghani, Nor Azura Md; Aripin, Rasimah; Yusop, Noorezatty Mohd

2015-02-01

Microarray involves of placing an orderly arrangement of thousands of gene sequences in a grid on a suitable surface. The technology has made a novelty discovery since its development and obtained an increasing attention among researchers. The widespread of microarray technology is largely due to its ability to perform simultaneous analysis of thousands of genes in a massively parallel manner in one experiment. Hence, it provides valuable knowledge on gene interaction and function. The microarray data set typically consists of tens of thousands of genes (variables) from just dozens of samples due to various constraints. Therefore, the sample covariance matrix in Hotelling's T2 statistic is not positive definite and become singular, thus it cannot be inverted. In this research, the Hotelling's T2 statistic is combined with a shrinkage approach as an alternative estimation to estimate the covariance matrix to detect significant gene sets. The use of shrinkage covariance matrix overcomes the singularity problem by converting an unbiased to an improved biased estimator of covariance matrix. Robust trimmed mean is integrated into the shrinkage matrix to reduce the influence of outliers and consequently increases its efficiency. The performance of the proposed method is measured using several simulation designs. The results are expected to outperform existing techniques in many tested conditions.

Gene-knockdown in the honey bee mite Varroa destructor by a non-invasive approach: studies on a glutathione S-transferase

Directory of Open Access Journals (Sweden)

Campbell Ewan M

2010-08-01

Full Text Available Abstract Background The parasitic mite Varroa destructor is considered the major pest of the European honey bee (Apis mellifera and responsible for declines in honey bee populations worldwide. Exploiting the full potential of gene sequences becoming available for V. destructor requires adaptation of modern molecular biology approaches to this non-model organism. Using a mu-class glutathione S-transferase (VdGST-mu1 as a candidate gene we investigated the feasibility of gene knockdown in V. destructor by double-stranded RNA-interference (dsRNAi. Results Intra-haemocoelic injection of dsRNA-VdGST-mu1 resulted in 97% reduction in VdGST-mu1 transcript levels 48 h post-injection compared to mites injected with a bolus of irrelevant dsRNA (LacZ. This gene suppression was maintained to, at least, 72 h. Total GST catalytic activity was reduced by 54% in VdGST-mu1 gene knockdown mites demonstrating the knockdown was effective at the translation step as well as the transcription steps. Although near total gene knockdown was achieved by intra-haemocoelic injection, only half of such treated mites survived this traumatic method of dsRNA administration and less invasive methods were assessed. V. destructor immersed overnight in 0.9% NaCl solution containing dsRNA exhibited excellent reduction in VdGST-mu1 transcript levels (87% compared to mites immersed in dsRNA-LacZ. Importantly, mites undergoing the immersion approach had greatly improved survival (75-80% over 72 h, approaching that of mites not undergoing any treatment. Conclusions Our findings on V. destructor are the first report of gene knockdown in any mite species and demonstrate that the small size of such organisms is not a major impediment to applying gene knockdown approaches to the study of such parasitic pests. The immersion in dsRNA solution method provides an easy, inexpensive, relatively high throughput method of gene silencing suitable for studies in V. destructor, other small mites and

Cognitive Learning Styles: Can You Engineer a "Perfect" Match?

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Khuzzan, Sharifah Mazlina Syed; Goulding, Jack Steven

2016-01-01

Education and training is widely acknowledged as being one of the key factors for leveraging organisational success. However, it is equally acknowledged that skills development and the acquisition of learning through managed cognitive approaches has yet to provide a "perfect" match. Whilst it is argued that an ideal learning scenario…

Image Segmentation, Registration, Compression, and Matching

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Yadegar, Jacob; Wei, Hai; Yadegar, Joseph; Ray, Nilanjan; Zabuawala, Sakina

2011-01-01

A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity

Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool.

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Chen, Edward Y; Tan, Christopher M; Kou, Yan; Duan, Qiaonan; Wang, Zichen; Meirelles, Gabriela Vaz; Clark, Neil R; Ma'ayan, Avi

2013-04-15

System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes/proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries. While many enrichment analysis tools and gene-set libraries databases have been developed, there is still room for improvement. Here, we present Enrichr, an integrative web-based and mobile software application that includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. We applied Enrichr to analyze nine cancer cell lines by comparing their enrichment signatures to the enrichment signatures of matched normal tissues. We observed a common pattern of up regulation of the polycomb group PRC2 and enrichment for the histone mark H3K27me3 in many cancer cell lines, as well as alterations in Toll-like receptor and interlukin signaling in K562 cells when compared with normal myeloid CD33+ cells. Such analyses provide global visualization of critical differences between normal tissues and cancer cell lines but can be applied to many other scenarios. Enrichr is an easy to use intuitive enrichment analysis web-based tool providing various types of visualization summaries of collective functions of gene lists. Enrichr is open source and freely available online at: http://amp.pharm.mssm.edu/Enrichr.

Latent palmprint matching.

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Jain, Anil K; Feng, Jianjiang

2009-06-01

The evidential value of palmprints in forensic applications is clear as about 30 percent of the latents recovered from crime scenes are from palms. While biometric systems for palmprint-based personal authentication in access control type of applications have been developed, they mostly deal with low-resolution (about 100 ppi) palmprints and only perform full-to-full palmprint matching. We propose a latent-to-full palmprint matching system that is needed in forensic applications. Our system deals with palmprints captured at 500 ppi (the current standard in forensic applications) or higher resolution and uses minutiae as features to be compatible with the methodology used by latent experts. Latent palmprint matching is a challenging problem because latent prints lifted at crime scenes are of poor image quality, cover only a small area of the palm, and have a complex background. Other difficulties include a large number of minutiae in full prints (about 10 times as many as fingerprints), and the presence of many creases in latents and full prints. A robust algorithm to reliably estimate the local ridge direction and frequency in palmprints is developed. This facilitates the extraction of ridge and minutiae features even in poor quality palmprints. A fixed-length minutia descriptor, MinutiaCode, is utilized to capture distinctive information around each minutia and an alignment-based minutiae matching algorithm is used to match two palmprints. Two sets of partial palmprints (150 live-scan partial palmprints and 100 latent palmprints) are matched to a background database of 10,200 full palmprints to test the proposed system. Despite the inherent difficulty of latent-to-full palmprint matching, rank-1 recognition rates of 78.7 and 69 percent, respectively, were achieved in searching live-scan partial palmprints and latent palmprints against the background database.

Combining Generalized Phase Contrast with matched filtering into a versatile beam shaping approach

DEFF Research Database (Denmark)

Glückstad, Jesper; Palima, Darwin

2010-01-01

We adapt concepts from matched filtering to propose a method for generating reconfigurable multiple beams. Combined with the Generalized Phase Contrast (GPC) technique, the proposed method coined mGPC can yield dynamically reconfigurable optical beam arrays with high light efficiency for optical...... manipulation, high-speed sorting and other parallel spatial light applications [1]....

Matching the quasiparton distribution in a momentum subtraction scheme

Science.gov (United States)

Stewart, Iain W.; Zhao, Yong

2018-03-01

The quasiparton distribution is a spatial correlation of quarks or gluons along the z direction in a moving nucleon which enables direct lattice calculations of parton distribution functions. It can be defined with a nonperturbative renormalization in a regularization independent momentum subtraction scheme (RI/MOM), which can then be perturbatively related to the collinear parton distribution in the MS ¯ scheme. Here we carry out a direct matching from the RI/MOM scheme for the quasi-PDF to the MS ¯ PDF, determining the non-singlet quark matching coefficient at next-to-leading order in perturbation theory. We find that the RI/MOM matching coefficient is insensitive to the ultraviolet region of convolution integral, exhibits improved perturbative convergence when converting between the quasi-PDF and PDF, and is consistent with a quasi-PDF that vanishes in the unphysical region as the proton momentum Pz→∞ , unlike other schemes. This direct approach therefore has the potential to improve the accuracy for converting quasidistribution lattice calculations to collinear distributions.

Landmine detection using two-tapped joint orthogonal matching pursuits

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Goldberg, Sean; Glenn, Taylor; Wilson, Joseph N.; Gader, Paul D.

2012-06-01

Joint Orthogonal Matching Pursuits (JOMP) is used here in the context of landmine detection using data obtained from an electromagnetic induction (EMI) sensor. The response from an object containing metal can be decomposed into a discrete spectrum of relaxation frequencies (DSRF) from which we construct a dictionary. A greedy iterative algorithm is proposed for computing successive residuals of a signal by subtracting away the highest matching dictionary element at each step. The nal condence of a particular signal is a combination of the reciprocal of this residual and the mean of the complex component. A two-tap approach comparing signals on opposite sides of the geometric location of the sensor is examined and found to produce better classication. It is found that using only a single pursuit does a comparable job, reducing complexity and allowing for real-time implementation in automated target recognition systems. JOMP is particularly highlighted in comparison with a previous EMI detection algorithm known as String Match.

Virtual gap element approach for the treatment of non-matching interface using three-dimensional solid elements

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Song, Yeo-Ul; Youn, Sung-Kie; Park, K. C.

2017-10-01

A method for three-dimensional non-matching interface treatment with a virtual gap element is developed. When partitioned structures contain curved interfaces and have different brick meshes, the discretized models have gaps along the interfaces. As these gaps bring unexpected errors, special treatments are required to handle the gaps. In the present work, a virtual gap element is introduced to link the frame and surface domain nodes in the frame work of the mortar method. Since the surface of the hexahedron element is quadrilateral, the gap element is pyramidal. The pyramidal gap element consists of four domain nodes and one frame node. Zero-strain condition in the gap element is utilized for the interpolation of frame nodes in terms of the domain nodes. This approach is taken to satisfy the momentum and energy conservation. The present method is applicable not only to curved interfaces with gaps, but also to flat interfaces in three dimensions. Several numerical examples are given to describe the effectiveness and accuracy of the proposed method.

Screening for single nucleotide variants, small indels and exon deletions with a next-generation sequencing based gene panel approach for Usher syndrome.

Science.gov (United States)

Krawitz, Peter M; Schiska, Daniela; Krüger, Ulrike; Appelt, Sandra; Heinrich, Verena; Parkhomchuk, Dmitri; Timmermann, Bernd; Millan, Jose M; Robinson, Peter N; Mundlos, Stefan; Hecht, Jochen; Gross, Manfred

2014-09-01

Usher syndrome is an autosomal recessive disorder characterized both by deafness and blindness. For the three clinical subtypes of Usher syndrome causal mutations in altogether 12 genes and a modifier gene have been identified. Due to the genetic heterogeneity of Usher syndrome, the molecular analysis is predestined for a comprehensive and parallelized analysis of all known genes by next-generation sequencing (NGS) approaches. We describe here the targeted enrichment and deep sequencing for exons of Usher genes and compare the costs and workload of this approach compared to Sanger sequencing. We also present a bioinformatics analysis pipeline that allows us to detect single-nucleotide variants, short insertions and deletions, as well as copy number variations of one or more exons on the same sequence data. Additionally, we present a flexible in silico gene panel for the analysis of sequence variants, in which newly identified genes can easily be included. We applied this approach to a cohort of 44 Usher patients and detected biallelic pathogenic mutations in 35 individuals and monoallelic mutations in eight individuals of our cohort. Thirty-nine of the sequence variants, including two heterozygous deletions comprising several exons of USH2A, have not been reported so far. Our NGS-based approach allowed us to assess single-nucleotide variants, small indels, and whole exon deletions in a single test. The described diagnostic approach is fast and cost-effective with a high molecular diagnostic yield.

Pediatric Multiple Sclerosis: Genes, Environment, and a Comprehensive Therapeutic Approach.

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Cappa, Ryan; Theroux, Liana; Brenton, J Nicholas

2017-10-01

Pediatric multiple sclerosis is an increasingly recognized and studied disorder that accounts for 3% to 10% of all patients with multiple sclerosis. The risk for pediatric multiple sclerosis is thought to reflect a complex interplay between environmental and genetic risk factors. Environmental exposures, including sunlight (ultraviolet radiation, vitamin D levels), infections (Epstein-Barr virus), passive smoking, and obesity, have been identified as potential risk factors in youth. Genetic predisposition contributes to the risk of multiple sclerosis, and the major histocompatibility complex on chromosome 6 makes the single largest contribution to susceptibility to multiple sclerosis. With the use of large-scale genome-wide association studies, other non-major histocompatibility complex alleles have been identified as independent risk factors for the disease. The bridge between environment and genes likely lies in the study of epigenetic processes, which are environmentally-influenced mechanisms through which gene expression may be modified. This article will review these topics to provide a framework for discussion of a comprehensive approach to counseling and ultimately treating the pediatric patient with multiple sclerosis. Copyright © 2017 Elsevier Inc. All rights reserved.

Quantity precommitment and price matching

DEFF Research Database (Denmark)

Tumennasan, Norovsambuu

We revisit the question of whether price matching is anti-competitive in a capacity constrained duopoly setting. We show that the effect of price matching depends on capacity. Specifically, price matching has no effect when capacity is relatively low, but it benefits the firms when capacity...... is relatively high. Interestingly, when capacity is in an intermediate range, price matching benefits only the small firm but does not affect the large firm in any way. Therefore, one has to consider capacity seriously when evaluating if price matching is anti-competitive. If the firms choose their capacities...... simultaneously before pricing decisions, then the effect of price matching is either pro-competitive or ambiguous. We show that if the cost of capacity is high, then price matching can only (weakly) decrease the market price. On the other hand, if the cost of capacity is low, then the effect of price matching...

NINJA-OPS: Fast Accurate Marker Gene Alignment Using Concatenated Ribosomes.

Directory of Open Access Journals (Sweden)

Gabriel A Al-Ghalith

2016-01-01

Full Text Available The explosion of bioinformatics technologies in the form of next generation sequencing (NGS has facilitated a massive influx of genomics data in the form of short reads. Short read mapping is therefore a fundamental component of next generation sequencing pipelines which routinely match these short reads against reference genomes for contig assembly. However, such techniques have seldom been applied to microbial marker gene sequencing studies, which have mostly relied on novel heuristic approaches. We propose NINJA Is Not Just Another OTU-Picking Solution (NINJA-OPS, or NINJA for short, a fast and highly accurate novel method enabling reference-based marker gene matching (picking Operational Taxonomic Units, or OTUs. NINJA takes advantage of the Burrows-Wheeler (BW alignment using an artificial reference chromosome composed of concatenated reference sequences, the "concatesome," as the BW input. Other features include automatic support for paired-end reads with arbitrary insert sizes. NINJA is also free and open source and implements several pre-filtering methods that elicit substantial speedup when coupled with existing tools. We applied NINJA to several published microbiome studies, obtaining accuracy similar to or better than previous reference-based OTU-picking methods while achieving an order of magnitude or more speedup and using a fraction of the memory footprint. NINJA is a complete pipeline that takes a FASTA-formatted input file and outputs a QIIME-formatted taxonomy-annotated BIOM file for an entire MiSeq run of human gut microbiome 16S genes in under 10 minutes on a dual-core laptop.

