INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(75810, 2010, 'bio', 'CellPublisher: a web platform for the intuitive visualization and sharing of metabolic, signalling and regulatory pathways', 'Flórez, Lope A|Lammers, Christoph R|Michna, Raphael|Stülke, Jörg', 'Department of General Microbiology, Georg-August University Göttingen, Grisebachstr. 8, 37077 Göttingen, Germany.|Department of General Microbiology, Georg-August University Göttingen, Grisebachstr. 8, 37077 Göttingen, Germany.|Department of General Microbiology, Georg-August University Göttingen, Grisebachstr. 8, 37077 Göttingen, Germany.|Department of General Microbiology, Georg-August University Göttingen, Grisebachstr. 8, 37077 Göttingen, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Computational Biology|Gene Expression Regulation|Internet|Metabolic Networks and Pathways|Models, Biological|Signal Transduction|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq585', '20947526', 'Systems biology relies increasingly on collaborations between several groups with different expertise. Therefore, the systems biology community is adopting standards that allow effective communication of concepts, as well as transmission and processing of pathway information. The Systems Biology Graphical Notation (SBGN) is a graphical language for biological pathways that has both a biological as well as a computational meaning. The program CellDesigner allows the codification of biological phenomena in an SBGN compliant form. CellPublisher is a web server that allows the conversion of CellDesigner files to web-based navigatable diagrams based on the user interface of Google maps. Thus, CellPublisher complements CellDesigner by facilitating the understanding of complex diagrams and by providing the possibility to share any CellDesigner diagram online with collaborators and get their feedback. Due to the intuitive interface of the online diagrams, CellPublisher serves as a basis for discovery of novel properties of the modelled networks.'),
(75811, 2010, 'bio', 'Investigating the correlations among the chemical structures, bioactivity profiles and molecular targets of small molecules', 'Cheng, Tiejun|Wang, Yanli|Bryant, Stephen H', 'National Center for Biotechnology Information, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.', 'United States|United States|United States', 23, 'Data Mining|Databases, Factual|Knowledge Bases|National Library of Medicine (U.S.)|Pharmaceutical Preparations|United States', 'Journal Article', '10.1093/bioinformatics/btq550', '20947527', 'Most of the previous data mining studies based on the NCI-60 dataset, due to its intrinsic cell-based nature, can hardly provide insights into the molecular targets for screened compounds. On the other hand, the abundant information of the compound-target associations in PubChem can offer extensive experimental evidence of molecular targets for tested compounds. Therefore, by taking advantages of the data from both public repositories, one may investigate the correlations between the bioactivity profiles of small molecules from the NCI-60 dataset (cellular level) and their patterns of interactions with relevant protein targets from PubChem (molecular level) simultaneously.'),
(75812, 2010, 'bio', 'Flapjack--graphical genotype visualization', 'Milne, Iain|Shaw, Paul|Stephen, Gordon|Bayer, Micha|Cardle, Linda|Thomas, William T B|Flavell, Andrew J|Marshall, David', 'Genetics Programme, Scottish Crop Research Institute, Invergowrie, Dundee, UK.|Genetics Programme, Scottish Crop Research Institute, Invergowrie, Dundee, UK.|Genetics Programme, Scottish Crop Research Institute, Invergowrie, Dundee, UK.|Genetics Programme, Scottish Crop Research Institute, Invergowrie, Dundee, UK.|Genetics Programme, Scottish Crop Research Institute, Invergowrie, Dundee, UK.|Genetics Programme, Scottish Crop Research Institute, Invergowrie, Dundee, UK.|Genetics Programme, Scottish Crop Research Institute, Invergowrie, Dundee, UK.|Genetics Programme, Scottish Crop Research Institute, Invergowrie, Dundee, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Chromosome Mapping|Computer Graphics|Genotype|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Software', 'Journal Article', '10.1093/bioinformatics/btq580', '20956241', 'New software tools for graphical genotyping are required that can routinely handle the large data volumes generated by the high-throughput single-nucleotide polymorphism (SNP) platforms, genotyping-by-sequencing and other comparable genotyping technologies. Flapjack has been developed to facilitate analysis of these data, providing real time rendering with rapid navigation and comparisons between lines, markers and chromosomes, with visualization, sorting and querying based on associated data, such as phenotypes, quantitative trait loci or other mappable features.'),
(75813, 2010, 'bio', 'FILTREST3D: discrimination of structural models using restraints from experimental data', 'Gajda, Michal J|Tuszynska, Irina|Kaczor, Marta|Bakulina, Anastasia Yu|Bujnicki, Janusz M', 'International Institute of Molecular and Cell Biology, ul. Ks. Trojdena 4, Warsaw, Poland.|International Institute of Molecular and Cell Biology, ul. Ks. Trojdena 4, Warsaw, Poland.|International Institute of Molecular and Cell Biology, ul. Ks. Trojdena 4, Warsaw, Poland.|International Institute of Molecular and Cell Biology, ul. Ks. Trojdena 4, Warsaw, Poland.|International Institute of Molecular and Cell Biology, ul. Ks. Trojdena 4, Warsaw, Poland.', 'Poland|Poland|Poland|Poland|Poland', 14, 'Computational Biology|Models, Molecular|Nucleic Acid Conformation|Protein Conformation|Software', 'Journal Article', '10.1093/bioinformatics/btq582', '20956242', 'Automatic methods for macromolecular structure prediction (fold recognition, de novo folding and docking programs) produce large sets of alternative models. These large model sets often include many native-like structures, which are often scored as false positives. Such native-like models can be more easily identified based on data from experimental analyses used as structural restraints (e.g. identification of nearby residues by cross-linking, chemical modification, site-directed mutagenesis, deuterium exchange coupled with mass spectrometry, etc.). We present a simple server for scoring and ranking of models according to their agreement with user-defined restraints.'),
(75814, 2010, 'bio', 'SPLATCHE2: a spatially explicit simulation framework for complex demography, genetic admixture and recombination', 'Ray, Nicolas|Currat, Mathias|Foll, Matthieu|Excoffier, Laurent', 'EnviroSPACE laboratory, Climate Change and Climate Impacts, Institute for Environmental Sciences, University of Geneva, Battelle - Building D, 7 route de Drize, 1227 Carouge, Switzerland.|EnviroSPACE laboratory, Climate Change and Climate Impacts, Institute for Environmental Sciences, University of Geneva, Battelle - Building D, 7 route de Drize, 1227 Carouge, Switzerland.|EnviroSPACE laboratory, Climate Change and Climate Impacts, Institute for Environmental Sciences, University of Geneva, Battelle - Building D, 7 route de Drize, 1227 Carouge, Switzerland.|EnviroSPACE laboratory, Climate Change and Climate Impacts, Institute for Environmental Sciences, University of Geneva, Battelle - Building D, 7 route de Drize, 1227 Carouge, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland', 81, 'Biological Evolution|Computer Simulation|Demography|Genetic Markers|Genetic Variation|Genetics, Population|Humans|Population Groups|Recombination, Genetic|Software', 'Journal Article', '10.1093/bioinformatics/btq579', '20956243', 'SPLATCHE2 is a program to simulate the demography of populations and the resulting molecular diversity for a wide range of evolutionary scenarios. The spatially explicit simulation framework can account for environmental heterogeneity and fluctuations, and it can manage multiple population sources. A coalescent-based approach is used to generate genetic markers mostly used in population genetics studies (DNA sequences, SNPs, STRs or RFLPs). Various combinations of independent, fully or partially linked genetic markers can be produced under a recombination model based on the ancestral recombination graph. Competition between two populations (or species) can also be simulated with user-defined levels of admixture between the two populations. SPLATCHE2 may be used to generate the expected genetic diversity under complex demographic scenarios and can thus serve to test null hypotheses. For model parameter estimation, SPLATCHE2 can easily be integrated into an Approximate Bayesian Computation (ABC) framework.'),
(75815, 2010, 'bio', 'Interactive microbial genome visualization with GView', 'Petkau, Aaron|Stuart-Edwards, Matthew|Stothard, Paul|Van Domselaar, Gary', 'National Microbiology Laboratory-Public Health Agency of Canada, Winnipeg, Manitoba, Canada.|National Microbiology Laboratory-Public Health Agency of Canada, Winnipeg, Manitoba, Canada.|National Microbiology Laboratory-Public Health Agency of Canada, Winnipeg, Manitoba, Canada.|National Microbiology Laboratory-Public Health Agency of Canada, Winnipeg, Manitoba, Canada.', 'Canada|Canada|Canada|Canada', 0, 'Computer Graphics|Genome, Bacterial|Genomics|Roseobacter|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq588', '20956244', 'GView is a Java application for viewing and examining prokaryotic genomes in a circular or linear context. It accepts standard sequence file formats and an optional style specification file to generate customizable, publication quality genome maps in bitmap and scalable vector graphics formats. GView features an interactive pan-and-zoom interface, a command-line interface for incorporation in genome analysis pipelines, and a public Application Programming Interface for incorporation in other Java applications.'),
(75816, 2010, 'bio', 'High-quality annotation of promoter regions for 913 bacterial genomes', 'Rangannan, Vetriselvi|Bansal, Manju', 'Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.|Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.', 'India|India', 27, 'Algorithms|Base Composition|Base Sequence|DNA, Bacterial|Genome, Bacterial|Molecular Sequence Annotation|Promoter Regions, Genetic', 'Journal Article', '10.1093/bioinformatics/btq577', '20956245', 'The number of bacterial genomes being sequenced is increasing very rapidly and hence, it is crucial to have procedures for rapid and reliable annotation of their functional elements such as promoter regions, which control the expression of each gene or each transcription unit of the genome. The present work addresses this requirement and presents a generic method applicable across organisms.'),
(75817, 2010, 'bio', 'State reduction for network intervention in probabilistic Boolean networks', 'Qian, Xiaoning|Ghaffari, Noushin|Ivanov, Ivan|Dougherty, Edward R', 'Department of Computer Science & Engineering, University of South Florida, Tampa, FL 33620, USA. xqian@cse.usf.edu|Department of Computer Science & Engineering, University of South Florida, Tampa, FL 33620, USA. xqian@cse.usf.edu|Department of Computer Science & Engineering, University of South Florida, Tampa, FL 33620, USA. xqian@cse.usf.edu|Department of Computer Science & Engineering, University of South Florida, Tampa, FL 33620, USA. xqian@cse.usf.edu', 'United States|United States|United States|United States', 25, 'Algorithms|Gastrointestinal Neoplasms|Gene Regulatory Networks|Humans|Markov Chains|Models, Biological|Models, Genetic|Models, Statistical|Probability', 'Journal Article', '10.1093/bioinformatics/btq575', '20956246', 'A key goal of studying biological systems is to design therapeutic intervention strategies. Probabilistic Boolean networks (PBNs) constitute a mathematical model which enables modeling, predicting and intervening in their long-run behavior using Markov chain theory. The long-run dynamics of a PBN, as represented by its steady-state distribution (SSD), can guide the design of effective intervention strategies for the modeled systems. A major obstacle for its application is the large state space of the underlying Markov chain, which poses a serious computational challenge. Hence, it is critical to reduce the model complexity of PBNs for practical applications.'),
(75818, 2010, 'bio', 'Identifying functional miRNA-mRNA regulatory modules with correspondence latent dirichlet allocation', 'Liu, Bing|Liu, Lin|Tsykin, Anna|Goodall, Gregory J|Green, Jeffrey E|Zhu, Min|Kim, Chang Hee|Li, Jiuyong', 'School of Computer and Information Science, University of South Australia, Mawson Lakes, SA, Australia. bing.liu@unisa.edu.au|School of Computer and Information Science, University of South Australia, Mawson Lakes, SA, Australia. bing.liu@unisa.edu.au|School of Computer and Information Science, University of South Australia, Mawson Lakes, SA, Australia. bing.liu@unisa.edu.au|School of Computer and Information Science, University of South Australia, Mawson Lakes, SA, Australia. bing.liu@unisa.edu.au|School of Computer and Information Science, University of South Australia, Mawson Lakes, SA, Australia. bing.liu@unisa.edu.au|School of Computer and Information Science, University of South Australia, Mawson Lakes, SA, Australia. bing.liu@unisa.edu.au|School of Computer and Information Science, University of South Australia, Mawson Lakes, SA, Australia. bing.liu@unisa.edu.au|School of Computer and Information Science, University of South Australia, Mawson Lakes, SA, Australia. bing.liu@unisa.edu.au', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia', 0, 'Animals|Female|Gene Expression Profiling|Gene Expression Regulation|Gene Regulatory Networks|Mammary Neoplasms, Experimental|Mice|MicroRNAs|Models, Statistical|RNA, Messenger', 'Journal Article', '10.1093/bioinformatics/btq576', '20956247', 'MicroRNAs (miRNAs) are small non-coding RNAs that cause mRNA degradation and translational inhibition. They are important regulators of development and cellular homeostasis through their control of diverse processes. Recently, great efforts have been made to elucidate their regulatory mechanism, but the functions of most miRNAs and their precise regulatory mechanisms remain elusive. With more and more matched expression profiles of miRNAs and mRNAs having been made available, it is of great interest to utilize both expression profiles to discover the functional regulatory networks of miRNAs and their target mRNAs for potential biological processes that they may participate in.'),
(75819, 2010, 'bio', 'Model-free unsupervised gene set screening based on information enrichment in expression profiles', 'Niida, Atushi|Imoto, Seiya|Yamaguchi, Rui|Nagasaki, Masao|Fujita, André|Shimamura, Teppei|Miyano, Satoru', 'Human Genome Center, Institute of Medical Science, University of Tokyo, Japan. aniida@ims.u-tokyo.ac.jp|Human Genome Center, Institute of Medical Science, University of Tokyo, Japan. aniida@ims.u-tokyo.ac.jp|Human Genome Center, Institute of Medical Science, University of Tokyo, Japan. aniida@ims.u-tokyo.ac.jp|Human Genome Center, Institute of Medical Science, University of Tokyo, Japan. aniida@ims.u-tokyo.ac.jp|Human Genome Center, Institute of Medical Science, University of Tokyo, Japan. aniida@ims.u-tokyo.ac.jp|Human Genome Center, Institute of Medical Science, University of Tokyo, Japan. aniida@ims.u-tokyo.ac.jp|Human Genome Center, Institute of Medical Science, University of Tokyo, Japan. aniida@ims.u-tokyo.ac.jp', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Algorithms|Gene Expression Profiling|Models, Genetic', 'Evaluation Studies', '10.1093/bioinformatics/btq592', '20959379', 'A number of unsupervised gene set screening methods have recently been developed for search of putative functional gene sets based on their expression profiles. Most of the methods statistically evaluate whether the expression profiles of each gene set are fit to assumed models: e.g. co-expression across all samples or a subgroup of samples. However, it is possible that they fail to capture informative gene sets whose expression profiles are not fit to the assumed models.'),
(75820, 2010, 'bio', 'VEGA: variational segmentation for copy number detection', 'Morganella, Sandro|Cerulo, Luigi|Viglietto, Giuseppe|Ceccarelli, Michele', 'Department of Biological and Environmental Studies, University of Sannio, Benevento, Italy.|Department of Biological and Environmental Studies, University of Sannio, Benevento, Italy.|Department of Biological and Environmental Studies, University of Sannio, Benevento, Italy.|Department of Biological and Environmental Studies, University of Sannio, Benevento, Italy.', 'Italy|Italy|Italy|Italy', 13, 'Algorithms|Brain Neoplasms|Chromosome Aberrations|Comparative Genomic Hybridization|Computational Biology|DNA Copy Number Variations|Genome|Glioblastoma|Humans|Lymphoma, Mantle-Cell', 'Journal Article', '10.1093/bioinformatics/btq586', '20959380', 'Genomic copy number (CN) information is useful to study genetic traits of many diseases. Using array comparative genomic hybridization (aCGH), researchers are able to measure the copy number of thousands of DNA loci at the same time. Therefore, a current challenge in bioinformatics is the development of efficient algorithms to detect the map of aberrant chromosomal regions.'),
(75821, 2010, 'bio', 'SmashCommunity: a metagenomic annotation and analysis tool', 'Arumugam, Manimozhiyan|Harrington, Eoghan D|Foerstner, Konrad U|Raes, Jeroen|Bork, Peer', 'EMBL, Meyerhofstrasse 1, 69117 Heidelberg, Germany.|EMBL, Meyerhofstrasse 1, 69117 Heidelberg, Germany.|EMBL, Meyerhofstrasse 1, 69117 Heidelberg, Germany.|EMBL, Meyerhofstrasse 1, 69117 Heidelberg, Germany.|EMBL, Meyerhofstrasse 1, 69117 Heidelberg, Germany.', 'Germany|Germany|Germany|Germany|Germany', 0, 'Genes|Metagenomics|Molecular Sequence Annotation|Phylogeny|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq536', '20959381', 'SmashCommunity is a stand-alone metagenomic annotation and analysis pipeline suitable for data from Sanger and 454 sequencing technologies. It supports state-of-the-art software for essential metagenomic tasks such as assembly and gene prediction. It provides tools to estimate the quantitative phylogenetic and functional compositions of metagenomes, to compare compositions of multiple metagenomes and to produce intuitive visual representations of such analyses.'),
(75822, 2010, 'bio', 'MiRonTop: mining microRNAs targets across large scale gene expression studies', 'Le Brigand, Kevin|Robbe-Sermesant, Karine|Mari, Bernard|Barbry, Pascal', 'Centre National de la Recherche Scientifique, Institut de Pharmacologie Moléculaire et Cellulaire, UMR6097, 06560 Sophia-Antipolis, Nice, France.|Centre National de la Recherche Scientifique, Institut de Pharmacologie Moléculaire et Cellulaire, UMR6097, 06560 Sophia-Antipolis, Nice, France.|Centre National de la Recherche Scientifique, Institut de Pharmacologie Moléculaire et Cellulaire, UMR6097, 06560 Sophia-Antipolis, Nice, France.|Centre National de la Recherche Scientifique, Institut de Pharmacologie Moléculaire et Cellulaire, UMR6097, 06560 Sophia-Antipolis, Nice, France.', 'France|France|France|France', 44, '3 Untranslated Regions|Data Mining|Gene Expression|Gene Expression Profiling|Gene Expression Regulation|Internet|MicroRNAs|Oligonucleotide Array Sequence Analysis|RNA, Messenger|Software', 'Journal Article', '10.1093/bioinformatics/btq589', '20959382', 'Current challenges in microRNA (miRNA) research are to improve the identification of in vivo mRNA targets and clarify the complex interplay existing between a specific miRNA and multiple biological networks. MiRonTop is an online java web tool that integrates DNA microarrays or high-throughput sequencing data to identify the potential implication of miRNAs on a specific biological system. It allows a rapid characterization of the most pertinent mRNA targets according to several existing miRNA target prediction approaches. It also provides useful representations of the enrichment scores according to the position of the target site along the 3-UTR, where the contribution of the sites located in the vicinity of the stop codon and of the polyA tail can be clearly highlighted. It provides different graphs of miRNA enrichment associated with up- or down-regulated transcripts and different summary tables about selections of mRNA targets and their functional annotations by Gene Ontology.'),
(75823, 2010, 'bio', 'Interactional and functional centrality in transcriptional co-expression networks', 'Prifti, Edi|Zucker, Jean-Daniel|Clément, Karine|Henegar, Corneliu', 'INSERM, UMR-S 872, Les Cordeliers, Eq. 7 Nutriomique, Paris, France. edi.prifti@crc.jussieu.fr|INSERM, UMR-S 872, Les Cordeliers, Eq. 7 Nutriomique, Paris, France. edi.prifti@crc.jussieu.fr|INSERM, UMR-S 872, Les Cordeliers, Eq. 7 Nutriomique, Paris, France. edi.prifti@crc.jussieu.fr|INSERM, UMR-S 872, Les Cordeliers, Eq. 7 Nutriomique, Paris, France. edi.prifti@crc.jussieu.fr', 'France|France|France|France', 0, 'Algorithms|Databases, Genetic|Gene Expression Profiling|Gene Regulatory Networks|Models, Genetic|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btq591', '20959383', 'The noisy nature of transcriptomic data hinders the biological relevance of conventional network centrality measures, often used to select gene candidates in co-expression networks. Therefore, new tools and methods are required to improve the prediction of mechanistically important transcriptional targets.'),
(75824, 2010, 'bio', 'Proceedings of the ISMB (Intelligent Systems for Molecular Biology) 2010 Conference July 11-13, 2010 Boston, Massachusetts, USA', '-', '-', '-', 0, 'Animals|Computational Biology|Humans', 'Congress', '10.1093/bioinformatics/btq591', '20963926', '-'),
(75825, 2010, 'bio', 'CNAseg--a novel framework for identification of copy number changes in cancer from second-generation sequencing data', 'Ivakhno, Sergii|Royce, Tom|Cox, Anthony J|Evers, Dirk J|Cheetham, R Keira|Tavaré, Simon', 'Cancer Research UK Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK. Sergii.Ivakhno@cancer.org.uk|Cancer Research UK Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK. Sergii.Ivakhno@cancer.org.uk|Cancer Research UK Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK. Sergii.Ivakhno@cancer.org.uk|Cancer Research UK Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK. Sergii.Ivakhno@cancer.org.uk|Cancer Research UK Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK. Sergii.Ivakhno@cancer.org.uk|Cancer Research UK Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK. Sergii.Ivakhno@cancer.org.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 70, 'Algorithms|Base Composition|Cell Line, Tumor|DNA Copy Number Variations|Genome, Human|Humans|Mutation|Neoplasms|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btq587', '20966003', 'Copy number abnormalities (CNAs) represent an important type of genetic mutation that can lead to abnormal cell growth and proliferation. New high-throughput sequencing technologies promise comprehensive characterization of CNAs. In contrast to microarrays, where probe design follows a carefully developed protocol, reads represent a random sample from a library and may be prone to representation biases due to GC content and other factors. The discrimination between true and false positive CNAs becomes an important issue.'),
(75826, 2010, 'bio', 'R/qtl: high-throughput multiple QTL mapping', 'Arends, Danny|Prins, Pjotr|Jansen, Ritsert C|Broman, Karl W', 'Groningen Bioinformatics Centre, University of Groningen, Groningen, The Netherlands.|Groningen Bioinformatics Centre, University of Groningen, Groningen, The Netherlands.|Groningen Bioinformatics Centre, University of Groningen, Groningen, The Netherlands.|Groningen Bioinformatics Centre, University of Groningen, Groningen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Chromosome Mapping|Genomics|Quantitative Trait Loci|Software', 'Journal Article', '10.1093/bioinformatics/btq565', '20966004', 'R/qtl is free and powerful software for mapping and exploring quantitative trait loci (QTL). R/qtl provides a fully comprehensive range of methods for a wide range of experimental cross types. We recently added multiple QTL mapping (MQM) to R/qtl. MQM adds higher statistical power to detect and disentangle the effects of multiple linked and unlinked QTL compared with many other methods. MQM for R/qtl adds many new features including improved handling of missing data, analysis of 10,000 s of molecular traits, permutation for determining significance thresholds for QTL and QTL hot spots, and visualizations for cis-trans and QTL interaction effects. MQM for R/qtl is the first free and open source implementation of MQM that is multi-platform, scalable and suitable for automated procedures and large genetical genomics datasets.'),
(75827, 2010, 'bio', 'SmashCell: a software framework for the analysis of single-cell amplified genome sequences', 'Harrington, Eoghan D|Arumugam, Manimozhiyan|Raes, Jeroen|Bork, Peer|Relman, David A', 'Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA. eoghanh@stanford.edu|Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA. eoghanh@stanford.edu|Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA. eoghanh@stanford.edu|Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA. eoghanh@stanford.edu|Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA. eoghanh@stanford.edu', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Chromosome Mapping|Genome|Genomics|Nucleic Acid Amplification Techniques|Sequence Analysis, DNA|Single-Cell Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btq564', '20966005', 'Recent advances in single-cell manipulation technology, whole genome amplification and high-throughput sequencing have now made it possible to sequence the genome of an individual cell. The bioinformatic analysis of these genomes, however, is far more complicated than the analysis of those generated using traditional, culture-based methods. In order to simplify this analysis, we have developed SmashCell (Simple Metagenomics Analysis SHell-for sequences from single Cells). It is designed to automate the main steps in microbial genome analysis-assembly, gene prediction, functional annotation-in a way that allows parameter and algorithm exploration at each step in the process. It also manages the data created by these analyses and provides visualization methods for rapid analysis of the results.'),
(75828, 2010, 'bio', 'Discovering homotypic binding events at high spatial resolution', 'Guo, Yuchun|Papachristoudis, Georgios|Altshuler, Robert C|Gerber, Georg K|Jaakkola, Tommi S|Gifford, David K|Mahony, Shaun', 'MIT Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA.|MIT Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA.|MIT Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA.|MIT Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA.|MIT Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA.|MIT Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA.|MIT Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Binding Sites|Chromatin Immunoprecipitation|DNA-Binding Proteins|Genome|Models, Statistical|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btq590', '20966006', 'Clusters of protein-DNA interaction events involving the same transcription factor are known to act as key components of invertebrate and mammalian promoters and enhancers. However, detecting closely spaced homotypic events from ChIP-Seq data is challenging because random variation in the ChIP fragmentation process obscures event locations.'),
(75829, 2011, 'bio', 'Generalized random set framework for functional enrichment analysis using primary genomics datasets', 'Freudenberg, Johannes M|Sivaganesan, Siva|Phatak, Mukta|Shinde, Kaustubh|Medvedovic, Mario', 'Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA.|Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA.|Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA.|Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA.|Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA.', 'United States|United States|United States|United States|United States', 0, 'Animals|Breast Neoplasms|Data Interpretation, Statistical|Diet|Female|Gene Expression|Gene Expression Profiling|Genomics|Humans|Rats', 'Journal Article', '10.1093/bioinformatics/btq593', '20971985', 'Functional enrichment analysis using primary genomics datasets is an emerging approach to complement established methods for functional enrichment based on predefined lists of functionally related genes. Currently used methods depend on creating lists of significant and non-significant genes based on ad hoc significance cutoffs. This can lead to loss of statistical power and can introduce biases affecting the interpretation of experimental results.'),
(75830, 2011, 'bio', 'GAMES identifies and annotates mutations in next-generation sequencing projects', 'Sana, Maria Elena|Iascone, Maria|Marchetti, Daniela|Palatini, Jeff|Galasso, Marco|Volinia, Stefano', 'DAMA, Data Mining for Analysis of DNA, Department of Morphology and Embryology and TecnoPolo for Life Sciences, University of Ferrara, Ferrara, Italy.|DAMA, Data Mining for Analysis of DNA, Department of Morphology and Embryology and TecnoPolo for Life Sciences, University of Ferrara, Ferrara, Italy.|DAMA, Data Mining for Analysis of DNA, Department of Morphology and Embryology and TecnoPolo for Life Sciences, University of Ferrara, Ferrara, Italy.|DAMA, Data Mining for Analysis of DNA, Department of Morphology and Embryology and TecnoPolo for Life Sciences, University of Ferrara, Ferrara, Italy.|DAMA, Data Mining for Analysis of DNA, Department of Morphology and Embryology and TecnoPolo for Life Sciences, University of Ferrara, Ferrara, Italy.|DAMA, Data Mining for Analysis of DNA, Department of Morphology and Embryology and TecnoPolo for Life Sciences, University of Ferrara, Ferrara, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy', 0, 'DNA Mutational Analysis|Genomics|High-Throughput Nucleotide Sequencing|Molecular Sequence Annotation|Software', 'Journal Article', '10.1093/bioinformatics/btq603', '20971986', 'Next-generation sequencing (NGS) methods have the potential for changing the landscape of biomedical science, but at the same time pose several problems in analysis and interpretation. Currently, there are many commercial and public software packages that analyze NGS data. However, the limitations of these applications include output which is insufficiently annotated and of difficult functional comprehension to end users.'),
(75831, 2010, 'bio', 'Interoperability between phenotype and anatomy ontologies', 'Hoehndorf, Robert|Oellrich, Anika|Rebholz-Schuhmann, Dietrich', 'European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rh497@cam.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rh497@cam.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rh497@cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Disease|Humans|Phenotype|Semantics|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btq578', '20971987', 'Phenotypic information is important for the analysis of the molecular mechanisms underlying disease. A formal ontological representation of phenotypic information can help to identify, interpret and infer phenotypic traits based on experimental findings. The methods that are currently used to represent data and information about phenotypes fail to make the semantics of the phenotypic trait explicit and do not interoperate with ontologies of anatomy and other domains. Therefore, valuable resources for the analysis of phenotype studies remain unconnected and inaccessible to automated analysis and reasoning.'),
(75832, 2010, 'bio', 'The GMOD Drupal bioinformatic server framework', 'Papanicolaou, Alexie|Heckel, David G', 'Centre for Conservation and Ecology, University of Exeter in Cornwall, Penryn, UK. alexie@butterflybase.org|Centre for Conservation and Ecology, University of Exeter in Cornwall, Penryn, UK. alexie@butterflybase.org', 'United Kingdom|United Kingdom', 0, 'Computational Biology|Database Management Systems|Databases, Factual|Internet|RNA Interference|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq599', '20971988', 'Next-generation sequencing technologies have led to the widespread use of -omic applications. As a result, there is now a pronounced bioinformatic bottleneck. The general model organism database (GMOD) tool kit (http://gmod.org) has produced a number of resources aimed at addressing this issue. It lacks, however, a robust online solution that can deploy heterogeneous data and software within a Web content management system (CMS).'),
(75833, 2010, 'bio', 'ECCB10 Proceedings of the 9th European Conference on Computational Biology, September 26-29, 2010, Ghent, Belgium', '-', '-', '-', 0, 'Computational Biology', 'Congress', '10.1093/bioinformatics/btq499', '20976873', '-'),
(75834, 2011, 'bio', 'Optimized data fusion for K-means Laplacian clustering', 'Yu, Shi|Liu, Xinhai|Tranchevent, Léon-Charles|Glänzel, Wolfgang|Suykens, Johan A K|De Moor, Bart|Moreau, Yves', 'Signals, Identification, System Theory and Automation, Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium. shiyu@uchicago.edu|Signals, Identification, System Theory and Automation, Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium. shiyu@uchicago.edu|Signals, Identification, System Theory and Automation, Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium. shiyu@uchicago.edu|Signals, Identification, System Theory and Automation, Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium. shiyu@uchicago.edu|Signals, Identification, System Theory and Automation, Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium. shiyu@uchicago.edu|Signals, Identification, System Theory and Automation, Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium. shiyu@uchicago.edu|Signals, Identification, System Theory and Automation, Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium. shiyu@uchicago.edu', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 13, 'Algorithms|Cluster Analysis|Disease|Software', 'Journal Article', '10.1093/bioinformatics/btq569', '20980271', 'We propose a novel algorithm to combine multiple kernels and Laplacians for clustering analysis. The new algorithm is formulated on a Rayleigh quotient objective function and is solved as a bi-level alternating minimization procedure. Using the proposed algorithm, the coefficients of kernels and Laplacians can be optimized automatically.'),
(75835, 2010, 'bio', 'Identification of subfamily-specific sites based on active sites modeling and clustering', 'de Melo-Minardi, Raquel C|Bastard, Karine|Artiguenave, François', 'Department of Computer Science, Federal University of Minas Gerais, Belo Horizonte, Brazil. raquelcm@dcc.ufmg.br|Department of Computer Science, Federal University of Minas Gerais, Belo Horizonte, Brazil. raquelcm@dcc.ufmg.br|Department of Computer Science, Federal University of Minas Gerais, Belo Horizonte, Brazil. raquelcm@dcc.ufmg.br', 'Brazil|Brazil|Brazil', 24, 'Catalytic Domain|Cluster Analysis|Computational Biology|Enzymes|Models, Biological|Molecular Sequence Annotation|Phosphorus-Oxygen Lyases|Protein Kinases|Proteins|Sequence Alignment|Sequence Analysis, Protein|Serine Proteases', 'Journal Article', '10.1093/bioinformatics/btq595', '20980272', 'Current computational approaches to function prediction are mostly based on protein sequence classification and transfer of annotation from known proteins to their closest homologous sequences relying on the orthology concept of function conservation. This approach suffers a major weakness: annotation reliability depends on global sequence similarity to known proteins and is poorly efficient for enzyme superfamilies that catalyze different reactions. Structural biology offers a different strategy to overcome the problem of annotation by adding information about protein 3D structures. This information can be used to identify amino acids located in active sites, focusing on detection of functional polymorphisms residues in an enzyme superfamily. Structural genomics programs are providing more and more novel protein structures at a high-throughput rate. However, there is still a huge gap between the number of sequences and available structures. Computational methods, such as homology modeling provides reliable approaches to bridge this gap and could be a new precise tool to annotate protein functions.'),
(75836, 2010, 'bio', 'Statistical distribution of amino acid sequences: a proof of Darwinian evolution', 'Eitner, Krystian|Koch, Uwe|Gaweda, Tomasz|Marciniak, Jedrzej', 'Adam Mickiewicz University, ul. Grunwaldzka 6, 60-780 Poznaxc5x84, Poland. eitner@amu.edu.pl|Adam Mickiewicz University, ul. Grunwaldzka 6, 60-780 Poznaxc5x84, Poland. eitner@amu.edu.pl|Adam Mickiewicz University, ul. Grunwaldzka 6, 60-780 Poznaxc5x84, Poland. eitner@amu.edu.pl|Adam Mickiewicz University, ul. Grunwaldzka 6, 60-780 Poznaxc5x84, Poland. eitner@amu.edu.pl', 'Poland|Poland|Poland|Poland', 10, 'Amino Acid Sequence|Amino Acids|Computational Biology|Enzymes|Evolution, Molecular|Humans|Oligopeptides|Proteins|Sequence Analysis, Protein|Statistical Distributions', 'Journal Article', '10.1093/bioinformatics/btq571', '21030460', 'The article presents results of the listing of the quantity of amino acids, dipeptides and tripeptides for all proteins available in the UNIPROT-TREMBL database and the listing for selected species and enzymes. UNIPROT-TREMBL contains protein sequences associated with computationally generated annotations and large-scale functional characterization. Due to the distinct metabolic pathways of amino acid syntheses and their physicochemical properties, the quantities of subpeptides in proteins vary. We have proved that the distribution of amino acids, dipeptides and tripeptides is statistical which confirms that the evolutionary biodiversity development model is subject to the theory of independent events. It seems interesting that certain short peptide combinations occur relatively rarely or even not at all. First, it confirms the Darwinian theory of evolution and second, it opens up opportunities for designing pharmaceuticals among rarely represented short peptide combinations. Furthermore, an innovative approach to the mass analysis of bioinformatic data is presented.'),
(75837, 2010, 'bio', 'PPO: predictor for prokaryotic operons', 'Chuang, Li-Yeh|Tsai, Jui-Hung|Yang, Cheng-Hong', 'Department of Chemical Engineering & Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung, Taiwan.|Department of Chemical Engineering & Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung, Taiwan.|Department of Chemical Engineering & Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung, Taiwan.', '-|-|-', 4, 'Algorithms|Computer Graphics|Genome, Bacterial|Operon|Software', 'Journal Article', '10.1093/bioinformatics/btq601', '21030461', 'We present an operon predictor for prokaryotic operons (PPO), which can predict operons in the entire prokaryotic genome. The prediction algorithm used in PPO allows the user to select binary particle swarm optimization (BPSO), a genetic algorithm (GA) or some other methods introduced in the literature to predict operons. The operon predictor on our web server and the provided database are easy to access and use. The main features offered are: (i) selection of the prediction algorithm, (ii) adjustable parameter settings of the prediction algorithm, (iii) graphic visualization of results, (iv) integrated database queries, (v) listing of experimentally verified operons, and (vi) related tools.'),
(75838, 2011, 'bio', 'SPHINX--an algorithm for taxonomic binning of metagenomic sequences', 'Mohammed, Monzoorul Haque|Ghosh, Tarini Shankar|Singh, Nitin Kumar|Mande, Sharmila S', 'Bio-sciences R&D Division, TCS Innovation Labs, Tata Consultancy Services Limited, Madhapur, Hyderabad, Andhra Pradesh, India.|Bio-sciences R&D Division, TCS Innovation Labs, Tata Consultancy Services Limited, Madhapur, Hyderabad, Andhra Pradesh, India.|Bio-sciences R&D Division, TCS Innovation Labs, Tata Consultancy Services Limited, Madhapur, Hyderabad, Andhra Pradesh, India.|Bio-sciences R&D Division, TCS Innovation Labs, Tata Consultancy Services Limited, Madhapur, Hyderabad, Andhra Pradesh, India.', 'India|India|India|India', 45, 'Algorithms|Animals|Cluster Analysis|Databases, Nucleic Acid|Gastrointestinal Tract|Metagenomics|Mice|Sensitivity and Specificity|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btq608', '21030462', 'Compared with composition-based binning algorithms, the binning accuracy and specificity of alignment-based binning algorithms is significantly higher. However, being alignment-based, the latter class of algorithms require enormous amount of time and computing resources for binning huge metagenomic datasets. The motivation was to develop a binning approach that can analyze metagenomic datasets as rapidly as composition-based approaches, but nevertheless has the accuracy and specificity of alignment-based algorithms. This article describes a hybrid binning approach (SPHINX) that achieves high binning efficiency by utilizing the principles of both composition- and alignment-based binning algorithms.'),
(75839, 2011, 'bio', 'A variable selection method for genome-wide association studies', 'He, Qianchuan|Lin, Dan-Yu', 'Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA.|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA.', 'United States|United States', 0, 'Computer Simulation|Genome-Wide Association Study|Linkage Disequilibrium|Logistic Models|Polymorphism, Single Nucleotide|Software', 'Evaluation Studies', '10.1093/bioinformatics/btq600', '21036813', 'Genome-wide association studies (GWAS) involving half a million or more single nucleotide polymorphisms (SNPs) allow genetic dissection of complex diseases in a holistic manner. The common practice of analyzing one SNP at a time does not fully realize the potential of GWAS to identify multiple causal variants and to predict risk of disease. Existing methods for joint analysis of GWAS data tend to miss causal SNPs that are marginally uncorrelated with disease and have high false discovery rates (FDRs).'),