Quick probabilistic binary image matching: changing the rules of the game

Science.gov (United States)

Mustafa, Adnan A. Y.

2016-09-01

A Probabilistic Matching Model for Binary Images (PMMBI) is presented that predicts the probability of matching binary images with any level of similarity. The model relates the number of mappings, the amount of similarity between the images and the detection confidence. We show the advantage of using a probabilistic approach to matching in similarity space as opposed to a linear search in size space. With PMMBI a complete model is available to predict the quick detection of dissimilar binary images. Furthermore, the similarity between the images can be measured to a good degree if the images are highly similar. PMMBI shows that only a few pixels need to be compared to detect dissimilarity between images, as low as two pixels in some cases. PMMBI is image size invariant; images of any size can be matched at the same quick speed. Near-duplicate images can also be detected without much difficulty. We present tests on real images that show the prediction accuracy of the model.

Identifying the greatest team and captain—A complex network approach to cricket matches

Science.gov (United States)

Mukherjee, Satyam

2012-12-01

We consider all Test matches played between 1877 and 2010 and One Day International (ODI) matches played between 1971 and 2010. We form directed and weighted networks of teams and also of their captains. The success of a team (or captain) is determined by the ‘quality’ of the wins, not simply by the number of wins. We apply the diffusion-based PageRank algorithm to the networks to assess the importance of the wins, and rank the respective teams and captains. Our analysis identifies Australia as the best team in both forms of cricket, Test and ODI. Steve Waugh is identified as the best captain in Test cricket and Ricky Ponting is the best captain in the ODI format. We also compare our ranking scheme with an existing ranking scheme, the Reliance ICC ranking. Our method does not depend on ‘external’ criteria in the ranking of teams (captains). The purpose of this paper is to introduce a revised ranking of cricket teams and to quantify the success of the captains.

Retrieving quasi-phase-matching structure with discrete layer-peeling method

DEFF Research Database (Denmark)

Zhang, Q. W.; Zeng, Xianglong; Wang, M.

2012-01-01

An approach to reconstruct a quasi-phase-matching grating by using a discrete layer-peeling algorithm is presented. Experimentally measured output spectra of Solc-type filters, based on uniform and chirped QPM structures, are used in the discrete layer-peeling algorithm. The reconstructed QPM...

Rapid Generation of Human Genetic Loss-of-Function iPSC Lines by Simultaneous Reprogramming and Gene Editing

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Andrew M. Tidball

2017-09-01

Full Text Available Specifically ablating genes in human induced pluripotent stem cells (iPSCs allows for studies of gene function as well as disease mechanisms in disorders caused by loss-of-function (LOF mutations. While techniques exist for engineering such lines, we have developed and rigorously validated a method of simultaneous iPSC reprogramming while generating CRISPR/Cas9-dependent insertions/deletions (indels. This approach allows for the efficient and rapid formation of genetic LOF human disease cell models with isogenic controls. The rate of mutagenized lines was strikingly consistent across experiments targeting four different human epileptic encephalopathy genes and a metabolic enzyme-encoding gene, and was more efficient and consistent than using CRISPR gene editing of established iPSC lines. The ability of our streamlined method to reproducibly generate heterozygous and homozygous LOF iPSC lines with passage-matched isogenic controls in a single step provides for the rapid development of LOF disease models with ideal control lines, even in the absence of patient tissue.

An Effective Semantic Event Matching System in the Internet of Things (IoT) Environment.

Science.gov (United States)

Alhakbani, Noura; Hassan, Mohammed Mehedi; Ykhlef, Mourad

2017-09-02

IoT sensors use the publish/subscribe model for communication to benefit from its decoupled nature with respect to space, time, and synchronization. Because of the heterogeneity of communicating parties, semantic decoupling is added as a fourth dimension. The added semantic decoupling complicates the matching process and reduces its efficiency. Our proposed algorithm clusters subscriptions and events according to topic and performs the matching process within these clusters, which increases the throughput by reducing the matching time from the range of 16-18 ms to 2-4 ms. Moreover, the accuracy of matching is improved when subscriptions must be fully approximated, as demonstrated by an over 40% increase in F-score results. This work shows the benefit of clustering, as well as the improvement in the matching accuracy and efficiency achieved using this approach.

The Interaction Between Schema Matching and Record Matching in Data Integration

KAUST Repository

Gu, Binbin; Li, Zhixu; Zhang, Xiangliang; Liu, An; Liu, Guanfeng; Zheng, Kai; Zhao, Lei; Zhou, Xiaofang

2016-01-01

Schema Matching (SM) and Record Matching (RM) are two necessary steps in integrating multiple relational tables of different schemas, where SM unifies the schemas and RM detects records referring to the same real-world entity. The two processes have

Facial emotion recognition in Williams syndrome and Down syndrome: A matching and developmental study.

Science.gov (United States)

Martínez-Castilla, Pastora; Burt, Michael; Borgatti, Renato; Gagliardi, Chiara

2015-01-01

In this study both the matching and developmental trajectories approaches were used to clarify questions that remain open in the literature on facial emotion recognition in Williams syndrome (WS) and Down syndrome (DS). The matching approach showed that individuals with WS or DS exhibit neither proficiency for the expression of happiness nor specific impairments for negative emotions. Instead, they present the same pattern of emotion recognition as typically developing (TD) individuals. Thus, the better performance on the recognition of positive compared to negative emotions usually reported in WS and DS is not specific of these populations but seems to represent a typical pattern. Prior studies based on the matching approach suggested that the development of facial emotion recognition is delayed in WS and atypical in DS. Nevertheless, and even though performance levels were lower in DS than in WS, the developmental trajectories approach used in this study evidenced that not only individuals with DS but also those with WS present atypical development in facial emotion recognition. Unlike in the TD participants, where developmental changes were observed along with age, in the WS and DS groups, the development of facial emotion recognition was static. Both individuals with WS and those with DS reached an early maximum developmental level due to cognitive constraints.

Robotic Liver Resection: A Case-Matched Comparison.

Science.gov (United States)

Kingham, T Peter; Leung, Universe; Kuk, Deborah; Gönen, Mithat; D'Angelica, Michael I; Allen, Peter J; DeMatteo, Ronald P; Laudone, Vincent P; Jarnagin, William R; Fong, Yuman

2016-06-01

In recent years, increasingly sophisticated tools have allowed for more complex robotic surgery. Robotic hepatectomy, however, is still in its infancy. Our goals were to examine the adoption of robotic hepatectomy and to compare outcomes between open and robotic liver resections. The robotic hepatectomy experience of 64 patients was compared to a modern case-matched series of 64 open hepatectomy patients at the same center. Matching was according to benign/malignant diagnosis and number of segments resected. Patient data were obtained retrospectively. The main outcomes and measures were operative time, estimated blood loss, conversion rate (robotic to open), Pringle maneuver use, single non-anatomic wedge resection rate, resection margin size, complication rates (infectious, hepatic, pulmonary, cardiac), hospital stay length, ICU stay length, readmission rate, and 90-day mortality rate. Sixty-four robotic hepatectomies were performed in 2010-2014. Forty-one percent were segmental and 34 % were wedge resections. There was a 6 % conversion rate, a 3 % 90-day mortality rate, and an 11 % morbidity rate. Compared to 64 matched patients who underwent open hepatectomy (2004-2012), there was a shorter median OR time (p = 0.02), lower median estimated blood loss (p optimization of outcomes and prospective examination of the economic cost of each approach.

A data mining approach for classifying DNA repair genes into ageing-related or non-ageing-related

Directory of Open Access Journals (Sweden)

Vasieva Olga

2011-01-01

Full Text Available Abstract Background The ageing of the worldwide population means there is a growing need for research on the biology of ageing. DNA damage is likely a key contributor to the ageing process and elucidating the role of different DNA repair systems in ageing is of great interest. In this paper we propose a data mining approach, based on classification methods (decision trees and Naive Bayes, for analysing data about human DNA repair genes. The goal is to build classification models that allow us to discriminate between ageing-related and non-ageing-related DNA repair genes, in order to better understand their different properties. Results The main patterns discovered by the classification methods are as follows: (a the number of protein-protein interactions was a predictor of DNA repair proteins being ageing-related; (b the use of predictor attributes based on protein-protein interactions considerably increased predictive accuracy of attributes based on Gene Ontology (GO annotations; (c GO terms related to "response to stimulus" seem reasonably good predictors of ageing-relatedness for DNA repair genes; (d interaction with the XRCC5 (Ku80 protein is a strong predictor of ageing-relatedness for DNA repair genes; and (e DNA repair genes with a high expression in T lymphocytes are more likely to be ageing-related. Conclusions The above patterns are broadly integrated in an analysis discussing relations between Ku, the non-homologous end joining DNA repair pathway, ageing and lymphocyte development. These patterns and their analysis support non-homologous end joining double strand break repair as central to the ageing-relatedness of DNA repair genes. Our work also showcases the use of protein interaction partners to improve accuracy in data mining methods and our approach could be applied to other ageing-related pathways.

Matching Matched Filtering with Deep Networks for Gravitational-Wave Astronomy

Science.gov (United States)

Gabbard, Hunter; Williams, Michael; Hayes, Fergus; Messenger, Chris

2018-04-01

We report on the construction of a deep convolutional neural network that can reproduce the sensitivity of a matched-filtering search for binary black hole gravitational-wave signals. The standard method for the detection of well-modeled transient gravitational-wave signals is matched filtering. We use only whitened time series of measured gravitational-wave strain as an input, and we train and test on simulated binary black hole signals in synthetic Gaussian noise representative of Advanced LIGO sensitivity. We show that our network can classify signal from noise with a performance that emulates that of match filtering applied to the same data sets when considering the sensitivity defined by receiver-operator characteristics.

Matching Matched Filtering with Deep Networks for Gravitational-Wave Astronomy.

Science.gov (United States)

Gabbard, Hunter; Williams, Michael; Hayes, Fergus; Messenger, Chris

2018-04-06

We report on the construction of a deep convolutional neural network that can reproduce the sensitivity of a matched-filtering search for binary black hole gravitational-wave signals. The standard method for the detection of well-modeled transient gravitational-wave signals is matched filtering. We use only whitened time series of measured gravitational-wave strain as an input, and we train and test on simulated binary black hole signals in synthetic Gaussian noise representative of Advanced LIGO sensitivity. We show that our network can classify signal from noise with a performance that emulates that of match filtering applied to the same data sets when considering the sensitivity defined by receiver-operator characteristics.

78 FR 42080 - Privacy Act of 1974; CMS Computer Match No. 2013-07; HHS Computer Match No. 1303; DoD-DMDC Match...

Science.gov (United States)

2013-07-15

... 1974; CMS Computer Match No. 2013-07; HHS Computer Match No. 1303; DoD-DMDC Match No. 18 AGENCY: Centers for Medicare & Medicaid Services (CMS), Department of Health and Human Services (HHS). ACTION... Act of 1974, as amended, this notice announces the establishment of a CMP that CMS plans to conduct...

SU-E-T-262: Planning for Proton Pencil Beam Scanning (PBS): Applications of Gradient Optimization for Field Matching

Energy Technology Data Exchange (ETDEWEB)

Lin, H; Kirk, M; Zhai, H; Ding, X; Liu, H; Hill-Kayser, C; Lustig, R; Tochner, Z; Deville, C; Vapiwala, N; McDonough, J; Both, S [University Pennsylvania, Philadelphia, PA (United States)

2014-06-01

Purpose: To propose the gradient optimization(GO) approach in planning for matching proton PBS fields and present two commonly used applications in our institution. Methods: GO is employed for PBS field matching in the scenarios that when the size of the target is beyond the field size limit of the beam delivery system or matching is required for beams from different angles to either improve the sparing of important organs or to pass through a short and simple beam path. Overlap is designed between adjacent fields and in the overlapped junction, the dose was optimized such that it gradually decreases in one field and the decrease is compensated by increase from another field. Clinical applications of this approach on craniospinal irradiation(CSI) and whole pelvis treatment were presented. Mathematical model was developed to study the relationships between dose errors, setup errors and junction lengths. Results: Uniform and conformal dose coverage to the entire target volumes was achieved for both applications using GO approach. For CSI, the gradient matching (6.7cm junction) between fields overcame the complexity of planning associated with feathering match lines. A slow dose gradient in the junction area significantly reduced the sensitivity of the treatment to setup errors. For whole pelvis, gradient matching (4cm junction) between posterior fields for superior target and bilateral fields for inferior target provided dose sparing to organs such as bowel, bladder and rectum. For a setup error of 3 mm in longitudinal direction from one field, mathematical model predicted dose errors of 10%, 6% and 4.3% for junction length of 3, 5 and 7cm. Conclusion: This GO approach improves the quality of the PBS treatment plan with matching fields while maintaining the safety of treatment delivery relative to potential misalignments.

SU-E-T-262: Planning for Proton Pencil Beam Scanning (PBS): Applications of Gradient Optimization for Field Matching

International Nuclear Information System (INIS)

Lin, H; Kirk, M; Zhai, H; Ding, X; Liu, H; Hill-Kayser, C; Lustig, R; Tochner, Z; Deville, C; Vapiwala, N; McDonough, J; Both, S

2014-01-01

Purpose: To propose the gradient optimization(GO) approach in planning for matching proton PBS fields and present two commonly used applications in our institution. Methods: GO is employed for PBS field matching in the scenarios that when the size of the target is beyond the field size limit of the beam delivery system or matching is required for beams from different angles to either improve the sparing of important organs or to pass through a short and simple beam path. Overlap is designed between adjacent fields and in the overlapped junction, the dose was optimized such that it gradually decreases in one field and the decrease is compensated by increase from another field. Clinical applications of this approach on craniospinal irradiation(CSI) and whole pelvis treatment were presented. Mathematical model was developed to study the relationships between dose errors, setup errors and junction lengths. Results: Uniform and conformal dose coverage to the entire target volumes was achieved for both applications using GO approach. For CSI, the gradient matching (6.7cm junction) between fields overcame the complexity of planning associated with feathering match lines. A slow dose gradient in the junction area significantly reduced the sensitivity of the treatment to setup errors. For whole pelvis, gradient matching (4cm junction) between posterior fields for superior target and bilateral fields for inferior target provided dose sparing to organs such as bowel, bladder and rectum. For a setup error of 3 mm in longitudinal direction from one field, mathematical model predicted dose errors of 10%, 6% and 4.3% for junction length of 3, 5 and 7cm. Conclusion: This GO approach improves the quality of the PBS treatment plan with matching fields while maintaining the safety of treatment delivery relative to potential misalignments

Matching methods evaluation framework for stereoscopic breast x-ray images.