(75840, 2010, 'bio', 'Benchmarking the performance of human antibody gene alignment utilities using a 454 sequence dataset', 'Jackson, Katherine J L|Boyd, Scott|Gaëta, Bruno A|Collins, Andrew M', 'School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia. katherine.jackson@unsw.edu.au|School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia. katherine.jackson@unsw.edu.au|School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia. katherine.jackson@unsw.edu.au|School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia. katherine.jackson@unsw.edu.au', 'Australia|Australia|Australia|Australia', 20, 'Benchmarking|Gene Rearrangement, B-Lymphocyte, Heavy Chain|Genes, Immunoglobulin Heavy Chain|Genotype|Humans|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/btq604', '21036814', 'Immunoglobulin heavy chain genes are formed by recombination of genes randomly selected from sets of IGHV, IGHD and IGHJ genes. Utilities have been developed to identify genes that contribute to observed VDJ rearrangements, but in the absence of datasets of known rearrangements, the evaluation of these utilities is problematic. We have analyzed thousands of VDJ rearrangements from an individual (S22) whose IGHV, IGHD and IGHJ genotype can be inferred from the dataset. Knowledge of this genotype means that the Stanford_S22 dataset can serve to benchmark the performance of IGH alignment utilities.'),
(75841, 2010, 'bio', 'Bayesian sampling of genomic rearrangement scenarios via double cut and join', 'Miklós, István|Tannier, Eric', 'Department of Stochastics, Rényi Institute, Budapest, Hungary. miklosi@renyi.hu|Department of Stochastics, Rényi Institute, Budapest, Hungary. miklosi@renyi.hu', 'Hungary|Hungary', 7, 'Animals|Bayes Theorem|Evolution, Molecular|Genome|Humans|Markov Chains|Models, Genetic|Monte Carlo Method|Saccharomyces cerevisiae', 'Journal Article', '10.1093/bioinformatics/btq574', '21037244', 'When comparing the organization of two genomes, it is important not to draw conclusions on their modes of evolution from a single most parsimonious scenario explaining their differences. Better estimations can be obtained by sampling many different genomic rearrangement scenarios. For this problem, the Double Cut and Join (DCJ) model, while less relevant, is computationally easier than the Hannenhalli-Pevzner (HP) model. Indeed, in some special cases, the total number of DCJ sorting scenarios can be analytically calculated, and uniformly distributed random DCJ scenarios can be drawn in polynomial running time, while the complexity of counting the number of HP scenarios and sampling from the uniform distribution of their space is unknown, and conjectured to be #P-complete. Statistical methods, like Markov chain Monte Carlo (MCMC) for sampling from the uniform distribution of the most parsimonious or the Bayesian distribution of all possible HP scenarios are required.'),
(75842, 2011, 'bio', 'Identification of human-specific transcript variants induced by DNA insertions in the human genome', 'Kim, Dong Seon|Hahn, Yoonsoo', 'Department of Life Science (BK21 Program), Chung-Ang University, Seoul, Korea.|Department of Life Science (BK21 Program), Chung-Ang University, Seoul, Korea.', '-|-', 21, 'Alternative Splicing|Animals|Base Sequence|DNA|DNA Transposable Elements|Evolution, Molecular|Exons|Expressed Sequence Tags|Genetic Variation|Genome, Human|Genomics|Humans|Molecular Sequence Data|Mutagenesis, Insertional|Pan troglodytes|Polyadenylation|Polymorphism, Genetic|Promoter Regions, Genetic|RNA Splice Sites|RNA, Messenger|Species Specificity|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btq612', '21037245', 'Many genes in the human genome produce a wide variety of transcript variants resulting from alternative exon splicing, differential promoter usage, or altered polyadenylation site utilization that may function differently in human cells. Here, we present a bioinformatics method for the systematic identification of human-specific novel transcript variants that might have arisen after the human-chimpanzee divergence.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(75843, 2011, 'bio', 'A stochastic expectation and maximization algorithm for detecting quantitative trait-associated genes', 'Zhan, Haimao|Chen, Xin|Xu, Shizhong', 'Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA.|Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA.|Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA.', 'United States|United States|United States', 0, 'Algorithms|Chromosome Mapping|Cluster Analysis|Gene Expression|Gene Expression Profiling|Gene Regulatory Networks|Genetic Association Studies|Hordeum|Linear Models|Oligonucleotide Array Sequence Analysis|Phenotype|Quantitative Trait Loci|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/btq558', '21037246', 'Most biological traits may be correlated with the underlying gene expression patterns that are partially determined by DNA sequence variation. The correlations between gene expressions and quantitative traits are essential for understanding the functions of genes and dissecting gene regulatory networks.'),
(75844, 2011, 'bio', 'Biological impact of missing-value imputation on downstream analyses of gene expression profiles', 'Oh, Sunghee|Kang, Dongwan D|Brock, Guy N|Tseng, George C', 'Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA.', 'United States|United States|United States|United States', 0, 'Cluster Analysis|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Reproducibility of Results', 'Evaluation Studies', '10.1093/bioinformatics/btq613', '21045072', 'Microarray experiments frequently produce multiple missing values (MVs) due to flaws such as dust, scratches, insufficient resolution or hybridization errors on the chips. Unfortunately, many downstream algorithms require a complete data matrix. The motivation of this work is to determine the impact of MV imputation on downstream analysis, and whether ranking of imputation methods by imputation accuracy correlates well with the biological impact of the imputation.'),
(75845, 2011, 'bio', 'dmGWAS: dense module searching for genome-wide association studies in protein-protein interaction networks', 'Jia, Peilin|Zheng, Siyuan|Long, Jirong|Zheng, Wei|Zhao, Zhongming', 'Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA.', 'United States|United States|United States|United States|United States', 0, 'Breast Neoplasms|Female|Gene Regulatory Networks|Genome-Wide Association Study|Humans|Pancreatic Neoplasms|Polymorphism, Single Nucleotide|Protein Interaction Mapping|Software', 'Journal Article', '10.1093/bioinformatics/btq615', '21045073', 'An important question that has emerged from the recent success of genome-wide association studies (GWAS) is how to detect genetic signals beyond single markers/genes in order to explore their combined effects on mediating complex diseases and traits. Integrative testing of GWAS association data with that from prior-knowledge databases and proteome studies has recently gained attention. These methodologies may hold promise for comprehensively examining the interactions between genes underlying the pathogenesis of complex diseases.'),
(75846, 2010, 'bio', 'Characterizing the regularity of tetrahedral packing motifs in protein tertiary structure', 'Day, Ryan|Lennox, Kristin P|Dahl, David B|Vannucci, Marina|Tsai, Jerry W', 'Department of Chemistry, University of the Pacific, Stockton, CA 95211, USA.|Department of Chemistry, University of the Pacific, Stockton, CA 95211, USA.|Department of Chemistry, University of the Pacific, Stockton, CA 95211, USA.|Department of Chemistry, University of the Pacific, Stockton, CA 95211, USA.|Department of Chemistry, University of the Pacific, Stockton, CA 95211, USA.', 'United States|United States|United States|United States|United States', 0, 'Amino Acid Motifs|Models, Molecular|Models, Statistical|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1093/bioinformatics/btq573', '21047817', 'While protein secondary structure is well understood, representing the repetitive nature of tertiary packing in proteins remains difficult. We have developed a construct called the relative packing group (RPG) that applies the clique concept from graph theory as a natural basis for defining the packing motifs in proteins. An RPG is defined as a clique of residues, where every member contacts all others as determined by the Delaunay tessellation. Geometrically similar RPGs define a regular element of tertiary structure or tertiary motif (TerMo). This intuitive construct provides a simple approach to characterize general repetitive elements of tertiary structure.'),
(75847, 2011, 'bio', 'Accelerating reaction-diffusion simulations with general-purpose graphics processing units', 'Vigelius, Matthias|Lane, Aidan|Meyer, Bernd', 'FIT Centre for Research in Intelligent Systems, Monash University, Clayton, Victoria, Australia. matthias.vigelius@monash.edu|FIT Centre for Research in Intelligent Systems, Monash University, Clayton, Victoria, Australia. matthias.vigelius@monash.edu|FIT Centre for Research in Intelligent Systems, Monash University, Clayton, Victoria, Australia. matthias.vigelius@monash.edu', 'Australia|Australia|Australia', 27, 'Algorithms|Computer Graphics|Computing Methodologies|Software|Stochastic Processes', 'Evaluation Studies', '10.1093/bioinformatics/btq622', '21062761', 'We present a massively parallel stochastic simulation algorithm (SSA) for reaction-diffusion systems implemented on Graphics Processing Units (GPUs). These are designated chips optimized to process a high number of floating point operations in parallel, rendering them well-suited for a range of scientific high-performance computations. Newer GPU generations provide a high-level programming interface which turns them into General-Purpose Graphics Processing Units (GPGPUs). Our SSA exploits GPGPU architecture to achieve a performance gain of two orders of magnitude over the fastest existing implementations on conventional hardware.'),
(75848, 2011, 'bio', 'Inverse perturbation for optimal intervention in gene regulatory networks', 'Bouaynaya, Nidhal|Shterenberg, Roman|Schonfeld, Dan', 'Department of Systems Engineering, University of Arkansas at Little Rock, Little Rock, AR 72204, USA. nxbouaynaya@ualr.edu|Department of Systems Engineering, University of Arkansas at Little Rock, Little Rock, AR 72204, USA. nxbouaynaya@ualr.edu|Department of Systems Engineering, University of Arkansas at Little Rock, Little Rock, AR 72204, USA. nxbouaynaya@ualr.edu', 'United States|United States|United States', 11, 'Gene Expression Regulation|Gene Regulatory Networks|Humans|Markov Chains|Melanoma|Models, Statistical|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/btq605', '21062762', 'Analysis and intervention in the dynamics of gene regulatory networks is at the heart of emerging efforts in the development of modern treatment of numerous ailments including cancer. The ultimate goal is to develop methods to intervene in the function of living organisms in order to drive cells away from a malignant state into a benign form. A serious limitation of much of the previous work in cancer network analysis is the use of external control, which requires intervention at each time step, for an indefinite time interval. This is in sharp contrast to the proposed approach, which relies on the solution of an inverse perturbation problem to introduce a one-time intervention in the structure of regulatory networks. This isolated intervention transforms the steady-state distribution of the dynamic system to the desired steady-state distribution.'),
(75849, 2011, 'bio', 'Improved performance on high-dimensional survival data by application of Survival-SVM', 'Van Belle, V|Pelckmans, K|Van Huffel, S|Suykens, J A K', 'Department of Electrical Engineering (ESAT), Katholieke Universiteit Leuven, Leuven, Belgium. vanya.vanbelle@esat.kuleuven.be|Department of Electrical Engineering (ESAT), Katholieke Universiteit Leuven, Leuven, Belgium. vanya.vanbelle@esat.kuleuven.be|Department of Electrical Engineering (ESAT), Katholieke Universiteit Leuven, Leuven, Belgium. vanya.vanbelle@esat.kuleuven.be|Department of Electrical Engineering (ESAT), Katholieke Universiteit Leuven, Leuven, Belgium. vanya.vanbelle@esat.kuleuven.be', 'Belgium|Belgium|Belgium|Belgium', 0, 'Artificial Intelligence|Gene Expression Profiling|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis|Survival Analysis', 'Evaluation Studies', '10.1093/bioinformatics/btq617', '21062763', 'New application areas of survival analysis as for example based on micro-array expression data call for novel tools able to handle high-dimensional data. While classical (semi-) parametric techniques as based on likelihood or partial likelihood functions are omnipresent in clinical studies, they are often inadequate for modelling in case when there are less observations than features in the data. Support vector machines (svms) and extensions are in general found particularly useful for such cases, both conceptually (non-parametric approach), computationally (boiling down to a convex program which can be solved efficiently), theoretically (for its intrinsic relation with learning theory) as well as empirically. This article discusses such an extension of svms which is tuned towards survival data. A particularly useful feature is that this method can incorporate such additional structure as additive models, positivity constraints of the parameters or regression constraints.'),
(75850, 2011, 'bio', 'NBC: the Naive Bayes Classification tool webserver for taxonomic classification of metagenomic reads', 'Rosen, Gail L|Reichenberger, Erin R|Rosenfeld, Aaron M', 'Department of Electrical and Computer Engineering, Drexel University, Philadelphia, PA, USA. gailr@ece.drexel.edu|Department of Electrical and Computer Engineering, Drexel University, Philadelphia, PA, USA. gailr@ece.drexel.edu|Department of Electrical and Computer Engineering, Drexel University, Philadelphia, PA, USA. gailr@ece.drexel.edu', 'United States|United States|United States', 0, 'Algorithms|Bayes Theorem|High-Throughput Nucleotide Sequencing|Internet|Metagenomics|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btq619', '21062764', 'Datasets from high-throughput sequencing technologies have yielded a vast amount of data about organisms in environmental samples. Yet, it is still a challenge to assess the exact organism content in these samples because the task of taxonomic classification is too computationally complex to annotate all reads in a dataset. An easy-to-use webserver is needed to process these reads. While many methods exist, only a few are publicly available on webservers, and out of those, most do not annotate all reads.'),
(75851, 2011, 'bio', 'A hybrid approach to extract protein-protein interactions', 'Bui, Quoc-Chinh|Katrenko, Sophia|Sloot, Peter M A', 'Computational Science, Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands. bqchinh@gmail.com|Computational Science, Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands. bqchinh@gmail.com|Computational Science, Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands. bqchinh@gmail.com', 'Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Animals|Artificial Intelligence|Data Mining|Protein Interaction Mapping', 'Evaluation Studies', '10.1093/bioinformatics/btq620', '21062765', 'Protein-protein interactions (PPIs) play an important role in understanding biological processes. Although recent research in text mining has achieved a significant progress in automatic PPI extraction from literature, performance of existing systems still needs to be improved.'),
(75852, 2011, 'bio', 'Improving evolutionary models of protein interaction networks', 'Gibson, Todd A|Goldberg, Debra S', 'Department of Computer Science, University of Colorado, 430 UCB, Boulder, CO 80309, USA.|Department of Computer Science, University of Colorado, 430 UCB, Boulder, CO 80309, USA.', 'United States|United States', 0, 'Cluster Analysis|Evolution, Molecular|Models, Biological|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1093/bioinformatics/btq623', '21067999', 'Theoretical models of biological networks are valuable tools in evolutionary inference. Theoretical models based on gene duplication and divergence provide biologically plausible evolutionary mechanics. Similarities found between empirical networks and their theoretically generated counterpart are considered evidence of the role modeled mechanics play in biological evolution. However, the method by which these models are parameterized can lead to questions about the validity of the inferences. Selecting parameter values in order to produce a particular topological value obfuscates the possibility that the model may produce a similar topology for a large range of parameter values. Alternately, a model may produce a large range of topologies, allowing (incorrect) parameter values to produce a valid topology from an otherwise flawed model. In order to lend biological credence to the modeled evolutionary mechanics, parameter values should be derived from the empirical data. Furthermore, recent work indicates that the timing and fate of gene duplications are critical to proper derivation of these parameters.'),
(75853, 2011, 'bio', 'Generation of a consensus protein domain dictionary', 'Schaeffer, R Dustin|Jonsson, Amanda L|Simms, Andrew M|Daggett, Valerie', 'Biomolecular Structure and Design Program, University of Washington, Seattle, WA 98195-5013, USA.|Biomolecular Structure and Design Program, University of Washington, Seattle, WA 98195-5013, USA.|Biomolecular Structure and Design Program, University of Washington, Seattle, WA 98195-5013, USA.|Biomolecular Structure and Design Program, University of Washington, Seattle, WA 98195-5013, USA.', 'United States|United States|United States|United States', 0, 'Computational Biology|Dictionaries as Topic|Models, Molecular|Molecular Sequence Annotation|Protein Folding|Protein Structure, Tertiary', 'Journal Article', '10.1093/bioinformatics/btq625', '21068000', 'The discovery of new protein folds is a relatively rare occurrence even as the rate of protein structure determination increases. This rarity reinforces the concept of folds as reusable units of structure and function shared by diverse proteins. If the folding mechanism of proteins is largely determined by their topology, then the folding pathways of members of existing folds could encompass the full set used by globular protein domains.'),
(75854, 2011, 'bio', 'PriSM: a primer selection and matching tool for amplification and sequencing of viral genomes', 'Yu, Qing|Ryan, Elizabeth M|Allen, Todd M|Birren, Bruce W|Henn, Matthew R|Lennon, Niall J', 'Broad Institute of MIT & Harvard, Cambridge, MA 02142, USA.|Broad Institute of MIT & Harvard, Cambridge, MA 02142, USA.|Broad Institute of MIT & Harvard, Cambridge, MA 02142, USA.|Broad Institute of MIT & Harvard, Cambridge, MA 02142, USA.|Broad Institute of MIT & Harvard, Cambridge, MA 02142, USA.|Broad Institute of MIT & Harvard, Cambridge, MA 02142, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|DNA Primers|Genome, Viral|HIV|Humans|Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btq624', '21068001', 'PriSM is a set of algorithms designed to select and match degenerate primer pairs for the amplification of viral genomes. The design of panels of hundreds of primer pairs takes just hours using this program, compared with days using a manual approach. PriSM allows for rapid in silico optimization of primers for downstream applications such as sequencing. As a validation, PriSM was used to create an amplification primer panel for human immunodeficiency virus (HIV) Clade B.'),
(75855, 2010, 'bio', 'The necessity of adjusting tests of protein category enrichment in discovery proteomics', 'Louie, Brenton|Higdon, Roger|Kolker, Eugene', 'Bioinformatics and High-throughput Analysis Laboratory, Seattle Childrens Research Institute, Seattle, WA 98101, USA.|Bioinformatics and High-throughput Analysis Laboratory, Seattle Childrens Research Institute, Seattle, WA 98101, USA.|Bioinformatics and High-throughput Analysis Laboratory, Seattle Childrens Research Institute, Seattle, WA 98101, USA.', 'United States|United States|United States', 6, 'Fungal Proteins|Hydrophobic and Hydrophilic Interactions|Logistic Models|Mass Spectrometry|Peptides|Proteins|Proteomics', 'Journal Article', '10.1093/bioinformatics/btq541', '21068002', 'Enrichment tests are used in high-throughput experimentation to measure the association between gene or protein expression and membership in groups or pathways. The Fishers exact test is commonly used. We specifically examined the associations produced by the Fisher test between protein identification by mass spectrometry discovery proteomics, and their Gene Ontology (GO) term assignments in a large yeast dataset. We found that direct application of the Fisher test is misleading in proteomics due to the bias in mass spectrometry to preferentially identify proteins based on their biochemical properties. False inference about associations can be made if this bias is not corrected. Our method adjusts Fisher tests for these biases and produces associations more directly attributable to protein expression rather than experimental bias.'),
(75856, 2011, 'bio', 'Fast and efficient dynamic nested effects models', 'Fröhlich, Holger|Praveen, Paurush|Tresch, Achim', 'Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn-Aachen International Center for IT, Bonn, Germany. frohlich@bit.uni-bonn.de|Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn-Aachen International Center for IT, Bonn, Germany. frohlich@bit.uni-bonn.de|Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn-Aachen International Center for IT, Bonn, Germany. frohlich@bit.uni-bonn.de', 'Germany|Germany|Germany', 0, 'Animals|Computer Simulation|Embryonic Stem Cells|Gene Regulatory Networks|Mice|Models, Biological|Models, Statistical|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btq631', '21068003', 'Targeted interventions in combination with the measurement of secondary effects can be used to computationally reverse engineer features of upstream non-transcriptional signaling cascades. Nested effect models (NEMs) have been introduced as a statistical approach to estimate the upstream signal flow from downstream nested subset structure of perturbation effects. The method was substantially extended later on by several authors and successfully applied to various datasets. The connection of NEMs to Bayesian Networks and factor graph models has been highlighted.'),
(75857, 2011, 'bio', 'The uniqueome: a mappability resource for short-tag sequencing', 'Koehler, Ryan|Issac, Hadar|Cloonan, Nicole|Grimmond, Sean M', 'VerdAscend Sciences, West Linn, OR 97068, USA.|VerdAscend Sciences, West Linn, OR 97068, USA.|VerdAscend Sciences, West Linn, OR 97068, USA.|VerdAscend Sciences, West Linn, OR 97068, USA.', 'United States|United States|United States|United States', 0, 'Animals|Chromosome Mapping|Genome|Genomics|Humans|Mice|Sequence Analysis, RNA|Sequence Tagged Sites|Software', 'Journal Article', '10.1093/bioinformatics/btq640', '21075741', 'Quantification applications of short-tag sequencing data (such as CNVseq and RNAseq) depend on knowing the uniqueness of specific genomic regions at a given threshold of error. Here, we present the uniqueome, a genomic resource for understanding the uniquely mappable proportion of genomic sequences. Pre-computed data are available for human, mouse, fly and worm genomes in both color-space and nucletotide-space, and we demonstrate the utility of this resource as applied to the quantification of RNAseq data.'),
(75858, 2011, 'bio', 'Inference of gene networks--application to Bifidobacterium', 'Lai, Darong|Yang, Xinyi|Wu, Gang|Liu, Yuanhua|Nardini, Christine', 'Key Laboratory of Computational Biology, Chinese Academy of Sciences Max Planck Institute Partner Institute for Computational Biology (CAS-MPG), Shanghai, Peoples Republic of China.|Key Laboratory of Computational Biology, Chinese Academy of Sciences Max Planck Institute Partner Institute for Computational Biology (CAS-MPG), Shanghai, Peoples Republic of China.|Key Laboratory of Computational Biology, Chinese Academy of Sciences Max Planck Institute Partner Institute for Computational Biology (CAS-MPG), Shanghai, Peoples Republic of China.|Key Laboratory of Computational Biology, Chinese Academy of Sciences Max Planck Institute Partner Institute for Computational Biology (CAS-MPG), Shanghai, Peoples Republic of China.|Key Laboratory of Computational Biology, Chinese Academy of Sciences Max Planck Institute Partner Institute for Computational Biology (CAS-MPG), Shanghai, Peoples Republic of China.', 'China|China|China|China|China', 0, 'Algorithms|Bifidobacterium|Gene Regulatory Networks|Software', 'Journal Article', '10.1093/bioinformatics/btq629', '21075742', 'The reliable and reproducible identification of gene interaction networks represents one of the grand challenges of both modern molecular biology and computational sciences. Approaches based on careful collection of literature data and network topological analysis, applied to unicellular organisms, have proven to offer results applicable to medical therapies. However, when little a priori knowledge is available, other approaches, not relying so strongly on previous literature, must be used. We propose here a novel algorithm (based on ordinary differential equations) able to infer the interactions occurring among genes, starting from gene expression steady state data.'),
(75859, 2011, 'bio', 'Analyzing marginal cases in differential shotgun proteomics', 'Carvalho, Paulo C|Fischer, Juliana S G|Perales, Jonas|Yates, John R|Barbosa, Valmir C|Bareinboim, Elias', 'Center for Technological Development in Health, Oswaldo Cruz Institute, Rio de Janeiro, Brazil. paulo@pcarvalho.com|Center for Technological Development in Health, Oswaldo Cruz Institute, Rio de Janeiro, Brazil. paulo@pcarvalho.com|Center for Technological Development in Health, Oswaldo Cruz Institute, Rio de Janeiro, Brazil. paulo@pcarvalho.com|Center for Technological Development in Health, Oswaldo Cruz Institute, Rio de Janeiro, Brazil. paulo@pcarvalho.com|Center for Technological Development in Health, Oswaldo Cruz Institute, Rio de Janeiro, Brazil. paulo@pcarvalho.com|Center for Technological Development in Health, Oswaldo Cruz Institute, Rio de Janeiro, Brazil. paulo@pcarvalho.com', 'Brazil|Brazil|Brazil|Brazil|Brazil|Brazil', 0, 'Bayes Theorem|Proteins|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/btq632', '21075743', 'We present an approach to statistically pinpoint differentially expressed proteins that have quantitation values near the quantitation threshold and are not identified in all replicates (marginal cases). Our method uses a Bayesian strategy to combine parametric statistics with an empirical distribution built from the reproducibility quality of the technical replicates.'),
(75860, 2011, 'bio', 'Evolutionary design principles and functional characteristics based on kingdom-specific network motifs', 'Kim, Tae-Hwan|Kim, Junil|Heslop-Harrison, Pat|Cho, Kwang-Hyun', 'Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.', '-|-|-|-', 15, 'Arabidopsis|Biological Evolution|Feedback, Physiological|Humans|Models, Biological|Protein Interaction Mapping|Saccharomyces cerevisiae', 'Journal Article', '10.1093/bioinformatics/btq633', '21075744', 'Network motifs within biological networks show non-random abundances in systems at different scales. Large directed protein networks at the cellular level are now well defined in several diverse species. We aimed to compare the nature of significantly observed two- and three-node network motifs across three different kingdoms (Arabidopsis thaliana for multicellular plants, Saccharomyces cerevisiae for unicellular fungi and Homo sapiens for animals).'),
(75861, 2011, 'bio', 'Protein Peeling 3D: new tools for analyzing protein structures', 'Gelly, Jean-Christophe|de Brevern, Alexandre G', 'Dynamique des Structures et Interactions des Macromolécules Biologiques, INSERM UMR-S 665, Université Paris Diderot-Paris 7, Paris, France. jean-christophe.gelly@univ-paris-diderot.fr|Dynamique des Structures et Interactions des Macromolécules Biologiques, INSERM UMR-S 665, Université Paris Diderot-Paris 7, Paris, France. jean-christophe.gelly@univ-paris-diderot.fr', 'France|France', 0, 'Algorithms|Computer Graphics|Internet|Models, Molecular|Protein Conformation|Protein Structure, Tertiary|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq610', '21075745', 'We present an improved version of our Protein Peeling web server dedicated to the analysis of protein structure architecture through the identification of protein units produced by an iterative splitting algorithm. New features include identification of structural domains, detection of unstructured terminal elements and evaluation of the stability of protein unit structures.'),
(75862, 2011, 'bio', 'Assigning duplication events to relative temporal scales in genome-wide studies', 'Huerta-Cepas, Jaime|Gabaldón, Toni', 'Centre for Genomic Regulation (CRG), Barcelona, Spain.|Centre for Genomic Regulation (CRG), Barcelona, Spain.', 'Spain|Spain', 0, 'Animals|Evolution, Molecular|Gene Duplication|Genome|Genomics|Humans|Mice|Phylogeny', 'Journal Article', '10.1093/bioinformatics/btq609', '21075746', 'In genome-wide analyses, the relative age of gene duplications is often estimated by measuring the rate of synonymous substitutions (dS) between paralogous sequences. On the other hand, recent studies have shown the feasibility of inferring, at genomic scales, the relative age of duplication events from the topology of gene family trees. This represents a promising alternative for large surveys requiring an automatic methodology to establish a timeline of duplication events and that are usually limited to the use of dS, which presents known limitations such as a fast saturation of the signal. However, both measures have never been compared in a common framework.'),
(75863, 2011, 'bio', 'QuACN: an R package for analyzing complex biological networks quantitatively', 'Mueller, Laurin A J|Kugler, Karl G|Dander, Andreas|Graber, Armin|Dehmer, Matthias', 'Department of Biomedical Sciences and Engineering, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall in Tirol, Austria. laurin.mueller@umit.at|Department of Biomedical Sciences and Engineering, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall in Tirol, Austria. laurin.mueller@umit.at|Department of Biomedical Sciences and Engineering, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall in Tirol, Austria. laurin.mueller@umit.at|Department of Biomedical Sciences and Engineering, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall in Tirol, Austria. laurin.mueller@umit.at|Department of Biomedical Sciences and Engineering, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall in Tirol, Austria. laurin.mueller@umit.at', 'Austria|Austria|Austria|Austria|Austria', 0, 'Models, Biological|Software', 'Journal Article', '10.1093/bioinformatics/btq606', '21075747', 'Network-based representations of biological data have become an important way to analyze high-throughput data. To interpret the large amount of data that is produced by different high-throughput technologies, networks offer multifaceted aspects to analyze the data. As networks represent biological relationships within their structure, it turned out to be fruitful to analyze their topology. Therefore, we developed a freely available, open source R-package called Quantitative Analysis of Complex Networks (QuACN) to meet this challenge. QuACN contains different, information-theoretic and non-information-theoretic, topological network descriptors to analyze, classify and compare biological networks.'),
(75864, 2011, 'bio', 'Differential effects of chromatin regulators and transcription factors on gene regulation: a nucleosomal perspective', 'Dong, Dong|Shao, Xiaojian|Zhang, Zhaolei', 'Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.|Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.|Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.', 'Canada|Canada|Canada', 1, 'Chromatin|Chromosomes|Gene Expression Regulation|Histones|Nucleosomes|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btq637', '21075748', 'Chromatin regulators (CR) and transcription factors (TF) are important trans-acting factors regulating transcription process, and many efforts have been devoted to understand their underlying mechanisms in gene regulation. However, the influences of CR and TF regulation effects on nucleosomes during transcription are still minimally understood, and it remains to be determined the extent to which CR and TF regulatory effect shape the organization of nucleosomes in the genome. In this article we attempted to address this problem and examine the patterns of CR and TF regulation effects from the nucleosome perspective.'),
(75865, 2011, 'bio', 'TE Displayer for post-genomic analysis of transposable elements', 'Rooke, Rebecca|Yang, Guojun', 'Department of Cell and Systems Biology, University of Toronto, Toronto, Canada.|Department of Cell and Systems Biology, University of Toronto, Toronto, Canada.', 'Canada|Canada', 3, 'Algorithms|Animals|DNA Transposable Elements|Genomics|Polymorphism, Genetic|Software', 'Journal Article', '10.1093/bioinformatics/btq639', '21075749', 'TE Displayer can be used to retrieve genetic polymorphisms caused by transposable elements (TEs) in large-genomic datasets and present the results on virtual gel images. This enables researchers to compare TE profiles in silico and provides reference profiles for experimental analyses.'),
(75866, 2011, 'bio', 'PLEXY: efficient target prediction for box C/D snoRNAs', 'Kehr, Stephanie|Bartschat, Sebastian|Stadler, Peter F|Tafer, Hakim', 'Department of Computer Science, University of Leipzig, Leipzig, Germany. steffi@bioinf.uni-leipzig.de|Department of Computer Science, University of Leipzig, Leipzig, Germany. steffi@bioinf.uni-leipzig.de|Department of Computer Science, University of Leipzig, Leipzig, Germany. steffi@bioinf.uni-leipzig.de|Department of Computer Science, University of Leipzig, Leipzig, Germany. steffi@bioinf.uni-leipzig.de', 'Germany|Germany|Germany|Germany', 35, 'Algorithms|RNA, Messenger|RNA, Ribosomal|RNA, Small Nucleolar|Sequence Analysis, RNA|Software|Thermodynamics', 'Journal Article', '10.1093/bioinformatics/btq642', '21076148', 'Small nucleolar RNAs (snoRNAs) are an abundant class of non-coding RNAs with a wide variety of cellular functions including chemical modification of RNA, telomere maintanance, pre-rRNA processing and regulatory activities in alternative splicing. The main role of box C/D snoRNAs is to determine the targets for 2-O-ribose methylation, which is important for rRNA maturation and splicing regulation of some mRNAs. The targets are still unknown, however, for many orphan snoRNAs. While a fast and efficient target predictor for box H/ACA snoRNAs is available, no comparable tool exists for box C/D snoRNAs, even though they bind to their targets in a much less complex manner.'),
(75867, 2010, 'bio', 'Statistical confidence measures for genome maps: application to the validation of genome assemblies', 'Servin, Bertrand|de Givry, Simon|Faraut, Thomas', 'INRA Toulouse-Laboratoire de Génétique Cellulaire, Castanet-Tolosan, France. Bertrand.Servin@toulouse.inra.fr|INRA Toulouse-Laboratoire de Génétique Cellulaire, Castanet-Tolosan, France. Bertrand.Servin@toulouse.inra.fr|INRA Toulouse-Laboratoire de Génétique Cellulaire, Castanet-Tolosan, France. Bertrand.Servin@toulouse.inra.fr', 'France|France|France', 0, 'Algorithms|Animals|Chromosome Mapping|Chromosomes, Mammalian|Data Interpretation, Statistical|Dogs|Genetic Markers|Genome|Radiation Hybrid Mapping|Software', 'Journal Article', '10.1093/bioinformatics/btq598', '21076149', 'Genome maps are imperative to address the genetic basis of the biology of an organism. While a growing number of genomes are being sequenced providing the ultimate genome maps-this being done at an even faster pace now using new generation sequencers-the process of constructing intermediate maps to build and validate a genome assembly remains an important component for producing complete genome sequences. However, current mapping approach lack statistical confidence measures necessary to identify precisely relevant inconsistencies between a genome map and an assembly.'),
(75868, 2011, 'bio', 'Automated construction and testing of multi-locus gene-gene associations', 'Abo, Ryan|Knight, Stacey|Thomas, Alun|Camp, Nicola J', 'Department of Biomedical Informatics, University of Utah School of Medicine, UT, USA. ryan.abo@hsc.utah.edu|Department of Biomedical Informatics, University of Utah School of Medicine, UT, USA. ryan.abo@hsc.utah.edu|Department of Biomedical Informatics, University of Utah School of Medicine, UT, USA. ryan.abo@hsc.utah.edu|Department of Biomedical Informatics, University of Utah School of Medicine, UT, USA. ryan.abo@hsc.utah.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Genes|Genetic Association Studies|Genetic Loci|Haplotypes|Monte Carlo Method|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btq616', '21076150', 'It has been argued that the missing heritability in common diseases may be in part due to rare variants and gene-gene effects. Haplotype analyses provide more power for rare variants and joint analyses across genes can address multi-gene effects. Currently, methods are lacking to perform joint multi-locus association analyses across more than one gene/region. Here, we present a haplotype-mining gene-gene analysis method, which considers multi-locus data for two genes/regions simultaneously. This approach extends our single region haplotype-mining algorithm, hapConstructor, to two genes/regions. It allows construction of multi-locus SNP sets at both genes and tests joint gene-gene effects and interactions between single variants or haplotype combinations. A Monte Carlo framework is used to provide statistical significance assessment of the joint and interaction statistics, thus the method can also be used with related individuals. This tool provides a flexible data-mining approach to identifying gene-gene effects that otherwise is currently unavailable.'),
(75869, 2011, 'bio', 'Control-free calling of copy number alterations in deep-sequencing data using GC-content normalization', 'Boeva, Valentina|Zinovyev, Andrei|Bleakley, Kevin|Vert, Jean-Philippe|Janoueix-Lerosey, Isabelle|Delattre, Olivier|Barillot, Emmanuel', 'Institut Curie, INSERM, U900, Paris, France. freec@curie.fr|Institut Curie, INSERM, U900, Paris, France. freec@curie.fr|Institut Curie, INSERM, U900, Paris, France. freec@curie.fr|Institut Curie, INSERM, U900, Paris, France. freec@curie.fr|Institut Curie, INSERM, U900, Paris, France. freec@curie.fr|Institut Curie, INSERM, U900, Paris, France. freec@curie.fr|Institut Curie, INSERM, U900, Paris, France. freec@curie.fr', 'France|France|France|France|France|France|France', 159, 'Algorithms|Base Composition|Cell Line, Tumor|Cytosine|DNA Copy Number Variations|Genomics|Guanine|High-Throughput Nucleotide Sequencing|Humans|Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/btq635', '21081509', 'We present a tool for control-free copy number alteration (CNA) detection using deep-sequencing data, particularly useful for cancer studies. The tool deals with two frequent problems in the analysis of cancer deep-sequencing data: absence of control sample and possible polyploidy of cancer cells. FREEC (control-FREE Copy number caller) automatically normalizes and segments copy number profiles (CNPs) and calls CNAs. If ploidy is known, FREEC assigns absolute copy number to each predicted CNA. To normalize raw CNPs, the user can provide a control dataset if available, otherwise GC content is used. We demonstrate that for Illumina single-end, mate-pair or paired-end sequencing, GC-contentr normalization provides smooth profiles that can be further segmented and analyzed in order to predict CNAs.'),
(75870, 2010, 'bio', 'iMAT: an integrative metabolic analysis tool', 'Zur, Hadas|Ruppin, Eytan|Shlomi, Tomer', 'The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel. zurhadas@post.tau.ac.il|The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel. zurhadas@post.tau.ac.il|The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel. zurhadas@post.tau.ac.il', 'Israel|Israel|Israel', 0, 'Gene Expression Profiling|Genome|Metabolic Networks and Pathways|Models, Biological|Principal Component Analysis|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/btq602', '21081510', 'iMAT is an Integrative Metabolic Analysis Tool, enabling the integration of transcriptomic and proteomic data with genome-scale metabolic network models to predict enzymes metabolic flux, based on the method previously described by Shlomi et al. The prediction of metabolic fluxes based on high-throughput molecular data sources could help to advance our understanding of cellular metabolism, since current experimental approaches are limited to measuring fluxes through merely a few dozen enzymes.'),
(75871, 2011, 'bio', 'GimmeMotifs: a de novo motif prediction pipeline for ChIP-sequencing experiments', 'van Heeringen, Simon J|Veenstra, Gert Jan C', 'Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen, Nijmegen, The Netherlands. s.vanheeringen@ncmls.ru.nl|Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen, Nijmegen, The Netherlands. s.vanheeringen@ncmls.ru.nl', 'Netherlands|Netherlands', 65, 'Algorithms|Animals|Binding Sites|Chromatin Immunoprecipitation|Computational Biology|Humans|Mice|Sequence Analysis, DNA|Software|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/btq636', '21081511', 'Accurate prediction of transcription factor binding motifs that are enriched in a collection of sequences remains a computational challenge. Here we report on GimmeMotifs, a pipeline that incorporates an ensemble of computational tools to predict motifs de novo from ChIP-sequencing (ChIP-seq) data. Similar redundant motifs are compared using the weighted information content (WIC) similarity score and clustered using an iterative procedure. A comprehensive output report is generated with several different evaluation metrics to compare and evaluate the results. Benchmarks show that the method performs well on human and mouse ChIP-seq datasets. GimmeMotifs consists of a suite of command-line scripts that can be easily implemented in a ChIP-seq analysis pipeline.'),