Science.gov (United States)

Rousson, Johanna; Naudin, Mathieu; Marchessoux, Cédric

2016-01-01

Three-dimensional (3-D) imaging has been intensively studied in the past few decades. Depth information is an important added value of 3-D systems over two-dimensional systems. Special focuses were devoted to the development of stereo matching methods for the generation of disparity maps (i.e., depth information within a 3-D scene). Dedicated frameworks were designed to evaluate and rank the performance of different stereo matching methods but never considering x-ray medical images. Yet, 3-D x-ray acquisition systems and 3-D medical displays have already been introduced into the diagnostic market. To access the depth information within x-ray stereoscopic images, computing accurate disparity maps is essential. We aimed at developing a framework dedicated to x-ray stereoscopic breast images used to evaluate and rank several stereo matching methods. A multiresolution pyramid optimization approach was integrated to the framework to increase the accuracy and the efficiency of the stereo matching techniques. Finally, a metric was designed to score the results of the stereo matching compared with the ground truth. Eight methods were evaluated and four of them [locally scaled sum of absolute differences (LSAD), zero mean sum of absolute differences, zero mean sum of squared differences, and locally scaled mean sum of squared differences] appeared to perform equally good with an average error score of 0.04 (0 is the perfect matching). LSAD was selected for generating the disparity maps.

Prediction of regulatory gene pairs using dynamic time warping and gene ontology.

Science.gov (United States)

Yang, Andy C; Hsu, Hui-Huang; Lu, Ming-Da; Tseng, Vincent S; Shih, Timothy K

2014-01-01

Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.

Matching Adherence Interventions to Patient Determinants Using the Theoretical Domains Framework

NARCIS (Netherlands)

Allemann, S.S.; Nieuwlaat, R.; Bemt, B.J. van den; Hersberger, K.E.; Arnet, I.

2016-01-01

Introduction: Despite much research, interventions to improve medication adherence report disappointing and inconsistent results. Tailored approaches that match interventions and patient determinants of non-adherence were seldom used in clinical trials. The presence of a multitude of theoretical

78 FR 48169 - Privacy Act of 1974; CMS Computer Match No. 2013-02; HHS Computer Match No. 1306; DoD-DMDC Match...

Science.gov (United States)

2013-08-07

... 1974; CMS Computer Match No. 2013-02; HHS Computer Match No. 1306; DoD-DMDC Match No. 12 AGENCY: Department of Health and Human Services (HHS), Centers for Medicare & Medicaid Services (CMS). ACTION: Notice... of 1974, as amended, this notice establishes a CMP that CMS plans to conduct with the Department of...

Matching-pursuit/split-operator Fourier-transform simulations of nonadiabatic quantum dynamics

Science.gov (United States)

Wu, Yinghua; Herman, Michael F.; Batista, Victor S.

2005-03-01

A rigorous and practical approach for simulations of nonadiabatic quantum dynamics is introduced. The algorithm involves a natural extension of the matching-pursuit/split-operator Fourier-transform (MP/SOFT) method [Y. Wu and V. S. Batista, J. Chem. Phys. 121, 1676 (2004)] recently developed for simulations of adiabatic quantum dynamics in multidimensional systems. The MP/SOFT propagation scheme, extended to nonadiabatic dynamics, recursively applies the time-evolution operator as defined by the standard perturbation expansion to first-, or second-order, accuracy. The expansion is implemented in dynamically adaptive coherent-state representations, generated by an approach that combines the matching-pursuit algorithm with a gradient-based optimization method. The accuracy and efficiency of the resulting propagation method are demonstrated as applied to the canonical model systems introduced by Tully for testing simulations of dual curve-crossing nonadiabatic dynamics.

GeneTopics - interpretation of gene sets via literature-driven topic models

Science.gov (United States)

2013-01-01

Background Annotation of a set of genes is often accomplished through comparison to a library of labelled gene sets such as biological processes or canonical pathways. However, this approach might fail if the employed libraries are not up to date with the latest research, don't capture relevant biological themes or are curated at a different level of granularity than is required to appropriately analyze the input gene set. At the same time, the vast biomedical literature offers an unstructured repository of the latest research findings that can be tapped to provide thematic sub-groupings for any input gene set. Methods Our proposed method relies on a gene-specific text corpus and extracts commonalities between documents in an unsupervised manner using a topic model approach. We automatically determine the number of topics summarizing the corpus and calculate a gene relevancy score for each topic allowing us to eliminate non-specific topics. As a result we obtain a set of literature topics in which each topic is associated with a subset of the input genes providing directly interpretable keywords and corresponding documents for literature research. Results We validate our method based on labelled gene sets from the KEGG metabolic pathway collection and the genetic association database (GAD) and show that the approach is able to detect topics consistent with the labelled annotation. Furthermore, we discuss the results on three different types of experimentally derived gene sets, (1) differentially expressed genes from a cardiac hypertrophy experiment in mice, (2) altered transcript abundance in human pancreatic beta cells, and (3) genes implicated by GWA studies to be associated with metabolite levels in a healthy population. In all three cases, we are able to replicate findings from the original papers in a quick and semi-automated manner. Conclusions Our approach provides a novel way of automatically generating meaningful annotations for gene sets that are directly

Pollen Sterility—A Promising Approach to Gene Confinement and Breeding for Genetically Modified Bioenergy Crops

Directory of Open Access Journals (Sweden)

Albert P. Kausch

2012-10-01

Full Text Available Advanced genetic and biotechnology tools will be required to realize the full potential of food and bioenergy crops. Given current regulatory concerns, many transgenic traits might never be deregulated for commercial release without a robust gene confinement strategy in place. The potential for transgene flow from genetically modified (GM crops is widely known. Pollen-mediated transfer is a major component of gene flow in flowering plants and therefore a potential avenue for the escape of transgenes from GM crops. One approach for preventing and/or mitigating transgene flow is the production of trait linked pollen sterility. To evaluate the feasibility of generating pollen sterility lines for gene confinement and breeding purposes we tested the utility of a promoter (Zm13Pro from a maize pollen-specific gene (Zm13 for driving expression of the reporter gene GUS and the cytotoxic gene barnase in transgenic rice (Oryza sativa ssp. Japonica cv. Nipponbare as a monocot proxy for bioenergy grasses. This study demonstrates that the Zm13 promoter can drive pollen-specific expression in stably transformed rice and may be useful for gametophytic transgene confinement and breeding strategies by pollen sterility in food and bioenergy crops.

Cell based-gene delivery approaches for the treatment of spinal cord injury and neurodegenerative disorders.

Science.gov (United States)

Taha, Masoumeh Fakhr

2010-03-01

Cell based-gene delivery has provided an important therapeutic strategy for different disorders in the recent years. This strategy is based on the transplantation of genetically modified cells to express specific genes and to target the delivery of therapeutic factors, especially for the treatment of cancers and neurological, immunological, cardiovascular and heamatopoietic disorders. Although, preliminary reports are encouraging, and experimental studies indicate functionally and structurally improvements in the animal models of different disorders, universal application of this strategy for human diseases requires more evidence. There are a number of parameters that need to be evaluated, including the optimal cell source, the most effective gene/genes to be delivered, the optimal vector and method of gene delivery into the cells and the most efficient route for the delivery of genetically modified cells into the patient. Also, some obstacles have to be overcome, including the safety and usefulness of the approaches and the stability of the improvements. Here, recent studies concerning with the cell-based gene delivery for spinal cord injury and some neurodegenerative disorders such as amyotrophic lateral sclerosis, Parkinson's disease and Alzheimer's disease are briefly reviewed, and their exciting consequences are discussed.

Matching Real and Synthetic Panoramic Images Using a Variant of Geometric Hashing

Science.gov (United States)

Li-Chee-Ming, J.; Armenakis, C.

2017-05-01

This work demonstrates an approach to automatically initialize a visual model-based tracker, and recover from lost tracking, without prior camera pose information. These approaches are commonly referred to as tracking-by-detection. Previous tracking-by-detection techniques used either fiducials (i.e. landmarks or markers) or the object's texture. The main contribution of this work is the development of a tracking-by-detection algorithm that is based solely on natural geometric features. A variant of geometric hashing, a model-to-image registration algorithm, is proposed that searches for a matching panoramic image from a database of synthetic panoramic images captured in a 3D virtual environment. The approach identifies corresponding features between the matched panoramic images. The corresponding features are to be used in a photogrammetric space resection to estimate the camera pose. The experiments apply this algorithm to initialize a model-based tracker in an indoor environment using the 3D CAD model of the building.

The Matchmaker Exchange: a platform for rare disease gene discovery.

Science.gov (United States)

Philippakis, Anthony A; Azzariti, Danielle R; Beltran, Sergi; Brookes, Anthony J; Brownstein, Catherine A; Brudno, Michael; Brunner, Han G; Buske, Orion J; Carey, Knox; Doll, Cassie; Dumitriu, Sergiu; Dyke, Stephanie O M; den Dunnen, Johan T; Firth, Helen V; Gibbs, Richard A; Girdea, Marta; Gonzalez, Michael; Haendel, Melissa A; Hamosh, Ada; Holm, Ingrid A; Huang, Lijia; Hurles, Matthew E; Hutton, Ben; Krier, Joel B; Misyura, Andriy; Mungall, Christopher J; Paschall, Justin; Paten, Benedict; Robinson, Peter N; Schiettecatte, François; Sobreira, Nara L; Swaminathan, Ganesh J; Taschner, Peter E; Terry, Sharon F; Washington, Nicole L; Züchner, Stephan; Boycott, Kym M; Rehm, Heidi L

2015-10-01

There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for "the needle in a haystack" to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can "match" these cases to build evidence for causality. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. Three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow. © 2015 WILEY PERIODICALS, INC.

Exploration of structural stability in deleterious nsSNPs of the XPA gene: A molecular dynamics approach

Directory of Open Access Journals (Sweden)

N NagaSundaram

2011-01-01

Full Text Available Background: Distinguishing the deleterious from the massive number of non-functional nsSNPs that occur within a single genome is a considerable challenge in mutation research. In this approach, we have used the existing in silico methods to explore the mutation-structure-function relationship in the XPA gene. Materials and Methods: We used the Sorting Intolerant From Tolerant (SIFT, Polymorphism Phenotyping (PolyPhen, I-Mutant 2.0, and the Protein Analysis THrough Evolutionary Relationships methods to predict the effects of deleterious nsSNPs on protein function and evaluated the impact of mutation on protein stability by Molecular Dynamics simulations. Results: By comparing the scores of all the four in silico methods, nsSNP with an ID rs104894131 at position C108F was predicted to be highly deleterious. We extended our Molecular dynamics approach to gain insight into the impact of this non-synonymous polymorphism on structural changes that may affect the activity of the XPA gene. Conclusion: Based on the in silico methods score, potential energy, root-mean-square deviation, and root-mean-square fluctuation, we predict that deleterious nsSNP at position C108F would play a significant role in causing disease by the XPA gene. Our approach would present the application of in silico tools in understanding the functional variation from the perspective of structure, evolution, and phenotype.

Assessment of different virus-mediated approaches for retinal gene therapy of Usher 1B.

Science.gov (United States)

Lopes, Vanda S; Diemer, Tanja; Williams, David S

2014-01-01

Usher syndrome type 1B, which is characterized by congenital deafness and progressive retinal degeneration, is caused by the loss of the function of MYO7A. Prevention of the retinal degeneration should be possible by delivering functional MYO7A to retinal cells. Although this approach has been used successfully in clinical trials for Leber congenital amaurosis (LCA2), it remains a challenge for Usher 1B because of the large size of the MYO7A cDNA. Different viral vectors have been tested for use in MYO7A gene therapy. Here, we review approaches with lentiviruses, which can accommodate larger genes, as well as attempts to use adeno-associated virus (AAV), which has a smaller packaging capacity. In conclusion, both types of viral vector appear to be effective. Despite concerns about the ability of lentiviruses to access the photoreceptor cells, a phenotype of the photoreceptors of Myo7a-mutant mice can be corrected. And although MYO7A cDNA is significantly larger than the nominal carrying capacity of AAV, AAV-MYO7A in single vectors also corrected Myo7a-mutant phenotypes in photoreceptor and RPE cells. Interestingly, however, a dual AAV vector approach was found to be much less effective.

Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data

Directory of Open Access Journals (Sweden)

Simpson David

2006-03-01

Full Text Available Abstract Background Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfunction of the rod and cone photoreceptor cells. Development and maintenance of photoreceptors requires appropriate regulation of the many genes specifically or highly expressed in these cells. Over the last decades, different experimental approaches have been developed to identify photoreceptor enriched genes. Recent progress in RNA analysis technology has generated large amounts of gene expression data relevant to retinal development. This paper assesses a machine learning methodology for supporting the identification of photoreceptor enriched genes based on expression data. Results Based on the analysis of publicly-available gene expression data from the developing mouse retina generated by serial analysis of gene expression (SAGE, this paper presents a predictive methodology comprising several in silico models for detecting key complex features and relationships encoded in the data, which may be useful to distinguish genes in terms of their functional roles. In order to understand temporal patterns of photoreceptor gene expression during retinal development, a two-way cluster analysis was firstly performed. By clustering SAGE libraries, a hierarchical tree reflecting relationships between developmental stages was obtained. By clustering SAGE tags, a more comprehensive expression profile for photoreceptor cells was revealed. To demonstrate the usefulness of machine learning-based models in predicting functional associations from the SAGE data, three supervised classification models were compared. The results indicated that a relatively simple instance-based model (KStar model performed significantly better than relatively more complex algorithms, e.g. neural networks. To deal with the problem of functional class imbalance occurring in the dataset, two data re

Reverse-engineering of gene networks for regulating early blood development from single-cell measurements.

Science.gov (United States)

Wei, Jiangyong; Hu, Xiaohua; Zou, Xiufen; Tian, Tianhai

2017-12-28

Recent advances in omics technologies have raised great opportunities to study large-scale regulatory networks inside the cell. In addition, single-cell experiments have measured the gene and protein activities in a large number of cells under the same experimental conditions. However, a significant challenge in computational biology and bioinformatics is how to derive quantitative information from the single-cell observations and how to develop sophisticated mathematical models to describe the dynamic properties of regulatory networks using the derived quantitative information. This work designs an integrated approach to reverse-engineer gene networks for regulating early blood development based on singel-cell experimental observations. The wanderlust algorithm is initially used to develop the pseudo-trajectory for the activities of a number of genes. Since the gene expression data in the developed pseudo-trajectory show large fluctuations, we then use Gaussian process regression methods to smooth the gene express data in order to obtain pseudo-trajectories with much less fluctuations. The proposed integrated framework consists of both bioinformatics algorithms to reconstruct the regulatory network and mathematical models using differential equations to describe the dynamics of gene expression. The developed approach is applied to study the network regulating early blood cell development. A graphic model is constructed for a regulatory network with forty genes and a dynamic model using differential equations is developed for a network of nine genes. Numerical results suggests that the proposed model is able to match experimental data very well. We also examine the networks with more regulatory relations and numerical results show that more regulations may exist. We test the possibility of auto-regulation but numerical simulations do not support the positive auto-regulation. In addition, robustness is used as an importantly additional criterion to select candidate

A matched expansion approach to practical self-force calculations

International Nuclear Information System (INIS)

Anderson, Warren G; Wiseman, Alan G

2005-01-01

We discuss a practical method of computing the self-force on a particle moving through a curved spacetime. This method involves two expansions to calculate the self-force, one arising from the particle's immediate past and the other from the more distant past. The expansion in the immediate past is a covariant Taylor series and can be carried out for all geometries. The more distant expansion is a mode sum, and may be carried out in those cases where the wave equation for the field mediating the self-force admits a mode expansion of the solution. In particular, this method can be used to calculate the gravitational self-force for a particle of mass μ orbiting a black hole of mass M to order μ 2 , provided μ/M << 1. We discuss how to use these two expansions to construct a full self-force, and in particular investigate criteria for matching the two expansions. As with all methods of computing self-forces for particles moving in black hole spacetimes, one encounters considerable technical difficulty in applying this method; nevertheless, it appears that the convergence of each series is good enough that a practical implementation may be plausible

Analysis of insecticide resistance-related genes of the Carmine spider mite Tetranychus cinnabarinus based on a de novo assembled transcriptome.

Directory of Open Access Journals (Sweden)

Zhifeng Xu

Full Text Available The carmine spider mite (CSM, Tetranychus cinnabarinus, is an important pest mite in agriculture, because it can develop insecticide resistance easily. To gain valuable gene information and molecular basis for the future insecticide resistance study of CSM, the first transcriptome analysis of CSM was conducted. A total of 45,016 contigs and 25,519 unigenes were generated from the de novo transcriptome assembly, and 15,167 unigenes were annotated via BLAST querying against current databases, including nr, SwissProt, the Clusters of Orthologous Groups (COGs, Kyoto Encyclopedia of Genes and Genomes (KEGG and Gene Ontology (GO. Aligning the transcript to Tetranychus urticae genome, the 19255 (75.45% of the transcripts had significant (e-value <10-5 matches to T. urticae DNA genome, 19111 sequences matched to T. urticae proteome with an average protein length coverage of 42.55%. Core Eukaryotic Genes Mapping Approach (CEGMA analysis identified 435 core eukaryotic genes (CEGs in the CSM dataset corresponding to 95% coverage. Ten gene categories that relate to insecticide resistance in arthropod were generated from CSM transcriptome, including 53 P450-, 22 GSTs-, 23 CarEs-, 1 AChE-, 7 GluCls-, 9 nAChRs-, 8 GABA receptor-, 1 sodium channel-, 6 ATPase- and 12 Cyt b genes. We developed significant molecular resources for T. cinnabarinus putatively involved in insecticide resistance. The transcriptome assembly analysis will significantly facilitate our study on the mechanism of adapting environmental stress (including insecticide in CSM at the molecular level, and will be very important for developing new control strategies against this pest mite.

Time Series Analysis Using Geometric Template Matching.

Science.gov (United States)

Frank, Jordan; Mannor, Shie; Pineau, Joelle; Precup, Doina

2013-03-01

We present a novel framework for analyzing univariate time series data. At the heart of the approach is a versatile algorithm for measuring the similarity of two segments of time series called geometric template matching (GeTeM). First, we use GeTeM to compute a similarity measure for clustering and nearest-neighbor classification. Next, we present a semi-supervised learning algorithm that uses the similarity measure with hierarchical clustering in order to improve classification performance when unlabeled training data are available. Finally, we present a boosting framework called TDEBOOST, which uses an ensemble of GeTeM classifiers. TDEBOOST augments the traditional boosting approach with an additional step in which the features used as inputs to the classifier are adapted at each step to improve the training error. We empirically evaluate the proposed approaches on several datasets, such as accelerometer data collected from wearable sensors and ECG data.

An Approach for Predicting Essential Genes Using Multiple Homology Mapping and Machine Learning Algorithms.

Science.gov (United States)

Hua, Hong-Li; Zhang, Fa-Zhan; Labena, Abraham Alemayehu; Dong, Chuan; Jin, Yan-Ting; Guo, Feng-Biao

Investigation of essential genes is significant to comprehend the minimal gene sets of cell and discover potential drug targets. In this study, a novel approach based on multiple homology mapping and machine learning method was introduced to predict essential genes. We focused on 25 bacteria which have characterized essential genes. The predictions yielded the highest area under receiver operating characteristic (ROC) curve (AUC) of 0.9716 through tenfold cross-validation test. Proper features were utilized to construct models to make predictions in distantly related bacteria. The accuracy of predictions was evaluated via the consistency of predictions and known essential genes of target species. The highest AUC of 0.9552 and average AUC of 0.8314 were achieved when making predictions across organisms. An independent dataset from Synechococcus elongatus , which was released recently, was obtained for further assessment of the performance of our model. The AUC score of predictions is 0.7855, which is higher than other methods. This research presents that features obtained by homology mapping uniquely can achieve quite great or even better results than those integrated features. Meanwhile, the work indicates that machine learning-based method can assign more efficient weight coefficients than using empirical formula based on biological knowledge.

Mining a database of single amplified genomes from Red Sea brine pool extremophiles—improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA)

Science.gov (United States)

Grötzinger, Stefan W.; Alam, Intikhab; Ba Alawi, Wail; Bajic, Vladimir B.; Stingl, Ulrich; Eppinger, Jörg

2014-01-01

Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile's genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available

Mining a database of single amplified genomes from Red Sea brine pool extremophiles-improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA).

KAUST Repository

Grötzinger, Stefan W.

2014-04-07

Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile\\'s genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available

Best Practices for NPT Transit Matching

International Nuclear Information System (INIS)

Gilligan, Kimberly V.; Whitaker, J. Michael; Oakberg, John A.; Snow, Catherine

2016-01-01

Transit matching is the process for relating or matching reports of shipments and receipts submitted to the International Atomic Energy Agency (IAEA). Transit matching is a component used by the IAEA in drawing safeguards conclusions and performing investigative analysis. Transit matching is part of IAEA safeguards activities and the State evaluation process, and it is included in the annual Safeguards Implementation Report (SIR). Annually, the IAEA currently receives reports of ~900,000 nuclear material transactions, of which ~500,000 are for domestic and foreign transfers. Of these the IAEA software can automatically match (i.e., machine match) about 95% of the domestic transfers and 25% of the foreign transfers. Given the increasing demands upon IAEA resources, it is highly desirable for the machine-matching process to match as many transfers as possible. Researchers at Oak Ridge National Laboratory (ORNL) have conducted an investigation funded by the National Nuclear Security Administration through the Next Generation Safeguards Initiative to identify opportunities to strengthen IAEA transit matching. Successful matching, and more specifically machine matching, is contingent on quality data from the reporting States. In February 2016, ORNL hosted representatives from three States, the IAEA, and Euratom to share results from past studies and to discuss the processes, policies, and procedures associated with State reporting for transit matching. Drawing on each entity's experience and knowledge, ORNL developed a best practices document to be shared with the international safeguards community to strengthen transit matching. This paper shares the recommendations that resulted from this strategic meeting and the next steps being taken to strengthen transit matching.

Best Practices for NPT Transit Matching

Energy Technology Data Exchange (ETDEWEB)

Gilligan, Kimberly V. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Whitaker, J. Michael [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Oakberg, John A. [Tetra Tech, Inc., Oak Ridge, TN (United States); Snow, Catherine [Sno Consulting, LLC, Sandy, UT (United States)

2016-09-01

Transit matching is the process for relating or matching reports of shipments and receipts submitted to the International Atomic Energy Agency (IAEA). Transit matching is a component used by the IAEA in drawing safeguards conclusions and performing investigative analysis. Transit matching is part of IAEA safeguards activities and the State evaluation process, and it is included in the annual Safeguards Implementation Report (SIR). Annually, the IAEA currently receives reports of ~900,000 nuclear material transactions, of which ~500,000 are for domestic and foreign transfers. Of these the IAEA software can automatically match (i.e., machine match) about 95% of the domestic transfers and 25% of the foreign transfers. Given the increasing demands upon IAEA resources, it is highly desirable for the machine-matching process to match as many transfers as possible. Researchers at Oak Ridge National Laboratory (ORNL) have conducted an investigation funded by the National Nuclear Security Administration through the Next Generation Safeguards Initiative to identify opportunities to strengthen IAEA transit matching. Successful matching, and more specifically machine matching, is contingent on quality data from the reporting States. In February 2016, ORNL hosted representatives from three States, the IAEA, and Euratom to share results from past studies and to discuss the processes, policies, and procedures associated with State reporting for transit matching. Drawing on each entity's experience and knowledge, ORNL developed a best practices document to be shared with the international safeguards community to strengthen transit matching. This paper shares the recommendations that resulted from this strategic meeting and the next steps being taken to strengthen transit matching.

Influence of leukotriene gene polymorphisms on chronic rhinosinusitis

Directory of Open Access Journals (Sweden)

Duval Melanie

2008-03-01

Full Text Available Abstract Background Chronic rhinosinusitis (CRS is increasingly viewed as an inflammatory condition of the sinonasal mucosa interacting with bacteria and/or fungi. However, factors conferring susceptibility to disease remain unknown. Advances in genomics offer powerful tools to explore this disorder. The goal of this study was to evaluate the effect of single nucleotide polymorphisms (SNP on CRS in a panel of genes related to cysteinyl leukotriene metabolism. Methods Severe cases of CRS and postal code match controls were recruited prospectively. A total of 206 cases and 200 controls were available for the present study. Using a candidate gene approach, five genes related to cysteinyl leukotriene metabolism were assessed. For each gene, we selected the maximally informative set of common SNPs (tagSNPs using the European-derived (CEU HapMap dataset. These SNPs are in arachidonate 5-lipoxygenase (ALOX5, arachidonate 5-lipoxygenase-activating protein (ALOX5AP, leukotriene C4 synthase (LTC4S, cysteinyl leukotriene receptor 1 (CYSLTR1 and cysteinyl leukotriene receptor 2 (CYSLTR2 genes. Results A total of 59 SNPs were genotyped to capture the common genetic variations within these genes. Three SNPs located within the ALOX5, CYSLTR1 and ALOX5AP genes reached the nominal p-value threshold (p Conclusion While these initial results do not support that polymorphsims in genes assessed involved in the leukotriene pathways are contributing to the pathogenesis of CRS, this initial study was not powered to detect polymorphisms with relative risk of 2.0 or less, where we could expect many gene effects for complex diseases to occur. Thus, despite this lack of significant association noted in this study, we believe that validation with external populations and the use of better-powered studies in the future may allow more conclusive findings.

Imaging reporter gene for monitoring gene therapy

International Nuclear Information System (INIS)

Beco, V. de; Baillet, G.; Tamgac, F.; Tofighi, M.; Weinmann, P.; Vergote, J.; Moretti, J.L.; Tamgac, G.

2002-01-01

Scintigraphic images can be obtained to document gene function at cellular level. This approach is presented here and the use of a reporter gene to monitor gene therapy is described. Two main ways are presented: either the use of a reporter gene coding for an enzyme the action of which will be monitored by radiolabeled pro-drug, or a cellular receptor gene, the action of which is documented by a radio labeled cognate receptor ligand. (author)

A dual transcript-discovery approach to improve the delimitation of gene features from RNA-seq data in the chicken model

Directory of Open Access Journals (Sweden)

Mickael Orgeur

2018-01-01

Full Text Available The sequence of the chicken genome, like several other draft genome sequences, is presently not fully covered. Gaps, contigs assigned with low confidence and uncharacterized chromosomes result in gene fragmentation and imprecise gene annotation. Transcript abundance estimation from RNA sequencing (RNA-seq data relies on read quality, library complexity and expression normalization. In addition, the quality of the genome sequence used to map sequencing reads, and the gene annotation that defines gene features, must also be taken into account. A partially covered genome sequence causes the loss of sequencing reads from the mapping step, while an inaccurate definition of gene features induces imprecise read counts from the assignment step. Both steps can significantly bias interpretation of RNA-seq data. Here, we describe a dual transcript-discovery approach combining a genome-guided gene prediction and a de novo transcriptome assembly. This dual approach enabled us to increase the assignment rate of RNA-seq data by nearly 20% as compared to when using only the chicken reference annotation, contributing therefore to a more accurate estimation of transcript abundance. More generally, this strategy could be applied to any organism with partial genome sequence and/or lacking a manually-curated reference annotation in order to improve the accuracy of gene expression studies.

Matching tomographic IMRT fields with static photon fields

International Nuclear Information System (INIS)

Sethi, A.; Leybovich, L.; Dogan, N.; Emami, B.

2001-01-01

The matching of abutting radiation fields presents a challenging problem in radiation therapy. Due to sharp penumbra of linear accelerator beams, small (1-2 mm) errors in field positioning can lead to large (>30%) hot or cold spots in the abutment region. With head and neck immobilization devices (thermoplastic mask/aquaplast) an average setup error of 3 mm has been reported. Therefore hot or cold spots approaching 50% of the prescription dose may occur along the matchline. Although abutting radiation fields have been investigated for static fields, there is no reported study regarding matching of tomographic IMRT and static fields. Compared to static fields, the matching of tomographic IMRT fields with static fields is more complicated. Since IMRT and static fields are planned on separate treatment planning computers, the dose in the abutment region is not specified. In addition, commonly used techniques for matching fields, such as feathering of junctions, are not practical. We have developed a method that substantially reduces dose inhomogeneity in the abutment region. In this method, a 'buffer zone' around the matchline was created and was included as part of the target for both IMRT and static field plans. In both fields, a small dose gradient (≤3%/mm) in the buffer zone was created. In the IMRT plan, the buffer zone was divided into three sections with dose varying from 83% to 25% of prescription dose. The static field dose profile was modified using either a specially designed physical (hard) or a dynamic (soft) wedge. When these modified fields were matched, the combined dose in the abutment region varied by ≤10% in the presence of setup errors spanning 4 mm (±2 mm) when the hard wedge was used and 10 mm (±5 mm) with the soft wedge

Functional Genomic Approaches for the Study of Fetal/Placental Development in Swine with Special Emphasis on Imprinted Genes

Science.gov (United States)

The overall focus of this chapter will be the application of functional genomic approaches for the study of the imprinted gene family in swine. While there are varied definitions of “functional genomics” in general they focus on the application of genomic approaches such as DNA microarrays, single n...

OpWise: Operons aid the identification of differentially expressed genes in bacterial microarray experiments

Directory of Open Access Journals (Sweden)

Arkin Adam P

2006-01-01

Full Text Available Abstract Background Differentially expressed genes are typically identified by analyzing the variation between replicate measurements. These procedures implicitly assume that there are no systematic errors in the data even though several sources of systematic error are known. Results OpWise estimates the amount of systematic error in bacterial microarray data by assuming that genes in the same operon have matching expression patterns. OpWise then performs a Bayesian analysis of a linear model to estimate significance. In simulations, OpWise corrects for systematic error and is robust to deviations from its assumptions. In several bacterial data sets, significant amounts of systematic error are present, and replicate-based approaches overstate the confidence of the changers dramatically, while OpWise does not. Finally, OpWise can identify additional changers by assigning genes higher confidence if they are consistent with other genes in the same operon. Conclusion Although microarray data can contain large amounts of systematic error, operons provide an external standard and allow for reasonable estimates of significance. OpWise is available at http://microbesonline.org/OpWise.