(75872, 2011, 'bio', 'SESAME (SEquence Sorter & AMplicon Explorer): genotyping based on high-throughput multiplex amplicon sequencing', 'Meglécz, Emese|Piry, Sylvain|Desmarais, Erick|Galan, Maxime|Gilles, André|Guivier, Emmanuel|Pech, Nicolas|Martin, Jean-François', 'Aix-Marseille Université, CNRS, IRD, UMR 6116-IMEP, Equipe Evolution, Génome et Environnement, Marseille, France. emese.meglecz@univ-provence.fr|Aix-Marseille Université, CNRS, IRD, UMR 6116-IMEP, Equipe Evolution, Génome et Environnement, Marseille, France. emese.meglecz@univ-provence.fr|Aix-Marseille Université, CNRS, IRD, UMR 6116-IMEP, Equipe Evolution, Génome et Environnement, Marseille, France. emese.meglecz@univ-provence.fr|Aix-Marseille Université, CNRS, IRD, UMR 6116-IMEP, Equipe Evolution, Génome et Environnement, Marseille, France. emese.meglecz@univ-provence.fr|Aix-Marseille Université, CNRS, IRD, UMR 6116-IMEP, Equipe Evolution, Génome et Environnement, Marseille, France. emese.meglecz@univ-provence.fr|Aix-Marseille Université, CNRS, IRD, UMR 6116-IMEP, Equipe Evolution, Génome et Environnement, Marseille, France. emese.meglecz@univ-provence.fr|Aix-Marseille Université, CNRS, IRD, UMR 6116-IMEP, Equipe Evolution, Génome et Environnement, Marseille, France. emese.meglecz@univ-provence.fr|Aix-Marseille Université, CNRS, IRD, UMR 6116-IMEP, Equipe Evolution, Génome et Environnement, Marseille, France. emese.meglecz@univ-provence.fr', 'France|France|France|France|France|France|France|France', 18, 'Alleles|Genotype|High-Throughput Nucleotide Sequencing|Internet|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq641', '21084284', 'Characterizing genetic diversity through genotyping short amplicons is central to evolutionary biology. Next-generation sequencing (NGS) technologies changed the scale at which these type of data are acquired. SESAME is a web application package that assists genotyping of multiplexed individuals for several markers based on NGS amplicon sequencing. It automatically assigns reads to loci and individuals, corrects reads if standard samples are available and provides an intuitive graphical user interface (GUI) for allele validation based on the sequences and associated decision-making tools. The aim of SESAME is to help allele identification among a large number of sequences.'),
(75873, 2011, 'bio', 'PETcofold: predicting conserved interactions and structures of two multiple alignments of RNA sequences', 'Seemann, Stefan E|Richter, Andreas S|Gesell, Tanja|Backofen, Rolf|Gorodkin, Jan', 'Center for non-coding RNA in Technology and Health, University of Copenhagen, Frederiksberg C, Denmark.|Center for non-coding RNA in Technology and Health, University of Copenhagen, Frederiksberg C, Denmark.|Center for non-coding RNA in Technology and Health, University of Copenhagen, Frederiksberg C, Denmark.|Center for non-coding RNA in Technology and Health, University of Copenhagen, Frederiksberg C, Denmark.|Center for non-coding RNA in Technology and Health, University of Copenhagen, Frederiksberg C, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark', 0, 'Algorithms|Animals|Base Pairing|Base Sequence|Conserved Sequence|Molecular Sequence Data|Nucleic Acid Conformation|RNA, Bacterial|RNA, Messenger|RNA, Small Nucleolar|RNA, Untranslated|Sequence Alignment|Sequence Analysis, RNA|Software|Vertebrates', 'Evaluation Studies', '10.1093/bioinformatics/btq634', '21088024', 'Predicting RNA-RNA interactions is essential for determining the function of putative non-coding RNAs. Existing methods for the prediction of interactions are all based on single sequences. Since comparative methods have already been useful in RNA structure determination, we assume that conserved RNA-RNA interactions also imply conserved function. Of these, we further assume that a non-negligible amount of the existing RNA-RNA interactions have also acquired compensating base changes throughout evolution. We implement a method, PETcofold, that can take covariance information in intra-molecular and inter-molecular base pairs into account to predict interactions and secondary structures of two multiple alignments of RNA sequences.'),
(75874, 2011, 'bio', 'SAMStat: monitoring biases in next generation sequencing data', 'Lassmann, Timo|Hayashizaki, Yoshihide|Daub, Carsten O', 'Omics Science Center, Riken Yokohama Institute, Tsurumi-ku, Yokohama, Japan. timolassmann@gmail.com|Omics Science Center, Riken Yokohama Institute, Tsurumi-ku, Yokohama, Japan. timolassmann@gmail.com|Omics Science Center, Riken Yokohama Institute, Tsurumi-ku, Yokohama, Japan. timolassmann@gmail.com', 'Japan|Japan|Japan', 0, 'Chromosome Mapping|Genome|Genomics|High-Throughput Nucleotide Sequencing|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btq614', '21088025', 'The sequence alignment/map format (SAM) is a commonly used format to store the alignments between millions of short reads and a reference genome. Often certain positions within the reads are inherently more likely to contain errors due to the protocols used to prepare the samples. Such biases can have adverse effects on both mapping rate and accuracy. To understand the relationship between potential protocol biases and poor mapping we wrote SAMstat, a simple C program plotting nucleotide overrepresentation and other statistics in mapped and unmapped reads in a concise html page. Collecting such statistics also makes it easy to highlight problems in the data processing and enables non-experts to track data quality over time.'),
(75875, 2011, 'bio', 'Scoring-and-unfolding trimmed tree assembler: concepts, constructs and comparisons', 'Narzisi, Giuseppe|Mishra, Bud', 'Courant Institute of Mathematical Sciences, New York University, New York, NY 10012, USA. narzisi@nyu.edu|Courant Institute of Mathematical Sciences, New York University, New York, NY 10012, USA. narzisi@nyu.edu', 'United States|United States', 15, 'Algorithms|Genome, Bacterial|Genomics|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq646', '21088026', 'Mired by its connection to a well-known -complete combinatorial optimization problem-namely, the Shortest Common Superstring Problem (SCSP)-historically, the whole-genome sequence assembly (WGSA) problem has been assumed to be amenable only to greedy and heuristic methods. By placing efficiency as their first priority, these methods opted to rely only on local searches, and are thus inherently approximate, ambiguous or error prone, especially, for genomes with complex structures. Furthermore, since choice of the best heuristics depended critically on the properties of (e.g. errors in) the input data and the available long range information, these approaches hindered designing an error free WGSA pipeline.'),
(75876, 2011, 'bio', 'GPU-BLAST: using graphics processors to accelerate protein sequence alignment', 'Vouzis, Panagiotis D|Sahinidis, Nikolaos V', 'Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA.|Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA.', 'United States|United States', 141, 'Algorithms|Computational Biology|Computers|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btq644', '21088027', 'The Basic Local Alignment Search Tool (BLAST) is one of the most widely used bioinformatics tools. The widespread impact of BLAST is reflected in over 53,000 citations that this software has received in the past two decades, and the use of the word blast as a verb referring to biological sequence comparison. Any improvement in the execution speed of BLAST would be of great importance in the practice of bioinformatics, and facilitate coping with ever increasing sizes of biomolecular databases.'),
(75877, 2010, 'bio', 'GSearcher: agile attribute querying for biological networks', 'Su, Gang|Athey, Brian D|Meng, Fan', 'Bioinformatics Program, National Center for Integrative Biomedical Informatics, University of Michigan, Ann Arbor, MI, USA. sugang@umich.edu|Bioinformatics Program, National Center for Integrative Biomedical Informatics, University of Michigan, Ann Arbor, MI, USA. sugang@umich.edu|Bioinformatics Program, National Center for Integrative Biomedical Informatics, University of Michigan, Ann Arbor, MI, USA. sugang@umich.edu', 'United States|United States|United States', 1, 'Data Mining|Models, Biological|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq597', '21088028', 'GSearcher provides a highly interactive user experience in navigating attribute data associated with large and complex biological networks. The user may either perform a quick search using keywords, phrases or regular expressions, or build a complex query with a group of filters for efficient and flexible exploration of large datasets.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(75878, 2011, 'bio', 'Efficient change point detection for genomic sequences of continuous measurements', 'Muggeo, Vito M R|Adelfio, Giada', 'Dipartimento di Scienze Statistiche e Matematiche Vianelli, Università di Palermo, Palermo, Italy. vito.muggeo@unipa.it|Dipartimento di Scienze Statistiche e Matematiche Vianelli, Università di Palermo, Palermo, Italy. vito.muggeo@unipa.it', 'Italy|Italy', 62, 'Breast Neoplasms|Cell Line|Cell Line, Tumor|Comparative Genomic Hybridization|Computer Simulation|Female|Genomics|Humans|Models, Statistical|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btq647', '21088029', 'Knowing the exact locations of multiple change points in genomic sequences serves several biological needs, for instance when data represent aCGH profiles and it is of interest to identify possibly damaged genes involved in cancer and other diseases. Only a few of the currently available methods deal explicitly with estimation of the number and location of change points, and moreover these methods may be somewhat vulnerable to deviations of model assumptions usually employed.'),
(75879, 2011, 'bio', 'Anatomy of a hash-based long read sequence mapping algorithm for next generation DNA sequencing', 'Misra, Sanchit|Agrawal, Ankit|Liao, Wei-keng|Choudhary, Alok', 'Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL 60208, USA. smi539@eecs.northwestern.edu|Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL 60208, USA. smi539@eecs.northwestern.edu|Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL 60208, USA. smi539@eecs.northwestern.edu|Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL 60208, USA. smi539@eecs.northwestern.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Chromosome Mapping|Genome|High-Throughput Nucleotide Sequencing|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq648', '21088030', 'Recently, a number of programs have been proposed for mapping short reads to a reference genome. Many of them are heavily optimized for short-read mapping and hence are very efficient for shorter queries, but that makes them inefficient or not applicable for reads longer than 200 bp. However, many sequencers are already generating longer reads and more are expected to follow. For long read sequence mapping, there are limited options, BLAT, SSAHA2, FANGS and BWA-SW are among the popular ones. However, resequencing and personalized medicine need much faster software to map these long sequencing reads to a reference genome to identify SNPs or rare transcripts.'),
(75880, 2011, 'bio', 'SLIM: a sliding linear model for estimating the proportion of true null hypotheses in datasets with dependence structures', 'Wang, Hong-Qiang|Tuominen, Lindsey K|Tsai, Chung-Jui', 'Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA 30602, USA.|Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA 30602, USA.|Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA 30602, USA.', 'Georgia|Georgia|Georgia', 79, 'Algorithms|Computer Simulation|Gene Expression Profiling|Linear Models|Oligonucleotide Array Sequence Analysis|Populus', 'Journal Article', '10.1093/bioinformatics/btq650', '21098430', 'The pre-estimate of the proportion of null hypotheses (xcfx80(0)) plays a critical role in controlling false discovery rate (FDR) in multiple hypothesis testing. However, hidden complex dependence structures of many genomics datasets distort the distribution of p-values, rendering existing xcfx80(0) estimators less effective.'),
(75881, 2011, 'bio', 'Paintomics: a web based tool for the joint visualization of transcriptomics and metabolomics data', 'García-Alcalde, Fernando|García-López, Federico|Dopazo, Joaquín|Conesa, Ana', 'Bioinformatics and Genomics Department, Centro de Investigaciones Príncipe Felipe, Valencia, Spain.|Bioinformatics and Genomics Department, Centro de Investigaciones Príncipe Felipe, Valencia, Spain.|Bioinformatics and Genomics Department, Centro de Investigaciones Príncipe Felipe, Valencia, Spain.|Bioinformatics and Genomics Department, Centro de Investigaciones Príncipe Felipe, Valencia, Spain.', 'Spain|Spain|Spain|Spain', 80, 'Arabidopsis|Computational Biology|Gene Expression Profiling|Internet|Metabolomics|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq594', '21098431', 'The development of the omics technologies such as transcriptomics, proteomics and metabolomics has made possible the realization of systems biology studies where biological systems are interrogated at different levels of biochemical activity (gene expression, protein activity and/or metabolite concentration). An effective approach to the analysis of these complex datasets is the joined visualization of the disparate biomolecular data on the framework of known biological pathways.'),
(75882, 2011, 'bio', 'Improving structure alignment-based prediction of SCOP families using Vorolign kernels', 'Hamp, Tobias|Birzele, Fabian|Buchwald, Fabian|Kramer, Stefan', 'Institut für Informatik/I12, Technische Universität München, München, Germany.|Institut für Informatik/I12, Technische Universität München, München, Germany.|Institut für Informatik/I12, Technische Universität München, München, Germany.|Institut für Informatik/I12, Technische Universität München, München, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Artificial Intelligence|Classification|Models, Molecular|Protein Structure, Tertiary|Proteins', 'Evaluation Studies', '10.1093/bioinformatics/btq618', '21098432', 'The slow growth of expert-curated databases compared to experimental databases makes it necessary to build upon highly accurate automated processing pipelines to make the most of the data until curation becomes available. We address this problem in the context of protein structures and their classification into structural and functional classes, more specifically, the structural classification of proteins (SCOP). Structural alignment methods like Vorolign already provide good classification results, but effectively work in a 1-Nearest Neighbor mode. Model-based (in contrast to instance-based) approaches so far have been shown to be of limited values due to small classes arising in such classification schemes.'),
(75883, 2011, 'bio', 'Prognostic transcriptional association networks: a new supervised approach based on regression trees', 'Nepomuceno-Chamorro, Isabel|Azuaje, Francisco|Devaux, Yvan|Nazarov, Petr V|Muller, Arnaud|Aguilar-Ruiz, Jesús S|Wagner, Daniel R', 'Departamento Lenguajes y Sistemas Informáticos, Universidad de Sevilla, Seville, Spain. inepomuceno@us.es|Departamento Lenguajes y Sistemas Informáticos, Universidad de Sevilla, Seville, Spain. inepomuceno@us.es|Departamento Lenguajes y Sistemas Informáticos, Universidad de Sevilla, Seville, Spain. inepomuceno@us.es|Departamento Lenguajes y Sistemas Informáticos, Universidad de Sevilla, Seville, Spain. inepomuceno@us.es|Departamento Lenguajes y Sistemas Informáticos, Universidad de Sevilla, Seville, Spain. inepomuceno@us.es|Departamento Lenguajes y Sistemas Informáticos, Universidad de Sevilla, Seville, Spain. inepomuceno@us.es|Departamento Lenguajes y Sistemas Informáticos, Universidad de Sevilla, Seville, Spain. inepomuceno@us.es', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain', 11, 'Algorithms|Gene Expression|Gene Regulatory Networks|Humans|Linear Models|Myocardial Infarction|Prognosis', 'Journal Article', '10.1093/bioinformatics/btq645', '21098433', 'The application of information encoded in molecular networks for prognostic purposes is a crucial objective of systems biomedicine. This approach has not been widely investigated in the cardiovascular research area. Within this area, the prediction of clinical outcomes after suffering a heart attack would represent a significant step forward. We developed a new quantitative prediction-based method for this prognostic problem based on the discovery of clinically relevant transcriptional association networks. This method integrates regression trees and clinical class-specific networks, and can be applied to other clinical domains.'),
(75884, 2011, 'bio', 'von Bertalanffy 10: a COBRA toolbox extension to thermodynamically constrain metabolic models', 'Fleming, Ronan M T|Thiele, Ines', 'Science Institute, University of Iceland, Reykjavik, Iceland. ronan.mt.fleming@gmail.com|Science Institute, University of Iceland, Reykjavik, Iceland. ronan.mt.fleming@gmail.com', 'Iceland|Iceland', 33, 'Algorithms|Metabolism|Models, Biological|Software|Thermodynamics', 'Journal Article', '10.1093/bioinformatics/btq607', '21115436', 'In flux balance analysis of genome scale stoichiometric models of metabolism, the principal constraints are uptake or secretion rates, the steady state mass conservation assumption and reaction directionality. Here, we introduce an algorithmic pipeline for quantitative assignment of reaction directionality in multi-compartmental genome scale models based on an application of the second law of thermodynamics to each reaction. Given experimental or computationally estimated standard metabolite species Gibbs energy and metabolite concentrations, the algorithms bounds reaction Gibbs energy, which is transformed to in vivo pH, temperature, ionic strength and electrical potential.'),
(75885, 2011, 'bio', 'HiTEC: accurate error correction in high-throughput sequencing data', 'Ilie, Lucian|Fazayeli, Farideh|Ilie, Silvana', 'Department of Computer Science, University of Western Ontario, London, ON N6A 5B7, Canada. ilie@csd.uwo.ca|Department of Computer Science, University of Western Ontario, London, ON N6A 5B7, Canada. ilie@csd.uwo.ca|Department of Computer Science, University of Western Ontario, London, ON N6A 5B7, Canada. ilie@csd.uwo.ca', 'Canada|Canada|Canada', 94, 'Algorithms|Genome|Models, Genetic|Reproducibility of Results|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq653', '21115437', 'High-throughput sequencing technologies produce very large amounts of data and sequencing errors constitute one of the major problems in analyzing such data. Current algorithms for correcting these errors are not very accurate and do not automatically adapt to the given data.'),
(75886, 2011, 'bio', 'Real-world comparison of CPU and GPU implementations of SNPrank: a network analysis tool for GWAS', 'Davis, Nicholas A|Pandey, Ahwan|McKinney, B A', 'Department of Mathematical and Computer Sciences, University of Tulsa, Tulsa, OK 74104, USA.|Department of Mathematical and Computer Sciences, University of Tulsa, Tulsa, OK 74104, USA.|Department of Mathematical and Computer Sciences, University of Tulsa, Tulsa, OK 74104, USA.', 'United States|United States|United States', 13, 'Algorithms|Computational Biology|Computer Graphics|Computers|Genome-Wide Association Study|Polymorphism, Single Nucleotide|Programming Languages|Software', 'Evaluation Studies', '10.1093/bioinformatics/btq638', '21115438', 'Bioinformatics researchers have a variety of programming languages and architectures at their disposal, and recent advances in graphics processing unit (GPU) computing have added a promising new option. However, many performance comparisons inflate the actual advantages of GPU technology. In this study, we carry out a realistic performance evaluation of SNPrank, a network centrality algorithm that ranks single nucleotide polymorhisms (SNPs) based on their importance in the context of a phenotype-specific interaction network. Our goal is to identify the best computational engine for the SNPrank web application and to provide a variety of well-tested implementations of SNPrank for Bioinformaticists to integrate into their research.'),
(75887, 2011, 'bio', 'Identification of protein complexes from co-immunoprecipitation data', 'Geva, Guy|Sharan, Roded', 'School of Computer Science, Tel Aviv University, Tel Aviv, Israel.|School of Computer Science, Tel Aviv University, Tel Aviv, Israel.', 'Israel|Israel', 38, 'Algorithms|Fungal Proteins|Immunoprecipitation|Multiprotein Complexes', 'Evaluation Studies', '10.1093/bioinformatics/btq652', '21115439', 'Advanced technologies are producing large-scale protein-protein interaction data at an ever increasing pace. A fundamental challenge in analyzing these data is the inference of protein machineries. Previous methods for detecting protein complexes have been mainly based on analyzing binary protein-protein interaction data, ignoring the more involved co-complex relations obtained from co-immunoprecipitation experiments.'),
(75888, 2011, 'bio', 'A dynamic data structure for flexible molecular maintenance and informatics', 'Bajaj, Chandrajit|Chowdhury, Rezaul Alam|Rasheed, Muhibur', 'Department of Computer Science, University of Texas at Austin, Austin, TX, USA. bajaj@cs.utexas.edu|Department of Computer Science, University of Texas at Austin, Austin, TX, USA. bajaj@cs.utexas.edu|Department of Computer Science, University of Texas at Austin, Austin, TX, USA. bajaj@cs.utexas.edu', 'United States|United States|United States', 8, 'Computational Biology|Drug Design|Models, Molecular|Molecular Conformation|Molecular Dynamics Simulation|Protein Conformation|Proteins', 'Journal Article', '10.1093/bioinformatics/btq627', '21115440', 'We present the Dynamic Packing Grid (DPG), a neighborhood data structure for maintaining and manipulating flexible molecules and assemblies, for efficient computation of binding affinities in drug design or in molecular dynamics calculations.'),
(75889, 2011, 'bio', 'A performance enhanced PSI-BLAST based on hybrid alignment', 'Li, Yuheng|Chia, Nicholas|Lauria, Mario|Bundschuh, Ralf', 'Covidien, 60 Middletown Avenue, North Haven, CT 06473, USA.|Covidien, 60 Middletown Avenue, North Haven, CT 06473, USA.|Covidien, 60 Middletown Avenue, North Haven, CT 06473, USA.|Covidien, 60 Middletown Avenue, North Haven, CT 06473, USA.', 'United States|United States|United States|United States', 11, 'Algorithms|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology|Software', 'Evaluation Studies', '10.1093/bioinformatics/btq621', '21115441', 'Sequence alignment is one of the most popular tools of modern biology. NCBIs PSI-BLAST utilizes iterative model building in order to better detect distant homologs with greater sensitivity than non-iterative BLAST. However, PSI-BLASTs performance is limited by the fact that it relies on deterministic alignments. Using a semi-probabilistic alignment scheme such as Hybrid alignment should allow for better informed model building and improved identification of homologous sequences, particularly remote homologs.'),
(75890, 2011, 'bio', 'Improving the quality of protein similarity network clustering algorithms using the network edge weight distribution', 'Apeltsin, Leonard|Morris, John H|Babbitt, Patricia C|Ferrin, Thomas E', 'Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA.|Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA.|Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA.|Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA.', 'United States|United States|United States|United States', 28, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Cluster Analysis|Pattern Recognition, Automated|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btq655', '21118823', 'Clustering protein sequence data into functionally specific families is a difficult but important problem in biological research. One useful approach for tackling this problem involves representing the sequence dataset as a protein similarity network, and afterwards clustering the network using advanced graph analysis techniques. Although a multitude of such network clustering algorithms have been developed over the past few years, comparing algorithms is often difficult because performance is affected by the specifics of network construction. We investigate an important aspect of network construction used in analyzing protein superfamilies and present a heuristic approach for improving the performance of several algorithms.'),
(75891, 2011, 'bio', 'maxAlike: maximum likelihood-based sequence reconstruction with application to improved primer design for unknown sequences', 'Menzel, Peter|Stadler, Peter F|Gorodkin, Jan', 'Center for non-coding RNA in Technology and Health, IBHV, University of Copenhagen, Grønnegårdsvej 3, DK-1870 Frederiksberg, Denmark.|Center for non-coding RNA in Technology and Health, IBHV, University of Copenhagen, Grønnegårdsvej 3, DK-1870 Frederiksberg, Denmark.|Center for non-coding RNA in Technology and Health, IBHV, University of Copenhagen, Grønnegårdsvej 3, DK-1870 Frederiksberg, Denmark.', 'Denmark|Denmark|Denmark', 6, 'Algorithms|Animals|DNA Primers|Humans|Image Processing, Computer-Assisted|Polymerase Chain Reaction|Sequence Analysis, DNA|Sequence Homology|Software', 'Journal Article', '10.1093/bioinformatics/btq651', '21123221', 'The task of reconstructing a genomic sequence from a particular species is gaining more and more importance in the light of the rapid development of high-throughput sequencing technologies and their limitations. Applications include not only compensation for missing data in unsequenced genomic regions and the design of oligonucleotide primers for target genes in species with lacking sequence information but also the preparation of customized queries for homology searches.'),
(75892, 2011, 'bio', 'Open source platform for the execution and analysis of mechanical refolding experiments', 'Aioanei, Daniel|Brucale, Marco|Samorí, Bruno', 'Department of Biochemistry G.Moruzzi, University of Bologna, Via Irnerio 48, 40126 Bologna, Italy. aioaneid@gmail.com|Department of Biochemistry G.Moruzzi, University of Bologna, Via Irnerio 48, 40126 Bologna, Italy. aioaneid@gmail.com|Department of Biochemistry G.Moruzzi, University of Bologna, Via Irnerio 48, 40126 Bologna, Italy. aioaneid@gmail.com', 'Italy|Italy|Italy', 4, 'Computational Biology|Kinetics|Protein Denaturation|Protein Refolding|Software', 'Journal Article', '10.1093/bioinformatics/btq663', '21123222', 'Single-molecule force spectroscopy has facilitated the experimental investigation of biomolecular force-coupled kinetics, from which the kinetics at zero force can be extrapolated via explicit theoretical models. The atomic force microscope (AFM) in particular is routinely used to study protein unfolding kinetics, but only rarely protein folding kinetics. The discrepancy arises because mechanical protein refolding studies are more technically challenging.'),
(75893, 2011, 'bio', 'Genetic algorithm for shift-uncertainty correction in 1-D NMR-based metabolite identifications and quantifications', 'Schleif, F-M|Riemer, T|Börner, U|Schnapka-Hille, L|Cross, M', 'Department of Computer Science, University of Bielefeld, Bielefeld, Germany. schleif@informatik.uni-leipzig.de|Department of Computer Science, University of Bielefeld, Bielefeld, Germany. schleif@informatik.uni-leipzig.de|Department of Computer Science, University of Bielefeld, Bielefeld, Germany. schleif@informatik.uni-leipzig.de|Department of Computer Science, University of Bielefeld, Bielefeld, Germany. schleif@informatik.uni-leipzig.de|Department of Computer Science, University of Bielefeld, Bielefeld, Germany. schleif@informatik.uni-leipzig.de', 'Germany|Germany|Germany|Germany|Germany', 11, 'Algorithms|Amino Acids|Animals|Cell Line|Least-Squares Analysis|Magnetic Resonance Imaging|Mice|Stem Cells|Systems Biology|Uncertainty', 'Journal Article', '10.1093/bioinformatics/btq661', '21123223', 'The analysis of metabolic processes is becoming increasingly important to our understanding of complex biological systems and disease states. Nuclear magnetic resonance spectroscopy (NMR) is a particularly relevant technology in this respect, since the NMR signals provide a quantitative measure of the metabolite concentrations. However, due to the complexity of the spectra typical of biological samples, the demands of clinical and high-throughput analysis will only be fully met by a system capable of reliable, automatic processing of the spectra. An initial step in this direction has been taken by Targeted Profiling (TP), employing a set of known and predicted metabolite signatures fitted against the signal. However, an accurate fitting procedure for (1)H NMR data is complicated by shift uncertainties in the peak systems caused by measurement imperfections. These uncertainties have a large impact on the accuracy of identification and quantification and currently require compensation by very time consuming manual interactions. Here, we present an approach, termed Extended Targeted Profiling (ETP), that estimates shift uncertainties based on a genetic algorithm (GA) combined with a least squares optimization (LSQO). The estimated shifts are used to correct the known metabolite signatures leading to significantly improved identification and quantification. In this way, use of the automated system significantly reduces the effort normally associated with manual processing and paves the way for reliable, high-throughput analysis of complex NMR spectra.'),
(75894, 2010, 'bio', 'GLay: community structure analysis of biological networks', 'Su, Gang|Kuchinsky, Allan|Morris, John H|States, David J|Meng, Fan', 'Bioinformatics Program, University of Michigan, Ann Arbor, MI, USA. sugang@umich.edu|Bioinformatics Program, University of Michigan, Ann Arbor, MI, USA. sugang@umich.edu|Bioinformatics Program, University of Michigan, Ann Arbor, MI, USA. sugang@umich.edu|Bioinformatics Program, University of Michigan, Ann Arbor, MI, USA. sugang@umich.edu|Bioinformatics Program, University of Michigan, Ann Arbor, MI, USA. sugang@umich.edu', 'United States|United States|United States|United States|United States', 116, 'Algorithms|Computer Graphics|Models, Biological|Software', 'Journal Article', '10.1093/bioinformatics/btq596', '21123224', 'GLay provides Cytoscape users an assorted collection of versatile community structure algorithms and graph layout functions for network clustering and structured visualization. High performance is achieved by dynamically linking highly optimized C functions to the Cytoscape JAVA program, which makes GLay especially suitable for decomposition, display and exploratory analysis of large biological networks.'),
(75895, 2011, 'bio', 'MTR: taxonomic annotation of short metagenomic reads using clustering at multiple taxonomic ranks', 'Gori, Fabio|Folino, Gianluigi|Jetten, Mike S M|Marchiori, Elena', 'Radboud University Nijmegen, Institute for Computing and Information Sciences, Nijmegen, The Netherlands. gori@cs.ru.nl|Radboud University Nijmegen, Institute for Computing and Information Sciences, Nijmegen, The Netherlands. gori@cs.ru.nl|Radboud University Nijmegen, Institute for Computing and Information Sciences, Nijmegen, The Netherlands. gori@cs.ru.nl|Radboud University Nijmegen, Institute for Computing and Information Sciences, Nijmegen, The Netherlands. gori@cs.ru.nl', 'Netherlands|Netherlands|Netherlands|Netherlands', 43, 'Algorithms|Biodiversity|Cluster Analysis|Metagenome|Metagenomics|Phylogeny', 'Journal Article', '10.1093/bioinformatics/btq649', '21127032', 'Metagenomics is a recent field of biology that studies microbial communities by analyzing their genomic content directly sequenced from the environment. A metagenomic dataset consists of many short DNA or RNA fragments called reads. One interesting problem in metagenomic data analysis is the discovery of the taxonomic composition of a given dataset. A simple method for this task, called the Lowest Common Ancestor (LCA), is employed in state-of-the-art computational tools for metagenomic data analysis of very short reads (about 100 bp). However LCA has two main drawbacks: it possibly assigns many reads to high taxonomic ranks and it discards a high number of reads.'),
(75896, 2011, 'bio', 'New approach for segmentation and quantification of two-dimensional gel electrophoresis images', 'dos Anjos, António|Møller, Anders L B|Ersbøll, Bjarne K|Finnie, Christine|Shahbazkia, Hamid R', 'Department of Electronic and Informatics Engineering, University of Algarve, Faro, Portugal. antoniodosanjos@gmail.com|Department of Electronic and Informatics Engineering, University of Algarve, Faro, Portugal. antoniodosanjos@gmail.com|Department of Electronic and Informatics Engineering, University of Algarve, Faro, Portugal. antoniodosanjos@gmail.com|Department of Electronic and Informatics Engineering, University of Algarve, Faro, Portugal. antoniodosanjos@gmail.com|Department of Electronic and Informatics Engineering, University of Algarve, Faro, Portugal. antoniodosanjos@gmail.com', 'Portugal|Portugal|Portugal|Portugal|Portugal', 20, 'Algorithms|Electrophoresis, Gel, Two-Dimensional|Image Processing, Computer-Assisted|Proteins|Reproducibility of Results|Software', 'Journal Article', '10.1093/bioinformatics/btq666', '21127033', 'Detection of protein spots in two-dimensional gel electrophoresis images (2-DE) is a very complex task and current approaches addressing this problem still suffer from significant shortcomings. When quantifying a spot, most of the current software applications include a lot of background due to poor segmentation. Other software applications use a fixed window for this task, resulting in omission of part of the protein spot, or including background in the quantification. The approach presented here for the segmentation and quantification of 2-DE aims to minimize these problems.'),
(75897, 2011, 'bio', 'A regression framework incorporating quantitative and negative interaction data improves quantitative prediction of PDZ domain-peptide interaction from primary sequence', 'Shao, Xiaojian|Tan, Chris S H|Voss, Courtney|Li, Shawn S C|Deng, Naiyang|Bader, Gary D', 'Department of Applied Mathematics, College of Science, China Agricultural University, Beijing, 100083, China.|Department of Applied Mathematics, College of Science, China Agricultural University, Beijing, 100083, China.|Department of Applied Mathematics, College of Science, China Agricultural University, Beijing, 100083, China.|Department of Applied Mathematics, College of Science, China Agricultural University, Beijing, 100083, China.|Department of Applied Mathematics, College of Science, China Agricultural University, Beijing, 100083, China.|Department of Applied Mathematics, College of Science, China Agricultural University, Beijing, 100083, China.', 'China|China|China|China|China|China', 24, 'Animals|Computational Biology|Ligands|Mice|Models, Molecular|Mutation|PDZ Domains|Peptides|Protein Binding|Protein Structure, Tertiary|Proteins|Regression Analysis|Reproducibility of Results', 'Journal Article', '10.1093/bioinformatics/btq657', '21127034', 'Predicting protein interactions involving peptide recognition domains is essential for understanding the many important biological processes they mediate. It is important to consider the binding strength of these interactions to help us construct more biologically relevant protein interaction networks that consider cellular context and competition between potential binders.'),
(75898, 2011, 'bio', 'RSEQtools: a modular framework to analyze RNA-Seq data using compact, anonymized data summaries', 'Habegger, Lukas|Sboner, Andrea|Gianoulis, Tara A|Rozowsky, Joel|Agarwal, Ashish|Snyder, Michael|Gerstein, Mark', 'Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA. lukas.habegger@yale.edu|Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA. lukas.habegger@yale.edu|Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA. lukas.habegger@yale.edu|Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA. lukas.habegger@yale.edu|Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA. lukas.habegger@yale.edu|Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA. lukas.habegger@yale.edu|Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA. lukas.habegger@yale.edu', 'United States|United States|United States|United States|United States|United States|United States', 71, 'Confidentiality|Gene Expression Profiling|Genomics|High-Throughput Nucleotide Sequencing|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btq643', '21134889', 'The advent of next-generation sequencing for functional genomics has given rise to quantities of sequence information that are often so large that they are difficult to handle. Moreover, sequence reads from a specific individual can contain sufficient information to potentially identify and genetically characterize that person, raising privacy concerns. In order to address these issues, we have developed the Mapped Read Format (MRF), a compact data summary format for both short and long read alignments that enables the anonymization of confidential sequence information, while allowing one to still carry out many functional genomics studies. We have developed a suite of tools (RSEQtools) that use this format for the analysis of RNA-Seq experiments. These tools consist of a set of modules that perform common tasks such as calculating gene expression values, generating signal tracks of mapped reads and segmenting that signal into actively transcribed regions. Moreover, the tools can readily be used to build customizable RNA-Seq workflows. In addition to the anonymization afforded by MRF, this format also facilitates the decoupling of the alignment of reads from downstream analyses.'),
(75899, 2011, 'bio', 'Predicting in vitro drug sensitivity using Random Forests', 'Riddick, Gregory|Song, Hua|Ahn, Susie|Walling, Jennifer|Borges-Rivera, Diego|Zhang, Wei|Fine, Howard A', 'Neuro-Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. riddickgp@mail.nih.gov|Neuro-Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. riddickgp@mail.nih.gov|Neuro-Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. riddickgp@mail.nih.gov|Neuro-Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. riddickgp@mail.nih.gov|Neuro-Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. riddickgp@mail.nih.gov|Neuro-Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. riddickgp@mail.nih.gov|Neuro-Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. riddickgp@mail.nih.gov', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Antineoplastic Agents|Artificial Intelligence|Breast Neoplasms|Cell Line, Tumor|Drug Screening Assays, Antitumor|Female|Gene Expression Profiling|Glioma|Humans|Models, Statistical|Software', 'Evaluation Studies', '10.1093/bioinformatics/btq628', '21134890', 'Panels of cell lines such as the NCI-60 have long been used to test drug candidates for their ability to inhibit proliferation. Predictive models of in vitro drug sensitivity have previously been constructed using gene expression signatures generated from gene expression microarrays. These statistical models allow the prediction of drug response for cell lines not in the original NCI-60. We improve on existing techniques by developing a novel multistep algorithm that builds regression models of drug response using Random Forest, an ensemble approach based on classification and regression trees (CART).'),
(75900, 2011, 'bio', 'Toward the estimation of the absolute quality of individual protein structure models', 'Benkert, Pascal|Biasini, Marco|Schwede, Torsten', 'Biozentrum, University of Basel, Switzerland.|Biozentrum, University of Basel, Switzerland.|Biozentrum, University of Basel, Switzerland.', 'Switzerland|Switzerland|Switzerland', 1012, 'Data Interpretation, Statistical|Humans|Models, Molecular|Proteins|Regression Analysis', 'Journal Article', '10.1093/bioinformatics/btq662', '21134891', 'Quality assessment of protein structures is an important part of experimental structure validation and plays a crucial role in protein structure prediction, where the predicted models may contain substantial errors. Most current scoring functions are primarily designed to rank alternative models of the same sequence supporting model selection, whereas the prediction of the absolute quality of an individual protein model has received little attention in the field. However, reliable absolute quality estimates are crucial to assess the suitability of a model for specific biomedical applications.'),
(75901, 2011, 'bio', 'Rseg--an R package to optimize segmentation of SNP array data', 'Lamy, Philippe|Wiuf, Carsten|Ørntoft, Torben F|Andersen, Claus L', 'Department of Molecular Medicine, Aarhus University Hospital Skejby, Aarhus N, Denmark. plamy@cs.au.dk|Department of Molecular Medicine, Aarhus University Hospital Skejby, Aarhus N, Denmark. plamy@cs.au.dk|Department of Molecular Medicine, Aarhus University Hospital Skejby, Aarhus N, Denmark. plamy@cs.au.dk|Department of Molecular Medicine, Aarhus University Hospital Skejby, Aarhus N, Denmark. plamy@cs.au.dk', 'Denmark|Denmark|Denmark|Denmark', 4, 'Algorithms|Genomics|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btq668', '21134892', 'The use of high-density SNP arrays for investigating copy number alterations in clinical tumor samples, with intra tumor heterogeneity and varying degrees of normal cell contamination, imposes several problems for commonly used segmentation algorithms. This calls for flexibility when setting thresholds for calling gains and losses. In addition, sample normalization can induce artifacts in the copy-number ratios for the non-changed genomic elements in the tumor samples.'),
(75902, 2011, 'bio', 'MASISH: a database for gene expression in maize seeds', 'Miquel, M|López-Ribera, I|Ràmia, M|Casillas, S|Barbadilla, A|Vicient, C M', 'Department of Molecular Genetics, Centre for Research in Agricultural Genomics, CSIC (IRTA-UAB), Jordi Girona, 18, 08034 Barcelona, Spain.|Department of Molecular Genetics, Centre for Research in Agricultural Genomics, CSIC (IRTA-UAB), Jordi Girona, 18, 08034 Barcelona, Spain.|Department of Molecular Genetics, Centre for Research in Agricultural Genomics, CSIC (IRTA-UAB), Jordi Girona, 18, 08034 Barcelona, Spain.|Department of Molecular Genetics, Centre for Research in Agricultural Genomics, CSIC (IRTA-UAB), Jordi Girona, 18, 08034 Barcelona, Spain.|Department of Molecular Genetics, Centre for Research in Agricultural Genomics, CSIC (IRTA-UAB), Jordi Girona, 18, 08034 Barcelona, Spain.|Department of Molecular Genetics, Centre for Research in Agricultural Genomics, CSIC (IRTA-UAB), Jordi Girona, 18, 08034 Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain', 0, 'Computational Biology|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation, Plant|Internet|Seeds|Software|Zea mays', 'Journal Article', '10.1093/bioinformatics/btq654', '21134893', 'Grass seeds are complex organs composed by multiple tissues and cell types that develop coordinately to produce a viable embryo. The identification of genes involved in seed development is of great interest, but systematic spatial analyses of gene expression on maize seeds at the cell level have not yet been performed. MASISH is an online database holding information for gene expression spatial patterns in maize seeds based on in situ hybridization experiments. The web-based query interface allows the execution of gene queries and provides hybridization images, published references and information of the analyzed genes.'),
(75903, 2011, 'bio', 'RNA-RNA interaction prediction based on multiple sequence alignments', 'Li, Andrew X|Marz, Manja|Qin, Jing|Reidys, Christian M', 'Tianjin Key Laboratory of Combinatorics, Nankai University Tianjin 300071, Peoples Republic of China.|Tianjin Key Laboratory of Combinatorics, Nankai University Tianjin 300071, Peoples Republic of China.|Tianjin Key Laboratory of Combinatorics, Nankai University Tianjin 300071, Peoples Republic of China.|Tianjin Key Laboratory of Combinatorics, Nankai University Tianjin 300071, Peoples Republic of China.', 'China|China|China|China', 32, 'Algorithms|Base Pairing|Base Sequence|Models, Statistical|Molecular Sequence Data|RNA|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btq659', '21134894', 'Many computerized methods for RNA-RNA interaction structure prediction have been developed. Recently, O(N(6)) time and O(N(4)) space dynamic programming algorithms have become available that compute the partition function of RNA-RNA interaction complexes. However, few of these methods incorporate the knowledge concerning related sequences, thus relevant evolutionary information is often neglected from the structure determination. Therefore, it is of considerable practical interest to introduce a method taking into consideration both: thermodynamic stability as well as sequence/structure covariation.'),
(75904, 2011, 'bio', 'Algorithms for sorting unsigned linear genomes by the DCJ operations', 'Jiang, Haitao|Zhu, Binhai|Zhu, Daming', 'Department of Computer Science, Montana State University, Bozeman, MT 59717, USA.|Department of Computer Science, Montana State University, Bozeman, MT 59717, USA.|Department of Computer Science, Montana State University, Bozeman, MT 59717, USA.', 'United States|United States|United States', 0, 'Algorithms|Genome|Genomics|Software', 'Journal Article', '10.1093/bioinformatics/btq674', '21134895', 'The double cut and join operation (abbreviated as DCJ) has been extensively used for genomic rearrangement. Although the DCJ distance between signed genomes with both linear and circular (uni- and multi-) chromosomes is well studied, the only known result for the NP-complete unsigned DCJ distance problem is an approximation algorithm for unsigned linear unichromosomal genomes. In this article, we study the problem of computing the DCJ distance on two unsigned linear multichromosomal genomes (abbreviated as UDCJ).'),
(75905, 2011, 'bio', 'MSPocket: an orientation-independent algorithm for the detection of ligand binding pockets', 'Zhu, Hongbo|Pisabarro, M Teresa', 'Structural Bioinformatics, BIOTEC Technical University of Dresden, Tatzberg 47-51, 01307 Dresden, Germany. hongboz@biotec.tu-dresden.de|Structural Bioinformatics, BIOTEC Technical University of Dresden, Tatzberg 47-51, 01307 Dresden, Germany. hongboz@biotec.tu-dresden.de', 'Germany|Germany', 0, 'Algorithms|Binding Sites|Ligands|Models, Molecular|Protein Binding|Proteins|Reproducibility of Results', 'Journal Article', '10.1093/bioinformatics/btq672', '21134896', 'Identification of ligand binding pockets on proteins is crucial for the characterization of protein functions. It provides valuable information for protein-ligand docking and rational engineering of small molecules that regulate protein functions. A major number of current prediction algorithms of ligand binding pockets are based on cubic grid representation of proteins and, thus, the results are often protein orientation dependent.'),
(75906, 2011, 'bio', 'Toward an automatic method for extracting cancer- and other disease-related point mutations from the biomedical literature', 'Doughty, Emily|Kertesz-Farkas, Attila|Bodenreider, Olivier|Thompson, Gary|Adadey, Asa|Peterson, Thomas|Kann, Maricel G', 'University of Maryland, Baltimore County, Baltimore, MD 21250, USA.|University of Maryland, Baltimore County, Baltimore, MD 21250, USA.|University of Maryland, Baltimore County, Baltimore, MD 21250, USA.|University of Maryland, Baltimore County, Baltimore, MD 21250, USA.|University of Maryland, Baltimore County, Baltimore, MD 21250, USA.|University of Maryland, Baltimore County, Baltimore, MD 21250, USA.|University of Maryland, Baltimore County, Baltimore, MD 21250, USA.', 'United States|United States|United States|United States|United States|United States|United States', 51, 'Algorithms|Computational Biology|Databases, Factual|Humans|Information Storage and Retrieval|Neoplasms|Point Mutation|Publications|Reproducibility of Results|Software', 'Journal Article', '10.1093/bioinformatics/btq667', '21138947', 'A major goal of biomedical research in personalized medicine is to find relationships between mutations and their corresponding disease phenotypes. However, most of the disease-related mutational data are currently buried in the biomedical literature in textual form and lack the necessary structure to allow easy retrieval and visualization. We introduce a high-throughput computational method for the identification of relevant disease mutations in PubMed abstracts applied to prostate (PCa) and breast cancer (BCa) mutations.'),
(75907, 2011, 'bio', 'W-ChIPeaks: a comprehensive web application tool for processing ChIP-chip and ChIP-seq data', 'Lan, Xun|Bonneville, Russell|Apostolos, Jeff|Wu, Wangcheng|Jin, Victor X', 'Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43221, USA.|Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43221, USA.|Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43221, USA.|Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43221, USA.|Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43221, USA.', 'United States|United States|United States|United States|United States', 0, 'High-Throughput Nucleotide Sequencing|Internet|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btq669', '21138948', 'ChIP-based technology is becoming the leading technology to globally profile thousands of transcription factors and elucidate the transcriptional regulation mechanisms in living cells. It has evolved rapidly in recent years, from hybridization with spotted or tiling microarray (ChIP-chip), to pair-end tag sequencing (ChIP-PET), to current massively parallel sequencing (ChIP-seq). Although there are many tools available for identifying binding sites (peaks) for ChIP-chip and ChIP-seq, few of them are available as easy-accessible online web tools for processing both ChIP-chip and ChIP-seq data for the ChIP-based user community. As such, we have developed a comprehensive web application tool for processing ChIP-chip and ChIP-seq data. Our web tool W-ChIPeaks employed a probe-based (or bin-based) enrichment threshold to define peaks and applied statistical methods to control false discovery rate for identified peaks. The web tool includes two different web interfaces: PELT for ChIP-chip, BELT for ChIP-seq, where both were tested on previously published experimental data. The novel features of our tool include a comprehensive output for identified peaks with GFF, BED, bedGraph and .wig formats, annotated genes to which these peaks are related, a graphical interpretation and visualization of the results via a user-friendly web interface.'),
(75908, 2011, 'bio', 'Bayesian ensemble methods for survival prediction in gene expression data', 'Bonato, Vinicius|Baladandayuthapani, Veerabhadran|Broom, Bradley M|Sulman, Erik P|Aldape, Kenneth D|Do, Kim-Anh', 'Pfizer Inc., Groton, CT 06340, USA.|Pfizer Inc., Groton, CT 06340, USA.|Pfizer Inc., Groton, CT 06340, USA.|Pfizer Inc., Groton, CT 06340, USA.|Pfizer Inc., Groton, CT 06340, USA.|Pfizer Inc., Groton, CT 06340, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Bayes Theorem|Brain Neoplasms|Breast Neoplasms|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Models, Genetic|Oligonucleotide Array Sequence Analysis|Survival Analysis', 'Journal Article', '10.1093/bioinformatics/btq660', '21148161', 'We propose a Bayesian ensemble method for survival prediction in high-dimensional gene expression data. We specify a fully Bayesian hierarchical approach based on an ensemble sum-of-trees model and illustrate our method using three popular survival models. Our non-parametric method incorporates both additive and interaction effects between genes, which results in high predictive accuracy compared with other methods. In addition, our method provides model-free variable selection of important prognostic markers based on controlling the false discovery rates, thus providing a unified procedure to select relevant genes and predict survivor functions.'),
(75909, 2011, 'bio', 'SlideSort: all pairs similarity search for short reads', 'Shimizu, Kana|Tsuda, Koji', 'Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, Japan.|Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, Japan.', 'Japan|Japan', 16, 'Algorithms|Base Sequence|Computational Biology|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq677', '21148542', 'Recent progress in DNA sequencing technologies calls for fast and accurate algorithms that can evaluate sequence similarity for a huge amount of short reads. Searching similar pairs from a string pool is a fundamental process of de novo genome assembly, genome-wide alignment and other important analyses.'),
(75910, 2011, 'bio', 'Mugsy: fast multiple alignment of closely related whole genomes', 'Angiuoli, Samuel V|Salzberg, Steven L', 'Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA. angiuoli@cs.umd.edu|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA. angiuoli@cs.umd.edu', 'United States|United States', 0, 'Algorithms|Genome, Bacterial|Genomics|Humans|Sequence Alignment|Software|Streptococcus pneumoniae', 'Journal Article', '10.1093/bioinformatics/btq665', '21148543', 'The relative ease and low cost of current generation sequencing technologies has led to a dramatic increase in the number of sequenced genomes for species across the tree of life. This increasing volume of data requires tools that can quickly compare multiple whole-genome sequences, millions of base pairs in length, to aid in the study of populations, pan-genomes, and genome evolution.'),
(75911, 2011, 'bio', 'Non-destructive biocomputing security system based on gas-controlled biofuel cell and potentially used for intelligent medical diagnostics', 'Zhou, Ming|Zheng, Xiliang|Wang, Jin|Dong, Shaojun', 'State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, PR China.|State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, PR China.|State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, PR China.|State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, PR China.', 'China|China|China|China', 16, 'Bioelectric Energy Sources|Biofuels|Computers, Molecular|Electrodes|Gases|Glucose|Hydrogen-Ion Concentration|Logic|Synthetic Biology', 'Journal Article', '10.1093/bioinformatics/btq678', '21148544', 'Biofuel cells (BFCs) based on enzymes and microbes are the promising future alternative sources of sustainable electrical energy under mild conditions (i.e. ambient temperature and neutral pH). By combining the adaptive behavior of BFCs self-regulating energy release with the versatility of biocomputing, we construct a novel gas-controlled biocomputing security system, which could be used as the potential implantable self-powered and smart medical system with the logic diagnosis aim.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(75912, 2011, 'bio', 'SurreyFBA: a command line tool and graphics user interface for constraint-based modeling of genome-scale metabolic reaction networks', 'Gevorgyan, Albert|Bushell, Michael E|Avignone-Rossa, Claudio|Kierzek, Andrzej M', 'Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey GU2 7XH, UK.|Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey GU2 7XH, UK.|Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey GU2 7XH, UK.|Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey GU2 7XH, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 35, 'Animals|Computational Biology|Genome|Humans|Metabolic Networks and Pathways|Models, Biological|Software', 'Journal Article', '10.1093/bioinformatics/btq679', '21148545', 'Constraint-based modeling of genome-scale metabolic networks has been successfully used in numerous applications such as prediction of gene essentiality and metabolic engineering. We present SurreyFBA, which provides constraint-based simulations and network map visualization in a free, stand-alone software. In addition to basic simulation protocols, the tool also implements the analysis of minimal substrate and product sets, which is useful for metabolic engineering and prediction of nutritional requirements in complex in vivo environments, but not available in other commonly used programs. The SurreyFBA is based on a command line interface to the GLPK solver distributed as binary and source code for the three major operating systems. The command line tool, implemented in C++, is easily executed within scripting languages used in the bioinformatics community and provides efficient implementation of tasks requiring iterative calls to the linear programming solver. SurreyFBA includes JyMet, a graphics user interface allowing spreadsheet-based model presentation, visualization of numerical results on metabolic networks represented in the Petri net convention, as well as in charts and plots.'),
(75913, 2011, 'bio', 'Improved predictions by Pconsnet using multiple templates', 'Larsson, Per|Skwark, Marcin J|Wallner, Björn|Elofsson, Arne', 'Center for Biomembrane Research, Department of Biochemistry and Biophysics, Swedish e-Science Research Centre, Stockholm Bioinformatics Centre, SciLifeLab, Stockholm University SE-10691 Stockholm, Sweden.|Center for Biomembrane Research, Department of Biochemistry and Biophysics, Swedish e-Science Research Centre, Stockholm Bioinformatics Centre, SciLifeLab, Stockholm University SE-10691 Stockholm, Sweden.|Center for Biomembrane Research, Department of Biochemistry and Biophysics, Swedish e-Science Research Centre, Stockholm Bioinformatics Centre, SciLifeLab, Stockholm University SE-10691 Stockholm, Sweden.|Center for Biomembrane Research, Department of Biochemistry and Biophysics, Swedish e-Science Research Centre, Stockholm Bioinformatics Centre, SciLifeLab, Stockholm University SE-10691 Stockholm, Sweden.', 'Sweden|Sweden|Sweden|Sweden', 0, 'Computational Biology|Models, Molecular|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btq664', '21149277', 'Multiple templates can often be used to build more accurate homology models than models built from a single template. Here we introduce PconsM, an automated protocol that uses multiple templates to build protein models. PconsM has been among the top-performing methods in the recent CASP experiments and consistently perform better than the single template models used in Pcons.net. In particular for the easier targets with many alternative templates with a high degree of sequence identity, quality is readily improved with a few percentages over the highest ranked model built on a single template. PconsM is available as an additional pipeline within the Pcons.net protein structure prediction server.'),
(75914, 2011, 'bio', 'Exploring metabolic pathways in genome-scale networks via generating flux modes', 'Rezola, A|de Figueiredo, L F|Brock, M|Pey, J|Podhorski, A|Wittmann, C|Schuster, S|Bockmayr, A|Planes, F J', 'Biomedical Engineering, University of Navarra, 20018 San Sebastian, Spain.|Biomedical Engineering, University of Navarra, 20018 San Sebastian, Spain.|Biomedical Engineering, University of Navarra, 20018 San Sebastian, Spain.|Biomedical Engineering, University of Navarra, 20018 San Sebastian, Spain.|Biomedical Engineering, University of Navarra, 20018 San Sebastian, Spain.|Biomedical Engineering, University of Navarra, 20018 San Sebastian, Spain.|Biomedical Engineering, University of Navarra, 20018 San Sebastian, Spain.|Biomedical Engineering, University of Navarra, 20018 San Sebastian, Spain.|Biomedical Engineering, University of Navarra, 20018 San Sebastian, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain', 37, 'Acyl Coenzyme A|Computational Biology|Computer Simulation|Escherichia coli|Genome, Bacterial|Lysine|Metabolic Networks and Pathways|Models, Theoretical|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq681', '21149278', 'The reconstruction of metabolic networks at the genome scale has allowed the analysis of metabolic pathways at an unprecedented level of complexity. Elementary flux modes (EFMs) are an appropriate concept for such analysis. However, their number grows in a combinatorial fashion as the size of the metabolic network increases, which renders the application of EFMs approach to large metabolic networks difficult. Novel methods are expected to deal with such complexity.'),
(75915, 2011, 'bio', 'MU2A--reconciling the genome and transcriptome to determine the effects of base substitutions', 'Garla, Vijay|Kong, Yong|Szpakowski, Sebastian|Krauthammer, Michael', 'Department of Biological and Biomedical Sciences, Interdepartmental Program in Computational Biology and Bioinformatics, Yale University School of Medicine, 310 Cedar Street, New Haven, CT 06520, USA.|Department of Biological and Biomedical Sciences, Interdepartmental Program in Computational Biology and Bioinformatics, Yale University School of Medicine, 310 Cedar Street, New Haven, CT 06520, USA.|Department of Biological and Biomedical Sciences, Interdepartmental Program in Computational Biology and Bioinformatics, Yale University School of Medicine, 310 Cedar Street, New Haven, CT 06520, USA.|Department of Biological and Biomedical Sciences, Interdepartmental Program in Computational Biology and Bioinformatics, Yale University School of Medicine, 310 Cedar Street, New Haven, CT 06520, USA.', 'United States|United States|United States|United States', 5, 'Genetic Variation|Genome|Humans|Internet|Molecular Sequence Annotation|Mutation|Neoplasms|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btq658', '21149339', 'Next-generation sequencing technologies enable the identification of sequence variation in the genome and transcriptome. Differences between the reference genome and transcript libraries complicate the determination of the effect of genomic sequence variants on protein products, similarly, these differences complicate the mapping of sequence variants found in transcripts to their respective genomic position. We have developed MU2A, a publicly available web service for variant annotation that reconciles differences between the genome and transcriptome, enabling the rapid and accurate determination of the effects of genomic variants on protein products, and the mapping of variants detected in transcripts to genomic coordinates. The MU2A web service is available at http://krauthammerlab.med.yale.edu/mu2a. We have released MU2A as open source, available at http://code.google.com/p/mu2a/.'),
(75916, 2011, 'bio', 'Cytoscape 28: new features for data integration and network visualization', 'Smoot, Michael E|Ono, Keiichiro|Ruscheinski, Johannes|Wang, Peng-Liang|Ideker, Trey', 'Department of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA. msmoot@ucsd.edu|Department of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA. msmoot@ucsd.edu|Department of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA. msmoot@ucsd.edu|Department of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA. msmoot@ucsd.edu|Department of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA. msmoot@ucsd.edu', 'United States|United States|United States|United States|United States', 2811, 'Computational Biology|Software|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/btq675', '21149340', 'Cytoscape is a popular bioinformatics package for biological network visualization and data integration. Version 2.8 introduces two powerful new features--Custom Node Graphics and Attribute Equations--which can be used jointly to greatly enhance Cytoscapes data integration and visualization capabilities. Custom Node Graphics allow an image to be projected onto a node, including images generated dynamically or at remote locations. Attribute Equations provide Cytoscape with spreadsheet-like functionality in which the value of an attribute is computed dynamically as a function of other attributes and network properties.'),
(75917, 2011, 'bio', 'Genotype calling and mapping of multisite variants using an Atlantic salmon iSelect SNP array', 'Gidskehaug, Lars|Kent, Matthew|Hayes, Ben J|Lien, Sigbjørn', 'CIGENE/Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, N-1432 Aas, Norway. lg@camo.no|CIGENE/Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, N-1432 Aas, Norway. lg@camo.no|CIGENE/Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, N-1432 Aas, Norway. lg@camo.no|CIGENE/Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, N-1432 Aas, Norway. lg@camo.no', 'Norway|Norway|Norway|Norway', 48, 'Animals|Chromosome Mapping|Genome|Genotype|Norway|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Reproducibility of Results|Salmo salar|Software', 'Journal Article', '10.1093/bioinformatics/btq673', '21149341', 'Due to a genome duplication event in the recent history of salmonids, modern Atlantic salmon (Salmo salar) have a mosaic genome with roughly one-third being tetraploid. This is a complicating factor in genotyping and genetic mapping since polymorphisms within duplicated regions (multisite variants, MSVs) are challenging to call and to assign to the correct paralogue. Standard genotyping software offered by Illumina has not been written to interpret MSVs and will either fail or miscall these polymorphisms. For the purpose of mapping, linkage or association studies in non-diploid species, there is a pressing need for software that includes analysis of MSVs in addition to regular single nucleotide polymorphism (SNP) markers.'),
(75918, 2011, 'bio', 'Scaffolding pre-assembled contigs using SSPACE', 'Boetzer, Marten|Henkel, Christiaan V|Jansen, Hans J|Butler, Derek|Pirovano, Walter', 'BaseClear B.V., Einsteinweg 5, 2333 CC Leiden, Leiden,The Netherlands.|BaseClear B.V., Einsteinweg 5, 2333 CC Leiden, Leiden,The Netherlands.|BaseClear B.V., Einsteinweg 5, 2333 CC Leiden, Leiden,The Netherlands.|BaseClear B.V., Einsteinweg 5, 2333 CC Leiden, Leiden,The Netherlands.|BaseClear B.V., Einsteinweg 5, 2333 CC Leiden, Leiden,The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 1347, 'Algorithms|Contig Mapping|Gene Library|Genome|Genomics|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq683', '21149342', 'De novo assembly tools play a main role in reconstructing genomes from next-generation sequencing (NGS) data and usually yield a number of contigs. Using paired-read sequencing data it is possible to assess the order, distance and orientation of contigs and combine them into so-called scaffolds. Although the latter process is a crucial step in finishing genomes, scaffolding algorithms are often built-in functions in de novo assembly tools and cannot be independently controlled. We here present a new tool, called SSPACE, which is a stand-alone scaffolder of pre-assembled contigs using paired-read data. Main features are: a short runtime, multiple library input of paired-end and/or mate pair datasets and possible contig extension with unmapped sequence reads. SSPACE shows promising results on both prokaryote and eukaryote genomic testsets where the amount of initial contigs was reduced by at least 75%.'),
(75919, 2011, 'bio', 'When the Web meets the cell: using personalized PageRank for analyzing protein interaction networks', 'Iván, Gábor|Grolmusz, Vince', 'Protein Information Technology Group, Eötvös University, Pázmány Péter sétány 1/C and Uratim Ltd., InfoPark D, H-1117 Budapest, Hungary.|Protein Information Technology Group, Eötvös University, Pázmány Péter sétány 1/C and Uratim Ltd., InfoPark D, H-1117 Budapest, Hungary.', 'Hungary|Hungary', 51, 'Algorithms|Databases, Protein|Humans|Internet|Protein Interaction Maps|Proteomics', 'Journal Article', '10.1093/bioinformatics/btq680', '21149343', 'Enormous and constantly increasing quantity of biological information is represented in metabolic and in protein interaction network databases. Most of these data are freely accessible through large public depositories. The robust analysis of these resources needs novel technologies, being developed today.'),
(75920, 2011, 'bio', 'A Bayesian approach for estimating calibration curves and unknown concentrations in immunoassays', 'Feng, Feng|Sales, Ana Paula|Kepler, Thomas B', 'Center for Computational Immunology, Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC 27705, USA. feng.feng@duke.edu|Center for Computational Immunology, Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC 27705, USA. feng.feng@duke.edu|Center for Computational Immunology, Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC 27705, USA. feng.feng@duke.edu', 'United States|United States|United States', 12, 'Algorithms|Bayes Theorem|Calibration|Computational Biology|Computer Simulation|Evaluation Studies as Topic|Immunoassay|Markov Chains|Models, Statistical|Monte Carlo Method|Software|Uncertainty', 'Journal Article', '10.1093/bioinformatics/btq686', '21149344', 'Immunoassays are primary diagnostic and research tools throughout the medical and life sciences. The common approach to the processing of immunoassay data involves estimation of the calibration curve followed by inversion of the calibration function to read off the concentration estimates. This approach, however, does not lend itself easily to acceptable estimation of confidence limits on the estimated concentrations. Such estimates must account for uncertainty in the calibration curve as well as uncertainty in the target measurement. Even point estimates can be problematic: because of the non-linearity of calibration curves and error heteroscedasticity, the neglect of components of measurement error can produce significant bias.'),
(75921, 2011, 'bio', 'PE-Assembler: de novo assembler using short paired-end reads', 'Ariyaratne, Pramila Nuwantha|Sung, Wing-Kin', 'Computational & Mathematical Biology Group, Genome Institute of Singapore, Singapore.|Computational & Mathematical Biology Group, Genome Institute of Singapore, Singapore.', 'Singapore|Singapore', 30, 'Computer Simulation|Escherichia coli|Genome|Genomics|Schizosaccharomyces|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq626', '21149345', 'Many de novo genome assemblers have been proposed recently. The basis for most existing methods relies on the de bruijn graph: a complex graph structure that attempts to encompass the entire genome. Such graphs can be prohibitively large, may fail to capture subtle information and is difficult to be parallelized.'),
(75922, 2011, 'bio', 'The Bayesian lasso for genome-wide association studies', 'Li, Jiahan|Das, Kiranmoy|Fu, Guifang|Li, Runze|Wu, Rongling', 'Department of Statistics, Pennsylvania State University, State College, PA 16802, USA.|Department of Statistics, Pennsylvania State University, State College, PA 16802, USA.|Department of Statistics, Pennsylvania State University, State College, PA 16802, USA.|Department of Statistics, Pennsylvania State University, State College, PA 16802, USA.|Department of Statistics, Pennsylvania State University, State College, PA 16802, USA.', 'United States|United States|United States|United States|United States', 134, 'Algorithms|Bayes Theorem|Body Mass Index|Computer Simulation|Female|Genome-Wide Association Study|Humans|Male|Markov Chains|Models, Statistical|Polymorphism, Single Nucleotide|Principal Component Analysis', 'Journal Article', '10.1093/bioinformatics/btq688', '21156729', 'Despite their success in identifying genes that affect complex disease or traits, current genome-wide association studies (GWASs) based on a single SNP analysis are too simple to elucidate a comprehensive picture of the genetic architecture of phenotypes. A simultaneous analysis of a large number of SNPs, although statistically challenging, especially with a small number of samples, is crucial for genetic modeling.'),
(75923, 2011, 'bio', 'Alignment-free estimation of nucleotide diversity', 'Haubold, Bernhard|Reed, Floyd A|Pfaffelhuber, Peter', 'Department of Evolutionary Genetics, Albert-Ludwigs University, Freiburg, Germany.|Department of Evolutionary Genetics, Albert-Ludwigs University, Freiburg, Germany.|Department of Evolutionary Genetics, Albert-Ludwigs University, Freiburg, Germany.', 'Germany|Germany|Germany', 17, 'Algorithms|Animals|Computational Biology|Computer Simulation|Drosophila|Genetic Variation|Genome, Insect|Recombination, Genetic|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btq689', '21156730', 'Sequencing capacity is currently growing more rapidly than CPU speed, leading to an analysis bottleneck in many genome projects. Alignment-free sequence analysis methods tend to be more efficient than their alignment-based counterparts. They may, therefore, be important in the long run for keeping sequence analysis abreast with sequencing.'),
(75924, 2011, 'bio', 'Using bioinformatics to predict the functional impact of SNVs', 'Cline, Melissa S|Karchin, Rachel', 'Department of Molecular Cell and Developmental Biology, University of California, Santa Cruz, CA, USA.|Department of Molecular Cell and Developmental Biology, University of California, Santa Cruz, CA, USA.', 'United States|United States', 54, 'Algorithms|Amino Acid Substitution|Artificial Intelligence|Computational Biology|Evolution, Molecular|MicroRNAs|Polymorphism, Single Nucleotide|Protein Processing, Post-Translational|RNA Splicing|Sequence Analysis, Protein|Structure-Activity Relationship|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btq695', '21159622', 'The past decade has seen the introduction of fast and relatively inexpensive methods to detect genetic variation across the genome and exponential growth in the number of known single nucleotide variants (SNVs). There is increasing interest in bioinformatics approaches to identify variants that are functionally important from millions of candidate variants. Here, we describe the essential components of bioinformatics tools that predict functional SNVs.'),
(75925, 2011, 'bio', 'Variable selection for discriminant analysis with Markov random field priors for the analysis of microarray data', 'Stingo, Francesco C|Vannucci, Marina', 'Department of Statistics, Rice University, Houston, TX 77005, USA.|Department of Statistics, Rice University, Houston, TX 77005, USA.', 'United States|United States', 40, 'Algorithms|Bayes Theorem|Discriminant Analysis|Gene Expression Profiling|Gene Regulatory Networks|Markov Chains|Oligonucleotide Array Sequence Analysis|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/btq690', '21159623', 'Discriminant analysis is an effective tool for the classification of experimental units into groups. Here, we consider the typical problem of classifying subjects according to phenotypes via gene expression data and propose a method that incorporates variable selection into the inferential procedure, for the identification of the important biomarkers. To achieve this goal, we build upon a conjugate normal discriminant model, both linear and quadratic, and include a stochastic search variable selection procedure via an MCMC algorithm. Furthermore, we incorporate into the model prior information on the relationships among the genes as described by a gene-gene network. We use a Markov random field (MRF) prior to map the network connections among genes. Our prior model assumes that neighboring genes in the network are more likely to have a joint effect on the relevant biological processes.'),
(75926, 2011, 'bio', 'Automated analysis of information processing, kinetic independence and modular architecture in biochemical networks using MIDIA', 'Bowsher, Clive G', 'School of Mathematics, University of Bristol, Edinburgh, UK. C.Bowsher@bristol.ac', 'United Kingdom', 3, 'Algorithms|Computational Biology|Electronic Data Processing|Gene Regulatory Networks|Kinetics|Metabolic Networks and Pathways|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/btq694', '21159624', 'Understanding the encoding and propagation of information by biochemical reaction networks and the relationship of such information processing properties to modular network structure is of fundamental importance in the study of cell signalling and regulation. However, a rigorous, automated approach for general biochemical networks has not been available, and high-throughput analysis has therefore been out of reach.'),
(75927, 2011, 'bio', 'Using non-uniform read distribution models to improve isoform expression inference in RNA-Seq', 'Wu, Zhengpeng|Wang, Xi|Zhang, Xuegong', 'TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.|TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.|TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.', 'China|China|China', 69, 'Computational Biology|Computer Simulation|Gene Expression Profiling|Models, Statistical|Oligonucleotide Probes|Protein Isoforms|RNA|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btq696', '21169371', 'RNA-Seq technology based on next-generation sequencing provides the unprecedented ability of studying transcriptomes at high resolution and accuracy, and the potential of measuring expression of multiple isoforms from the same gene at high precision. Solved by maximum likelihood estimation, isoform expression can be inferred in RNA-Seq using statistical models based on the assumption that sequenced reads are distributed uniformly along transcripts. Modification of the model is needed when considering situations where RNA-Seq data do not follow uniform distribution.'),
(75928, 2011, 'bio', 'Identifying cancer driver genes in tumor genome sequencing studies', 'Youn, Ahrim|Simon, Richard', 'Biometric Research Branch, National Cancer Institute, Bethesda, MD 20892-7434, USA.|Biometric Research Branch, National Cancer Institute, Bethesda, MD 20892-7434, USA.', 'United States|United States', 120, 'DNA Mutational Analysis|Genes, Neoplasm|Genome|Genomics|Humans|Lung Neoplasms|Mutation|Neoplasms', 'Journal Article', '10.1093/bioinformatics/btq630', '21169372', 'Major tumor sequencing projects have been conducted in the past few years to identify genes that contain driver somatic mutations in tumor samples. These genes have been defined as those for which the non-silent mutation rate is significantly greater than a background mutation rate estimated from silent mutations. Several methods have been used for estimating the background mutation rate.'),
(75929, 2011, 'bio', 'SAIL--a software system for sample and phenotype availability across biobanks and cohorts', 'Gostev, Mikhail|Fernandez-Banet, Julio|Rung, Johan|Dietrich, Joern|Prokopenko, Inga|Ripatti, Samuli|McCarthy, Mark I|Brazma, Alvis|Krestyaninova, Maria', 'Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. gostev@ebi.ac.uk|Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. gostev@ebi.ac.uk|Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. gostev@ebi.ac.uk|Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. gostev@ebi.ac.uk|Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. gostev@ebi.ac.uk|Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. gostev@ebi.ac.uk|Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. gostev@ebi.ac.uk|Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. gostev@ebi.ac.uk|Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. gostev@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 13, 'Computational Biology|Database Management Systems|Genomics|Internet|Meta-Analysis as Topic|Phenotype|Software', 'Journal Article', '10.1093/bioinformatics/btq693', '21169373', 'The Sample avAILability system-SAIL-is a web based application for searching, browsing and annotating biological sample collections or biobank entries. By providing individual-level information on the availability of specific data types (phenotypes, genetic or genomic data) and samples within a collection, rather than the actual measurement data, resource integration can be facilitated. A flexible data structure enables the collection owners to provide descriptive information on their samples using existing or custom vocabularies. Users can query for the available samples by various parameters combining them via logical expressions. The system can be scaled to hold data from millions of samples with thousands of variables.'),
(75930, 2011, 'bio', 'Multi-level mixed effects models for bead arrays', 'Kim, Ryung S|Lin, Juan', 'Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA. ryung.kim@einstein.yu.edu|Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA. ryung.kim@einstein.yu.edu', 'United States|United States', 5, 'Algorithms|Animals|Mice|Microspheres|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sensitivity and Specificity|Software', 'Comparative Study', '10.1093/bioinformatics/btq708', '21169374', 'Bead arrays are becoming a popular platform for high-throughput expression arrays. However, the number of the beads targeting a transcript and the variation of their intensities differ from sample to sample in these arrays. This property results in different accuracy of expression intensities of a transcript across arrays.'),
(75931, 2011, 'bio', 'Adjustment for local ancestry in genetic association analysis of admixed populations', 'Wang, Xuexia|Zhu, Xiaofeng|Qin, Huaizhen|Cooper, Richard S|Ewens, Warren J|Li, Chun|Li, Mingyao', 'Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA.|Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA.|Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA.|Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA.|Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA.|Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA.|Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA.', 'United States|United States|United States|United States|United States|United States|United States', 39, 'Computer Simulation|Gene Frequency|Genetic Predisposition to Disease|Genetics, Population|Genome-Wide Association Study|Genotype|Humans|Likelihood Functions|Logistic Models|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btq709', '21169375', 'Admixed populations offer a unique opportunity for mapping diseases that have large disease allele frequency differences between ancestral populations. However, association analysis in such populations is challenging because population stratification may lead to association with loci unlinked to the disease locus.'),
(75932, 2011, 'bio', 'DROP: an SVM domain linker predictor trained with optimal features selected by random forest', 'Ebina, Teppei|Toh, Hiroyuki|Kuroda, Yutaka', 'Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, Koganei-shi, Tokyo 184-8588, Japan.|Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, Koganei-shi, Tokyo 184-8588, Japan.|Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, Koganei-shi, Tokyo 184-8588, Japan.', 'Japan|Japan|Japan', 47, 'Algorithms|Computational Biology|Protein Structure, Secondary|Proteins|Proteomics', 'Journal Article', '10.1093/bioinformatics/btq700', '21169376', 'Biologically important proteins are often large, multidomain proteins, which are difficult to characterize by high-throughput experimental methods. Efficient domain/boundary predictions are thus increasingly required in diverse area of proteomics research for computationally dissecting proteins into readily analyzable domains.'),
(75933, 2011, 'bio', 'ABMapper: a suffix array-based tool for multi-location searching and splice-junction mapping', 'Lou, Shao-Ke|Ni, Bing|Lo, Leung-Yau|Tsui, Stephen Kwok-Wing|Chan, Ting-Fung|Leung, Kwong-Sak', 'Hong Kong Bioinformatics Centre, Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin NT, Hong Kong SAR.|Hong Kong Bioinformatics Centre, Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin NT, Hong Kong SAR.|Hong Kong Bioinformatics Centre, Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin NT, Hong Kong SAR.|Hong Kong Bioinformatics Centre, Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin NT, Hong Kong SAR.|Hong Kong Bioinformatics Centre, Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin NT, Hong Kong SAR.|Hong Kong Bioinformatics Centre, Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin NT, Hong Kong SAR.', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong', 10, 'Genomics|Humans|RNA Splicing|Sequence Alignment|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btq656', '21169377', 'Sequencing reads generated by RNA-sequencing (RNA-seq) must first be mapped back to the genome through alignment before they can be further analyzed. Current fast and memory-saving short-read mappers could give us a quick view of the transcriptome. However, they are neither designed for reads that span across splice junctions nor for repetitive reads, which can be mapped to multiple locations in the genome (multi-reads). Here, we describe a new software package: ABMapper, which is specifically designed for exploring all putative locations of reads that are mapped to splice junctions or repetitive in nature.'),
(75934, 2011, 'bio', 'phangorn: phylogenetic analysis in R', 'Schliep, Klaus Peter', 'UMR CNRS 7138 Systématique, Adaptation, Evolution, Université Pierre et Marie Curie, Muséum National dHistoire Naturelle, Paris, France. klaus.kschliep@snv.jussieu.fr', 'France', 1013, 'Computational Biology|Likelihood Functions|Models, Genetic|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btq706', '21169378', 'phangorn is a package for phylogenetic reconstruction and analysis in the R language. Previously it was only possible to estimate phylogenetic trees with distance methods in R. phangorn, now offers the possibility of reconstructing phylogenies with distance based methods, maximum parsimony or maximum likelihood (ML) and performing Hadamard conjugation. Extending the general ML framework, this package provides the possibility of estimating mixture and partition models. Furthermore, phangorn offers several functions for comparing trees, phylogenetic models or splits, simulating character data and performing congruence analyses.'),