Radargrammetric DSM generation in mountainous areas through adaptive-window least squares matching constrained by enhanced epipolar geometry

Science.gov (United States)

Dong, Yuting; Zhang, Lu; Balz, Timo; Luo, Heng; Liao, Mingsheng

2018-03-01

Radargrammetry is a powerful tool to construct digital surface models (DSMs) especially in heavily vegetated and mountainous areas where SAR interferometry (InSAR) technology suffers from decorrelation problems. In radargrammetry, the most challenging step is to produce an accurate disparity map through massive image matching, from which terrain height information can be derived using a rigorous sensor orientation model. However, precise stereoscopic SAR (StereoSAR) image matching is a very difficult task in mountainous areas due to the presence of speckle noise and dissimilar geometric/radiometric distortions. In this article, an adaptive-window least squares matching (AW-LSM) approach with an enhanced epipolar geometric constraint is proposed to robustly identify homologous points after compensation for radiometric discrepancies and geometric distortions. The matching procedure consists of two stages. In the first stage, the right image is re-projected into the left image space to generate epipolar images using rigorous imaging geometries enhanced with elevation information extracted from the prior DEM data e.g. SRTM DEM instead of the mean height of the mapped area. Consequently, the dissimilarities in geometric distortions between the left and right images are largely reduced, and the residual disparity corresponds to the height difference between true ground surface and the prior DEM. In the second stage, massive per-pixel matching between StereoSAR epipolar images identifies the residual disparity. To ensure the reliability and accuracy of the matching results, we develop an iterative matching scheme in which the classic cross correlation matching is used to obtain initial results, followed by the least squares matching (LSM) to refine the matching results. An adaptively resizing search window strategy is adopted during the dense matching step to help find right matching points. The feasibility and effectiveness of the proposed approach is demonstrated using

The Brown-Servranckx matching transformer for simultaneous RFQ to DTL H+ and H- matching

International Nuclear Information System (INIS)

Wadlinger, E.A.; Garnett, R.W.

1996-01-01

The issue involved in the simultaneous matching of H + and H - beams between an RFQ and DTL lies in the fact that both beams experience the same electric-field forces at a given position in the RFQ. Hence, the two beams are focused to the same correlation. However, matching to a DTL requires correlation of the opposite sign. The Brown-Servranckx quarter-wave (λ / 4) matching transformer system, which requires four quadrupoles, provides a method to simultaneously match H + and H - beams between an RFQ and a DTL. The method requires the use of a special RFQ section to obtain the Twiss parameter conditions β x = β y and α x = α y = 0 at the exit of the RFQ. This matching between the RFQ and DTL is described. (author)

The Brown-Servranckx matching transformer for simultaneous RFQ to DTL H+ and H- matching

International Nuclear Information System (INIS)

Wadlinger, E.A.; Garnett, R.W.

1996-01-01

The issue involved in simultaneous matching of H + and H - beams between an RFQ and DTL lies in the fact that both beams experience the same electric-field forces at a given position in the RFQ. Hence, the two beams are focused to the same correlation. However, matching to a DTL requires correlation of the opposite sign. The Brown-Servranckx quarter-wave (λ/4) matching transformer system, which requires four quadrupoles, provides a method to simultaneously match H + and H - beams between an RFQ and a DTL. The method requires the use of a special RFQ section to obtain the Twiss parameter conditions β x =β y and α x =α y =0 at the exit of the RFQ. This matching between the RFQ and DTL is described

A new template matching method based on contour information

Science.gov (United States)

Cai, Huiying; Zhu, Feng; Wu, Qingxiao; Li, Sicong

2014-11-01

Template matching is a significant approach in machine vision due to its effectiveness and robustness. However, most of the template matching methods are so time consuming that they can't be used to many real time applications. The closed contour matching method is a popular kind of template matching methods. This paper presents a new closed contour template matching method which is suitable for two dimensional objects. Coarse-to-fine searching strategy is used to improve the matching efficiency and a partial computation elimination scheme is proposed to further speed up the searching process. The method consists of offline model construction and online matching. In the process of model construction, triples and distance image are obtained from the template image. A certain number of triples which are composed by three points are created from the contour information that is extracted from the template image. The rule to select the three points is that the template contour is divided equally into three parts by these points. The distance image is obtained here by distance transform. Each point on the distance image represents the nearest distance between current point and the points on the template contour. During the process of matching, triples of the searching image are created with the same rule as the triples of the model. Through the similarity that is invariant to rotation, translation and scaling between triangles, the triples corresponding to the triples of the model are found. Then we can obtain the initial RST (rotation, translation and scaling) parameters mapping the searching contour to the template contour. In order to speed up the searching process, the points on the searching contour are sampled to reduce the number of the triples. To verify the RST parameters, the searching contour is projected into the distance image, and the mean distance can be computed rapidly by simple operations of addition and multiplication. In the fine searching process

Discovering genes underlying QTL

Energy Technology Data Exchange (ETDEWEB)

Vanavichit, Apichart [Kasetsart University, Kamphaengsaen, Nakorn Pathom (Thailand)

2002-02-01

A map-based approach has allowed scientists to discover few genes at a time. In addition, the reproductive barrier between cultivated rice and wild relatives has prevented us from utilizing the germ plasm by a map-based approach. Most genetic traits important to agriculture or human diseases are manifested as observable, quantitative phenotypes called Quantitative Trait Loci (QTL). In many instances, the complexity of the phenotype/genotype interaction and the general lack of clearly identifiable gene products render the direct molecular cloning approach ineffective, thus additional strategies like genome mapping are required to identify the QTL in question. Genome mapping requires no prior knowledge of the gene function, but utilizes statistical methods to identify the most likely gene location. To completely characterize genes of interest, the initially mapped region of a gene location will have to be narrowed down to a size that is suitable for cloning and sequencing. Strategies for gene identification within the critical region have to be applied after the sequencing of a potentially large clone or set of clones that contains this gene(s). Tremendous success of positional cloning has been shown for cloning many genes responsible for human diseases, including cystic fibrosis and muscular dystrophy as well as plant disease resistance genes. Genome and QTL mapping, positional cloning: the pre-genomics era, comparative approaches to gene identification, and positional cloning: the genomics era are discussed in the report. (M. Suetake)

A new approach to enhance the performance of decision tree for classifying gene expression data.

Science.gov (United States)

Hassan, Md; Kotagiri, Ramamohanarao

2013-12-20

Gene expression data classification is a challenging task due to the large dimensionality and very small number of samples. Decision tree is one of the popular machine learning approaches to address such classification problems. However, the existing decision tree algorithms use a single gene feature at each node to split the data into its child nodes and hence might suffer from poor performance specially when classifying gene expression dataset. By using a new decision tree algorithm where, each node of the tree consists of more than one gene, we enhance the classification performance of traditional decision tree classifiers. Our method selects suitable genes that are combined using a linear function to form a derived composite feature. To determine the structure of the tree we use the area under the Receiver Operating Characteristics curve (AUC). Experimental analysis demonstrates higher classification accuracy using the new decision tree compared to the other existing decision trees in literature. We experimentally compare the effect of our scheme against other well known decision tree techniques. Experiments show that our algorithm can substantially boost the classification performance of the decision tree.

Matched-Filter Thermography

Directory of Open Access Journals (Sweden)

Nima Tabatabaei

2018-04-01

Full Text Available Conventional infrared thermography techniques, including pulsed and lock-in thermography, have shown great potential for non-destructive evaluation of broad spectrum of materials, spanning from metals to polymers to biological tissues. However, performance of these techniques is often limited due to the diffuse nature of thermal wave fields, resulting in an inherent compromise between inspection depth and depth resolution. Recently, matched-filter thermography has been introduced as a means for overcoming this classic limitation to enable depth-resolved subsurface thermal imaging and improving axial/depth resolution. This paper reviews the basic principles and experimental results of matched-filter thermography: first, mathematical and signal processing concepts related to matched-fileting and pulse compression are discussed. Next, theoretical modeling of thermal-wave responses to matched-filter thermography using two categories of pulse compression techniques (linear frequency modulation and binary phase coding are reviewed. Key experimental results from literature demonstrating the maintenance of axial resolution while inspecting deep into opaque and turbid media are also presented and discussed. Finally, the concept of thermal coherence tomography for deconvolution of thermal responses of axially superposed sources and creation of depth-selective images in a diffusion-wave field is reviewed.

Genetic Approaches to Study Meiosis and Meiosis-Specific Gene Expression in Saccharomyces cerevisiae.

Science.gov (United States)

Kassir, Yona; Stuart, David T

2017-01-01

The budding yeast Saccharomyces cerevisiae has a long history as a model organism for studies of meiosis and the cell cycle. The popularity of this yeast as a model is in large part due to the variety of genetic and cytological approaches that can be effectively performed with the cells. Cultures of the cells can be induced to synchronously progress through meiosis and sporulation allowing large-scale gene expression and biochemical studies to be performed. Additionally, the spore tetrads resulting from meiosis make it possible to characterize the haploid products of meiosis allowing investigation of meiotic recombination and chromosome segregation. Here we describe genetic methods for analysis progression of S. cerevisiae through meiosis and sporulation with an emphasis on strategies for the genetic analysis of regulators of meiosis-specific genes.

MATCHING AERIAL IMAGES TO 3D BUILDING MODELS BASED ON CONTEXT-BASED GEOMETRIC HASHING

Directory of Open Access Journals (Sweden)

J. Jung

2016-06-01

Full Text Available In this paper, a new model-to-image framework to automatically align a single airborne image with existing 3D building models using geometric hashing is proposed. As a prerequisite process for various applications such as data fusion, object tracking, change detection and texture mapping, the proposed registration method is used for determining accurate exterior orientation parameters (EOPs of a single image. This model-to-image matching process consists of three steps: 1 feature extraction, 2 similarity measure and matching, and 3 adjustment of EOPs of a single image. For feature extraction, we proposed two types of matching cues, edged corner points representing the saliency of building corner points with associated edges and contextual relations among the edged corner points within an individual roof. These matching features are extracted from both 3D building and a single airborne image. A set of matched corners are found with given proximity measure through geometric hashing and optimal matches are then finally determined by maximizing the matching cost encoding contextual similarity between matching candidates. Final matched corners are used for adjusting EOPs of the single airborne image by the least square method based on co-linearity equations. The result shows that acceptable accuracy of single image's EOP can be achievable by the proposed registration approach as an alternative to labour-intensive manual registration process.

The causal effect of restrictive bank lending on employment growth: A matching approach

OpenAIRE

Kleemann, Michael; Wiegand, Manuel

2013-01-01

Does restrictive bank lending cause lower employment growth at the firm-level or does it reflect firm characteristics that drive the deterioration of employment figures? Applying propensity score matching, we estimate the treatment effect of restrictive bank lending on employment growth. Combining balance sheet information and survey data on a firm's current and expected future business situation, we rule out the impact of firm heterogeneity. We find that credit constraints have a significant...

Spatial competition with intermediated matching

NARCIS (Netherlands)

van Raalte, C.L.J.P.; Webers, H.M.

1995-01-01

This paper analyzes the spatial competition in commission fees between two match makers. These match makers serve as middlemen between buyers and sellers who are located uniformly on a circle. The profits of the match makers are determined by their respective market sizes. A limited willingness to

An ensemble method to predict target genes and pathways in uveal melanoma

Directory of Open Access Journals (Sweden)

Wei Chao

2018-04-01

Full Text Available This work proposes to predict target genes and pathways for uveal melanoma (UM based on an ensemble method and pathway analyses. Methods: The ensemble method integrated a correlation method (Pearson correlation coefficient, PCC, a causal inference method (IDA and a regression method (Lasso utilizing the Borda count election method. Subsequently, to validate the performance of PIL method, comparisons between confirmed database and predicted miRNA targets were performed. Ultimately, pathway enrichment analysis was conducted on target genes in top 1000 miRNA-mRNA interactions to identify target pathways for UM patients. Results: Thirty eight of the predicted interactions were matched with the confirmed interactions, indicating that the ensemble method was a suitable and feasible approach to predict miRNA targets. We obtained 50 seed miRNA-mRNA interactions of UM patients and extracted target genes from these interactions, such as ASPG, BSDC1 and C4BP. The 601 target genes in top 1,000 miRNA-mRNA interactions were enriched in 12 target pathways, of which Phototransduction was the most significant one. Conclusion: The target genes and pathways might provide a new way to reveal the molecular mechanism of UM and give hand for target treatments and preventions of this malignant tumor.

MBR-SIFT: A mirror reflected invariant feature descriptor using a binary representation for image matching.

Directory of Open Access Journals (Sweden)

Mingzhe Su

Full Text Available The traditional scale invariant feature transform (SIFT method can extract distinctive features for image matching. However, it is extremely time-consuming in SIFT matching because of the use of the Euclidean distance measure. Recently, many binary SIFT (BSIFT methods have been developed to improve matching efficiency; however, none of them is invariant to mirror reflection. To address these problems, in this paper, we present a horizontal or vertical mirror reflection invariant binary descriptor named MBR-SIFT, in addition to a novel image matching approach. First, 16 cells in the local region around the SIFT keypoint are reorganized, and then the 128-dimensional vector of the SIFT descriptor is transformed into a reconstructed vector according to eight directions. Finally, the MBR-SIFT descriptor is obtained after binarization and reverse coding. To improve the matching speed and accuracy, a fast matching algorithm that includes a coarse-to-fine two-step matching strategy in addition to two similarity measures for the MBR-SIFT descriptor are proposed. Experimental results on the UKBench dataset show that the proposed method not only solves the problem of mirror reflection, but also ensures desirable matching accuracy and speed.

MBR-SIFT: A mirror reflected invariant feature descriptor using a binary representation for image matching.

Science.gov (United States)

Su, Mingzhe; Ma, Yan; Zhang, Xiangfen; Wang, Yan; Zhang, Yuping

2017-01-01

The traditional scale invariant feature transform (SIFT) method can extract distinctive features for image matching. However, it is extremely time-consuming in SIFT matching because of the use of the Euclidean distance measure. Recently, many binary SIFT (BSIFT) methods have been developed to improve matching efficiency; however, none of them is invariant to mirror reflection. To address these problems, in this paper, we present a horizontal or vertical mirror reflection invariant binary descriptor named MBR-SIFT, in addition to a novel image matching approach. First, 16 cells in the local region around the SIFT keypoint are reorganized, and then the 128-dimensional vector of the SIFT descriptor is transformed into a reconstructed vector according to eight directions. Finally, the MBR-SIFT descriptor is obtained after binarization and reverse coding. To improve the matching speed and accuracy, a fast matching algorithm that includes a coarse-to-fine two-step matching strategy in addition to two similarity measures for the MBR-SIFT descriptor are proposed. Experimental results on the UKBench dataset show that the proposed method not only solves the problem of mirror reflection, but also ensures desirable matching accuracy and speed.