(75935, 2011, 'bio', 'Lipid Data Analyzer: unattended identification and quantitation of lipids in LC-MS data', 'Hartler, Jürgen|Trötzmüller, Martin|Chitraju, Chandramohan|Spener, Friedrich|Köfeler, Harald C|Thallinger, Gerhard G', 'Institute for Genomics and Bioinformatics, Graz University of Technology, Graz, Austria.|Institute for Genomics and Bioinformatics, Graz University of Technology, Graz, Austria.|Institute for Genomics and Bioinformatics, Graz University of Technology, Graz, Austria.|Institute for Genomics and Bioinformatics, Graz University of Technology, Graz, Austria.|Institute for Genomics and Bioinformatics, Graz University of Technology, Graz, Austria.|Institute for Genomics and Bioinformatics, Graz University of Technology, Graz, Austria.', 'Austria|Austria|Austria|Austria|Austria|Austria', 110, 'Algorithms|Animals|Chromatography, Liquid|Hepatocytes|Lipids|Male|Mass Spectrometry|Mice|Mice, Inbred C57BL|Predictive Value of Tests|Sensitivity and Specificity|Software', 'Journal Article', '10.1093/bioinformatics/btq699', '21169379', 'The accurate measurement of the lipidome permits insights into physiological and pathological processes. Of the present high-throughput technologies, LC-MS especially bears potential of monitoring quantitative changes in hundreds of lipids simultaneously. In order to extract valuable information from huge amount of mass spectrometry data, the aid of automated, reliable, highly sensitive and specific analysis algorithms is indispensable.'),
(75936, 2011, 'bio', 'A novel method for assigning functional linkages to proteins using enhanced phylogenetic trees', 'Ta, Hung Xuan|Koskinen, Patrik|Holm, Liisa', 'Institute of Biotechnology, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland. xuanhung.ta@helsinki.fi|Institute of Biotechnology, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland. xuanhung.ta@helsinki.fi|Institute of Biotechnology, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland. xuanhung.ta@helsinki.fi', 'Finland|Finland|Finland', 7, 'Algorithms|Computational Biology|Evolution, Molecular|Humans|Phylogeny|Proteins|Saccharomyces cerevisiae', 'Journal Article', '10.1093/bioinformatics/btq705', '21169380', 'Functional linkages implicate pairwise relationships between proteins that work together to implement biological tasks. During evolution, functionally linked proteins are likely to be preserved or eliminated across a range of genomes in a correlated fashion. Based on this hypothesis, phylogenetic profiling-based approaches try to detect pairs of protein families that show similar evolutionary patterns. Traditionally, the evolutionary pattern of a protein is encoded by either a binary profile of presence and absence of this protein across species or an occurrence profile that indicates the distribution of copies of this protein across species.'),
(75937, 2011, 'bio', 'Functional integration of a metabolic network model and expression data without arbitrary thresholding', 'Jensen, Paul A|Papin, Jason A', 'Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA.|Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA.', 'United States|United States', 72, 'Algorithms|Fermentation|Gene Expression Profiling|Metabolic Networks and Pathways|Models, Biological|Saccharomyces cerevisiae|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq702', '21172910', 'Flux balance analysis (FBA) has been used extensively to analyze genome-scale, constraint-based models of metabolism in a variety of organisms. The predictive accuracy of such models has recently been improved through the integration of high-throughput expression profiles of metabolic genes and proteins. However, extensions of FBA often require that such data be discretized a priori into sets of genes or proteins that are either on or off. This procedure requires selecting relatively subjective expression thresholds, often requiring several iterations and refinements to capture the expression dynamics and retain model functionality.'),
(75938, 2011, 'bio', 'Fast tomographic reconstruction on multicore computers', 'Agulleiro, J I|Fernandez, J J', 'University of Almeria, Almeria, Spain.|University of Almeria, Almeria, Spain.', 'Spain|Spain', 128, 'Algorithms|Electron Microscope Tomography|Image Processing, Computer-Assisted|Software', 'Journal Article', '10.1093/bioinformatics/btq692', '21172911', 'Tomo3D implements a multithreaded vectorized approach to tomographic reconstruction that takes full advantage of the computer power in modern multicore computers. Full resolution tomograms are generated at high speed on standard computers with no special system requirements. Tomo3D has the most common reconstruction methods implemented, namely weighted Back-projection (WBP) and simultaneous iterative reconstruction technique (SIRT). It proves to be competitive with current graphic processor unit solutions in terms of processing time, in the order of a few seconds with WBP or minutes with SIRT. The program is compatible with standard packages, which easily allows integration in the electron tomography workflow.'),
(75939, 2011, 'bio', 'Statistical analysis of the cancer cells molecular entropy using high-throughput data', 'van Wieringen, Wessel N|van der Vaart, Aad W', 'Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands. wvanwie@few.vu.nl|Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands. wvanwie@few.vu.nl', 'Netherlands|Netherlands', 0, 'Computer Simulation|DNA Copy Number Variations|Entropy|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|High-Throughput Nucleotide Sequencing|Humans|Models, Statistical|Neoplasms', 'Journal Article', '10.1093/bioinformatics/btq704', '21172912', 'As cancer progresses, DNA copy number aberrations accumulate and the genomic entropy (chromosomal disorganization) increases. For this surge to have any oncogenetic effect, it should (to some extent) be reflected at other molecular levels of the cancer cell, in particular that of the transcriptome. Such a coincidence of cancer progression and the propagation of an entropy increase through the molecular levels of the cancer cell would enhance the understanding of cancer evolution.'),
(75940, 2011, 'bio', 'Improvements in the reconstruction of time-varying gene regulatory networks: dynamic programming and regularization by information sharing among genes', 'Grzegorczyk, Marco|Husmeier, Dirk', 'Department of Statistics, TU Dortmund University, Dortmund, Germany. grzegorczyk@statistik.tu-dortmund.de|Department of Statistics, TU Dortmund University, Dortmund, Germany. grzegorczyk@statistik.tu-dortmund.de', 'Germany|Germany', 54, 'Algorithms|Arabidopsis|Bayes Theorem|Cluster Analysis|Computational Biology|Gene Expression Profiling|Gene Regulatory Networks|Markov Chains|Models, Statistical|Monte Carlo Method|Saccharomyces cerevisiae', 'Journal Article', '10.1093/bioinformatics/btq711', '21177328', 'Dynamic Bayesian networks (DBNs) have been applied widely to reconstruct the structure of regulatory processes from time series data, and they have established themselves as a standard modelling tool in computational systems biology. The conventional approach is based on the assumption of a homogeneous Markov chain, and many recent research efforts have focused on relaxing this restriction. An approach that enjoys particular popularity is based on a combination of a DBN with a multiple changepoint process, and the application of a Bayesian inference scheme via reversible jump Markov chain Monte Carlo (RJMCMC). In the present article, we expand this approach in two ways. First, we show that a dynamic programming scheme allows the changepoints to be sampled from the correct conditional distribution, which results in improved convergence over RJMCMC. Second, we introduce a novel Bayesian clustering and information sharing scheme among nodes, which provides a mechanism for automatic model complexity tuning.'),
(75941, 2011, 'bio', 'ASSIMILATOR: a new tool to inform selection of associated genetic variants for functional studies', 'Martin, Paul|Barton, Anne|Eyre, Stephen', 'Arthritis Research UK Epidemiology Unit, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK. paul.martin-2@manchester.ac.uk|Arthritis Research UK Epidemiology Unit, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK. paul.martin-2@manchester.ac.uk|Arthritis Research UK Epidemiology Unit, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK. paul.martin-2@manchester.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Genome-Wide Association Study|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btq611', '21177990', 'Fine-mapping experiments from genome-wide association studies (GWAS) are underway for many complex diseases. These are likely to identify a number of putative causal variants, which cannot be separated further in terms of strength of genetic association due to linkage disequilibrium. The challenge will be selecting which variant to prioritize for subsequent expensive functional studies. A wealth of functional information generated from wet lab experiments now exists but cannot be easily interrogated by the user. Here, we describe a program designed to quickly assimilate this data called ASSIMILATOR and validate the method by interrogating two regions to show its effectiveness.'),
(75942, 2011, 'bio', 'DiNAMIC: a method to identify recurrent DNA copy number aberrations in tumors', 'Walter, Vonn|Nobel, Andrew B|Wright, Fred A', 'Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. vwalter@email.unc.edu|Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. vwalter@email.unc.edu|Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. vwalter@email.unc.edu', 'United States|United States|United States', 27, 'Algorithms|Computational Biology|DNA Copy Number Variations|DNA, Neoplasm|Humans|Neoplasms|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq717', '21183584', 'DNA copy number gains and losses are commonly found in tumor tissue, and some of these aberrations play a role in tumor genesis and development. Although high resolution DNA copy number data can be obtained using array-based techniques, no single method is widely used to distinguish between recurrent and sporadic copy number aberrations.'),
(75943, 2011, 'bio', 'CompleteMOTIFs: DNA motif discovery platform for transcription factor binding experiments', 'Kuttippurathu, Lakshmi|Hsing, Michael|Liu, Yongchao|Schmidt, Bertil|Maskell, Douglas L|Lee, Kyungjoon|He, Aibin|Pu, William T|Kong, Sek Won', 'Childrens Hospital Informatics Program at the Harvard-MIT, Division of Health Sciences and Technology, Department of Medicine, Childrens Hospital Boston, Boston, MA 02115, USA.|Childrens Hospital Informatics Program at the Harvard-MIT, Division of Health Sciences and Technology, Department of Medicine, Childrens Hospital Boston, Boston, MA 02115, USA.|Childrens Hospital Informatics Program at the Harvard-MIT, Division of Health Sciences and Technology, Department of Medicine, Childrens Hospital Boston, Boston, MA 02115, USA.|Childrens Hospital Informatics Program at the Harvard-MIT, Division of Health Sciences and Technology, Department of Medicine, Childrens Hospital Boston, Boston, MA 02115, USA.|Childrens Hospital Informatics Program at the Harvard-MIT, Division of Health Sciences and Technology, Department of Medicine, Childrens Hospital Boston, Boston, MA 02115, USA.|Childrens Hospital Informatics Program at the Harvard-MIT, Division of Health Sciences and Technology, Department of Medicine, Childrens Hospital Boston, Boston, MA 02115, USA.|Childrens Hospital Informatics Program at the Harvard-MIT, Division of Health Sciences and Technology, Department of Medicine, Childrens Hospital Boston, Boston, MA 02115, USA.|Childrens Hospital Informatics Program at the Harvard-MIT, Division of Health Sciences and Technology, Department of Medicine, Childrens Hospital Boston, Boston, MA 02115, USA.|Childrens Hospital Informatics Program at the Harvard-MIT, Division of Health Sciences and Technology, Department of Medicine, Childrens Hospital Boston, Boston, MA 02115, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 39, 'Algorithms|Binding Sites|DNA|Databases, Nucleic Acid|Internet|Models, Statistical|Molecular Sequence Annotation|Protein Binding|Protein Interaction Domains and Motifs|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btq707', '21183585', 'CompleteMOTIFs (cMOTIFs) is an integrated web tool developed to facilitate systematic discovery of overrepresented transcription factor binding motifs from high-throughput chromatin immunoprecipitation experiments. Comprehensive annotations and Boolean logic operations on multiple peak locations enable users to focus on genomic regions of interest for de novo motif discovery using tools such as MEME, Weeder and ChIPMunk. The pipeline incorporates a scanning tool for known motifs from TRANSFAC and JASPAR databases, and performs an enrichment test using local or precalculated background models that significantly improve the motif scanning result. Furthermore, using the cMOTIFs pipeline, we demonstrated that multiple transcription factors could cooperatively bind to the upstream of important stem cell differentiation regulators.'),
(75944, 2011, 'bio', 'Ct3d: tracking microglia motility in 3D using a novel cosegmentation approach', 'Xiao, Hang|Li, Ying|Du, Jiulin|Mosig, Axel', 'Department of Biophysics, Institute of Neuroscience, Shanghai Institutes for Biological Sciences, 200031 Shanghai, China.|Department of Biophysics, Institute of Neuroscience, Shanghai Institutes for Biological Sciences, 200031 Shanghai, China.|Department of Biophysics, Institute of Neuroscience, Shanghai Institutes for Biological Sciences, 200031 Shanghai, China.|Department of Biophysics, Institute of Neuroscience, Shanghai Institutes for Biological Sciences, 200031 Shanghai, China.', 'China|China|China|China', 0, 'Algorithms|Animals|Cell Movement|Cell Tracking|Computational Biology|Imaging, Three-Dimensional|Microglia|Microscopy, Confocal|Software|Zebrafish', 'Journal Article', '10.1093/bioinformatics/btq691', '21186244', 'Cell tracking is an important method to quantitatively analyze time-lapse microscopy data. While numerous methods and tools exist for tracking cells in 2D time-lapse images, only few and very application-specific tracking tools are available for 3D time-lapse images, which is of high relevance in immunoimaging, in particular for studying the motility of microglia in vivo.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(75945, 2011, 'bio', 'PUGSVM: a caBIG™ analytical tool for multiclass gene selection and predictive classification', 'Yu, Guoqiang|Li, Huai|Ha, Sook|Shih, Ie-Ming|Clarke, Robert|Hoffman, Eric P|Madhavan, Subha|Xuan, Jianhua|Wang, Yue', 'Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 11, 'Algorithms|Computational Biology|Gene Expression Profiling|Genes, Neoplasm|Humans|Neoplasms|Phenotype|Software', 'Journal Article', '10.1093/bioinformatics/btq721', '21186245', 'Phenotypic Up-regulated Gene Support Vector Machine (PUGSVM) is a cancer Biomedical Informatics Grid (caBIG™) analytical tool for multiclass gene selection and classification. PUGSVM addresses the problem of imbalanced class separability, small sample size and high gene space dimensionality, where multiclass gene markers are defined by the union of one-versus-everyone phenotypic upregulated genes, and used by a well-matched one-versus-rest support vector machine. PUGSVM provides a simple yet more accurate strategy to identify statistically reproducible mechanistic marker genes for characterization of heterogeneous diseases.'),
(75946, 2011, 'bio', 'A sub-pathway-based approach for identifying drug response principal network', 'Chen, Xiujie|Xu, Jiankai|Huang, Bangqing|Li, Jin|Wu, Xin|Ma, Ling|Jia, Xiaodong|Bian, Xiusen|Tan, Fujian|Liu, Lei|Chen, Sheng|Li, Xia', 'College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenxiujie@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenxiujie@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenxiujie@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenxiujie@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenxiujie@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenxiujie@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenxiujie@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenxiujie@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenxiujie@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenxiujie@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenxiujie@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenxiujie@ems.hrbmu.edu.cn', 'China|China|China|China|China|China|China|China|China|China|China|China', 38, 'Cell Line, Tumor|Dexamethasone|Gene Expression Profiling|Humans|Male|Metabolic Networks and Pathways|Oligonucleotide Array Sequence Analysis|Principal Component Analysis|Prostatic Neoplasms', 'Comparative Study', '10.1093/bioinformatics/btq714', '21186246', 'The high redundancy of and high degree of cross-talk between biological pathways hint that a sub-pathway may respond more effectively or sensitively than the whole pathway. However, few current pathway enrichment analysis methods account for the sub-pathways or structures of the tested pathways. We present a sub-pathway-based enrichment approach for identifying a drug response principal network, which takes into consideration the quantitative structures of the pathways.'),
(75947, 2011, 'bio', 'A computationally efficient modular optimal discovery procedure', 'Woo, Sangsoon|Leek, Jeffrey T|Storey, John D', 'Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.|Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.|Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.', 'United States|United States|United States', 0, 'Algorithms|Computational Biology|Computer Simulation|Gene Expression|Gene Expression Profiling|Humans|Likelihood Functions|Models, Statistical|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btq701', '21186247', 'It is well known that patterns of differential gene expression across biological conditions are often shared by many genes, particularly those within functional groups. Taking advantage of these patterns can lead to increased statistical power and biological clarity when testing for differential expression in a microarray experiment. The optimal discovery procedure (ODP), which maximizes the expected number of true positives for each fixed number of expected false positives, is a framework aimed at this goal. Storey et al. introduced an estimator of the ODP for identifying differentially expressed genes. However, their ODP estimator grows quadratically in computational time with respect to the number of genes. Reducing this computational burden is a key step in making the ODP practical for usage in a variety of high-throughput problems.'),
(75948, 2011, 'bio', 'Voroprot: an interactive tool for the analysis and visualization of complex geometric features of protein structure', 'Olechnovic, Kliment|Margelevicius, Mindaugas|Venclovas, Ceslovas', 'Institute of Biotechnology, Vilnius University, Vilnius, Lithuania.|Institute of Biotechnology, Vilnius University, Vilnius, Lithuania.|Institute of Biotechnology, Vilnius University, Vilnius, Lithuania.', 'Lithuania|Lithuania|Lithuania', 0, 'Computer Graphics|Computer Simulation|Imaging, Three-Dimensional|Models, Molecular|Protein Conformation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btq720', '21186248', 'We present Voroprot, an interactive cross-platform software tool that provides a unique set of capabilities for exploring geometric features of protein structure. Voroprot allows the construction and visualization of the Apollonius diagram (also known as the additively weighted Voronoi diagram), the Apollonius graph, protein alpha shapes, interatomic contact surfaces, solvent accessible surfaces, pockets and cavities inside protein structure.'),
(75949, 2011, 'bio', 'Discovering approximate-associated sequence patterns for protein-DNA interactions', 'Chan, Tak-Ming|Wong, Ka-Chun|Lee, Kin-Hong|Wong, Man-Hon|Lau, Chi-Kong|Tsui, Stephen Kwok-Wing|Leung, Kwong-Sak', 'Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N. T., Hong Kong.|Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N. T., Hong Kong.|Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N. T., Hong Kong.|Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N. T., Hong Kong.|Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N. T., Hong Kong.|Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N. T., Hong Kong.|Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N. T., Hong Kong.', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong', 17, 'Algorithms|Base Sequence|Binding Sites|Computational Biology|DNA|DNA-Binding Proteins|Gene Expression Regulation|Protein Binding|Protein Structure, Tertiary|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btq682', '21193520', 'The bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) are fundamental protein-DNA interactions in transcriptional regulation. Extensive efforts have been made to better understand the protein-DNA interactions. Recent mining on exact TF-TFBS-associated sequence patterns (rules) has shown great potentials and achieved very promising results. However, exact rules cannot handle variations in real data, resulting in limited informative rules. In this article, we generalize the exact rules to approximate ones for both TFs and TFBSs, which are essential for biological variations.'),
(75950, 2011, 'bio', 'Multilign: an algorithm to predict secondary structures conserved in multiple RNA sequences', 'Xu, Zhenjiang|Mathews, David H', 'Department of Biochemistry and Biophysics, University of Rochester Medical Center, Rochester, NY, USA.|Department of Biochemistry and Biophysics, University of Rochester Medical Center, Rochester, NY, USA.', 'United States|United States', 0, 'Algorithms|Computational Biology|Nucleic Acid Conformation|RNA|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1093/bioinformatics/btq726', '21193521', 'With recent advances in sequencing, structural and functional studies of RNA lag behind the discovery of sequences. Computational analysis of RNA is increasingly important to reveal structure-function relationships with low cost and speed. The purpose of this study is to use multiple homologous sequences to infer a conserved RNA structure.'),
(75951, 2011, 'bio', 'Principal network analysis: identification of subnetworks representing major dynamics using gene expression data', 'Kim, Yongsoo|Kim, Taek-Kyun|Kim, Yungu|Yoo, Jiho|You, Sungyong|Lee, Inyoul|Carlson, George|Hood, Leroy|Choi, Seungjin|Hwang, Daehee', 'School of Interdisciplinary Bioscience and Bioengineering, POSTECH, Pohang, Republic of Korea.|School of Interdisciplinary Bioscience and Bioengineering, POSTECH, Pohang, Republic of Korea.|School of Interdisciplinary Bioscience and Bioengineering, POSTECH, Pohang, Republic of Korea.|School of Interdisciplinary Bioscience and Bioengineering, POSTECH, Pohang, Republic of Korea.|School of Interdisciplinary Bioscience and Bioengineering, POSTECH, Pohang, Republic of Korea.|School of Interdisciplinary Bioscience and Bioengineering, POSTECH, Pohang, Republic of Korea.|School of Interdisciplinary Bioscience and Bioengineering, POSTECH, Pohang, Republic of Korea.|School of Interdisciplinary Bioscience and Bioengineering, POSTECH, Pohang, Republic of Korea.|School of Interdisciplinary Bioscience and Bioengineering, POSTECH, Pohang, Republic of Korea.|School of Interdisciplinary Bioscience and Bioengineering, POSTECH, Pohang, Republic of Korea.', '-|-|-|-|-|-|-|-|-|-', 0, 'Animals|Biochemical Phenomena|Cell Differentiation|Cell Line|Cell Proliferation|Computer Simulation|Gene Expression Profiling|Gene Regulatory Networks|Humans|Mice|Neuregulin-1|Prion Diseases|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq670', '21193522', 'Systems biology attempts to describe complex systems behaviors in terms of dynamic operations of biological networks. However, there is lack of tools that can effectively decode complex network dynamics over multiple conditions.'),
(75952, 2011, 'bio', 'Cancer therapy design based on pathway logic', 'Layek, Ritwik|Datta, Aniruddha|Bittner, Michael|Dougherty, Edward R', 'Department of Electrical and Computer Engineering, Texas A & M University, College Station, TX 77843-3128, USA.|Department of Electrical and Computer Engineering, Texas A & M University, College Station, TX 77843-3128, USA.|Department of Electrical and Computer Engineering, Texas A & M University, College Station, TX 77843-3128, USA.|Department of Electrical and Computer Engineering, Texas A & M University, College Station, TX 77843-3128, USA.', 'United States|United States|United States|United States', 51, 'Humans|Intercellular Signaling Peptides and Proteins|Models, Biological|Models, Statistical|Neoplasms|Signal Transduction|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq703', '21193523', 'Cancer encompasses various diseases associated with loss of cell cycle control, leading to uncontrolled cell proliferation and/or reduced apoptosis. Cancer is usually caused by malfunction(s) in the cellular signaling pathways. Malfunctions occur in different ways and at different locations in a pathway. Consequently, therapy design should first identify the location and type of malfunction to arrive at a suitable drug combination.'),
(75953, 2011, 'bio', 'Tabix: fast retrieval of sequence features from generic TAB-delimited files', 'Li, Heng', 'Program in Medical Population Genetics, The Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA. hengli@broadinstitute.org', 'United States', 194, 'Algorithms|Computational Biology|Genome|Genomics|Information Storage and Retrieval|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq671', '21208982', 'Tabix is the first generic tool that indexes position sorted files in TAB-delimited formats such as GFF, BED, PSL, SAM and SQL export, and quickly retrieves features overlapping specified regions. Tabix features include few seek function calls per query, data compression with gzip compatibility and direct FTP/HTTP access. Tabix is implemented as a free command-line tool as well as a library in C, Java, Perl and Python. It is particularly useful for manually examining local genomic features on the command line and enables genome viewers to support huge data files and remote custom tracks over networks.'),
(75954, 2011, 'bio', 'Wave-spec: a preprocessing package for mass spectrometry data', 'Li, Ming|Chen, Shuo|Zhang, Joan|Chen, Heidi|Shyr, Yu', 'Department of Biostatistics, Vanderbilt University, Nashville, Tennessee 37232, USA.|Department of Biostatistics, Vanderbilt University, Nashville, Tennessee 37232, USA.|Department of Biostatistics, Vanderbilt University, Nashville, Tennessee 37232, USA.|Department of Biostatistics, Vanderbilt University, Nashville, Tennessee 37232, USA.|Department of Biostatistics, Vanderbilt University, Nashville, Tennessee 37232, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Calibration|Electronic Data Processing|Software|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Journal Article', '10.1093/bioinformatics/btq724', '21208983', 'Wave-spec is a pre-processing package for mass spectrometry (MS) data. The package includes several novel algorithms that overcome conventional difficulties with the pre-processing of such data. In this application note, we demonstrate step-by-step use of this package on a real-world MALDI dataset.'),
(75955, 2011, 'bio', 'Model selection in Bayesian segmentation of multiple DNA alignments', 'Oldmeadow, Christopher|Keith, Jonathan M', 'Centre for Clinical Epidemiology and Biostatistics, University of Newcastle, NSW, Victoria, Australia. christopher.oldmeadow@newcastle.edu.au|Centre for Clinical Epidemiology and Biostatistics, University of Newcastle, NSW, Victoria, Australia. christopher.oldmeadow@newcastle.edu.au', 'Australia|Australia', 0, 'Algorithms|Animals|Bayes Theorem|Computational Biology|Computer Simulation|DNA|Evolution, Molecular|Genomics|Mice|Models, Statistical|Primates|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btq716', '21208984', 'The analysis of multiple sequence alignments is allowing researchers to glean valuable insights into evolution, as well as identify genomic regions that may be functional, or discover novel classes of functional elements. Understanding the distribution of conservation levels that constitutes the evolutionary landscape is crucial to distinguishing functional regions from non-functional. Recent evidence suggests that a binary classification of evolutionary rates is inappropriate for this purpose and finds only highly conserved functional elements. Given that the distribution of evolutionary rates is multi-modal, determining the number of modes is of paramount concern. Through simulation, we evaluate the performance of a number of information criterion approaches derived from MCMC simulations in determining the dimension of a model.'),
(75956, 2011, 'bio', 'MBRole: enrichment analysis of metabolomic data', 'Chagoyen, Monica|Pazos, Florencio', 'Computational Systems Biology Group, National Centre for Biotechnology (CNB-CSIC), Madrid, Spain. monica.chagoyen@cnb.csic.es|Computational Systems Biology Group, National Centre for Biotechnology (CNB-CSIC), Madrid, Spain. monica.chagoyen@cnb.csic.es', 'Spain|Spain', 106, 'Computational Biology|Databases, Factual|Internet|Metabolomics|Software', 'Journal Article', '10.1093/bioinformatics/btr001', '21208985', 'While many tools exist for performing enrichment analysis of transcriptomic and proteomic data in order to interpret them in biological terms, almost no equivalent tools exist for metabolomic data. We present Metabolite Biological Role (MBRole), a web server for carrying out over-representation analysis of biological and chemical annotations in arbitrary sets of metabolites (small chemical compounds) coming from metabolomic data of any organism or sample.'),
(75957, 2011, 'bio', 'MIRACH: efficient model checker for quantitative biological pathway models', 'Koh, Chuan Hock|Nagasaki, Masao|Saito, Ayumu|Li, Chen|Wong, Limsoon|Miyano, Satoru', 'NUS Graduate School for Integrative Sciences and Engineering, Singapore, Singapore.|NUS Graduate School for Integrative Sciences and Engineering, Singapore, Singapore.|NUS Graduate School for Integrative Sciences and Engineering, Singapore, Singapore.|NUS Graduate School for Integrative Sciences and Engineering, Singapore, Singapore.|NUS Graduate School for Integrative Sciences and Engineering, Singapore, Singapore.|NUS Graduate School for Integrative Sciences and Engineering, Singapore, Singapore.', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 4, 'Algorithms|Confidence Intervals|Models, Biological|Models, Statistical|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq727', '21208986', 'Model checking is playing an increasingly important role in systems biology as larger and more complex biological pathways are being modeled. In this article we report the release of an efficient model checker MIRACH 1.0, which supports any model written in popular formats such as CSML and SBML. MIRACH is integrated with a Petri-net-based simulation engine, enabling efficient online (on-the-fly) checking. In our experiment, by using Levchenko et al. model, we reveal that timesaving gains by using MIRACH easily surpass 400% compared with its offline-based counterpart.'),
(75958, 2011, 'bio', 'flowPhyto: enabling automated analysis of microscopic algae from continuous flow cytometric data', 'Ribalet, Francois|Schruth, David M|Armbrust, E Virginia', 'School of Oceanography, University of Washington, Seattle, WA 98195, USA.|School of Oceanography, University of Washington, Seattle, WA 98195, USA.|School of Oceanography, University of Washington, Seattle, WA 98195, USA.', 'United States|United States|United States', 12, 'Computer Graphics|Electronic Data Processing|Flow Cytometry|Microalgae|Software|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/btr003', '21208987', 'Flow cytometry is a widely used technique among biologists to study the abundances of populations of microscopic algae living in aquatic environments. A new generation of high-frequency flow cytometers collects up to several hundred samples per day and can run continuously for several weeks. Automated computational methods are needed to analyze the different phytoplankton populations present in each sample. Software packages in the programming environment R provide powerful tools for conducting such analyses.'),
(75959, 2011, 'bio', 'The CCPN Metabolomics Project: a fast protocol for metabolite identification by 2D-NMR', 'Chignola, Francesca|Mari, Silvia|Stevens, Tim J|Fogh, Rasmus H|Mannella, Valeria|Boucher, Wayne|Musco, Giovanna', 'Biomolecular NMR Laboratory, Dulbecco Telethon Institute c/o San Raffaele Scientific Institute - DIBIT, Via Olgettina 58, 20132 Milan, Italy.|Biomolecular NMR Laboratory, Dulbecco Telethon Institute c/o San Raffaele Scientific Institute - DIBIT, Via Olgettina 58, 20132 Milan, Italy.|Biomolecular NMR Laboratory, Dulbecco Telethon Institute c/o San Raffaele Scientific Institute - DIBIT, Via Olgettina 58, 20132 Milan, Italy.|Biomolecular NMR Laboratory, Dulbecco Telethon Institute c/o San Raffaele Scientific Institute - DIBIT, Via Olgettina 58, 20132 Milan, Italy.|Biomolecular NMR Laboratory, Dulbecco Telethon Institute c/o San Raffaele Scientific Institute - DIBIT, Via Olgettina 58, 20132 Milan, Italy.|Biomolecular NMR Laboratory, Dulbecco Telethon Institute c/o San Raffaele Scientific Institute - DIBIT, Via Olgettina 58, 20132 Milan, Italy.|Biomolecular NMR Laboratory, Dulbecco Telethon Institute c/o San Raffaele Scientific Institute - DIBIT, Via Olgettina 58, 20132 Milan, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Computational Biology|Databases, Factual|Magnetic Resonance Spectroscopy|Metabolomics|Software', 'Journal Article', '10.1093/bioinformatics/btr013', '21216771', 'We present here the freely available Metabolomics Project resource specifically designed to work under the CcpNmr Analysis program produced by CCPN (Collaborative Computing Project for NMR) (Vranken et al., 2005, The CCPN data model for NMR spectroscopy: development of a software pipeline. Proteins, 59, 687-696). The project consists of a database of assigned 1D and 2D spectra of many common metabolites. The project aims to help the user to analyze and assign 1D and 2D NMR spectra of unknown metabolite mixtures. Spectra of unknown mixtures can be easily superimposed and compared with the database spectra, thus facilitating their assignment and identification.'),
(75960, 2011, 'bio', 'Improved side-chain modeling by coupling clash-detection guided iterative search with rotamer relaxation', 'Cao, Yang|Song, Lin|Miao, Zhichao|Hu, Yun|Tian, Liqing|Jiang, Taijiao', 'National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.|National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.|National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.|National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.|National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.|National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.', 'China|China|China|China|China|China', 29, 'Algorithms|Computational Biology|Models, Molecular|Protein Conformation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btr009', '21216772', 'Side-chain modeling has seen wide applications in computational structure biology. Most of the popular side-chain modeling programs explore the conformation space using discrete rigid rotamers for speed and efficiency. However, in the tightly packed environments of protein interiors, these methods will inherently lead to atomic clashes and hinder the prediction accuracy.'),
(75961, 2011, 'bio', 'A method for identifying haplotypes carrying the causative allele in positive natural selection and genome-wide association studies', 'Ong, Rick Twee-Hee|Liu, Xuanyao|Poh, Wan-Ting|Sim, Xueling|Chia, Kee-Seng|Teo, Yik-Ying', 'Department of Epidemiology and Public Health, National University of Singapore, Singapore. g0801900@nus.edu.sg|Department of Epidemiology and Public Health, National University of Singapore, Singapore. g0801900@nus.edu.sg|Department of Epidemiology and Public Health, National University of Singapore, Singapore. g0801900@nus.edu.sg|Department of Epidemiology and Public Health, National University of Singapore, Singapore. g0801900@nus.edu.sg|Department of Epidemiology and Public Health, National University of Singapore, Singapore. g0801900@nus.edu.sg|Department of Epidemiology and Public Health, National University of Singapore, Singapore. g0801900@nus.edu.sg', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 6, 'Algorithms|Alleles|Computational Biology|Databases, Genetic|Genetics, Population|Genome, Human|Genome-Wide Association Study|Haplotypes|Humans|Polymorphism, Single Nucleotide|Selection, Genetic|Software', 'Journal Article', '10.1093/bioinformatics/btr007', '21216773', 'Methods for detecting positive selection relied on finding evidence of long haplotypes to identify candidate regions under selection. However, these methods generally do not identify the length and form of the selected haplotype.'),
(75962, 2011, 'bio', 'The Physiome Model Repository 2', 'Yu, Tommy|Lloyd, Catherine M|Nickerson, David P|Cooling, Michael T|Miller, Andrew K|Garny, Alan|Terkildsen, Jonna R|Lawson, James|Britten, Randall D|Hunter, Peter J|Nielsen, Poul M F', 'Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand. tommy.yu@auckland.ac.nz|Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand. tommy.yu@auckland.ac.nz|Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand. tommy.yu@auckland.ac.nz|Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand. tommy.yu@auckland.ac.nz|Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand. tommy.yu@auckland.ac.nz|Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand. tommy.yu@auckland.ac.nz|Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand. tommy.yu@auckland.ac.nz|Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand. tommy.yu@auckland.ac.nz|Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand. tommy.yu@auckland.ac.nz|Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand. tommy.yu@auckland.ac.nz|Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand. tommy.yu@auckland.ac.nz', 'New Zealand|New Zealand|New Zealand|New Zealand|New Zealand|New Zealand|New Zealand|New Zealand|New ', 84, 'Computational Biology|Databases, Factual|Internet|Models, Biological|Software', 'Journal Article', '10.1093/bioinformatics/btq723', '21216774', 'The Physiome Model Repository 2 (PMR2) software was created as part of the IUPS Physiome Project (Hunter and Borg, 2003), and today it serves as the foundation for the CellML model repository. Key advantages brought to the end user by PMR2 include: facilities for model exchange, enhanced collaboration and a detailed change history for each model.'),
(75963, 2011, 'bio', 'A greedy, graph-based algorithm for the alignment of multiple homologous gene lists', 'Fostier, Jan|Proost, Sebastian|Dhoedt, Bart|Saeys, Yvan|Demeester, Piet|Van de Peer, Yves|Vandepoele, Klaas', 'Department of Information Technology, Ghent University, Ghent, Belgium.|Department of Information Technology, Ghent University, Ghent, Belgium.|Department of Information Technology, Ghent University, Ghent, Belgium.|Department of Information Technology, Ghent University, Ghent, Belgium.|Department of Information Technology, Ghent University, Ghent, Belgium.|Department of Information Technology, Ghent University, Ghent, Belgium.|Department of Information Technology, Ghent University, Ghent, Belgium.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 15, 'Algorithms|Arabidopsis|Computational Biology|Genome|Genomics|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btr008', '21216775', 'Many comparative genomics studies rely on the correct identification of homologous genomic regions using accurate alignment tools. In such case, the alphabet of the input sequences consists of complete genes, rather than nucleotides or amino acids. As optimal multiple sequence alignment is computationally impractical, a progressive alignment strategy is often employed. However, such an approach is susceptible to the propagation of alignment errors in early pairwise alignment steps, especially when dealing with strongly diverged genomic regions. In this article, we present a novel accurate and efficient greedy, graph-based algorithm for the alignment of multiple homologous genomic segments, represented as ordered gene lists.'),
(75964, 2011, 'bio', 'MADGene: retrieval and processing of gene identifier lists for the analysis of heterogeneous microarray datasets', 'Baron, Daniel|Bihouée, Audrey|Teusan, Raluca|Dubois, Emeric|Savagner, Frédérique|Steenman, Marja|Houlgatte, Rémi|Ramstein, Gérard', 'INSERM U915, IRT-UN, University of Nantes, France.|INSERM U915, IRT-UN, University of Nantes, France.|INSERM U915, IRT-UN, University of Nantes, France.|INSERM U915, IRT-UN, University of Nantes, France.|INSERM U915, IRT-UN, University of Nantes, France.|INSERM U915, IRT-UN, University of Nantes, France.|INSERM U915, IRT-UN, University of Nantes, France.|INSERM U915, IRT-UN, University of Nantes, France.', 'France|France|France|France|France|France|France|France', 36, 'Cluster Analysis|Computational Biology|Databases, Genetic|Internet|Meta-Analysis as Topic|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq710', '21216776', 'MADGene is a software environment comprising a web-based database and a java application. This platform aims at unifying gene identifiers (ids) and performing gene set analysis. MADGene allows the user to perform inter-conversion of clone and gene ids over a large range of nomenclatures relative to 17 species. We propose a set of 23 functions to facilitate the analysis of gene sets and we give two microarray applications to show how MADGene can be used to conduct meta-analyses.'),
(75965, 2011, 'bio', 'HiSpOD: probe design for functional DNA microarrays', 'Dugat-Bony, Eric|Missaoui, Mohieddine|Peyretaillade, Eric|Biderre-Petit, Corinne|Bouzid, Ourdia|Gouinaud, Christophe|Hill, David|Peyret, Pierre', 'Clermont Université, Université Blaise Pascal, Laboratoire Microorganismes: Génome et Environnement, BP 10448, Clermont-Ferrand, France.|Clermont Université, Université Blaise Pascal, Laboratoire Microorganismes: Génome et Environnement, BP 10448, Clermont-Ferrand, France.|Clermont Université, Université Blaise Pascal, Laboratoire Microorganismes: Génome et Environnement, BP 10448, Clermont-Ferrand, France.|Clermont Université, Université Blaise Pascal, Laboratoire Microorganismes: Génome et Environnement, BP 10448, Clermont-Ferrand, France.|Clermont Université, Université Blaise Pascal, Laboratoire Microorganismes: Génome et Environnement, BP 10448, Clermont-Ferrand, France.|Clermont Université, Université Blaise Pascal, Laboratoire Microorganismes: Génome et Environnement, BP 10448, Clermont-Ferrand, France.|Clermont Université, Université Blaise Pascal, Laboratoire Microorganismes: Génome et Environnement, BP 10448, Clermont-Ferrand, France.|Clermont Université, Université Blaise Pascal, Laboratoire Microorganismes: Génome et Environnement, BP 10448, Clermont-Ferrand, France.', 'France|France|France|France|France|France|France|France', 27, 'Algorithms|Base Sequence|Biodegradation, Environmental|Consensus Sequence|Databases, Nucleic Acid|Environmental Monitoring|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes|Sensitivity and Specificity|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btq712', '21216777', 'The use of DNA microarrays allows the monitoring of the extreme microbial diversity encountered in complex samples like environmental ones as well as that of their functional capacities. However, no probe design software currently available is adapted to easily design efficient and explorative probes for functional gene arrays.'),
(75966, 2011, 'bio', 'X-MATE: a flexible system for mapping short read data', 'Wood, David L A|Xu, Qinying|Pearson, John V|Cloonan, Nicole|Grimmond, Sean M', 'The University of Queensland, Queensland, Australia.|The University of Queensland, Queensland, Australia.|The University of Queensland, Queensland, Australia.|The University of Queensland, Queensland, Australia.|The University of Queensland, Queensland, Australia.', 'Australia|Australia|Australia|Australia|Australia', 8, 'Chromosome Mapping|Computational Biology|Databases, Genetic|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btq698', '21216778', 'Accurate and complete mapping of short-read sequencing to a reference genome greatly enhances the discovery of biological results and improves statistical predictions. We recently presented RNA-MATE, a pipeline for the recursive mapping of RNA-Seq datasets. With the rapid increase in genome re-sequencing projects, progression of available mapping software and the evolution of file formats, we now present X-MATE, an updated version of RNA-MATE, capable of mapping both RNA-Seq and DNA datasets and with improved performance, output file formats, configuration files, and flexibility in core mapping software.'),
(75967, 2011, 'bio', 'A Java API for working with PubChem datasets', 'Southern, Mark R|Griffin, Patrick R', 'Translational Research Institute and Molecular Therapeutics, The Scripps Research Institute, Scripps Florida, Jupiter, FL 33458, USA. southern@scripps.edu|Translational Research Institute and Molecular Therapeutics, The Scripps Research Institute, Scripps Florida, Jupiter, FL 33458, USA. southern@scripps.edu', 'United States|United States', 6, 'Computational Biology|Databases, Factual|Information Storage and Retrieval|Internet|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/btq715', '21216779', 'PubChem is a public repository of chemical structures and associated biological activities. The PubChem BioAssay database contains assay descriptions, conditions and readouts and biological screening results that have been submitted by the biomedical research community. The PubChem web site and Power User Gateway (PUG) web service allow users to interact with the data and raw files are available via FTP. These resources are helpful to many but there can also be great benefit by using a software API to manipulate the data. Here, we describe a Java API with entity objects mapped to the PubChem Schema and with wrapper functions for calling the NCBI eUtilities and PubChem PUG web services. PubChem BioAssays and associated chemical compounds can then be queried and manipulated in a local relational database. Features include chemical structure searching and generation and display of curve fits from stored dose-response experiments, something that is not yet available within PubChem itself. The aim is to provide researchers with a fast, consistent, queryable local resource from which to manipulate PubChem BioAssays in a database agnostic manner. It is not intended as an end user tool but to provide a platform for further automation and tools development.'),
(75968, 2011, 'bio', 'A novel hybrid gene prediction method employing protein multiple sequence alignments', 'Keller, Oliver|Kollmar, Martin|Stanke, Mario|Waack, Stephan', 'Institute of Computer Science, University of Göttingen, Goldschmidtstrasse 7, Greifswald, Germany. keller@cs.uni-goettingen.de|Institute of Computer Science, University of Göttingen, Goldschmidtstrasse 7, Greifswald, Germany. keller@cs.uni-goettingen.de|Institute of Computer Science, University of Göttingen, Goldschmidtstrasse 7, Greifswald, Germany. keller@cs.uni-goettingen.de|Institute of Computer Science, University of Göttingen, Goldschmidtstrasse 7, Greifswald, Germany. keller@cs.uni-goettingen.de', 'Germany|Germany|Germany|Germany', 182, 'Algorithms|Amino Acid Sequence|Animals|Computational Biology|Dyneins|Electronic Data Processing|Exons|Humans|Models, Genetic|Multigene Family|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btr010', '21216780', 'As improved DNA sequencing techniques have increased enormously the speed of producing new eukaryotic genome assemblies, the further development of automated gene prediction methods continues to be essential. While the classification of proteins into families is a task heavily relying on correct gene predictions, it can at the same time provide a source of additional information for the prediction, complementary to those presently used.'),
(75969, 2011, 'bio', 'R/mpMap: a computational platform for the genetic analysis of multiparent recombinant inbred lines', 'Huang, B Emma|George, Andrew W', 'Division of Mathematics, Informatics and Statistics, CSIRO, St Lucia, QLD, Australia. emma.huang@csiro.au|Division of Mathematics, Informatics and Statistics, CSIRO, St Lucia, QLD, Australia. emma.huang@csiro.au', 'Australia|Australia', 62, 'Chromosome Mapping|Computational Biology|Computer Simulation|Crosses, Genetic|Genetic Markers|Haplotypes|Likelihood Functions|Models, Genetic|Quantitative Trait Loci|Software', 'Journal Article', '10.1093/bioinformatics/btq719', '21217121', 'Multiparent crosses of recombinant inbred lines provide opportunity to map markers and quantitative trait loci (QTL) with much greater resolution than is possible in biparental crosses. Realizing the full potential of these crosses requires computational tools capable of handling the increased statistical complexity of the analyses. R/mpMap provides a flexible and extensible environment, which interfaces easily with other packages to satisfy this demand. Functions in the package encompass simulation, marker map construction, haplotype reconstruction and QTL mapping. We demonstrate the easy-to-use features of mpMap through a simulated data example.'),
(75970, 2011, 'bio', 'A fast, lock-free approach for efficient parallel counting of occurrences of k-mers', 'Marçais, Guillaume|Kingsford, Carl', 'Department of Computer Science, University of Maryland, College Park, MD 20742, USA. gmarcais@umd.edu|Department of Computer Science, University of Maryland, College Park, MD 20742, USA. gmarcais@umd.edu', 'United States|United States', 936, 'Algorithms|Animals|Base Sequence|Computational Biology|Genome|Humans|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr011', '21217122', 'Counting the number of occurrences of every k-mer (substring of length k) in a long string is a central subproblem in many applications, including genome assembly, error correction of sequencing reads, fast multiple sequence alignment and repeat detection. Recently, the deep sequence coverage generated by next-generation sequencing technologies has caused the amount of sequence to be processed during a genome project to grow rapidly, and has rendered current k-mer counting tools too slow and memory intensive. At the same time, large multicore computers have become commonplace in research facilities allowing for a new parallel computational paradigm.'),
(75971, 2011, 'bio', 'Robust linear regression methods in association studies', 'Lourenço, V M|Pires, A M|Kirst, M', 'Department of Mathematics, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal. vmml@fct.unl.pt|Department of Mathematics, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal. vmml@fct.unl.pt|Department of Mathematics, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal. vmml@fct.unl.pt', 'Portugal|Portugal|Portugal', 22, 'Computational Biology|Computer Simulation|Genetic Association Studies|Least-Squares Analysis|Linear Models|Polymorphism, Single Nucleotide|Quantitative Trait, Heritable', 'Journal Article', '10.1093/bioinformatics/btr006', '21217123', 'It is well known that data deficiencies, such as coding/rounding errors, outliers or missing values, may lead to misleading results for many statistical methods. Robust statistical methods are designed to accommodate certain types of those deficiencies, allowing for reliable results under various conditions. We analyze the case of statistical tests to detect associations between genomic individual variations (SNP) and quantitative traits when deviations from the normality assumption are observed. We consider the classical analysis of variance tests for the parameters of the appropriate linear model and a robust version of those tests based on M-regression. We then compare their empirical power and level using simulated data with several degrees of contamination.'),
(75972, 2011, 'bio', 'GPU accelerated biochemical network simulation', 'Zhou, Yanxiang|Liepe, Juliane|Sheng, Xia|Stumpf, Michael P H|Barnes, Chris', 'Institute of Mathematical Sciences, Imperial College London, London, UK.|Institute of Mathematical Sciences, Imperial College London, London, UK.|Institute of Mathematical Sciences, Imperial College London, London, UK.|Institute of Mathematical Sciences, Imperial College London, London, UK.|Institute of Mathematical Sciences, Imperial College London, London, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 51, 'Algorithms|Computational Biology|Computer Graphics|Computer Simulation|Models, Biological|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btr015', '21224286', 'Mathematical modelling is central to systems and synthetic biology. Using simulations to calculate statistics or to explore parameter space is a common means for analysing these models and can be computationally intensive. However, in many cases, the simulations are easily parallelizable. Graphics processing units (GPUs) are capable of efficiently running highly parallel programs and outperform CPUs in terms of raw computing power. Despite their computational advantages, their adoption by the systems biology community is relatively slow, since differences in hardware architecture between GPUs and CPUs complicate the porting of existing code.'),
(75973, 2011, 'bio', 'A k-mer scheme to predict piRNAs and characterize locust piRNAs', 'Zhang, Yi|Wang, Xianhui|Kang, Le', 'Institute of Zoology, Chinese Academy of Sciences, Beijing, China.|Institute of Zoology, Chinese Academy of Sciences, Beijing, China.|Institute of Zoology, Chinese Academy of Sciences, Beijing, China.', 'China|China|China', 74, 'Algorithms|Animals|Computational Biology|Grasshoppers|Humans|RNA, Small Interfering|Retroelements|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btr016', '21224287', 'Identifying piwi-interacting RNAs (piRNAs) of non-model organisms is a difficult and unsolved problem because piRNAs lack conservative secondary structure motifs and sequence homology in different species.'),
(75974, 2011, 'bio', 'CNAmet: an R package for integrating copy number, methylation and expression data', 'Louhimo, Riku|Hautaniemi, Sampsa', 'Institute of Biomedicine and Genome-Scale Biology Research Program, University of Helsinki, Finland.|Institute of Biomedicine and Genome-Scale Biology Research Program, University of Helsinki, Finland.', 'Finland|Finland', 50, 'Algorithms|Computational Biology|DNA Methylation|Female|Gene Dosage|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genomic Instability|Glioblastoma|Humans|Ovarian Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/btr019', '21228048', 'Gene copy number and DNA methylation alterations are key regulators of gene expression in cancer. Accordingly, genes that show simultaneous methylation, copy number and expression alterations are likely to have a key role in tumor progression. We have implemented a novel software package (CNAmet) for integrative analysis of high-throughput copy number, DNA methylation and gene expression data. To demonstrate the utility of CNAmet, we use copy number, DNA methylation and gene expression data from 50 glioblastoma multiforme and 188 ovarian cancer primary tumor samples. Our results reveal a synergistic effect of DNA methylation and copy number alterations on gene expression for several known oncogenes as well as novel candidate oncogenes.'),
(75975, 2011, 'bio', 'ESS++: a C++ objected-oriented algorithm for Bayesian stochastic search model exploration', 'Bottolo, Leonardo|Chadeau-Hyam, Marc|Hastie, David I|Langley, Sarah R|Petretto, Enrico|Tiret, Laurence|Tregouet, David|Richardson, Sylvia', 'Department of Epidemiology and Biostatistics, Imperial College London, UK. l.bottolo@imperial.ac.uk|Department of Epidemiology and Biostatistics, Imperial College London, UK. l.bottolo@imperial.ac.uk|Department of Epidemiology and Biostatistics, Imperial College London, UK. l.bottolo@imperial.ac.uk|Department of Epidemiology and Biostatistics, Imperial College London, UK. l.bottolo@imperial.ac.uk|Department of Epidemiology and Biostatistics, Imperial College London, UK. l.bottolo@imperial.ac.uk|Department of Epidemiology and Biostatistics, Imperial College London, UK. l.bottolo@imperial.ac.uk|Department of Epidemiology and Biostatistics, Imperial College London, UK. l.bottolo@imperial.ac.uk|Department of Epidemiology and Biostatistics, Imperial College London, UK. l.bottolo@imperial.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 23, 'Algorithms|Bayes Theorem|Gene Expression Regulation|Linear Models|Models, Statistical|Programming Languages|Software|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/btq684', '21233165', 'ESS++ is a C++ implementation of a fully Bayesian variable selection approach for single and multiple response linear regression. ESS++ works well both when the number of observations is larger than the number of predictors and in the large p, small n case. In the current version, ESS++ can handle several hundred observations, thousands of predictors and a few responses simultaneously. The core engine of ESS++ for the selection of relevant predictors is based on Evolutionary Monte Carlo. Our implementation is open source, allowing community-based alterations and improvements.'),
(75976, 2011, 'bio', 'A pipeline for RNA-seq data processing and quality assessment', 'Goncalves, Angela|Tikhonov, Andrew|Brazma, Alvis|Kapushesky, Misha', 'EMBL Outstation-Hinxton, European Bioinformatics Institute, Cambridge, UK. angela.goncalves@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Cambridge, UK. angela.goncalves@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Cambridge, UK. angela.goncalves@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Cambridge, UK. angela.goncalves@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Computational Biology|Databases, Genetic|Gene Expression Profiling|Internet|RNA|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btr012', '21233166', 'We present an R based pipeline, ArrayExpressHTS, for pre-processing, expression estimation and data quality assessment of high-throughput sequencing transcriptional profiling (RNA-seq) datasets. The pipeline starts from raw sequence files and produces standard Bioconductor R objects containing gene or transcript measurements for downstream analysis along with web reports for data quality assessment. It may be run locally on a users own computer or remotely on a distributed R-cloud farm at the European Bioinformatics Institute. It can be used to analyse users own datasets or public RNA-seq datasets from the ArrayExpress Archive.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(75977, 2011, 'bio', 'AGE: defining breakpoints of genomic structural variants at single-nucleotide resolution, through optimal alignments with gap excision', 'Abyzov, Alexej|Gerstein, Mark', 'Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA.|Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA.', 'United States|United States', 0, 'Algorithms|Contig Mapping|Genome, Human|Genomic Structural Variation|Humans|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btq713', '21233167', 'Defining the precise location of structural variations (SVs) at single-nucleotide breakpoint resolution is an important problem, as it is a prerequisite for classifying SVs, evaluating their functional impact and reconstructing personal genome sequences. Given approximate breakpoint locations and a bridging assembly or split read, the problem essentially reduces to finding a correct sequence alignment. Classical algorithms for alignment and their generalizations guarantee finding the optimal (in terms of scoring) global or local alignment of two sequences. However, they cannot generally be applied to finding the biologically correct alignment of genomic sequences containing SVs because of the need to simultaneously span the SV (e.g. make a large gap) and perform precise local alignments at the flanking ends.'),
(75978, 2011, 'bio', 'High-accuracy prediction of bacterial type III secreted effectors based on position-specific amino acid composition profiles', 'Wang, Yejun|Zhang, Qing|Sun, Ming-An|Guo, Dianjing', 'The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong.|The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong.|The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong.|The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong.', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong', 71, 'Algorithms|Amino Acid Sequence|Bacterial Proteins|Bacterial Secretion Systems|Bayes Theorem|Computational Biology|Genome, Bacterial|Models, Statistical|Ralstonia solanacearum|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btr021', '21233168', 'Bacterial type III secreted (T3S) effectors are delivered into host cells specifically via type III secretion systems (T3SSs), which play important roles in the interaction between bacteria and their hosts. Previous computational methods for T3S protein prediction have only achieved limited accuracy, and distinct features for effective T3S protein prediction remain to be identified.'),
(75979, 2011, 'bio', 'Clustering 16S rRNA for OTU prediction: a method of unsupervised Bayesian clustering', 'Hao, Xiaolin|Jiang, Rui|Chen, Ting', 'Department of Biology, University of Southern California, University Park, Los Angeles, CA 90089, USA.|Department of Biology, University of Southern California, University Park, Los Angeles, CA 90089, USA.|Department of Biology, University of Southern California, University Park, Los Angeles, CA 90089, USA.', 'United States|United States|United States', 0, 'Bayes Theorem|Cluster Analysis|Computational Biology|Humans|Metagenome|Models, Statistical|RNA, Ribosomal, 16S|Sequence Analysis, DNA|Skin', 'Journal Article', '10.1093/bioinformatics/btq725', '21233169', 'With the advancements of next-generation sequencing technology, it is now possible to study samples directly obtained from the environment. Particularly, 16S rRNA gene sequences have been frequently used to profile the diversity of organisms in a sample. However, such studies are still taxed to determine both the number of operational taxonomic units (OTUs) and their relative abundance in a sample.'),
(75980, 2011, 'bio', 'Automated bond order assignment as an optimization problem', 'Dehof, Anna Katharina|Rurainski, Alexander|Bui, Quang Bao Anh|Böcker, Sebastian|Lenhof, Hans-Peter|Hildebrandt, Andreas', 'Center for Bioinformatics, Saarland University, Saarbrücken, Germany. anna.dehof@bioinf.uni-sb.de|Center for Bioinformatics, Saarland University, Saarbrücken, Germany. anna.dehof@bioinf.uni-sb.de|Center for Bioinformatics, Saarland University, Saarbrücken, Germany. anna.dehof@bioinf.uni-sb.de|Center for Bioinformatics, Saarland University, Saarbrücken, Germany. anna.dehof@bioinf.uni-sb.de|Center for Bioinformatics, Saarland University, Saarbrücken, Germany. anna.dehof@bioinf.uni-sb.de|Center for Bioinformatics, Saarland University, Saarbrücken, Germany. anna.dehof@bioinf.uni-sb.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 9, 'Algorithms|Computational Biology|Hydrogen Bonding|Ligands|Linear Models|Molecular Conformation|Nucleic Acids|Proteins', 'Journal Article', '10.1093/bioinformatics/btq718', '21245051', 'Numerous applications in Computational Biology process molecular structures and hence strongly rely not only on correct atomic coordinates but also on correct bond order information. For proteins and nucleic acids, bond orders can be easily deduced but this does not hold for other types of molecules like ligands. For ligands, bond order information is not always provided in molecular databases and thus a variety of approaches tackling this problem have been developed. In this work, we extend an ansatz proposed by Wang et al. that assigns connectivity-based penalty scores and tries to heuristically approximate its optimum. In this work, we present three efficient and exact solvers for the problem replacing the heuristic approximation scheme of the original approach: an A*, an ILP and an fixed-parameter approach (FPT) approach.'),
(75981, 2011, 'bio', 'Identifying viral integration sites using SeqMap 20', 'Hawkins, Troy B|Dantzer, Jessica|Peters, Brandon|Dinauer, Mary|Mockaitis, Keithanne|Mooney, Sean|Cornetta, Kenneth', 'Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA. troyhawk@iupui.edu|Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA. troyhawk@iupui.edu|Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA. troyhawk@iupui.edu|Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA. troyhawk@iupui.edu|Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA. troyhawk@iupui.edu|Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA. troyhawk@iupui.edu|Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA. troyhawk@iupui.edu', 'India|India|India|India|India|India|India', 0, 'Cluster Analysis|Genome, Viral|High-Throughput Nucleotide Sequencing|Internet|Retroviridae|Sequence Alignment|Software|Virus Integration', 'Journal Article', '10.1093/bioinformatics/btq722', '21245052', 'Retroviral integration has been implicated in several biomedical applications, including identification of cancer-associated genes and malignant transformation in gene therapy clinical trials. We introduce an efficient and scalable method for fast identification of viral vector integration sites from long read high-throughput sequencing. Individual sequence reads are masked to remove non-genomic sequence, aligned to the host genome and assembled into contiguous fragments used to pinpoint the position of integration.'),
(75982, 2011, 'bio', 'Succinct data structures for assembling large genomes', 'Conway, Thomas C|Bromage, Andrew J', 'NICTA Victoria Research Laboratory, Department of Computer Science and Engineering, The University of Melbourne, Parkville, Australia. tom.conway@nicta.com.au|NICTA Victoria Research Laboratory, Department of Computer Science and Engineering, The University of Melbourne, Parkville, Australia. tom.conway@nicta.com.au', 'Australia|Australia', 73, 'Computational Biology|Genome, Human|Genomics|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq697', '21245053', 'Second-generation sequencing technology makes it feasible for many researches to obtain enough sequence reads to attempt the de novo assembly of higher eukaryotes (including mammals). De novo assembly not only provides a tool for understanding wide scale biological variation, but within human biomedicine, it offers a direct way of observing both large-scale structural variation and fine-scale sequence variation. Unfortunately, improvements in the computational feasibility for de novo assembly have not matched the improvements in the gathering of sequence data. This is for two reasons: the inherent computational complexity of the problem and the in-practice memory requirements of tools.'),
(75983, 2011, 'bio', 'BayesPeak--an R package for analysing ChIP-seq data', 'Cairns, Jonathan|Spyrou, Christiana|Stark, Rory|Smith, Mike L|Lynch, Andy G|Tavaré, Simon', 'Department of Oncology, University of Cambridge, Li Ka Shing Centre, Cambridge, UK. jonathan.cairns@cancer.org.uk|Department of Oncology, University of Cambridge, Li Ka Shing Centre, Cambridge, UK. jonathan.cairns@cancer.org.uk|Department of Oncology, University of Cambridge, Li Ka Shing Centre, Cambridge, UK. jonathan.cairns@cancer.org.uk|Department of Oncology, University of Cambridge, Li Ka Shing Centre, Cambridge, UK. jonathan.cairns@cancer.org.uk|Department of Oncology, University of Cambridge, Li Ka Shing Centre, Cambridge, UK. jonathan.cairns@cancer.org.uk|Department of Oncology, University of Cambridge, Li Ka Shing Centre, Cambridge, UK. jonathan.cairns@cancer.org.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 28, 'Algorithms|Bayes Theorem|Chromatin Immunoprecipitation|Genome|Markov Chains|Recoverin|Software', 'Journal Article', '10.1093/bioinformatics/btq685', '21245054', 'Identification of genomic regions of interest in ChIP-seq data, commonly referred to as peak-calling, aims to find the locations of transcription factor binding sites, modified histones or nucleosomes. The BayesPeak algorithm was developed to model the data structure using Bayesian statistical techniques and was shown to be a reliable method, but did not have a full-genome implementation.'),
(75984, 2011, 'bio', 'Efficient simulation under a population genetics model of carcinogenesis', 'Zhu, Tianqi|Hu, Yucheng|Ma, Zhi-Ming|Zhang, De-Xing|Li, Tiejun|Yang, Ziheng', 'School of Mathematical Sciences, Peking University, Beijing 100871, China.|School of Mathematical Sciences, Peking University, Beijing 100871, China.|School of Mathematical Sciences, Peking University, Beijing 100871, China.|School of Mathematical Sciences, Peking University, Beijing 100871, China.|School of Mathematical Sciences, Peking University, Beijing 100871, China.|School of Mathematical Sciences, Peking University, Beijing 100871, China.', 'China|China|China|China|China|China', 0, 'Algorithms|Computer Simulation|Evolution, Molecular|Genetics, Population|Models, Genetic|Mutation|Neoplasms|Population Density', 'Comparative Study', '10.1093/bioinformatics/btr025', '21247938', 'Cancer is well known to be the end result of somatic mutations that disrupt normal cell division. The number of such mutations that have to be accumulated in a cell before cancer develops depends on the type of cancer. The waiting time T(m) until the appearance of m mutations in a cell is thus an important quantity in population genetics models of carcinogenesis. Such models are often difficult to analyze theoretically because of the complex interactions of mutation, drift and selection. They are also computationally expensive to simulate because of the large number of cells and the low mutation rate.'),
(75985, 2011, 'bio', 'Compression of DNA sequence reads in FASTQ format', 'Deorowicz, Sebastian|Grabowski, Szymon', 'Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland. sebastian.deorowicz@polsl.pl|Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland. sebastian.deorowicz@polsl.pl', 'Poland|Poland', 0, 'Algorithms|Base Sequence|Computational Biology|Data Compression|Genomics|Internet|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btr014', '21252073', 'Modern sequencing instruments are able to generate at least hundreds of millions short reads of genomic data. Those huge volumes of data require effective means to store them, provide quick access to any record and enable fast decompression.'),
(75986, 2011, 'bio', 'PhyloPro: a web-based tool for the generation and visualization of phylogenetic profiles across Eukarya', 'Xiong, Xuejian|Song, Hongyan|On, Tuan|Lochovsky, Lucas|Provart, Nicholas J|Parkinson, John', 'Program in Molecular Structure and Function, Hospital for Sick Children, Canada.|Program in Molecular Structure and Function, Hospital for Sick Children, Canada.|Program in Molecular Structure and Function, Hospital for Sick Children, Canada.|Program in Molecular Structure and Function, Hospital for Sick Children, Canada.|Program in Molecular Structure and Function, Hospital for Sick Children, Canada.|Program in Molecular Structure and Function, Hospital for Sick Children, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada', 6, 'Biological Evolution|Cluster Analysis|Computational Biology|Eukaryota|Genomics|Internet|Phylogeny|Programming Languages|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr023', '21252074', 'With increasing numbers of eukaryotic genome sequences, phylogenetic profiles of eukaryotic genes are becoming increasingly informative. Here, we introduce a new web-tool Phylopro (http://compsysbio.org/phylopro/), which uses the 120 available eukaryotic genome sequences to visualize the evolutionary trajectories of user-defined subsets of model organism genes. Applied to pathways or complexes, PhyloPro allows the user to rapidly identify core conserved elements of biological processes together with those that may represent lineage-specific innovations. PhyloPro thus provides a valuable resource for the evolutionary and comparative studies of biological systems.'),
(75987, 2011, 'bio', 'Dalliance: interactive genome viewing on the web', 'Down, Thomas A|Piipari, Matias|Hubbard, Tim J P', 'Wellcome Trust/CRUK Gurdon Institute, Cambridge CB2 1QN, UK. thomas@biodalliance.org|Wellcome Trust/CRUK Gurdon Institute, Cambridge CB2 1QN, UK. thomas@biodalliance.org|Wellcome Trust/CRUK Gurdon Institute, Cambridge CB2 1QN, UK. thomas@biodalliance.org', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Computational Biology|Computer Communication Networks|Computer Graphics|Genome|Genomics|Internet|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/btr020', '21252075', 'Dalliance is a new genome viewer which offers a high level of interactivity while running within a web browser. All data is fetched using the established distributed annotation system (DAS) protocol, making it easy to customize the browser and add extra data.'),
(75988, 2011, 'bio', 'Length bias correction for RNA-seq data in gene set analyses', 'Gao, Liyan|Fang, Zhide|Zhang, Kui|Zhi, Degui|Cui, Xiangqin', 'Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA.|Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA.|Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA.|Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA.|Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA.', 'United States|United States|United States|United States|United States', 0, 'Bias|Computer Simulation|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis|RNA|Sequence Analysis, RNA', 'Comparative Study', '10.1093/bioinformatics/btr005', '21252076', 'Next-generation sequencing technologies are being rapidly applied to quantifying transcripts (RNA-seq). However, due to the unique properties of the RNA-seq data, the differential expression of longer transcripts is more likely to be identified than that of shorter transcripts with the same effect size. This bias complicates the downstream gene set analysis (GSA) because the methods for GSA previously developed for microarray data are based on the assumption that genes with same effect size have equal probability (power) to be identified as significantly differentially expressed. Since transcript length is not related to gene expression, adjusting for such length dependency in GSA becomes necessary.'),
(75989, 2011, 'bio', 'Biological assessment of robust noise models in microarray data analysis', 'Posekany, A|Felsenstein, K|Sykacek, P', 'Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria.|Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria.|Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria.', 'Austria|Austria|Austria', 0, 'Algorithms|Analysis of Variance|Bayes Theorem|Gene Expression Profiling|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results', 'Journal Article', '10.1093/bioinformatics/btr018', '21252077', 'Although several recently proposed analysis packages for microarray data can cope with heavy-tailed noise, many applications rely on Gaussian assumptions. Gaussian noise models foster computational efficiency. This comes, however, at the expense of increased sensitivity to outlying observations. Assessing potential insufficiencies of Gaussian noise in microarray data analysis is thus important and of general interest.'),
(75990, 2011, 'bio', 'Graphics processing unit implementations of relative expression analysis algorithms enable dramatic computational speedup', 'Magis, Andrew T|Earls, John C|Ko, Youn-Hee|Eddy, James A|Price, Nathan D', 'Department of Computer Science, University of Illinois, Urbana, IL 61801, USA.|Department of Computer Science, University of Illinois, Urbana, IL 61801, USA.|Department of Computer Science, University of Illinois, Urbana, IL 61801, USA.|Department of Computer Science, University of Illinois, Urbana, IL 61801, USA.|Department of Computer Science, University of Illinois, Urbana, IL 61801, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Computational Biology|Computer Graphics|Gene Expression Profiling|Humans', 'Journal Article', '10.1093/bioinformatics/btr033', '21257608', 'The top-scoring pair (TSP) and top-scoring triplet (TST) algorithms are powerful methods for classification from expression data, but analysis of all combinations across thousands of human transcriptome samples is computationally intensive, and has not yet been achieved for TST. Implementation of these algorithms for the graphics processing unit results in dramatic speedup of two orders of magnitude, greatly increasing the searchable combinations and accelerating the pace of discovery.'),
(75991, 2011, 'bio', 'OrthoNets: simultaneous visual analysis of orthologs and their interaction neighborhoods across different organisms', 'Hao, Yanqi|Merkoulovitch, Anna|Vlasblom, James|Pu, Shuye|Turinsky, Andrei L|Roudeva, Denitza|Turner, Brian|Greenblatt, Jack|Wodak, Shoshana J', 'Molecular Structure & Function program, Hospital for Sick Children, Toronto, ON, Canada.|Molecular Structure & Function program, Hospital for Sick Children, Toronto, ON, Canada.|Molecular Structure & Function program, Hospital for Sick Children, Toronto, ON, Canada.|Molecular Structure & Function program, Hospital for Sick Children, Toronto, ON, Canada.|Molecular Structure & Function program, Hospital for Sick Children, Toronto, ON, Canada.|Molecular Structure & Function program, Hospital for Sick Children, Toronto, ON, Canada.|Molecular Structure & Function program, Hospital for Sick Children, Toronto, ON, Canada.|Molecular Structure & Function program, Hospital for Sick Children, Toronto, ON, Canada.|Molecular Structure & Function program, Hospital for Sick Children, Toronto, ON, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 4, 'Computational Biology|Databases, Protein|Protein Interaction Mapping|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr035', '21257609', 'Protein interaction networks contain a wealth of biological information, but their large size often hinders cross-organism comparisons. We present OrthoNets, a Cytoscape plugin that displays protein-protein interaction (PPI) networks from two organisms simultaneously, highlighting orthology relationships and aggregating several types of biomedical annotations. OrthoNets also allows PPI networks derived from experiments to be overlaid on networks extracted from public databases, supporting the identification and verification of new interactors. Any newly identified PPIs can be validated by checking whether their orthologs interact in another organism.'),
(75992, 2011, 'bio', 'WIST: toolkit for rapid, customized LIMS development', 'Huang, Y Wayne|Arkin, Adam P|Chandonia, John-Marc', 'Physical Biosciences Division, Lawrence Berkeley National Laboratory, University of California, Berkeley, CA 94720, USA.|Physical Biosciences Division, Lawrence Berkeley National Laboratory, University of California, Berkeley, CA 94720, USA.|Physical Biosciences Division, Lawrence Berkeley National Laboratory, University of California, Berkeley, CA 94720, USA.', 'United States|United States|United States', 7, 'Clinical Laboratory Information Systems|Computational Biology|Databases, Factual|Internet|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq676', '21258060', 'Workflow Information Storage Toolkit (WIST) is a set of application programming interfaces and web applications that allow for the rapid development of customized laboratory information management systems (LIMS). WIST provides common LIMS input components, and allows them to be arranged and configured using a flexible language that specifies each components visual and semantic characteristics. WIST includes a complete set of web applications for adding, editing and viewing data, as well as a powerful setup tool that can build new LIMS modules by analyzing existing database schema.'),
(75993, 2011, 'bio', 'Recovering key biological constituents through sparse representation of gene expression', 'Prat, Yosef|Fromer, Menachem|Linial, Nathan|Linial, Michal', 'School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.|School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.|School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.|School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.', 'Israel|Israel|Israel|Israel', 0, 'Artificial Intelligence|Computational Biology|Gene Expression Profiling|Plasmodium falciparum|RNA, Fungal|RNA, Protozoan|Saccharomyces cerevisiae', 'Journal Article', '10.1093/bioinformatics/btr002', '21258061', 'Large-scale RNA expression measurements are generating enormous quantities of data. During the last two decades, many methods were developed for extracting insights regarding the interrelationships between genes from such data. The mathematical and computational perspectives that underlie these methods are usually algebraic or probabilistic.'),
(75994, 2011, 'bio', 'HTSanalyzeR: an R/Bioconductor package for integrated network analysis of high-throughput screens', 'Wang, Xin|Terfve, Camille|Rose, John C|Markowetz, Florian', 'Cancer Research UK Cambridge Research Institute, Cambridge CB2 0RE, UK.|Cancer Research UK Cambridge Research Institute, Cambridge CB2 0RE, UK.|Cancer Research UK Cambridge Research Institute, Cambridge CB2 0RE, UK.|Cancer Research UK Cambridge Research Institute, Cambridge CB2 0RE, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Computational Biology|Gene Regulatory Networks|Genomics|High-Throughput Nucleotide Sequencing|Phenotype|RNA Interference|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr028', '21258062', 'High-throughput screens (HTS) by RNAi or small molecules are among the most promising tools in functional genomics. They enable researchers to observe detailed reactions to experimental perturbations on a genome-wide scale. While there is a core set of computational approaches used in many publications to analyze these data, a specialized software combining them and making them easily accessible has so far been missing.'),
(75995, 2011, 'bio', 'Automated validation of genetic variants from large databases: ensuring that variant references refer to the same genomic locations', 'Tong, Mark Y|Cassa, Christopher A|Kohane, Isaac S', 'Harvard Medical School, Boston, MA 02115, USA. mt153@hms.harvard.edu|Harvard Medical School, Boston, MA 02115, USA. mt153@hms.harvard.edu|Harvard Medical School, Boston, MA 02115, USA. mt153@hms.harvard.edu', 'United States|United States|United States', 0, 'Algorithms|Amino Acid Substitution|Codon|Computational Biology|Databases, Genetic|Electronic Data Processing|Humans|Molecular Sequence Annotation|Point Mutation|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr029', '21258063', 'Accurate annotations of genomic variants are necessary to achieve full-genome clinical interpretations that are scientifically sound and medically relevant. Many disease associations, especially those reported before the completion of the HGP, are limited in applicability because of potential inconsistencies with our current standards for genomic coordinates, nomenclature and gene structure. In an effort to validate and link variants from the medical genetics literature to an unambiguous reference for each variant, we developed a software pipeline and reviewed 68 641 single amino acid mutations from Online Mendelian Inheritance in Man (OMIM), Human Gene Mutation Database (HGMD) and dbSNP. The frequency of unresolved mutation annotations varied widely among the databases, ranging from 4 to 23%. A taxonomy of primary causes for unresolved mutations was produced.'),
(75996, 2011, 'bio', 'Computational inference of grammars for larger-than-gene structures from annotated gene sequences', 'Tsafnat, Guy|Schaeffer, Jaron|Clayphan, Andrew|Iredell, Jon R|Partridge, Sally R|Coiera, Enrico', 'Australian Institute of Health Innovation, University of New South Wales, Australia. guyt@unsw.edu.au|Australian Institute of Health Innovation, University of New South Wales, Australia. guyt@unsw.edu.au|Australian Institute of Health Innovation, University of New South Wales, Australia. guyt@unsw.edu.au|Australian Institute of Health Innovation, University of New South Wales, Australia. guyt@unsw.edu.au|Australian Institute of Health Innovation, University of New South Wales, Australia. guyt@unsw.edu.au|Australian Institute of Health Innovation, University of New South Wales, Australia. guyt@unsw.edu.au', 'Australia|Australia|Australia|Australia|Australia|Australia', 0, 'Algorithms|Bayes Theorem|DNA|Databases, Genetic|Electronic Data Processing|Markov Chains|Molecular Sequence Annotation|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btr036', '21258064', 'Larger than gene structures (LGS) are DNA segments that include at least one gene and often other segments such as inverted repeats and gene promoters. Mobile genetic elements (MGE) such as integrons are LGS that play an important role in horizontal gene transfer, primarily in Gram-negative organisms. Known LGS have a profound effect on organism virulence, antibiotic resistance and other properties of the organism due to the number of genes involved. Expert-compiled grammars have been shown to be an effective computational representation of LGS, well suited to automating annotation, and supporting de novo gene discovery. However, development of LGS grammars by experts is labour intensive and restricted to known LGS.'),