Hierarchical Matching and Regression with Application to Photometric Redshift Estimation

Science.gov (United States)

Murtagh, Fionn

2017-06-01

This work emphasizes that heterogeneity, diversity, discontinuity, and discreteness in data is to be exploited in classification and regression problems. A global a priori model may not be desirable. For data analytics in cosmology, this is motivated by the variety of cosmological objects such as elliptical, spiral, active, and merging galaxies at a wide range of redshifts. Our aim is matching and similarity-based analytics that takes account of discrete relationships in the data. The information structure of the data is represented by a hierarchy or tree where the branch structure, rather than just the proximity, is important. The representation is related to p-adic number theory. The clustering or binning of the data values, related to the precision of the measurements, has a central role in this methodology. If used for regression, our approach is a method of cluster-wise regression, generalizing nearest neighbour regression. Both to exemplify this analytics approach, and to demonstrate computational benefits, we address the well-known photometric redshift or `photo-z' problem, seeking to match Sloan Digital Sky Survey (SDSS) spectroscopic and photometric redshifts.

The role of imprinted genes in humans

OpenAIRE

Ishida, Miho; Moore, Gudrun E.

2013-01-01

Detailed comprehensive molecular analysis using families and multiple matched tissues is essential to determine whether imprinted genes have a functional role in humans. See research article: http://genomebiology.com/2011/12/3/R25

Molecular genetic approach to human meningioma: loss of genes on chromosome 22

International Nuclear Information System (INIS)

Seizinger, B.R.; De La Monte, S.; Atkins, L.; Gusella, J.F.; Martuza, R.L.

1987-01-01

A molecular genetic approach employing polymorphic DNA markers has been used to investigate the role of chromosomal aberrations in meningioma, one of the most common tumors of the human nervous system. Comparison of the alleles detected by DNA markers in tumor DNA versus DNA from normal tissue revealed chromosomal alterations present in primary surgical specimens. In agreement with cytogenetic studies of cultured meningiomas, the most frequent alteration detected was loss of heterozygosity on chromosome 22. Forty of 51 patients were constitutionally heterozygous for at least one chromosome 22 DNA marker. Seventeen of the 40 constitutionally heterozygotic patients (43%) displayed hemizygosity for the corresponding marker in their meningioma tumor tissues. Loss of heterozygosity was also detected at a significantly lower frequency for markers on several other autosomes. In view of the striking association between acoustic neuroma and meningioma in bilateral acoustic neurofibromatosis and the discovery that acoustic neuromas display specific loss of genes on chromosome 22, the authors propose that a common mechanism involving chromosome 22 is operative in the development of both tumor types. Fine-structure mapping to reveal partial deletions in meningiomas may provide the means to clone and characterize a gene (or genes) of importance for tumorigenesis in this and possibly other clinically associated tumors of the human nervous system

Complexity Triggered by Economic Globalisation— The Issue of On-Line Betting-Related Match Fixing

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Wladimir Andreff

2017-02-01

Full Text Available Complexity in mainstream economics consists in high intermediary consumption of mathematics. A new approach to complexity economics dwells upon path-dependent global systems; their emergence and evolving organisation. The focus here is on the complexity of the real economic world due to globalisation. On-line betting related match-fixing is a case in point about which the article presents non-exhaustive empirical evidence and shows how it is analysed with the standard model of the economics of crime. There is no room for complexity in such an individualistic approach to corrupt behaviour applied to bet-related fixes. A more complex model is sketched based on interactions between a global (though underground market for fixes and the actual partly legal, partly illegal global sport betting market. These interactions exhibit how complex is the issue of combating betting-related match fixing. Reviewing those major policies envisaged for containing the latter—prohibition; sanctions; regulation; privatisation (betting rights—the article opts for a global ‘Sportbettobin’ tax on sport betting gains; in the same vein as the famous Tobin tax on international capital transfers. The novelty in this approach is a variable (increasing rate applied to increasing tranches of taxation (gains which should dry up the worst cases of on-line bettingrelated match fixing.

Sparse reconstruction using distribution agnostic bayesian matching pursuit

KAUST Repository

Masood, Mudassir

2013-11-01

A fast matching pursuit method using a Bayesian approach is introduced for sparse signal recovery. This method performs Bayesian estimates of sparse signals even when the signal prior is non-Gaussian or unknown. It is agnostic on signal statistics and utilizes a priori statistics of additive noise and the sparsity rate of the signal, which are shown to be easily estimated from data if not available. The method utilizes a greedy approach and order-recursive updates of its metrics to find the most dominant sparse supports to determine the approximate minimum mean-square error (MMSE) estimate of the sparse signal. Simulation results demonstrate the power and robustness of our proposed estimator. © 2013 IEEE.

Soccer Matches as Experiments - How Often Does the 'Best' Team Win?

Science.gov (United States)

Skinner, Gerald K.; Freeman, G. H.

2009-01-01

Models in which the number of goals scored by a team in a soccer match follow a Poisson distribution or a closely related one, have been widely discussed. We here consider a soccer match as an experiment to assess which of two teams is superior and examine the probability that the outcome of the experiment (match) truly represents the relative abilities of the two teams. Given a final score it is possible by using a Bayesian approach to quantify the probability that it was or was not the case that the best team won. For typical scores, the probability of a misleading result is significant. Modifying the rules of the game to increase thc typical number of goals scored would improve the situation, but a level of confidence that would normally be regarded as satisfactory could not be obtained unless the character of the game were radically changed.

Copy number variation analysis of matched ovarian primary tumors and peritoneal metastasis.

Directory of Open Access Journals (Sweden)

Joel A Malek

Full Text Available Ovarian cancer is the most deadly gynecological cancer. The high rate of mortality is due to the large tumor burden with extensive metastatic lesion of the abdominal cavity. Despite initial chemosensitivity and improved surgical procedures, abdominal recurrence remains an issue and results in patients' poor prognosis. Transcriptomic and genetic studies have revealed significant genome pathologies in the primary tumors and yielded important information regarding carcinogenesis. There are, however, few studies on genetic alterations and their consequences in peritoneal metastatic tumors when compared to their matched ovarian primary tumors. We used high-density SNP arrays to investigate copy number variations in matched primary and metastatic ovarian cancer from 9 patients. Here we show that copy number variations acquired by ovarian tumors are significantly different between matched primary and metastatic tumors and these are likely due to different functional requirements. We show that these copy number variations clearly differentially affect specific pathways including the JAK/STAT and cytokine signaling pathways. While many have shown complex involvement of cytokines in the ovarian cancer environment we provide evidence that ovarian tumors have specific copy number variation differences in many of these genes.

Nature versus nurture: A systematic approach to elucidate gene-environment interactions in the development of myopic refractive errors.

Science.gov (United States)

Miraldi Utz, Virginia

2017-01-01

Myopia is the most common eye disorder and major cause of visual impairment worldwide. As the incidence of myopia continues to rise, the need to further understand the complex roles of molecular and environmental factors controlling variation in refractive error is of increasing importance. Tkatchenko and colleagues applied a systematic approach using a combination of gene set enrichment analysis, genome-wide association studies, and functional analysis of a murine model to identify a myopia susceptibility gene, APLP2. Differential expression of refractive error was associated with time spent reading for those with low frequency variants in this gene. This provides support for the longstanding hypothesis of gene-environment interactions in refractive error development.

Looking into flowering time in almond (Prunus dulcis (Mill) D. A. Webb): the candidate gene approach.

Science.gov (United States)

Silva, C; Garcia-Mas, J; Sánchez, A M; Arús, P; Oliveira, M M

2005-03-01

Blooming time is one of the most important agronomic traits in almond. Biochemical and molecular events underlying flowering regulation must be understood before methods to stimulate late flowering can be developed. Attempts to elucidate the genetic control of this process have led to the identification of a major gene (Lb) and quantitative trait loci (QTLs) linked to observed phenotypic differences, but although this gene and these QTLs have been placed on the Prunus reference genetic map, their sequences and specific functions remain unknown. The aim of our investigation was to associate these loci with known genes using a candidate gene approach. Two almond cDNAs and eight Prunus expressed sequence tags were selected as candidate genes (CGs) since their sequences were highly identical to those of flowering regulatory genes characterized in other species. The CGs were amplified from both parental lines of the mapping population using specific primers. Sequence comparison revealed DNA polymorphisms between the parental lines, mainly of the single nucleotide type. Polymorphisms were used to develop co-dominant cleaved amplified polymorphic sequence markers or length polymorphisms based on insertion/deletion events for mapping the candidate genes on the Prunus reference map. Ten candidate genes were assigned to six linkage groups in the Prunus genome. The positions of two of these were compatible with the regions where two QTLs for blooming time were detected. One additional candidate was localized close to the position of the Evergrowing gene, which determines a non-deciduous behaviour in peach.

Mining a database of single amplified genomes from Red Sea brine pool extremophiles – Improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA

Directory of Open Access Journals (Sweden)

Stefan Wolfgang Grötzinger

2014-04-01

Full Text Available Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs and poor homology of novel extremophile’s genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the INDIGO data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes may translate into false positives when searching for specific functions. The Profile & Pattern Matching (PPM strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO-terms (which represent enzyme function profiles and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern. The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2,577 E.C. numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from 6 different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter and PROSITE IDs (pattern filter. Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns are present. Scripts for annotation, as well as for the PPM algorithm, are available through the INDIGO website.

Stinging Insect Matching Game

Science.gov (United States)

... for Kids ▸ Stinging Insect Matching Game Share | Stinging Insect Matching Game Stinging insects can ruin summer fun for those who are ... the difference between the different kinds of stinging insects in order to keep your summer safe and ...

Multiple Constraints Based Robust Matching of Poor-Texture Close-Range Images for Monitoring a Simulated Landslide

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Gang Qiao

2016-05-01

Full Text Available Landslides are one of the most destructive geo-hazards that can bring about great threats to both human lives and infrastructures. Landslide monitoring has been always a research hotspot. In particular, landslide simulation experimentation is an effective tool in landslide research to obtain critical parameters that help understand the mechanism and evaluate the triggering and controlling factors of slope failure. Compared with other traditional geotechnical monitoring approaches, the close-range photogrammetry technique shows potential in tracking and recording the 3D surface deformation and failure processes. In such cases, image matching usually plays a critical role in stereo image processing for the 3D geometric reconstruction. However, the complex imaging conditions such as rainfall, mass movement, illumination, and ponding will reduce the texture quality of the stereo images, bringing about difficulties in the image matching process and resulting in very sparse matches. To address this problem, this paper presents a multiple-constraints based robust image matching approach for poor-texture close-range images particularly useful in monitoring a simulated landslide. The Scale Invariant Feature Transform (SIFT algorithm was first applied to the stereo images for generation of scale-invariate feature points, followed by a two-step matching process: feature-based image matching and area-based image matching. In the first feature-based matching step, the triangulation process was performed based on the SIFT matches filtered by the Fundamental Matrix (FM and a robust checking procedure, to serve as the basic constraints for feature-based iterated matching of all the non-matched SIFT-derived feature points inside each triangle. In the following area-based image-matching step, the corresponding points of the non-matched features in each triangle of the master image were predicted in the homologous triangle of the searching image by using geometric

A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes

Science.gov (United States)

Seo, Minseok; Shin, Su-kyung; Kwon, Eun-Young; Kim, Sung-Eun; Bae, Yun-Jung; Lee, Seungyeoun; Sung, Mi-Kyung; Choi, Myung-Sook; Park, Taesung

2016-01-01

Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs) among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis. Phenotype association analysis provides a list of phenotype-associated genes (PAGs). However, it is sometimes necessary to identify genes that are both DEGs and PAGs. We consider the joint identification of DEGs and PAGs in microarray data analyses. The first approach we used was a naïve approach that detects DEGs and PAGs separately and then identifies the genes in an intersection of the list of PAGs and DEGs. The second approach we considered was a hierarchical approach that detects DEGs first and then chooses PAGs from among the DEGs or vice versa. In this study, we propose a new model-based approach for the joint identification of DEGs and PAGs. Unlike the previous two-step approaches, the proposed method identifies genes simultaneously that are DEGs and PAGs. This method uses standard regression models but adopts different null hypothesis from ordinary regression models, which allows us to perform joint identification in one-step. The proposed model-based methods were evaluated using experimental data and simulation studies. The proposed methods were used to analyze a microarray experiment in which the main interest lies in detecting genes that are both DEGs and PAGs, where DEGs are identified between two diet groups and PAGs are associated with four phenotypes reflecting the expression of leptin, adiponectin, insulin-like growth factor 1, and insulin. Model-based approaches provided a larger number of genes, which are both DEGs and PAGs, than other methods. Simulation studies showed that they have more power than other methods. Through analysis of

A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes.

Directory of Open Access Journals (Sweden)

Samuel Sunghwan Cho

Full Text Available Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis. Phenotype association analysis provides a list of phenotype-associated genes (PAGs. However, it is sometimes necessary to identify genes that are both DEGs and PAGs. We consider the joint identification of DEGs and PAGs in microarray data analyses. The first approach we used was a naïve approach that detects DEGs and PAGs separately and then identifies the genes in an intersection of the list of PAGs and DEGs. The second approach we considered was a hierarchical approach that detects DEGs first and then chooses PAGs from among the DEGs or vice versa. In this study, we propose a new model-based approach for the joint identification of DEGs and PAGs. Unlike the previous two-step approaches, the proposed method identifies genes simultaneously that are DEGs and PAGs. This method uses standard regression models but adopts different null hypothesis from ordinary regression models, which allows us to perform joint identification in one-step. The proposed model-based methods were evaluated using experimental data and simulation studies. The proposed methods were used to analyze a microarray experiment in which the main interest lies in detecting genes that are both DEGs and PAGs, where DEGs are identified between two diet groups and PAGs are associated with four phenotypes reflecting the expression of leptin, adiponectin, insulin-like growth factor 1, and insulin. Model-based approaches provided a larger number of genes, which are both DEGs and PAGs, than other methods. Simulation studies showed that they have more power than other methods

Mobile Visual Search Based on Histogram Matching and Zone Weight Learning

Science.gov (United States)

Zhu, Chuang; Tao, Li; Yang, Fan; Lu, Tao; Jia, Huizhu; Xie, Xiaodong

2018-01-01

In this paper, we propose a novel image retrieval algorithm for mobile visual search. At first, a short visual codebook is generated based on the descriptor database to represent the statistical information of the dataset. Then, an accurate local descriptor similarity score is computed by merging the tf-idf weighted histogram matching and the weighting strategy in compact descriptors for visual search (CDVS). At last, both the global descriptor matching score and the local descriptor similarity score are summed up to rerank the retrieval results according to the learned zone weights. The results show that the proposed approach outperforms the state-of-the-art image retrieval method in CDVS.

High-order FDTD methods via derivative matching for Maxwell's equations with material interfaces

International Nuclear Information System (INIS)

Zhao Shan; Wei, G.W.

2004-01-01

This paper introduces a series of novel hierarchical implicit derivative matching methods to restore the accuracy of high-order finite-difference time-domain (FDTD) schemes of computational electromagnetics (CEM) with material interfaces in one (1D) and two spatial dimensions (2D). By making use of fictitious points, systematic approaches are proposed to locally enforce the physical jump conditions at material interfaces in a preprocessing stage, to arbitrarily high orders of accuracy in principle. While often limited by numerical instability, orders up to 16 and 12 are achieved, respectively, in 1D and 2D. Detailed stability analyses are presented for the present approach to examine the upper limit in constructing embedded FDTD methods. As natural generalizations of the high-order FDTD schemes, the proposed derivative matching methods automatically reduce to the standard FDTD schemes when the material interfaces are absent. An interesting feature of the present approach is that it encompasses a variety of schemes of different orders in a single code. Another feature of the present approach is that it can be robustly implemented with other high accuracy time-domain approaches, such as the multiresolution time-domain method and the local spectral time-domain method, to cope with material interfaces. Numerical experiments on both 1D and 2D problems are carried out to test the convergence, examine the stability, access the efficiency, and explore the limitation of the proposed methods. It is found that operating at their best capacity, the proposed high-order schemes could be over 2000 times more efficient than their fourth-order versions in 2D. In conclusion, the present work indicates that the proposed hierarchical derivative matching methods might lead to practical high-order schemes for numerical solution of time-domain Maxwell's equations with material interfaces

Robust matching for voice recognition

Science.gov (United States)

Higgins, Alan; Bahler, L.; Porter, J.; Blais, P.

1994-10-01

This paper describes an automated method of comparing a voice sample of an unknown individual with samples from known speakers in order to establish or verify the individual's identity. The method is based on a statistical pattern matching approach that employs a simple training procedure, requires no human intervention (transcription, work or phonetic marketing, etc.), and makes no assumptions regarding the expected form of the statistical distributions of the observations. The content of the speech material (vocabulary, grammar, etc.) is not assumed to be constrained in any way. An algorithm is described which incorporates frame pruning and channel equalization processes designed to achieve robust performance with reasonable computational resources. An experimental implementation demonstrating the feasibility of the concept is described.

Establishing gene models from the Pinus pinaster genome using gene capture and BAC sequencing.

Science.gov (United States)

Seoane-Zonjic, Pedro; Cañas, Rafael A; Bautista, Rocío; Gómez-Maldonado, Josefa; Arrillaga, Isabel; Fernández-Pozo, Noé; Claros, M Gonzalo; Cánovas, Francisco M; Ávila, Concepción

2016-02-27

In the era of DNA throughput sequencing, assembling and understanding gymnosperm mega-genomes remains a challenge. Although drafts of three conifer genomes have recently been published, this number is too low to understand the full complexity of conifer genomes. Using techniques focused on specific genes, gene models can be established that can aid in the assembly of gene-rich regions, and this information can be used to compare genomes and understand functional evolution. In this study, gene capture technology combined with BAC isolation and sequencing was used as an experimental approach to establish de novo gene structures without a reference genome. Probes were designed for 866 maritime pine transcripts to sequence genes captured from genomic DNA. The gene models were constructed using GeneAssembler, a new bioinformatic pipeline, which reconstructed over 82% of the gene structures, and a high proportion (85%) of the captured gene models contained sequences from the promoter regulatory region. In a parallel experiment, the P. pinaster BAC library was screened to isolate clones containing genes whose cDNA sequence were already available. BAC clones containing the asparagine synthetase, sucrose synthase and xyloglucan endotransglycosylase gene sequences were isolated and used in this study. The gene models derived from the gene capture approach were compared with the genomic sequences derived from the BAC clones. This combined approach is a particularly efficient way to capture the genomic structures of gene families with a small number of members. The experimental approach used in this study is a valuable combined technique to study genomic gene structures in species for which a reference genome is unavailable. It can be used to establish exon/intron boundaries in unknown gene structures, to reconstruct incomplete genes and to obtain promoter sequences that can be used for transcriptional studies. A bioinformatics algorithm (GeneAssembler) is also provided as a

http://www.D-MELD.com, the Italian survival calculator to optimize donor to recipient matching and to identify the unsustainable matches in liver transplantation.

Science.gov (United States)

Avolio, Alfonso W; Agnes, Salvatore; Cillo, Umberto; Lirosi, Maria C; Romagnoli, Renato; Baccarani, Umberto; Zamboni, Fausto; Nicolini, Daniele; Donataccio, Matteo; Perrella, Alessandro; Ettorre, Giuseppe M; Romano, Marina; Morelli, Nicola; Vennarecci, Giovanni; de Waure, Chiara; Fagiuoli, Stefano; Burra, Patrizia; Cucchetti, Alessandro

2012-03-01

Optimization of donor-recipient match is one of the exciting challenges in liver transplantation. Using algorithms obtained by the Italian D-MELD study (5256 liver transplants, 21 Centers, 2002-2009 period), a web-based survival calculator was developed. The calculator is available online at the URL http://www.D-MELD.com. The access is free. Registration and authentication are required. The website was developed using PHP scripting language on HTML platform and it is hosted by the web provider Aruba.it. For a given donor (expressed by donor age) and for three potential recipients (expressed by values of bilirubin, creatinine, INR, and by recipient age, HCV, HBV, portal thrombosis, re-transplant status), the website calculates the patient survival at 90days, 1year, 3years, and allows the identification of possible unsustainable matches (i.e. donor-recipient matches with predicted patient survival less than 50% at 5 years). This innovative approach allows the selection of the best recipient for each referred donor, avoiding the allocation of a high-risk graft to a high-risk recipient. The use of the D-MELD.com website can help transplant surgeons, hepatologists, and transplant coordinators in everyday practice of matching donors and recipients, by selecting the more appropriate recipient among various candidates with different prognostic factors. © 2012 The Authors. Transplant International © 2012 European Society for Organ Transplantation.

Transductive and matched-pair machine learning for difficult target detection problems

Science.gov (United States)

Theiler, James

2014-06-01

This paper will describe the application of two non-traditional kinds of machine learning (transductive machine learning and the more recently proposed matched-pair machine learning) to the target detection problem. The approach combines explicit domain knowledge to model the target signal with a more agnostic machine-learning approach to characterize the background. The concept is illustrated with simulated data from an elliptically-contoured background distribution, on which a subpixel target of known spectral signature but unknown spatial extent has been implanted.

Prodrug encapsulated albumin nanoparticles as an alternative approach to manifest anti-proliferative effects of suicide gene therapy

International Nuclear Information System (INIS)

Tirkey, Bulbul; Bhushan, Bharat; Uday Kumar, S.; Gopinath, P.

2017-01-01

Conventional anticancer agents are associated with limited therapeutic efficacy and substantial nonspecific cytotoxicity. Thus, there is an imminent need for an alternative approach that can specifically annihilate the cancer cells with minimal side effects. Among such alternative approaches, CD::UPRT (cytosine deaminase uracil phosphoribosyl transferase) suicide gene therapy has tremendous potential due to its high efficacy. Prodrug 5-Fluorocytosine (5-FC) used in combination with CD::UPRT suicide gene suffers from limited solubility which subsequently leads to decline in therapeutic efficacy. In order to overcome this, 5-FC encapsulated bovine serum albumin nanoparticles (BSA-5-FC NPs) were prepared in this work by desolvation method. Physico-chemical characterizations studies revealed amorphous nature of BSA-5-FC NPs with uniform spherical morphology. Apart from increase in solubility, encapsulated 5-FC followed slow and sustained release profile. Suicide gene expressing stable clone of L-132 cells were adapted for investigating therapeutic potential of BSA-5-FC NPs. These nanoparticles were readily taken up by the cells in a concentration dependent manner and subsequently manifested apoptosis, which was further confirmed by morphological examination and gene expression analysis. These findings clearly illustrate that CD::UPRT suicide gene therapy can be efficiently utilized in combination with this nanosystem for improved suicide gene therapy and tumor eradication. - Highlights: • In this work, BSA-5-FC NPs has been prepared to achieve its sustained release and also facilitate its uptake by cells. • A protein based system has been realized for the first time to deliver prodrug for cancer therapy. • Physico-chemical characterizations further validate the formation of spherical, monodispersed and stable nanoparticles. • The therapeutic efficacy of BSA-5-FC NPs has been validated against CD::UPRT expressing stable cells.

Prodrug encapsulated albumin nanoparticles as an alternative approach to manifest anti-proliferative effects of suicide gene therapy

Energy Technology Data Exchange (ETDEWEB)

Tirkey, Bulbul [Nanobiotechnology Laboratory, Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667 (India); Bhushan, Bharat; Uday Kumar, S. [Nanobiotechnology Laboratory, Centre for Nanotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667 (India); Gopinath, P., E-mail: pgopifnt@iitr.ernet.in [Nanobiotechnology Laboratory, Centre for Nanotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667 (India); Nanobiotechnology Laboratory, Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667 (India)

2017-04-01

Conventional anticancer agents are associated with limited therapeutic efficacy and substantial nonspecific cytotoxicity. Thus, there is an imminent need for an alternative approach that can specifically annihilate the cancer cells with minimal side effects. Among such alternative approaches, CD::UPRT (cytosine deaminase uracil phosphoribosyl transferase) suicide gene therapy has tremendous potential due to its high efficacy. Prodrug 5-Fluorocytosine (5-FC) used in combination with CD::UPRT suicide gene suffers from limited solubility which subsequently leads to decline in therapeutic efficacy. In order to overcome this, 5-FC encapsulated bovine serum albumin nanoparticles (BSA-5-FC NPs) were prepared in this work by desolvation method. Physico-chemical characterizations studies revealed amorphous nature of BSA-5-FC NPs with uniform spherical morphology. Apart from increase in solubility, encapsulated 5-FC followed slow and sustained release profile. Suicide gene expressing stable clone of L-132 cells were adapted for investigating therapeutic potential of BSA-5-FC NPs. These nanoparticles were readily taken up by the cells in a concentration dependent manner and subsequently manifested apoptosis, which was further confirmed by morphological examination and gene expression analysis. These findings clearly illustrate that CD::UPRT suicide gene therapy can be efficiently utilized in combination with this nanosystem for improved suicide gene therapy and tumor eradication. - Highlights: • In this work, BSA-5-FC NPs has been prepared to achieve its sustained release and also facilitate its uptake by cells. • A protein based system has been realized for the first time to deliver prodrug for cancer therapy. • Physico-chemical characterizations further validate the formation of spherical, monodispersed and stable nanoparticles. • The therapeutic efficacy of BSA-5-FC NPs has been validated against CD::UPRT expressing stable cells.

Data matching for free-surface multiple attenuation by multidimensional deconvolution

Science.gov (United States)

van der Neut, Joost; Frijlink, Martijn; van Borselen, Roald

2012-09-01

A common strategy for surface-related multiple elimination of seismic data is to predict multiples by a convolutional model and subtract these adaptively from the input gathers. Problems can be posed by interfering multiples and primaries. Removing multiples by multidimensional deconvolution (MDD) (inversion) does not suffer from these problems. However, this approach requires data to be consistent, which is often not the case, especially not at interpolated near-offsets. A novel method is proposed to improve data consistency prior to inversion. This is done by backpropagating first-order multiples with a time-gated reference primary event and matching these with early primaries in the input gather. After data matching, multiple elimination by MDD can be applied with a deterministic inversion scheme.

Real-time eSports Match Result Prediction

OpenAIRE

Yang, Yifan; Qin, Tian; Lei, Yu-Heng

2016-01-01

In this paper, we try to predict the winning team of a match in the multiplayer eSports game Dota 2. To address the weaknesses of previous work, we consider more aspects of prior (pre-match) features from individual players' match history, as well as real-time (during-match) features at each minute as the match progresses. We use logistic regression, the proposed Attribute Sequence Model, and their combinations as the prediction models. In a dataset of 78362 matches where 20631 matches contai...

Efficient strategy for detecting gene × gene joint action and its application in schizophrenia

NARCIS (Netherlands)

Won, Sungho; Kwon, Min-Seok; Mattheisen, Manuel; Park, Suyeon; Park, Changsoon; Kihara, Daisuke; Cichon, Sven; Ophoff, Roel; Nöthen, Markus M.; Rietschel, Marcella; Baur, Max; Uitterlinden, Andre G.; Hofmann, A.; Lange, Christoph; Kahn, René S.; Linszen, Don H.; van Os, Jim; Wiersma, Durk; Bruggeman, Richard; Cahn, Wiepke; de Haan, Lieuwe; Krabbendam, Lydia; Myin-Germeys, Inez

2014-01-01

We propose a new approach to detect gene × gene joint action in genome-wide association studies (GWASs) for case-control designs. This approach offers an exhaustive search for all two-way joint action (including, as a special case, single gene action) that is computationally feasible at the

An approach for reduction of false predictions in reverse engineering of gene regulatory networks.

Science.gov (United States)

Khan, Abhinandan; Saha, Goutam; Pal, Rajat Kumar

2018-05-14

A gene regulatory network discloses the regulatory interactions amongst genes, at a particular condition of the human body. The accurate reconstruction of such networks from time-series genetic expression data using computational tools offers a stiff challenge for contemporary computer scientists. This is crucial to facilitate the understanding of the proper functioning of a living organism. Unfortunately, the computational methods produce many false predictions along with the correct predictions, which is unwanted. Investigations in the domain focus on the identification of as many correct regulations as possible in the reverse engineering of gene regulatory networks to make it more reliable and biologically relevant. One way to achieve this is to reduce the number of incorrect predictions in the reconstructed networks. In the present investigation, we have proposed a novel scheme to decrease the number of false predictions by suitably combining several metaheuristic techniques. We have implemented the same using a dataset ensemble approach (i.e. combining multiple datasets) also. We have employed the proposed methodology on real-world experimental datasets of the SOS DNA Repair network of Escherichia coli and the IMRA network of Saccharomyces cerevisiae. Subsequently, we have experimented upon somewhat larger, in silico networks, namely, DREAM3 and DREAM4 Challenge networks, and 15-gene and 20-gene networks extracted from the GeneNetWeaver database. To study the effect of multiple datasets on the quality of the inferred networks, we have used four datasets in each experiment. The obtained results are encouraging enough as the proposed methodology can reduce the number of false predictions significantly, without using any supplementary prior biological information for larger gene regulatory networks. It is also observed that if a small amount of prior biological information is incorporated here, the results improve further w.r.t. the prediction of true positives

Comparing Phylogenetic Trees by Matching Nodes Using the Transfer Distance Between Partitions.