(75997, 2011, 'bio', 'Computational refinement of post-translational modifications predicted from tandem mass spectrometry', 'Chung, Clement|Liu, Jian|Emili, Andrew|Frey, Brendan J', 'Department of Computer Science, University of Toronto, Toronto, Canada.|Department of Computer Science, University of Toronto, Toronto, Canada.|Department of Computer Science, University of Toronto, Toronto, Canada.|Department of Computer Science, University of Toronto, Toronto, Canada.', 'Canada|Canada|Canada|Canada', 14, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Bayes Theorem|Cluster Analysis|Computational Biology|Models, Statistical|Protein Processing, Post-Translational|Proteomics|Sequence Analysis, Protein|Software|Tandem Mass Spectrometry', 'Journal Article', '10.1093/bioinformatics/btr017', '21258065', 'A post-translational modification (PTM) is a chemical modification of a protein that occurs naturally. Many of these modifications, such as phosphorylation, are known to play pivotal roles in the regulation of protein function. Henceforth, PTM perturbations have been linked to diverse diseases like Parkinsons, Alzheimers, diabetes and cancer. To discover PTMs on a genome-wide scale, there is a recent surge of interest in analyzing tandem mass spectrometry data, and several unrestrictive (so-called blind) PTM search methods have been reported. However, these approaches are subject to noise in mass measurements and in the predicted modification site (amino acid position) within peptides, which can result in false PTM assignments.'),
(75998, 2011, 'bio', 'An efficient hierarchical generalized linear mixed model for pathway analysis of genome-wide association studies', 'Wang, Lily|Jia, Peilin|Wolfinger, Russell D|Chen, Xi|Grayson, Britney L|Aune, Thomas M|Zhao, Zhongming', 'Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA. lily.wang@vanderbilt.edu|Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA. lily.wang@vanderbilt.edu|Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA. lily.wang@vanderbilt.edu|Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA. lily.wang@vanderbilt.edu|Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA. lily.wang@vanderbilt.edu|Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA. lily.wang@vanderbilt.edu|Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA. lily.wang@vanderbilt.edu', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Computer Simulation|Genome-Wide Association Study|Genotype|Humans|Linear Models|Linkage Disequilibrium|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btq728', '21266443', 'In genome-wide association studies (GWAS) of complex diseases, genetic variants having real but weak associations often fail to be detected at the stringent genome-wide significance level. Pathway analysis, which tests disease association with combined association signals from a group of variants in the same pathway, has become increasingly popular. However, because of the complexities in genetic data and the large sample sizes in typical GWAS, pathway analysis remains to be challenging. We propose a new statistical model for pathway analysis of GWAS. This model includes a fixed effects component that models mean disease association for a group of genes, and a random effects component that models how each genes association with disease varies about the gene group mean, thus belongs to the class of mixed effects models.'),
(75999, 2011, 'bio', 'Classifying short gene expression time-courses with Bayesian estimation of piecewise constant functions', 'Hafemeister, Christoph|Costa, Ivan G|Schönhuth, Alexander|Schliep, Alexander', 'Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany. hafemeis@molgen.mpg.de|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany. hafemeis@molgen.mpg.de|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany. hafemeis@molgen.mpg.de|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany. hafemeis@molgen.mpg.de', 'Germany|Germany|Germany|Germany', 0, 'Animals|Bayes Theorem|Classification|Gene Expression|Gene Expression Profiling|Kinetics|Mice|Toxins, Biological', 'Journal Article', '10.1093/bioinformatics/btr037', '21266444', 'Analyzing short time-courses is a frequent and relevant problem in molecular biology, as, for example, 90% of gene expression time-course experiments span at most nine time-points. The biological or clinical questions addressed are elucidating gene regulation by identification of co-expressed genes, predicting response to treatment in clinical, trial-like settings or classifying novel toxic compounds based on similarity of gene expression time-courses to those of known toxic compounds. The latter problem is characterized by irregular and infrequent sample times and a total lack of prior assumptions about the incoming query, which comes in stark contrast to clinical settings and requires to implicitly perform a local, gapped alignment of time series. The current state-of-the-art method (SCOW) uses a variant of dynamic time warping and models time series as higher order polynomials (splines).'),
(76000, 2011, 'bio', 'Modular analysis of the probabilistic genetic interaction network', 'Hou, Lin|Wang, Lin|Qian, Minping|Li, Dong|Tang, Chao|Zhu, Yunping|Deng, Minghua|Li, Fangting', 'School of Mathematical Sciences, Peking University, Beijing 100871, China.|School of Mathematical Sciences, Peking University, Beijing 100871, China.|School of Mathematical Sciences, Peking University, Beijing 100871, China.|School of Mathematical Sciences, Peking University, Beijing 100871, China.|School of Mathematical Sciences, Peking University, Beijing 100871, China.|School of Mathematical Sciences, Peking University, Beijing 100871, China.|School of Mathematical Sciences, Peking University, Beijing 100871, China.|School of Mathematical Sciences, Peking University, Beijing 100871, China.', 'China|China|China|China|China|China|China|China', 9, 'Algorithms|Bayes Theorem|Cluster Analysis|Computational Biology|Gene Regulatory Networks|Markov Chains|Models, Genetic|Phosphorylation|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1093/bioinformatics/btr031', '21278184', 'Epistatic Miniarray Profiles (EMAP) has enabled the mapping of large-scale genetic interaction networks, however, the quantitative information gained from EMAP cannot be fully exploited since the data are usually interpreted as a discrete network based on an arbitrary hard threshold. To address such limitations, we adopted a mixture modeling procedure to construct a probabilistic genetic interaction network and then implemented a Bayesian approach to identify densely interacting modules in the probabilistic network.'),
(76001, 2011, 'bio', 'Quality control and preprocessing of metagenomic datasets', 'Schmieder, Robert|Edwards, Robert', 'Department of Computer Science, Computational Science Research Center, San Diego State University, San Diego, CA 92182, USA. rschmied@sciences.sdsu.edu|Department of Computer Science, Computational Science Research Center, San Diego State University, San Diego, CA 92182, USA. rschmied@sciences.sdsu.edu', 'United States|United States', 0, 'Computer Graphics|Information Storage and Retrieval|Internet|Metagenomics|Programming Languages|Quality Control|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr026', '21278185', 'Here, we present PRINSEQ for easy and rapid quality control and data preprocessing of genomic and metagenomic datasets. Summary statistics of FASTA (and QUAL) or FASTQ files are generated in tabular and graphical form and sequences can be filtered, reformatted and trimmed by a variety of options to improve downstream analysis.'),
(76002, 2011, 'bio', 'Modeling and comparing the organization of circular genomes', 'Shieh, Grace S|Zheng, Shurong|Johnson, Richard A|Chang, Yi-Feng|Shimizu, Kunio|Wang, Chia-Chang|Tang, Sen-Lin', 'Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. gshieh@stat.sinica.edu.tw|Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. gshieh@stat.sinica.edu.tw|Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. gshieh@stat.sinica.edu.tw|Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. gshieh@stat.sinica.edu.tw|Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. gshieh@stat.sinica.edu.tw|Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. gshieh@stat.sinica.edu.tw|Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. gshieh@stat.sinica.edu.tw', '-|-|-|-|-|-|-', 0, 'Bacteria|DNA, Circular|Genome, Bacterial|Genomics|Models, Genetic|Mycoplasma', 'Journal Article', '10.1093/bioinformatics/btr049', '21278186', 'Most prokaryotic genomes are circular with a single chromosome (called circular genomes), which consist of bacteria and archaea. Orthologous genes (abbreviated as orthologs) are genes directly evolved from an ancestor gene, and can be traced through different species in evolution. Shared orthologs between bacterial genomes have been used to measure their genome evolution. Here, organization of circular genomes is analyzed via distributions of shared orthologs between genomes. However, these distributions are often asymmetric and bimodal, to date, there is no joint distribution to model such data. This motivated us to develop a family of bivariate distributions with generalized von Mises marginals (BGVM) and its statistical inference.'),
(76003, 2011, 'bio', 'Identity-by-descent filtering of exome sequence data for disease-gene identification in autosomal recessive disorders', 'Rödelsperger, Christian|Krawitz, Peter|Bauer, Sebastian|Hecht, Jochen|Bigham, Abigail W|Bamshad, Michael|de Condor, Birgit Jonske|Schweiger, Michal R|Robinson, Peter N', 'Institute for Medical and Human Genetics, Berlin.|Institute for Medical and Human Genetics, Berlin.|Institute for Medical and Human Genetics, Berlin.|Institute for Medical and Human Genetics, Berlin.|Institute for Medical and Human Genetics, Berlin.|Institute for Medical and Human Genetics, Berlin.|Institute for Medical and Human Genetics, Berlin.|Institute for Medical and Human Genetics, Berlin.|Institute for Medical and Human Genetics, Berlin.', '-|-|-|-|-|-|-|-|-', 27, 'Algorithms|Computational Biology|Consanguinity|Exons|Genes, Recessive|Genetic Diseases, Inborn|Genome, Human|Genome-Wide Association Study|Genotype|Haplotypes|Humans|Inheritance Patterns|Markov Chains|Models, Genetic|Mutation', 'Journal Article', '10.1093/bioinformatics/btr022', '21278187', 'Next-generation sequencing and exome-capture technologies are currently revolutionizing the way geneticists screen for disease-causing mutations in rare Mendelian disorders. However, the identification of causal mutations is challenging due to the sheer number of variants that are identified in individual exomes. Although databases such as dbSNP or HapMap can be used to reduce the plethora of candidate genes by filtering out common variants, the remaining set of genes still remains on the order of dozens.'),
(76004, 2011, 'bio', 'PiNGO: a Cytoscape plugin to find candidate genes in biological networks', 'Smoot, Michael|Ono, Keiichiro|Ideker, Trey|Maere, Steven', 'Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA.|Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA.|Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA.|Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA.', 'United States|United States|United States|United States', 29, 'Algorithms|Computational Biology|Gene Regulatory Networks|Genes|Software', 'Journal Article', '10.1093/bioinformatics/btr045', '21278188', 'PiNGO is a tool to screen biological networks for candidate genes, i.e. genes predicted to be involved in a biological process of interest. The user can narrow the search to genes with particular known functions or exclude genes belonging to particular functional classes. PiNGO provides support for a wide range of organisms and Gene Ontology classification schemes, and it can easily be customized for other organisms and functional classifications. PiNGO is implemented as a plugin for Cytoscape, a popular network visualization platform.'),
(76005, 2011, 'bio', 'Conveyor: a workflow engine for bioinformatic analyses', 'Linke, Burkhard|Giegerich, Robert|Goesmann, Alexander', 'Bioinformatics Resource Faciliy, Center for Biotechnology and Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany. blinke@ceBiTec.Uni-Bielefeld.De|Bioinformatics Resource Faciliy, Center for Biotechnology and Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany. blinke@ceBiTec.Uni-Bielefeld.De|Bioinformatics Resource Faciliy, Center for Biotechnology and Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany. blinke@ceBiTec.Uni-Bielefeld.De', 'Germany|Germany|Germany', 0, 'Computational Biology|Escherichia coli|Genome, Bacterial|Genomics|Molecular Sequence Annotation|Software|Workflow', 'Journal Article', '10.1093/bioinformatics/btr040', '21278189', 'The rapidly increasing amounts of data available from new high-throughput methods have made data processing without automated pipelines infeasible. As was pointed out in several publications, integration of data and analytic resources into workflow systems provides a solution to this problem, simplifying the task of data analysis. Various applications for defining and running workflows in the field of bioinformatics have been proposed and published, e.g. Galaxy, Mobyle, Taverna, Pegasus or Kepler. One of the main aims of such workflow systems is to enable scientists to focus on analysing their datasets instead of taking care for data management, job management or monitoring the execution of computational tasks. The currently available workflow systems achieve this goal, but fundamentally differ in their way of executing workflows.'),
(76006, 2011, 'bio', 'A Ruby API to query the Ensembl database for genomic features', 'Strozzi, Francesco|Aerts, Jan', 'Parco Tecnologico Padano, Lodi, Italy.|Parco Tecnologico Padano, Lodi, Italy.', 'Italy|Italy', 9, 'Databases, Nucleic Acid|Genomics|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr050', '21278190', 'The Ensembl database makes genomic features available via its Genome Browser. It is also possible to access the underlying data through a Perl API for advanced querying. We have developed a full-featured Ruby API to the Ensembl databases, providing the same functionality as the Perl interface with additional features. A single Ruby API is used to access different releases of the Ensembl databases and is also able to query multi-species databases.'),
(76007, 2011, 'bio', 'Bambino: a variant detector and alignment viewer for next-generation sequencing data in the SAM/BAM format', 'Edmonson, Michael N|Zhang, Jinghui|Yan, Chunhua|Finney, Richard P|Meerzaman, Daoud M|Buetow, Kenneth H', 'National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. edmonson@nih.gov|National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. edmonson@nih.gov|National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. edmonson@nih.gov|National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. edmonson@nih.gov|National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. edmonson@nih.gov|National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. edmonson@nih.gov', 'United States|United States|United States|United States|United States|United States', 0, 'Computational Biology|Computer Graphics|DNA Mutational Analysis|Gene Frequency|Genomics|Genotype|Internet|Molecular Sequence Annotation|Polymorphism, Single Nucleotide|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btr032', '21278191', 'Bambino is a variant detector and graphical alignment viewer for next-generation sequencing data in the SAM/BAM format, which is capable of pooling data from multiple source files. The variant detector takes advantage of SAM-specific annotations, and produces detailed output suitable for genotyping and identification of somatic mutations. The assembly viewer can display reads in the context of either a user-provided or automatically generated reference sequence, retrieve genome annotation features from a UCSC genome annotation database, display histograms of non-reference allele frequencies, and predict protein-coding changes caused by SNPs.'),
(76008, 2011, 'bio', 'SHRiMP2: sensitive yet practical SHort Read Mapping', 'David, Matei|Dzamba, Misko|Lister, Dan|Ilie, Lucian|Brudno, Michael', 'Department of Computer Science, Princeton University, USA.|Department of Computer Science, Princeton University, USA.|Department of Computer Science, Princeton University, USA.|Department of Computer Science, Princeton University, USA.|Department of Computer Science, Princeton University, USA.', 'United States|United States|United States|United States|United States', 232, 'Algorithms|Chromosome Mapping|Genomics|Polymorphism, Genetic|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr046', '21278192', 'We report on a major update (version 2) of the original SHort Read Mapping Program (SHRiMP). SHRiMP2 primarily targets mapping sensitivity, and is able to achieve high accuracy at a very reasonable speed. SHRiMP2 supports both letter space and color space (AB/SOLiD) reads, enables for direct alignment of paired reads and uses parallel computation to fully utilize multi-core architectures.'),
(76009, 2011, 'bio', 'Easyfig: a genome comparison visualizer', 'Sullivan, Mitchell J|Petty, Nicola K|Beatson, Scott A', 'Australian Infectious Diseases Research Centre, School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, QLD 4072, Australia.|Australian Infectious Diseases Research Centre, School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, QLD 4072, Australia.|Australian Infectious Diseases Research Centre, School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, QLD 4072, Australia.', 'Australia|Australia|Australia', 898, 'Computer Graphics|Genome|Genomics|Software', 'Journal Article', '10.1093/bioinformatics/btr039', '21278367', 'Easyfig is a Python application for creating linear comparison figures of multiple genomic loci with an easy-to-use graphical user interface. BLAST comparisons between multiple genomic regions, ranging from single genes to whole prokaryote chromosomes, can be generated, visualized and interactively coloured, enabling a rapid transition between analysis and the preparation of publication quality figures.'),
(76010, 2011, 'bio', 'ISCB public policy statement on open access to scientific and technical research literature', 'Lathrop, Richard H|Rost, Burkhard|ISCB Membership, Executive Committee, Board of Directors, and Public Affairs Committee', 'Australian Infectious Diseases Research Centre, School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, QLD 4072, Australia.|Australian Infectious Diseases Research Centre, School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, QLD 4072, Australia.|Australian Infectious Diseases Research Centre, School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, QLD 4072, Australia.', 'Australia|Australia|Australia', 0, 'Access to Information|Periodicals as Topic|Policy|Publishing|Research', 'Journal Article', '10.1093/bioinformatics/btq687', '21282182', '-');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76011, 2011, 'bio', 'Quantitative trait prediction based on genetic marker-array data, a simulation study', 'Yip, Wai-Ki|Lange, Christoph', 'Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. wkyip@hsph.harvard.edu|Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. wkyip@hsph.harvard.edu', 'United States|United States', 6, 'Chromosome Mapping|Computer Simulation|Genetic Markers|Genome-Wide Association Study|Genotype|Humans|Inheritance Patterns|Models, Genetic|Phenotype|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Regression Analysis', 'Journal Article', '10.1093/bioinformatics/btr024', '21285022', 'Using simulation studies for quantitative trait loci (QTL), we evaluate the prediction quality of regression models that include as covariates single-nucleotide polymorphism (SNP) genetic markers which did not achieve genome-wide significance in the original genome-wide association study, but were among the SNPs with the smallest P-value for the selected association test. We compare the results of such regression models to the standard approach which is to include only SNPs that achieve genome-wide significance. Using mean square prediction error as the model metric, our simulation results suggest that by using the coefficient of determination (R(2)) value as a guideline to increase or reduce the number of SNPs included in the regression model, we can achieve better prediction quality than the standard approach. However, important parameters such as trait heritability, the approximate number of QTLs, etc. have to be determined from previous studies or have to be estimated accurately.'),
(76012, 2011, 'bio', 'Gobe: an interactive, web-based tool for comparative genomic visualization', 'Pedersen, Brent S|Tang, Haibao|Freeling, Michael', 'Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA. bpederse@berkeley.edu|Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA. bpederse@berkeley.edu|Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA. bpederse@berkeley.edu', 'United States|United States|United States', 0, 'Computer Graphics|Genomics|Internet|Software', 'Journal Article', '10.1093/bioinformatics/btr056', '21296748', 'Gobe is a web-based tool for viewing comparative genomic data. It supports viewing multiple genomic regions simultaneously. Its simple text format and flash-based rendering make it an interactive, exploratory research tool. Gobe can be used without installation through our web service, or downloaded and customized with stylesheets and javascript callback functions.'),
(76013, 2011, 'bio', 'LSPR: an integrated periodicity detection algorithm for unevenly sampled temporal microarray data', 'Yang, Rendong|Zhang, Chen|Su, Zhen', 'Division of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing, China.|Division of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing, China.|Division of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing, China.', 'China|China|China', 12, 'Algorithms|Arabidopsis|Circadian Rhythm|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Periodicity|Software', 'Journal Article', '10.1093/bioinformatics/btr041', '21296749', 'We propose a three-step periodicity detection algorithm named LSPR. Our method first preprocesses the raw time-series by removing the linear trend and filtering noise. In the second step, LSPR employs a Lomb-Scargle periodogram to estimate the periodicity in the time-series. Finally, harmonic regression is applied to model the cyclic components. Inferred periodic transcripts are selected by a false discovery rate procedure. We have applied LSPR to unevenly sampled synthetic data and two Arabidopsis diurnal expression datasets, and compared its performance with the existing well-established algorithms. Results show that LSPR is capable of identifying periodic transcripts more accurately than existing algorithms.'),
(76014, 2011, 'bio', 'SIMA: simultaneous multiple alignment of LC/MS peak lists', 'Voss, Björn|Hanselmann, Michael|Renard, Bernhard Y|Lindner, Martin S|Köthe, Ullrich|Kirchner, Marc|Hamprecht, Fred A', 'Interdisciplinary Center for Scientific Computing, University of Heidelberg, Heidelberg, Germany.|Interdisciplinary Center for Scientific Computing, University of Heidelberg, Heidelberg, Germany.|Interdisciplinary Center for Scientific Computing, University of Heidelberg, Heidelberg, Germany.|Interdisciplinary Center for Scientific Computing, University of Heidelberg, Heidelberg, Germany.|Interdisciplinary Center for Scientific Computing, University of Heidelberg, Heidelberg, Germany.|Interdisciplinary Center for Scientific Computing, University of Heidelberg, Heidelberg, Germany.|Interdisciplinary Center for Scientific Computing, University of Heidelberg, Heidelberg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 24, 'Algorithms|Chromatography, Liquid|Mass Spectrometry', 'Journal Article', '10.1093/bioinformatics/btr051', '21296750', 'Alignment of multiple liquid chromatography/mass spectrometry (LC/MS) experiments is a necessity today, which arises from the need for biological and technical repeats. Due to limits in sampling frequency and poor reproducibility of retention times, current LC systems suffer from missing observations and non-linear distortions of the retention times across runs. Existing approaches for peak correspondence estimation focus almost exclusively on solving the pairwise alignment problem, yielding straightforward but suboptimal results for multiple alignment problems.'),
(76015, 2011, 'bio', 'GOSSIP: a method for fast and accurate global alignment of protein structures', 'Kifer, I|Nussinov, R|Wolfson, H J', 'School of Computer Science, Raymond and Beverly Sackler Faculty of Exact Sciences, Sackler Institute of Molecular Medicine, Tel Aviv University, Tel Aviv, Israel.|School of Computer Science, Raymond and Beverly Sackler Faculty of Exact Sciences, Sackler Institute of Molecular Medicine, Tel Aviv University, Tel Aviv, Israel.|School of Computer Science, Raymond and Beverly Sackler Faculty of Exact Sciences, Sackler Institute of Molecular Medicine, Tel Aviv University, Tel Aviv, Israel.', 'Israel|Israel|Israel', 0, 'Cluster Analysis|Databases, Protein|Proteins|Sequence Alignment|Software|Structural Homology, Protein', 'Evaluation Studies', '10.1093/bioinformatics/btr044', '21296751', 'The database of known protein structures (PDB) is increasing rapidly. This results in a growing need for methods that can cope with the vast amount of structural data. To analyze the accumulating data, it is important to have a fast tool for identifying similar structures and clustering them by structural resemblance. Several excellent tools have been developed for the comparison of protein structures. These usually address the task of local structure alignment, an important yet computationally intensive problem due to its complexity. It is difficult to use such tools for comparing a large number of structures to each other at a reasonable time.'),
(76016, 2011, 'bio', 'DDN: a caBIG® analytical tool for differential network analysis', 'Zhang, Bai|Tian, Ye|Jin, Lu|Li, Huai|Shih, Ie-Ming|Madhavan, Subha|Clarke, Robert|Hoffman, Eric P|Xuan, Jianhua|Hilakivi-Clarke, Leena|Wang, Yue', 'Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 30, 'Animals|Computational Biology|Epigenesis, Genetic|Female|Gene Regulatory Networks|Mammary Glands, Animal|Rats|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btr052', '21296752', 'Differential dependency network (DDN) is a caBIG® (cancer Biomedical Informatics Grid) analytical tool for detecting and visualizing statistically significant topological changes in transcriptional networks representing two biological conditions. Developed under caBIG®s In Silico Research Centers of Excellence (ISRCE) Program, DDN enables differential network analysis and provides an alternative way for defining network biomarkers predictive of phenotypes. DDN also serves as a useful systems biology tool for users across biomedical research communities to infer how genetic, epigenetic or environment variables may affect biological networks and clinical phenotypes. Besides the standalone Java application, we have also developed a Cytoscape plug-in, CytoDDN, to integrate network analysis and visualization seamlessly.'),
(76017, 2011, 'bio', 'Model annotation for synthetic biology: automating model to nucleotide sequence conversion', 'Misirli, Goksel|Hallinan, Jennifer S|Yu, Tommy|Lawson, James R|Wimalaratne, Sarala M|Cooling, Michael T|Wipat, Anil', 'School of Computing Science, Newcastle University, Newcastle upon Tyne, UK.|School of Computing Science, Newcastle University, Newcastle upon Tyne, UK.|School of Computing Science, Newcastle University, Newcastle upon Tyne, UK.|School of Computing Science, Newcastle University, Newcastle upon Tyne, UK.|School of Computing Science, Newcastle University, Newcastle upon Tyne, UK.|School of Computing Science, Newcastle University, Newcastle upon Tyne, UK.|School of Computing Science, Newcastle University, Newcastle upon Tyne, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 22, 'Algorithms|Base Sequence|DNA|Models, Genetic|Molecular Sequence Annotation|Software|Synthetic Biology|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btr048', '21296753', 'The need for the automated computational design of genetic circuits is becoming increasingly apparent with the advent of ever more complex and ambitious synthetic biology projects. Currently, most circuits are designed through the assembly of models of individual parts such as promoters, ribosome binding sites and coding sequences. These low level models are combined to produce a dynamic model of a larger device that exhibits a desired behaviour. The larger model then acts as a blueprint for physical implementation at the DNA level. However, the conversion of models of complex genetic circuits into DNA sequences is a non-trivial undertaking due to the complexity of mapping the model parts to their physical manifestation. Automating this process is further hampered by the lack of computationally tractable information in most models.'),
(76018, 2011, 'bio', 'SpaCEM3: a software for biological module detection when data is incomplete, high dimensional and dependent', 'Vignes, Matthieu|Blanchet, Juliette|Leroux, Damien|Forbes, Florence', 'INRA Toulouse, Castanet Tolosan, France. matthieu.vignes@toulouse.inra.fr|INRA Toulouse, Castanet Tolosan, France. matthieu.vignes@toulouse.inra.fr|INRA Toulouse, Castanet Tolosan, France. matthieu.vignes@toulouse.inra.fr|INRA Toulouse, Castanet Tolosan, France. matthieu.vignes@toulouse.inra.fr', 'France|France|France|France', 0, 'Algorithms|Cluster Analysis|Computational Biology|Genomics|Markov Chains|Models, Biological|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/btr034', '21296754', 'Among classical methods for module detection, SpaCEM(3) provides ad hoc algorithms that were shown to be particularly well adapted to specific features of biological data: high-dimensionality, interactions between components (genes) and integrated treatment of missingness in observations. The software, currently in its version 2.0, is developed in C++ and can be used either via command line or with the GUI under Linux and Windows environments.'),
(76019, 2011, 'bio', 'Phage display can select over-hydrophobic sequences that may impair prediction of natural domain-peptide interactions', 'Luck, Katja|Travé, Gilles', 'Oncoproteins, Unité CNRS-UDS UMR 7242, Ecole Supérieure de Biotechnologie de Strasbourg, Illkirch, France. katja.luck@unistra.fr|Oncoproteins, Unité CNRS-UDS UMR 7242, Ecole Supérieure de Biotechnologie de Strasbourg, Illkirch, France. katja.luck@unistra.fr', 'France|France', 21, 'Amino Acid Motifs|Amino Acid Sequence|Amino Acids|Humans|Hydrophobic and Hydrophilic Interactions|PDZ Domains|Peptide Library|Peptides|Protein Binding|Protein Interaction Domains and Motifs', 'Journal Article', '10.1093/bioinformatics/btr060', '21300698', 'The phage display peptide selection approach is widely used for defining binding specificities of globular domains. PDZ domains recognize partner proteins via C-terminal motifs and are often used as a model for interaction predictions. Here, we investigated to which extent phage display data that were recently published for 54 human PDZ domains can be applied to the prediction of human PDZ-peptide interactions.'),
(76020, 2011, 'bio', 'uMELT: prediction of high-resolution melting curves and dynamic melting profiles of PCR products in a rich web application', 'Dwight, Zachary|Palais, Robert|Wittwer, Carl T', 'School of Computing, University of Utah, Salt Lake City, UT 84112, USA. zach.dwight@path.utah.edu|School of Computing, University of Utah, Salt Lake City, UT 84112, USA. zach.dwight@path.utah.edu|School of Computing, University of Utah, Salt Lake City, UT 84112, USA. zach.dwight@path.utah.edu', 'United States|United States|United States', 126, 'Algorithms|Base Sequence|DNA|Fluorescence|Internet|Nucleic Acid Denaturation|Polymerase Chain Reaction|Software|Temperature|Thermodynamics', 'Journal Article', '10.1093/bioinformatics/btr065', '21300699', 'uMelt(SM) is a flexible web-based tool for predicting DNA melting curves and denaturation profiles of PCR products. The user defines an amplicon sequence and chooses a set of thermodynamic and experimental parameters that include nearest neighbor stacking energies, loop entropy effects, cation (monovalent and Mg(++)) concentrations and a temperature range. Using an accelerated partition function algorithm along with chosen parameter values, uMelt interactively calculates and visualizes the mean helicity and the dissociation probability at each sequence position at temperatures within the temperature range. Predicted curves display the mean helicity as a function of temperature or as derivative plots. Predicted profiles display stability as a function of sequence position either as 50% helicity temperatures or as the helicity probability at specific temperatures. The loss of helicity associated with increasing temperature may be viewed dynamically to visualize domain formation within the molecule. Results from fluorescent high-resolution melting experiments match the number of predicted melting domains and their relative temperatures. However, the absolute melting temperatures vary with the selected thermodynamic parameters and current libraries do not account for the rapid melting rates and helix stabilizing dyes used in fluorescent melting experiments. uMelt provides a convenient platform for simulation and design of high-resolution melting assays.'),
(76021, 2011, 'bio', 'BioGRID REST Service, BiogridPlugin2 and BioGRID WebGraph: new tools for access to interaction data at BioGRID', 'Winter, Andrew G|Wildenhain, Jan|Tyers, Mike', 'Wellcome Trust Centre for Cell Biology and School of Biological Sciences, The University of Edinburgh, Edinburgh, UK. andrew.winter@ed.ac.uk|Wellcome Trust Centre for Cell Biology and School of Biological Sciences, The University of Edinburgh, Edinburgh, UK. andrew.winter@ed.ac.uk|Wellcome Trust Centre for Cell Biology and School of Biological Sciences, The University of Edinburgh, Edinburgh, UK. andrew.winter@ed.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Computational Biology|Computer Graphics|Databases, Factual|Gene Regulatory Networks|Internet|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr062', '21300700', 'The Biological General Repository for Interaction Datasets (BioGRID) representational state transfer (REST) service allows full URL-based access to curated protein and genetic interaction data at the BioGRID database. Appending URL parameters allows filtering of data by various attributes including gene names and identifiers, PubMed ID and evidence type. We also describe two visualization tools that interface with the REST service, the BiogridPlugin2 for Cytoscape and the BioGRID WebGraph.'),
(76022, 2011, 'bio', 'HLA*IMP--an integrated framework for imputing classical HLA alleles from SNP genotypes', 'Dilthey, Alexander T|Moutsianas, Loukas|Leslie, Stephen|McVean, Gil', 'Department of Statistics, University of Oxford, Oxford, UK.|Department of Statistics, University of Oxford, Oxford, UK.|Department of Statistics, University of Oxford, Oxford, UK.|Department of Statistics, University of Oxford, Oxford, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 103, 'Algorithms|Alleles|Genome-Wide Association Study|Genotype|HLA Antigens|Humans|Polymorphism, Single Nucleotide|Psoriasis|Software', 'Journal Article', '10.1093/bioinformatics/btr061', '21300701', 'Genetic variation at classical HLA alleles influences many phenotypes, including susceptibility to autoimmune disease, resistance to pathogens and the risk of adverse drug reactions. However, classical HLA typing methods are often prohibitively expensive for large-scale studies. We previously described a method for imputing classical alleles from linked SNP genotype data. Here, we present a modification of the original algorithm implemented in a freely available software suite that combines local data preparation and QC with probabilistic imputation through a remote server.'),
(76023, 2011, 'bio', 'tigre: Transcription factor inference through gaussian process reconstruction of expression for bioconductor', 'Honkela, Antti|Gao, Pei|Ropponen, Jonatan|Rattray, Magnus|Lawrence, Neil D', 'Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, Finland. antti.honkela@hiit.fi|Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, Finland. antti.honkela@hiit.fi|Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, Finland. antti.honkela@hiit.fi|Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, Finland. antti.honkela@hiit.fi|Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, Finland. antti.honkela@hiit.fi', 'Finland|Finland|Finland|Finland|Finland', 3, 'Gene Expression Profiling|Gene Expression Regulation|Oligonucleotide Array Sequence Analysis|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr057', '21300702', 'tigre is an R/Bioconductor package for inference of transcription factor activity and ranking candidate target genes from gene expression time series. The underlying methodology is based on Gaussian process inference on a differential equation model that allows the use of short, unevenly sampled, time series. The method has been designed with efficient parallel implementation in mind, and the package supports parallel operation even without additional software.'),
(76024, 2011, 'bio', 'SBML-PET-MPI: a parallel parameter estimation tool for Systems Biology Markup Language based models', 'Zi, Zhike', 'BIOSS Centre for Biological Signalling Studies, Center for Biological Systems Analysis (ZBSA), University of Freiburg, Freiburg, Germany. zhike.zi@bioss.uni-freiburg.de', 'Germany', 12, 'Algorithms|Models, Biological|Programming Languages|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btr038', '21303862', 'Parameter estimation is crucial for the modeling and dynamic analysis of biological systems. However, implementing parameter estimation is time consuming and computationally demanding. Here, we introduced a parallel parameter estimation tool for Systems Biology Markup Language (SBML)-based models (SBML-PET-MPI). SBML-PET-MPI allows the user to perform parameter estimation and parameter uncertainty analysis by collectively fitting multiple experimental datasets. The tool is developed and parallelized using the message passing interface (MPI) protocol, which provides good scalability with the number of processors.'),
(76025, 2011, 'bio', 'GeneTUKit: a software for document-level gene normalization', 'Huang, Minlie|Liu, Jingchen|Zhu, Xiaoyan', 'Department of Computer Science and Technology, Tsinghua University, Beijing, China. aihuang@tsinghua.edu.cn|Department of Computer Science and Technology, Tsinghua University, Beijing, China. aihuang@tsinghua.edu.cn|Department of Computer Science and Technology, Tsinghua University, Beijing, China. aihuang@tsinghua.edu.cn', 'China|China|China', 42, 'Data Mining|Genes|Reference Values|Software', 'Journal Article', '10.1093/bioinformatics/btr042', '21303863', 'Linking gene mentions in an article to entries of biological databases can facilitate indexing and querying biological literature greatly. Due to the high ambiguity of gene names, this task is particularly challenging. Manual annotation for this task is cost expensive, time consuming and labor intensive. Therefore, providing assistive tools to facilitate the task is of high value.'),
(76026, 2011, 'bio', 'GeneReporter--sequence-based document retrieval and annotation', 'Bartsch, Annekathrin|Bunk, Boyke|Haddad, Isam|Klein, Johannes|Münch, Richard|Johl, Thorsten|Kärst, Uwe|Jänsch, Lothar|Jahn, Dieter|Retter, Ida', 'Institute for Microbiology, Technische Universität Braunschweig, Braunschweig, Germany.|Institute for Microbiology, Technische Universität Braunschweig, Braunschweig, Germany.|Institute for Microbiology, Technische Universität Braunschweig, Braunschweig, Germany.|Institute for Microbiology, Technische Universität Braunschweig, Braunschweig, Germany.|Institute for Microbiology, Technische Universität Braunschweig, Braunschweig, Germany.|Institute for Microbiology, Technische Universität Braunschweig, Braunschweig, Germany.|Institute for Microbiology, Technische Universität Braunschweig, Braunschweig, Germany.|Institute for Microbiology, Technische Universität Braunschweig, Braunschweig, Germany.|Institute for Microbiology, Technische Universität Braunschweig, Braunschweig, Germany.|Institute for Microbiology, Technische Universität Braunschweig, Braunschweig, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 3, 'Computational Biology|Data Mining|Databases, Genetic|Internet|Molecular Sequence Annotation|Proteins|PubMed|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1093/bioinformatics/btr047', '21310745', 'GeneReporter is a web tool that reports functional information and relevant literature on a protein-coding sequence of interest. Its purpose is to support both manual genome annotation and document retrieval. PubMed references corresponding to a sequence are detected by the extraction of query words from UniProt entries of homologous sequences. Data on protein families, domains, potential cofactors, structure, function, cellular localization, metabolic contribution and corresponding DNA binding sites complement the information on a given gene product of interest.'),