Science.gov (United States)

Bogdanowicz, Damian; Giaro, Krzysztof

2017-05-01

Ability to quantify dissimilarity of different phylogenetic trees describing the relationship between the same group of taxa is required in various types of phylogenetic studies. For example, such metrics are used to assess the quality of phylogeny construction methods, to define optimization criteria in supertree building algorithms, or to find horizontal gene transfer (HGT) events. Among the set of metrics described so far in the literature, the most commonly used seems to be the Robinson-Foulds distance. In this article, we define a new metric for rooted trees-the Matching Pair (MP) distance. The MP metric uses the concept of the minimum-weight perfect matching in a complete bipartite graph constructed from partitions of all pairs of leaves of the compared phylogenetic trees. We analyze the properties of the MP metric and present computational experiments showing its potential applicability in tasks related to finding the HGT events.

An Improvement on LSB Matching and LSB Matching Revisited Steganography Methods

OpenAIRE

Qazanfari, Kazem; Safabakhsh, Reza

2017-01-01

The aim of the steganography methods is to communicate securely in a completely undetectable manner. LSB Matching and LSB Matching Revisited steganography methods are two general and esiest methods to achieve this aim. Being secured against first order steganalysis methods is the most important feature of these methods. On the other hand, these methods don't consider inter pixel dependency. Therefore, recently, several steganalysis methods are proposed that by using co-occurrence matrix detec...

Heterologous reconstitution of the intact geodin gene cluster in Aspergillus nidulans through a simple and versatile PCR based approach.

Directory of Open Access Journals (Sweden)

Morten Thrane Nielsen

Full Text Available Fungal natural products are a rich resource for bioactive molecules. To fully exploit this potential it is necessary to link genes to metabolites. Genetic information for numerous putative biosynthetic pathways has become available in recent years through genome sequencing. However, the lack of solid methodology for genetic manipulation of most species severely hampers pathway characterization. Here we present a simple PCR based approach for heterologous reconstitution of intact gene clusters. Specifically, the putative gene cluster responsible for geodin production from Aspergillus terreus was transferred in a two step procedure to an expression platform in A. nidulans. The individual cluster fragments were generated by PCR and assembled via efficient USER fusion prior to transformation and integration via re-iterative gene targeting. A total of 13 open reading frames contained in 25 kb of DNA were successfully transferred between the two species enabling geodin synthesis in A. nidulans. Subsequently, functions of three genes in the cluster were validated by genetic and chemical analyses. Specifically, ATEG_08451 (gedC encodes a polyketide synthase, ATEG_08453 (gedR encodes a transcription factor responsible for activation of the geodin gene cluster and ATEG_08460 (gedL encodes a halogenase that catalyzes conversion of sulochrin to dihydrogeodin. We expect that our approach for transferring intact biosynthetic pathways to a fungus with a well developed genetic toolbox will be instrumental in characterizing the many exciting pathways for secondary metabolite production that are currently being uncovered by the fungal genome sequencing projects.

DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.

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Arango-Argoty, Gustavo; Garner, Emily; Pruden, Amy; Heath, Lenwood S; Vikesland, Peter; Zhang, Liqing

2018-02-01

Growing concerns about increasing rates of antibiotic resistance call for expanded and comprehensive global monitoring. Advancing methods for monitoring of environmental media (e.g., wastewater, agricultural waste, food, and water) is especially needed for identifying potential resources of novel antibiotic resistance genes (ARGs), hot spots for gene exchange, and as pathways for the spread of ARGs and human exposure. Next-generation sequencing now enables direct access and profiling of the total metagenomic DNA pool, where ARGs are typically identified or predicted based on the "best hits" of sequence searches against existing databases. Unfortunately, this approach produces a high rate of false negatives. To address such limitations, we propose here a deep learning approach, taking into account a dissimilarity matrix created using all known categories of ARGs. Two deep learning models, DeepARG-SS and DeepARG-LS, were constructed for short read sequences and full gene length sequences, respectively. Evaluation of the deep learning models over 30 antibiotic resistance categories demonstrates that the DeepARG models can predict ARGs with both high precision (> 0.97) and recall (> 0.90). The models displayed an advantage over the typical best hit approach, yielding consistently lower false negative rates and thus higher overall recall (> 0.9). As more data become available for under-represented ARG categories, the DeepARG models' performance can be expected to be further enhanced due to the nature of the underlying neural networks. Our newly developed ARG database, DeepARG-DB, encompasses ARGs predicted with a high degree of confidence and extensive manual inspection, greatly expanding current ARG repositories. The deep learning models developed here offer more accurate antimicrobial resistance annotation relative to current bioinformatics practice. DeepARG does not require strict cutoffs, which enables identification of a much broader diversity of ARGs. The

A new approach to spherically symmetric junction surfaces and the matching of FLRW regions

International Nuclear Information System (INIS)

Kirchner, U

2004-01-01

We investigate timelike junctions (with surface layer) between spherically symmetric solutions of the Einstein-field equation. In contrast to previous investigations, this is done in a coordinate system in which the junction surface motion is absorbed in the metric, while all coordinates are continuous at the junction surface. The evolution equations for all relevant quantities are derived. We discuss the no-surface layer case (boundary surface) and study the behaviour for small surface energies. It is shown that one should expect cases in which the speed of light is reached within a finite proper time. We carefully discuss necessary and sufficient conditions for a possible matching of spherically symmetric sections. For timelike junctions between spherically symmetric spacetime sections we show explicitly that the time component of the Lanczos equation always reduces to an identity (independent of the surface equation of state). The results are applied to the matching of Friedmann-LemaItre-Robertson-Walker (FLRW) models. We discuss 'vacuum bubbles' and closed-open junctions in detail. As illustrations several numerical integration results are presented, some of them indicate that (observers comoving with) the junction surface can reach the speed of light within a finite time

Proteome Profiling Outperforms Transcriptome Profiling for Coexpression Based Gene Function Prediction

Energy Technology Data Exchange (ETDEWEB)

Wang, Jing; Ma, Zihao; Carr, Steven A.; Mertins, Philipp; Zhang, Hui; Zhang, Zhen; Chan, Daniel W.; Ellis, Matthew J. C.; Townsend, R. Reid; Smith, Richard D.; McDermott, Jason E.; Chen, Xian; Paulovich, Amanda G.; Boja, Emily S.; Mesri, Mehdi; Kinsinger, Christopher R.; Rodriguez, Henry; Rodland, Karin D.; Liebler, Daniel C.; Zhang, Bing

2016-11-11

Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this “guilt-by-association” (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies

Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features

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Mousavi Kahaki, Seyed Mostafa; Nordin, Md Jan; Ashtari, Amir H.; J. Zahra, Sophia

2016-01-01

An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics—such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient—are insufficient for achieving adequate results under different image deformations. Thus, new descriptor’s similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence. PMID:26985996

Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features.

Directory of Open Access Journals (Sweden)

Seyed Mostafa Mousavi Kahaki

Full Text Available An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics--such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient--are insufficient for achieving adequate results under different image deformations. Thus, new descriptor's similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence.

The approaches to mathematical modeling of recA, umuD genes expression in bacteria Escherichia coli after UV-irradiation

International Nuclear Information System (INIS)

Belov, O.V.

2006-01-01

The modern data of recA, umuD genes expression of the system of SOS-repair at classical object of radiation genetic researches - bacteria Escherichia coli, after ultraviolet irradiation are presented. Essentially a new method of analysis of SOS-genes expression is considered. It was shown that using this method it is possible to determine the character of induction of some SOS-genes more precisely. The possible approach to the mathematical description of SOS-response of cells by construction of the system of the differential equations is presented

Geographic Trends in the Plastic Surgery Match.

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Silvestre, Jason; Lin, Ines C; Serletti, Joseph M; Chang, Benjamin

2016-01-01

The integrated plastic surgery match is among the most competitive residency matches in recent years. Although previous studies have correlated applicant characteristics with successful match outcomes, none have comprehensively investigated the role of geography in the match. This study elucidates regional biases in the match. Plastic surgery residents who matched during 2011-2015 were eligible for study inclusion. Names of residents were obtained from official residency program websites and cross-referenced with data obtained from the Student Doctor Network. For each resident, region of residency program and medical school were compared. From 67 programs, 622 residents were identified. Most graduated from US medical schools (97.9%). A total of 94 residents matched at a home institution (15.1%). Half of the residents matched in the same region as their medical school (48.9%). Programs in the South matched the greatest number of residents from the same region (60.8%), whereas West programs matched the least (30.8%, p < 0.001). No regional differences existed regarding residents matching at their home institution (p = 0.268). More women matched at West programs (43.1%) versus East programs (30.6%, p < 0.05). A significant number of residents matched at their home institution. Roughly, half matched at a program in the same region as their medical school. Whether this regional phenomenon stems from applicant or program factors remains unknown. Yet, given the limited number of interviews and the high costs of interviewing, applicants and programs can use these data to help optimize the match process. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Towards a Next-Generation Catalogue Cross-Match Service

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Pineau, F.; Boch, T.; Derriere, S.; Arches Consortium

2015-09-01

We have been developing in the past several catalogue cross-match tools. On one hand the CDS XMatch service (Pineau et al. 2011), able to perform basic but very efficient cross-matches, scalable to the largest catalogues on a single regular server. On the other hand, as part of the European project ARCHES1, we have been developing a generic and flexible tool which performs potentially complex multi-catalogue cross-matches and which computes probabilities of association based on a novel statistical framework. Although the two approaches have been managed so far as different tracks, the need for next generation cross-match services dealing with both efficiency and complexity is becoming pressing with forthcoming projects which will produce huge high quality catalogues. We are addressing this challenge which is both theoretical and technical. In ARCHES we generalize to N catalogues the candidate selection criteria - based on the chi-square distribution - described in Pineau et al. (2011). We formulate and test a number of Bayesian hypothesis which necessarily increases dramatically with the number of catalogues. To assign a probability to each hypotheses, we rely on estimated priors which account for local densities of sources. We validated our developments by comparing the theoretical curves we derived with the results of Monte-Carlo simulations. The current prototype is able to take into account heterogeneous positional errors, object extension and proper motion. The technical complexity is managed by OO programming design patterns and SQL-like functionalities. Large tasks are split into smaller independent pieces for scalability. Performances are achieved resorting to multi-threading, sequential reads and several tree data-structures. In addition to kd-trees, we account for heterogeneous positional errors and object's extension using M-trees. Proper-motions are supported using a modified M-tree we developed, inspired from Time Parametrized R-trees (TPR

The genetic basis of resistance and matching-allele interactions of a host-parasite system: The Daphnia magna-Pasteuria ramosa model.

Directory of Open Access Journals (Sweden)

Gilberto Bento

2017-02-01

Full Text Available Negative frequency-dependent selection (NFDS is an evolutionary mechanism suggested to govern host-parasite coevolution and the maintenance of genetic diversity at host resistance loci, such as the vertebrate MHC and R-genes in plants. Matching-allele interactions of hosts and parasites that prevent the emergence of host and parasite genotypes that are universally resistant and infective are a genetic mechanism predicted to underpin NFDS. The underlying genetics of matching-allele interactions are unknown even in host-parasite systems with empirical support for coevolution by NFDS, as is the case for the planktonic crustacean Daphnia magna and the bacterial pathogen Pasteuria ramosa. We fine-map one locus associated with D. magna resistance to P. ramosa and genetically characterize two haplotypes of the Pasteuria resistance (PR- locus using de novo genome and transcriptome sequencing. Sequence comparison of PR-locus haplotypes finds dramatic structural polymorphisms between PR-locus haplotypes including a large portion of each haplotype being composed of non-homologous sequences resulting in haplotypes differing in size by 66 kb. The high divergence of PR-locus haplotypes suggest a history of multiple, diverse and repeated instances of structural mutation events and restricted recombination. Annotation of the haplotypes reveals striking differences in gene content. In particular, a group of glycosyltransferase genes that is present in the susceptible but absent in the resistant haplotype. Moreover, in natural populations, we find that the PR-locus polymorphism is associated with variation in resistance to different P. ramosa genotypes, pointing to the PR-locus polymorphism as being responsible for the matching-allele interactions that have been previously described for this system. Our results conclusively identify a genetic basis for the matching-allele interaction observed in a coevolving host-parasite system and provide a first insight into

The genetic basis of resistance and matching-allele interactions of a host-parasite system: The Daphnia magna-Pasteuria ramosa model.

Science.gov (United States)

Bento, Gilberto; Routtu, Jarkko; Fields, Peter D; Bourgeois, Yann; Du Pasquier, Louis; Ebert, Dieter

2017-02-01

Negative frequency-dependent selection (NFDS) is an evolutionary mechanism suggested to govern host-parasite coevolution and the maintenance of genetic diversity at host resistance loci, such as the vertebrate MHC and R-genes in plants. Matching-allele interactions of hosts and parasites that prevent the emergence of host and parasite genotypes that are universally resistant and infective are a genetic mechanism predicted to underpin NFDS. The underlying genetics of matching-allele interactions are unknown even in host-parasite systems with empirical support for coevolution by NFDS, as is the case for the planktonic crustacean Daphnia magna and the bacterial pathogen Pasteuria ramosa. We fine-map one locus associated with D. magna resistance to P. ramosa and genetically characterize two haplotypes of the Pasteuria resistance (PR-) locus using de novo genome and transcriptome sequencing. Sequence comparison of PR-locus haplotypes finds dramatic structural polymorphisms between PR-locus haplotypes including a large portion of each haplotype being composed of non-homologous sequences resulting in haplotypes differing in size by 66 kb. The high divergence of PR-locus haplotypes suggest a history of multiple, diverse and repeated instances of structural mutation events and restricted recombination. Annotation of the haplotypes reveals striking differences in gene content. In particular, a group of glycosyltransferase genes that is present in the susceptible but absent in the resistant haplotype. Moreover, in natural populations, we find that the PR-locus polymorphism is associated with variation in resistance to different P. ramosa genotypes, pointing to the PR-locus polymorphism as being responsible for the matching-allele interactions that have been previously described for this system. Our results conclusively identify a genetic basis for the matching-allele interaction observed in a coevolving host-parasite system and provide a first insight into its molecular basis.

Improvement of retinal blood vessel detection by spur removal and Gaussian matched filtering compensation

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Xiao, Di; Vignarajan, Janardhan; An, Dong; Tay-Kearney, Mei-Ling; Kanagasingam, Yogi

2016-03-01

Retinal photography is a non-invasive and well-accepted clinical diagnosis of ocular diseases. Qualitative and quantitative assessment of retinal images is crucial in ocular diseases related clinical application. In this paper, we proposed approaches for improving the quality of blood vessel detection based on our initial blood vessel detection methods. A blood vessel spur pruning method has been developed for removing the blood vessel spurs both on vessel medial lines and binary vessel masks, which are caused by artifacts and side-effect of Gaussian matched vessel enhancement. A Gaussian matched filtering compensation method has been developed for removing incorrect vessel branches in the areas of low illumination. The proposed approaches were applied and tested on the color fundus images from one publicly available database and our diabetic retinopathy screening dataset. A preliminary result has demonstrated the robustness and good performance of the proposed approaches and their potential application for improving retinal blood vessel detection.

Gene name ambiguity of eukaryotic nomenclatures.

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Chen, Lifeng; Liu, Hongfang; Friedman, Carol