(76027, 2011, 'bio', 'FISH Finder: a high-throughput tool for analyzing FISH images', 'Shirley, James W|Ty, Sereyvathana|Takebayashi, Shin-ichiro|Liu, Xiuwen|Gilbert, David M', 'Department of Biological Science, Florida State University, Tallahassee, FL 32306, USA.|Department of Biological Science, Florida State University, Tallahassee, FL 32306, USA.|Department of Biological Science, Florida State University, Tallahassee, FL 32306, USA.|Department of Biological Science, Florida State University, Tallahassee, FL 32306, USA.|Department of Biological Science, Florida State University, Tallahassee, FL 32306, USA.', 'United States|United States|United States|United States|United States', 12, 'Animals|Bayes Theorem|Cell Nucleus|Computer Graphics|Humans|Image Processing, Computer-Assisted|In Situ Hybridization, Fluorescence|Mice|Microscopy, Fluorescence|Software', 'Evaluation Studies', '10.1093/bioinformatics/btr053', '21310746', 'Fluorescence in situ hybridization (FISH) is used to study the organization and the positioning of specific DNA sequences within the cell nucleus. Analyzing the data from FISH images is a tedious process that invokes an element of subjectivity. Automated FISH image analysis offers savings in time as well as gaining the benefit of objective data analysis. While several FISH image analysis software tools have been developed, they often use a threshold-based segmentation algorithm for nucleus segmentation. As fluorescence signal intensities can vary significantly from experiment to experiment, from cell to cell, and within a cell, threshold-based segmentation is inflexible and often insufficient for automatic image analysis, leading to additional manual segmentation and potential subjective bias. To overcome these problems, we developed a graphical software tool called FISH Finder to automatically analyze FISH images that vary significantly. By posing the nucleus segmentation as a classification problem, compound Bayesian classifier is employed so that contextual information is utilized, resulting in reliable classification and boundary extraction. This makes it possible to analyze FISH images efficiently and objectively without adjustment of input parameters. Additionally, FISH Finder was designed to analyze the distances between differentially stained FISH probes.'),
(76028, 2011, 'bio', 'Entropy-accelerated exact clustering of protein decoys', 'Berenger, Francois|Zhou, Yong|Shrestha, Rojan|Zhang, Kam Y J', 'Zhang Initiative Research Unit, Advanced Science Institute, RIKEN, Wako, Saitama, Japan.|Zhang Initiative Research Unit, Advanced Science Institute, RIKEN, Wako, Saitama, Japan.|Zhang Initiative Research Unit, Advanced Science Institute, RIKEN, Wako, Saitama, Japan.|Zhang Initiative Research Unit, Advanced Science Institute, RIKEN, Wako, Saitama, Japan.', 'Japan|Japan|Japan|Japan', 18, 'Algorithms|Cluster Analysis|Entropy|Protein Conformation|Protein Folding|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btr072', '21310747', 'Clustering is commonly used to identify the best decoy among many generated in protein structure prediction when using energy alone is insufficient. Calculation of the pairwise distance matrix for a large decoy set is computationally expensive. Typically, only a reduced set of decoys using energy filtering is subjected to clustering analysis. A fast clustering method for a large decoy set would be beneficial to protein structure prediction and this still poses a challenge.'),
(76029, 2011, 'bio', 'Comments on Bayesian variable selection for disease classification using gene expression data', 'Baragatti, Meïli C|Pommeret, Denys', 'Zhang Initiative Research Unit, Advanced Science Institute, RIKEN, Wako, Saitama, Japan.|Zhang Initiative Research Unit, Advanced Science Institute, RIKEN, Wako, Saitama, Japan.', 'Japan|Japan', 2, 'Algorithms|Bayes Theorem|Disease|Gene Expression Profiling|Humans|Regression Analysis', 'Comment', '10.1093/bioinformatics/btr071', '21317136', '-'),
(76030, 2011, 'bio', 'Bases adjacent to mononucleotide repeats show an increased single nucleotide polymorphism frequency in the human genome', 'Siddle, K J|Goodship, J A|Keavney, B|Santibanez-Koref, M F', 'Institute of Human Genetics, Newcastle University, Newcastle upon Tyne,UK. kjsiddle@pasteur.fr|Institute of Human Genetics, Newcastle University, Newcastle upon Tyne,UK. kjsiddle@pasteur.fr|Institute of Human Genetics, Newcastle University, Newcastle upon Tyne,UK. kjsiddle@pasteur.fr|Institute of Human Genetics, Newcastle University, Newcastle upon Tyne,UK. kjsiddle@pasteur.fr', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 9, 'Genome, Human|Humans|Microsatellite Repeats|Nucleotides|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btr067', '21317137', 'Mononucleotide repeats (MNRs) are abundant in eukaryotic genomes and exhibit a high degree of length variability due to insertion and deletion events. However, the relationship between these repeats and mutation rates in surrounding sequences has not been systematically investigated. We have analyzed the frequency of single nucleotide polymorphisms (SNPs) at positions close to and within MNRs in the human genome. Overall, we find a 2- to 4-fold increase in the SNP frequency at positions immediately adjacent to the boundaries of MNRs, relative to that at more distant bases. This relationship exhibits a strong asymmetry between 3 and 5 ends of repeat tracts and is dependent upon the repeat motif, length and orientation of surrounding repeats. Our analysis suggests that the incorporation or exclusion of bases adjacent to the boundary of the repeat through substitutions, in which these nucleotides mutate towards or away from the base present within the repeat, respectively, may be another mechanism by which MNRs expand and contract in the human genome.'),
(76031, 2011, 'bio', 'Automated analysis of biological oscillator models using mode decomposition', 'Konopka, Tomasz', 'Biosystems, Biomodeling and Bioprocesses Group, Université Libre de Bruxelles, Brussels, Belgium. tkonopka@ulb.ac.be', 'Belgium', 2, 'Animals|Biological Clocks|Circadian Rhythm|Fourier Analysis|Gene Expression Profiling|Mice|Models, Biological|Software', 'Journal Article', '10.1093/bioinformatics/btr069', '21317138', 'Oscillating signals produced by biological systems have shapes, described by their Fourier spectra, that can potentially reveal the mechanisms that generate them. Extracting this information from measured signals is interesting for the validation of theoretical models, discovery and classification of interaction types, and for optimal experiment design.'),
(76032, 2011, 'bio', 'eGOB: eukaryotic Gene Order Browser', 'López, Marcela Dávila|Samuelsson, Tore', 'Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, Sahlgrenska Academy at University of Gothenburg, SE-405 30 Göteborg, Sweden.|Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, Sahlgrenska Academy at University of Gothenburg, SE-405 30 Göteborg, Sweden.', 'Sweden|Sweden', 8, 'Eukaryota|Gene Order|Genomics|Proteins|RNA, Untranslated|Software', 'Journal Article', '10.1093/bioinformatics/btr075', '21317139', 'A large number of genomes have been sequenced, allowing a range of comparative studies. Here, we present the eukaryotic Gene Order Browser with information on the order of protein and non-coding RNA (ncRNA) genes of 74 different eukaryotic species. The browser is able to display a gene of interest together with its genomic context in all species where that gene is present. Thereby, questions related to the evolution of gene organization and non-random gene order may be examined. The browser also provides access to data collected on pairs of adjacent genes that are evolutionarily conserved.'),
(76033, 2011, 'bio', 'SiGN-SSM: open source parallel software for estimating gene networks with state space models', 'Tamada, Yoshinori|Yamaguchi, Rui|Imoto, Seiya|Hirose, Osamu|Yoshida, Ryo|Nagasaki, Masao|Miyano, Satoru', 'Laboratory of DNA Information Analysis, Human Genome Center, Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan. tamada@ims.u-tokyo.ac.jp|Laboratory of DNA Information Analysis, Human Genome Center, Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan. tamada@ims.u-tokyo.ac.jp|Laboratory of DNA Information Analysis, Human Genome Center, Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan. tamada@ims.u-tokyo.ac.jp|Laboratory of DNA Information Analysis, Human Genome Center, Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan. tamada@ims.u-tokyo.ac.jp|Laboratory of DNA Information Analysis, Human Genome Center, Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan. tamada@ims.u-tokyo.ac.jp|Laboratory of DNA Information Analysis, Human Genome Center, Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan. tamada@ims.u-tokyo.ac.jp|Laboratory of DNA Information Analysis, Human Genome Center, Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan. tamada@ims.u-tokyo.ac.jp', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 5, 'Gene Expression Profiling|Gene Regulatory Networks|Models, Statistical|Software', 'Journal Article', '10.1093/bioinformatics/btr078', '21317140', 'SiGN-SSM is an open-source gene network estimation software able to run in parallel on PCs and massively parallel supercomputers. The software estimates a state space model (SSM), that is a statistical dynamic model suitable for analyzing short time and/or replicated time series gene expression profiles. SiGN-SSM implements a novel parameter constraint effective to stabilize the estimated models. Also, by using a supercomputer, it is able to determine the gene network structure by a statistical permutation test in a practical time. SiGN-SSM is applicable not only to analyzing temporal regulatory dependencies between genes, but also to extracting the differentially regulated genes from time series expression profiles.'),
(76034, 2011, 'bio', 'Network clustering: probing biological heterogeneity by sparse graphical models', 'Mukherjee, Sach|Hill, Steven M', 'Department of Statistics, University of Warwick, Coventry, UK. s.n.mukherjee@warwick.ac.uk|Department of Statistics, University of Warwick, Coventry, UK. s.n.mukherjee@warwick.ac.uk', 'United Kingdom|United Kingdom', 9, 'Cell Line, Tumor|Cluster Analysis|Computational Biology|Computer Graphics|Humans|Models, Biological|Neoplasms|Proteomics|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btr070', '21317141', 'Networks and pathways are important in describing the collective biological function of molecular players such as genes or proteins. In many areas of biology, for example in cancer studies, available data may harbour undiscovered subtypes which differ in terms of network phenotype. That is, samples may be heterogeneous with respect to underlying molecular networks. This motivates a need for unsupervised methods capable of discovering such subtypes and elucidating the corresponding network structures.'),
(76035, 2011, 'bio', 'Topological entropy of DNA sequences', 'Koslicki, David', 'Department of Mathematics, Pennsylvania State University, State College, PA 16801, USA. koslicki@math.psu.edu', 'United States', 31, 'Chromosomes, Human, Y|DNA|Entropy|Exons|Genome, Human|Humans|Introns|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btr077', '21317142', 'Topological entropy has been one of the most difficult to implement of all the entropy-theoretic notions. This is primarily due to finite sample effects and high-dimensionality problems. In particular, topological entropy has been implemented in previous literature to conclude that entropy of exons is higher than of introns, thus implying that exons are more random than introns.'),
(76036, 2011, 'bio', 'Cross-platform comparison of microarray data using order restricted inference', 'Klinglmueller, Florian|Tuechler, Thomas|Posch, Martin', 'Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.|Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.|Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.', 'Austria|Austria|Austria', 5, 'Animals|Data Interpretation, Statistical|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Rats', 'Evaluation Studies', '10.1093/bioinformatics/btr066', '21317143', 'Titration experiments measuring the gene expression from two different tissues, along with total RNA mixtures of the pure samples, are frequently used for quality evaluation of microarray technologies. Such a design implies that the true mRNA expression of each gene, is either constant or follows a monotonic trend between the mixtures, applying itself to the use of order restricted inference procedures. Exploiting only the postulated monotonicity of titration designs, we propose three statistical analysis methods for the validation of high-throughput genetic data and corresponding preprocessing techniques.'),
(76037, 2011, 'bio', 'Improving SNP discovery by base alignment quality', 'Li, Heng', 'Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA. hengli@broadinstitute.org', 'United States', 134, 'Algorithms|Base Sequence|Genomics|INDEL Mutation|Markov Chains|Polymorphism, Single Nucleotide|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btr076', '21320865', 'I propose a new application of profile Hidden Markov Models in the area of SNP discovery from resequencing data, to greatly reduce false SNP calls caused by misalignments around insertions and deletions (indels). The central concept is per-Base Alignment Quality, which accurately measures the probability of a read base being wrongly aligned. The effectiveness of BAQ has been positively confirmed on large datasets by the 1000 Genomes Project analysis subgroup.'),
(76038, 2011, 'bio', 'Identifying dispersed epigenomic domains from ChIP-Seq data', 'Song, Qiang|Smith, Andrew D', 'Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.|Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.', 'United States|United States', 103, 'Chromatin Immunoprecipitation|Epigenomics|Gene Expression Profiling|Histones|Markov Chains|Oligonucleotide Array Sequence Analysis|Protein Processing, Post-Translational|Software', 'Journal Article', '10.1093/bioinformatics/btr030', '21325299', 'Post-translational modifications to histones have several well known associations with regulation of gene expression. While some modifications appear concentrated narrowly, covering promoters or enhancers, others are dispersed as epigenomic domains. These domains mark contiguous regions sharing an epigenomic property, such as actively transcribed or poised genes, or heterochromatically silenced regions. While high-throughput methods like ChIP-Seq have led to a flood of high-quality data about these epigenomic domains, there remain important analysis problems that are not adequately solved by current analysis tools.'),
(76039, 2011, 'bio', 'Automated workflows for accurate mass-based putative metabolite identification in LC/MS-derived metabolomic datasets', 'Brown, Marie|Wedge, David C|Goodacre, Royston|Kell, Douglas B|Baker, Philip N|Kenny, Louise C|Mamas, Mamas A|Neyses, Ludwig|Dunn, Warwick B', 'School of Biomedicine, The University of Manchester, Manchester M13 9PT, UK.|School of Biomedicine, The University of Manchester, Manchester M13 9PT, UK.|School of Biomedicine, The University of Manchester, Manchester M13 9PT, UK.|School of Biomedicine, The University of Manchester, Manchester M13 9PT, UK.|School of Biomedicine, The University of Manchester, Manchester M13 9PT, UK.|School of Biomedicine, The University of Manchester, Manchester M13 9PT, UK.|School of Biomedicine, The University of Manchester, Manchester M13 9PT, UK.|School of Biomedicine, The University of Manchester, Manchester M13 9PT, UK.|School of Biomedicine, The University of Manchester, Manchester M13 9PT, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 138, 'Chromatography, Liquid|Mass Spectrometry|Metabolomics|Software|Workflow', 'Journal Article', '10.1093/bioinformatics/btr079', '21325300', 'The study of metabolites (metabolomics) is increasingly being applied to investigate microbial, plant, environmental and mammalian systems. One of the limiting factors is that of chemically identifying metabolites from mass spectrometric signals present in complex datasets.'),
(76040, 2011, 'bio', 'Annotating genes and genomes with DNA sequences extracted from biomedical articles', 'Haeussler, Maximilian|Gerner, Martin|Bergman, Casey M', 'Faculty of Life Sciences, University of Manchester, Manchester, UK. maximilianh@gmail.com|Faculty of Life Sciences, University of Manchester, Manchester, UK. maximilianh@gmail.com|Faculty of Life Sciences, University of Manchester, Manchester, UK. maximilianh@gmail.com', 'United Kingdom|United Kingdom|United Kingdom', 18, 'Base Sequence|Chromatin Immunoprecipitation|DNA|Data Mining|Databases, Nucleic Acid|Genes|Genome|Molecular Sequence Annotation|PubMed|Reverse Transcriptase Polymerase Chain Reaction|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr043', '21325301', 'Increasing rates of publication and DNA sequencing make the problem of finding relevant articles for a particular gene or genomic region more challenging than ever. Existing text-mining approaches focus on finding gene names or identifiers in English text. These are often not unique and do not identify the exact genomic location of a study.'),
(76041, 2011, 'bio', 'Proteomics to go: Proteomatic enables the user-friendly creation of versatile MS/MS data evaluation workflows', 'Specht, Michael|Kuhlgert, Sebastian|Fufezan, Christian|Hippler, Michael', 'Institute of Plant Biology and Biotechnology, Department of Biology, University of Muenster, Muenster, Germany. michael.specht@uni-muenster.de|Institute of Plant Biology and Biotechnology, Department of Biology, University of Muenster, Muenster, Germany. michael.specht@uni-muenster.de|Institute of Plant Biology and Biotechnology, Department of Biology, University of Muenster, Muenster, Germany. michael.specht@uni-muenster.de|Institute of Plant Biology and Biotechnology, Department of Biology, University of Muenster, Muenster, Germany. michael.specht@uni-muenster.de', 'Germany|Germany|Germany|Germany', 0, 'Proteomics|Software|Tandem Mass Spectrometry|User-Computer Interface|Workflow', 'Journal Article', '10.1093/bioinformatics/btr081', '21325302', 'We present Proteomatic, an operating system independent and user-friendly platform that enables the construction and execution of MS/MS data evaluation pipelines using free and commercial software. Required external programs such as for peptide identification are downloaded automatically in the case of free software. Due to a strict separation of functionality and presentation, and support for multiple scripting languages, new processing steps can be added easily.'),
(76042, 2011, 'bio', 'The effects of feedback loops on disease comorbidity in human signaling networks', 'Le, Duc-Hau|Kwon, Yung-Keun', 'School of Computer Engineering and Information Technology, University of Ulsan, 93 Daehak-ro, Nam-gu, Ulsan 680-749, Korea.|School of Computer Engineering and Information Technology, University of Ulsan, 93 Daehak-ro, Nam-gu, Ulsan 680-749, Korea.', '-|-', 0, 'Comorbidity|Disease|Feedback, Physiological|Humans|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btr082', '21325303', 'In general, diseases are more likely to be comorbid if they share associated genes or molecular interactions in a cellular process. However, there are still a number of pairs of diseases which show relatively high comorbidity but do not share any associated genes or interactions. This observation raises the need for a novel factor which can explain the underlying mechanism of comorbidity. We here consider a feedback loop (FBL) structure ubiquitously found in the human cell signaling network as a key motif to explain the comorbidity phenomenon, since it is well known to have effects on network dynamics.'),
(76043, 2011, 'bio', 'Flower: extracting information from pyrosequencing data', 'Malde, Ketil', 'The Norwegian Marine Data Centre, Institute of Marine Research, Bergen, Norway. ketil.malde@imr.no', 'Norway', 0, 'Base Sequence|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr063', '21330287', 'The SFF file format produced by Roches 454 sequencing technology is a compact, binary format that contains the flow values that are used for base and quality calling of the reads. Applications, e.g. in metagenomics, often depend on accurate sequence information, and access to flow values is important to estimate the probability of errors. Unfortunately, the programs supplied by Roche for accessing this information are not publicly available. Flower is a program that can extract the information contained in SFF files, and convert it to various textual output formats.'),
(76044, 2011, 'bio', 'Sensitive gene fusion detection using ambiguously mapping RNA-Seq read pairs', 'Kinsella, Marcus|Harismendy, Olivier|Nakano, Masakazu|Frazer, Kelly A|Bafna, Vineet', 'Bioinformatics and Systems Biology Program, Moores UCSD Cancer Center, Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA. mckinsel@ucsd.edu|Bioinformatics and Systems Biology Program, Moores UCSD Cancer Center, Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA. mckinsel@ucsd.edu|Bioinformatics and Systems Biology Program, Moores UCSD Cancer Center, Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA. mckinsel@ucsd.edu|Bioinformatics and Systems Biology Program, Moores UCSD Cancer Center, Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA. mckinsel@ucsd.edu|Bioinformatics and Systems Biology Program, Moores UCSD Cancer Center, Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA. mckinsel@ucsd.edu', 'United States|United States|United States|United States|United States', 41, 'Cell Line|Gene Expression Profiling|Gene Fusion|Humans|Male|Prostatic Neoplasms|RNA, Messenger|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btr085', '21330288', 'Paired-end whole transcriptome sequencing provides evidence for fusion transcripts. However, due to the repetitiveness of the transcriptome, many reads have multiple high-quality mappings. Previous methods to find gene fusions either ignored these reads or required additional longer single reads. This can obscure up to 30% of fusions and unnecessarily discards much of the data.'),
(76045, 2011, 'bio', 'Defining an informativeness metric for clustering gene expression data', 'Mar, Jessica C|Wells, Christine A|Quackenbush, John', 'Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. jess@jimmy.harvard.edu|Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. jess@jimmy.harvard.edu|Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. jess@jimmy.harvard.edu', 'United States|United States|United States', 0, 'Cluster Analysis|Data Interpretation, Statistical|Gene Expression|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis', 'Evaluation Studies', '10.1093/bioinformatics/btr074', '21330289', 'Unsupervised cluster analysis is an invaluable tool for exploratory microarray data analysis, as it organizes the data into groups of genes or samples in which the elements share common patterns. Once the data are clustered, finding the optimal number of informative subgroups within a dataset is a problem that, while important for understanding the underlying phenotypes, is one for which there is no robust, widely accepted solution.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76046, 2011, 'bio', 'FIMO: scanning for occurrences of a given motif', 'Grant, Charles E|Bailey, Timothy L|Noble, William Stafford', 'Department of Genome Sciences, University of Washington, Seattle, WA, USA.|Department of Genome Sciences, University of Washington, Seattle, WA, USA.|Department of Genome Sciences, University of Washington, Seattle, WA, USA.', 'United States|United States|United States', 1233, 'Amino Acid Motifs|Base Sequence|Binding Sites|CCCTC-Binding Factor|Conserved Sequence|DNA|Databases, Genetic|Genome, Human|Humans|Position-Specific Scoring Matrices|Repressor Proteins|Sequence Analysis, DNA|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btr064', '21330290', 'A motif is a short DNA or protein sequence that contributes to the biological function of the sequence in which it resides. Over the past several decades, many computational methods have been described for identifying, characterizing and searching with sequence motifs. Critical to nearly any motif-based sequence analysis pipeline is the ability to scan a sequence database for occurrences of a given motif described by a position-specific frequency matrix.'),
(76047, 2011, 'bio', 'libfbi: a C++ implementation for fast box intersection and application to sparse mass spectrometry data', 'Kirchner, Marc|Xu, Buote|Steen, Hanno|Steen, Judith A J', 'Proteomics Center, Department of Pathology, Childrens Hospital Boston, Harvard Medical School, Boston, MA 02115, USA. marc.kirchner@childrens.harvard.edu|Proteomics Center, Department of Pathology, Childrens Hospital Boston, Harvard Medical School, Boston, MA 02115, USA. marc.kirchner@childrens.harvard.edu|Proteomics Center, Department of Pathology, Childrens Hospital Boston, Harvard Medical School, Boston, MA 02115, USA. marc.kirchner@childrens.harvard.edu|Proteomics Center, Department of Pathology, Childrens Hospital Boston, Harvard Medical School, Boston, MA 02115, USA. marc.kirchner@childrens.harvard.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Chromatography, Liquid|Mass Spectrometry|Software', 'Journal Article', '10.1093/bioinformatics/btr084', '21330291', 'Algorithms for sparse data require fast search and subset selection capabilities for the determination of point neighborhoods. A natural data representation for such cases are space partitioning data structures. However, the associated range queries assume noise-free observations and cannot take into account observation-specific uncertainty estimates that are present in e.g. modern mass spectrometry data. In order to accommodate the inhomogeneous noise characteristics of sparse real-world datasets, point queries need to be reformulated in terms of box intersection queries, where box sizes correspond to uncertainty regions for each observation.'),
(76048, 2011, 'bio', 'Condensing biomedical journal texts through paragraph ranking', 'Chiang, Jung-Hsien|Liu, Heng-Hui|Huang, Yi-Ting', 'Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan. jchiang@mail.ncku.edu.tw|Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan. jchiang@mail.ncku.edu.tw|Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan. jchiang@mail.ncku.edu.tw', '-|-|-', 0, 'Abstracting and Indexing as Topic|Algorithms|Data Mining|Periodicals as Topic', 'Evaluation Studies', '10.1093/bioinformatics/btr080', '21330292', 'The growing availability of full-text scientific articles raises the important issue of how to most efficiently digest full-text content. Although article titles and abstracts provide accurate and concise information on an articles contents, their brevity inevitably entails the loss of detail. Full-text articles provide those details, but require more time to read. The primary goal of this study is to combine the advantages of concise abstracts and detail-rich full-texts to ease the burden of reading.'),
(76049, 2011, 'bio', 'Topology and prediction of RNA pseudoknots', 'Reidys, Christian M|Huang, Fenix W D|Andersen, Jørgen E|Penner, Robert C|Stadler, Peter F|Nebel, Markus E', 'Department of Mathematics, Center for Combinatorics, Key Laboratory of Pure Mathematics and Combinatorics, College of Life Science, Nankai University Tianjin 300071, PR China. duck@santafe.edu|Department of Mathematics, Center for Combinatorics, Key Laboratory of Pure Mathematics and Combinatorics, College of Life Science, Nankai University Tianjin 300071, PR China. duck@santafe.edu|Department of Mathematics, Center for Combinatorics, Key Laboratory of Pure Mathematics and Combinatorics, College of Life Science, Nankai University Tianjin 300071, PR China. duck@santafe.edu|Department of Mathematics, Center for Combinatorics, Key Laboratory of Pure Mathematics and Combinatorics, College of Life Science, Nankai University Tianjin 300071, PR China. duck@santafe.edu|Department of Mathematics, Center for Combinatorics, Key Laboratory of Pure Mathematics and Combinatorics, College of Life Science, Nankai University Tianjin 300071, PR China. duck@santafe.edu|Department of Mathematics, Center for Combinatorics, Key Laboratory of Pure Mathematics and Combinatorics, College of Life Science, Nankai University Tianjin 300071, PR China. duck@santafe.edu', 'China|China|China|China|China|China', 65, 'Algorithms|Base Pairing|Nucleic Acid Conformation|RNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btr090', '21335320', 'Several dynamic programming algorithms for predicting RNA structures with pseudoknots have been proposed that differ dramatically from one another in the classes of structures considered.'),
(76050, 2011, 'bio', 'ProtTest 3: fast selection of best-fit models of protein evolution', 'Darriba, Diego|Taboada, Guillermo L|Doallo, Ramón|Posada, David', 'Department of Biochemistry, Genetics and Immunology, University of Vigo, 36310 Vigo, Spain.|Department of Biochemistry, Genetics and Immunology, University of Vigo, 36310 Vigo, Spain.|Department of Biochemistry, Genetics and Immunology, University of Vigo, 36310 Vigo, Spain.|Department of Biochemistry, Genetics and Immunology, University of Vigo, 36310 Vigo, Spain.', 'Spain|Spain|Spain|Spain', 0, 'Evolution, Molecular|Models, Statistical|Phylogeny|Sequence Alignment|Sequence Analysis, Protein|Software', 'Evaluation Studies', '10.1093/bioinformatics/btr088', '21335321', 'We have implemented a high-performance computing (HPC) version of ProtTest that can be executed in parallel in multicore desktops and clusters. This version, called ProtTest 3, includes new features and extended capabilities.'),
(76051, 2011, 'bio', 'B2G-FAR, a species-centered GO annotation repository', 'Götz, Stefan|Arnold, Roland|Sebastián-León, Patricia|Martín-Rodríguez, Samuel|Tischler, Patrick|Jehl, Marc-André|Dopazo, Joaquín|Rattei, Thomas|Conesa, Ana', 'Bioinformatics and Genomics Department, Centro de Investigaciones Príncipe Felipe (CIPF), Valencia, Spain. sgoetz@cipf.es|Bioinformatics and Genomics Department, Centro de Investigaciones Príncipe Felipe (CIPF), Valencia, Spain. sgoetz@cipf.es|Bioinformatics and Genomics Department, Centro de Investigaciones Príncipe Felipe (CIPF), Valencia, Spain. sgoetz@cipf.es|Bioinformatics and Genomics Department, Centro de Investigaciones Príncipe Felipe (CIPF), Valencia, Spain. sgoetz@cipf.es|Bioinformatics and Genomics Department, Centro de Investigaciones Príncipe Felipe (CIPF), Valencia, Spain. sgoetz@cipf.es|Bioinformatics and Genomics Department, Centro de Investigaciones Príncipe Felipe (CIPF), Valencia, Spain. sgoetz@cipf.es|Bioinformatics and Genomics Department, Centro de Investigaciones Príncipe Felipe (CIPF), Valencia, Spain. sgoetz@cipf.es|Bioinformatics and Genomics Department, Centro de Investigaciones Príncipe Felipe (CIPF), Valencia, Spain. sgoetz@cipf.es|Bioinformatics and Genomics Department, Centro de Investigaciones Príncipe Felipe (CIPF), Valencia, Spain. sgoetz@cipf.es', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain', 105, 'Data Mining|Databases, Genetic|Genes|Genomics|High-Throughput Nucleotide Sequencing|Molecular Sequence Annotation|Oligonucleotide Array Sequence Analysis|Sequence Analysis, Protein|Software|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btr059', '21335611', 'Functional genomics research has expanded enormously in the last decade thanks to the cost reduction in high-throughput technologies and the development of computational tools that generate, standardize and share information on gene and protein function such as the Gene Ontology (GO). Nevertheless, many biologists, especially working with non-model organisms, still suffer from non-existing or low-coverage functional annotation, or simply struggle retrieving, summarizing and querying these data.'),
(76052, 2011, 'bio', 'fconv: Format conversion, manipulation and feature computation of molecular data', 'Neudert, Gerd|Klebe, Gerhard', 'Department of Pharmaceutical Chemistry, Philipps-Universität Marburg, Marburg, Germany.|Department of Pharmaceutical Chemistry, Philipps-Universität Marburg, Marburg, Germany.', 'Germany|Germany', 0, 'Algorithms|Chemical Phenomena|Ligands|Software', 'Journal Article', '10.1093/bioinformatics/btr055', '21335612', 'fconv is a program intended for parsing and manipulating multiple aspects and properties of molecular data. Up to now, it has been developed and extensively tested for 3 years. It has become a very robust and comprehensive tool involved in a broad range of computational workflows that are currently applied in our drug design environment. Typical tasks are as follows: conversion and error correction of formats such as PDB(QT), MOL2, SDF, DLG and CIF, extracting ligands from PDB as MOL2, automatic or ligand-based cavity detection, rmsd calculation and clustering, substructure searches, alignment and structural superposition, building of crystal packings, adding hydrogens, calculation of various properties like the number of rotatable bonds, molecular weights or vdW volumes. The atom type classification is based on a consistent assignment of internal atom types, which are by far more differentiated compared with e.g. Sybyl atom types. Apart from the predefined mapping of these types onto Sybyl types, the user is able to assign own mappings by providing modified template files, thus allowing for tailor-made atom type sets.'),
(76053, 2011, 'bio', 'A common layer of interoperability for biomedical ontologies based on OWL EL', 'Hoehndorf, Robert|Dumontier, Michel|Oellrich, Anika|Wimalaratne, Sarala|Rebholz-Schuhmann, Dietrich|Schofield, Paul|Gkoutos, Georgios V', 'Department of Genetics, University of Cambridge, Cambridge, UK. rh497@cam.ac.uk|Department of Genetics, University of Cambridge, Cambridge, UK. rh497@cam.ac.uk|Department of Genetics, University of Cambridge, Cambridge, UK. rh497@cam.ac.uk|Department of Genetics, University of Cambridge, Cambridge, UK. rh497@cam.ac.uk|Department of Genetics, University of Cambridge, Cambridge, UK. rh497@cam.ac.uk|Department of Genetics, University of Cambridge, Cambridge, UK. rh497@cam.ac.uk|Department of Genetics, University of Cambridge, Cambridge, UK. rh497@cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 36, 'Biomedical Research|Databases, Factual|Semantics|Software|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/btr058', '21343142', 'Ontologies are essential in biomedical research due to their ability to semantically integrate content from different scientific databases and resources. Their application improves capabilities for querying and mining biological knowledge. An increasing number of ontologies is being developed for this purpose, and considerable effort is invested into formally defining them in order to represent their semantics explicitly. However, current biomedical ontologies do not facilitate data integration and interoperability yet, since reasoning over these ontologies is very complex and cannot be performed efficiently or is even impossible. We propose the use of less expressive subsets of ontology representation languages to enable efficient reasoning and achieve the goal of genuine interoperability between ontologies.'),
(76054, 2011, 'bio', 'BiC: a web server for calculating bimodality of coexpression between gene and protein networks', 'Linderman, George C|Patel, Vishal N|Chance, Mark R|Bebek, Gurkan', 'Department of Biomedical Engineering, Case Center for Proteomics and Bioinformatics, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA.|Department of Biomedical Engineering, Case Center for Proteomics and Bioinformatics, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA.|Department of Biomedical Engineering, Case Center for Proteomics and Bioinformatics, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA.|Department of Biomedical Engineering, Case Center for Proteomics and Bioinformatics, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA.', 'United States|United States|United States|United States', 2, 'Algorithms|Gene Expression|Gene Expression Profiling|Gene Regulatory Networks|Internet|Oligonucleotide Array Sequence Analysis|Proteins|RNA, Messenger|Software', 'Journal Article', '10.1093/bioinformatics/btr086', '21345871', 'Bimodal patterns of expression have recently been shown to be useful not only in prioritizing genes that distinguish phenotypes, but also in prioritizing network models that correlate with proteomic evidence. In particular, subgroups of strongly coexpressed gene pairs result in an increased variance of the correlation distribution. This variance, a measure of association between sets of genes (or proteins), can be summarized as the bimodality of coexpression (BiC). We developed an online tool to calculate the BiC for user-defined gene lists and associated mRNA expression data. BiC is a comprehensive application that provides researchers with the ability to analyze both publicly available and user-collected array data.'),
(76055, 2011, 'bio', 'Improved structure, function and compatibility for CellProfiler: modular high-throughput image analysis software', 'Kamentsky, Lee|Jones, Thouis R|Fraser, Adam|Bray, Mark-Anthony|Logan, David J|Madden, Katherine L|Ljosa, Vebjorn|Rueden, Curtis|Eliceiri, Kevin W|Carpenter, Anne E', 'Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.|Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.|Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.|Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.|Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.|Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.|Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.|Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.|Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.|Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|High-Throughput Screening Assays|Image Processing, Computer-Assisted|Neurons|Software', 'Journal Article', '10.1093/bioinformatics/btr095', '21349861', 'There is a strong and growing need in the biology research community for accurate, automated image analysis. Here, we describe CellProfiler 2.0, which has been engineered to meet the needs of its growing user base. It is more robust and user friendly, with new algorithms and features to facilitate high-throughput work. ImageJ plugins can now be run within a CellProfiler pipeline.'),
(76056, 2011, 'bio', 'PrimerProspector: de novo design and taxonomic analysis of barcoded polymerase chain reaction primers', 'Walters, William A|Caporaso, J Gregory|Lauber, Christian L|Berg-Lyons, Donna|Fierer, Noah|Knight, Rob', 'Department of Molecular, Cellular, and Developmental Biology, Cooperative Institute for Research in Environmental Sciences, University of Colorado at Boulder, Boulder, CO 80309, USA.|Department of Molecular, Cellular, and Developmental Biology, Cooperative Institute for Research in Environmental Sciences, University of Colorado at Boulder, Boulder, CO 80309, USA.|Department of Molecular, Cellular, and Developmental Biology, Cooperative Institute for Research in Environmental Sciences, University of Colorado at Boulder, Boulder, CO 80309, USA.|Department of Molecular, Cellular, and Developmental Biology, Cooperative Institute for Research in Environmental Sciences, University of Colorado at Boulder, Boulder, CO 80309, USA.|Department of Molecular, Cellular, and Developmental Biology, Cooperative Institute for Research in Environmental Sciences, University of Colorado at Boulder, Boulder, CO 80309, USA.|Department of Molecular, Cellular, and Developmental Biology, Cooperative Institute for Research in Environmental Sciences, University of Colorado at Boulder, Boulder, CO 80309, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Base Sequence|DNA Primers|Humans|Phylogeny|Polymerase Chain Reaction|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btr087', '21349862', 'PCR amplification of DNA is a key preliminary step in many applications of high-throughput sequencing technologies, yet design of novel barcoded primers and taxonomic analysis of novel or existing primers remains a challenging task.'),
(76057, 2011, 'bio', 'ACT: aggregation and correlation toolbox for analyses of genome tracks', 'Jee, Justin|Rozowsky, Joel|Yip, Kevin Y|Lochovsky, Lucas|Bjornson, Robert|Zhong, Guoneng|Zhang, Zhengdong|Fu, Yutao|Wang, Jie|Weng, Zhiping|Gerstein, Mark', 'Program in Computational Biology and Bioinformatics, Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA.|Program in Computational Biology and Bioinformatics, Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA.|Program in Computational Biology and Bioinformatics, Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA.|Program in Computational Biology and Bioinformatics, Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA.|Program in Computational Biology and Bioinformatics, Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA.|Program in Computational Biology and Bioinformatics, Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA.|Program in Computational Biology and Bioinformatics, Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA.|Program in Computational Biology and Bioinformatics, Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA.|Program in Computational Biology and Bioinformatics, Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA.|Program in Computational Biology and Bioinformatics, Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA.|Program in Computational Biology and Bioinformatics, Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Genomics|Polymorphism, Single Nucleotide|Software|Transcription Initiation Site', 'Journal Article', '10.1093/bioinformatics/btr092', '21349863', 'We have implemented aggregation and correlation toolbox (ACT), an efficient, multifaceted toolbox for analyzing continuous signal and discrete region tracks from high-throughput genomic experiments, such as RNA-seq or ChIP-chip signal profiles from the ENCODE and modENCODE projects, or lists of single nucleotide polymorphisms from the 1000 genomes project. It is able to generate aggregate profiles of a given track around a set of specified anchor points, such as transcription start sites. It is also able to correlate related tracks and analyze them for saturation--i.e. how much of a certain feature is covered with each new succeeding experiment. The ACT site contains downloadable code in a variety of formats, interactive web servers (for use on small quantities of data), example datasets, documentation and a gallery of outputs. Here, we explain the components of the toolbox in more detail and apply them in various contexts.'),
(76058, 2011, 'bio', 'Assigning spectrum-specific P-values to protein identifications by mass spectrometry', 'Spirin, Victor|Shpunt, Alexander|Seebacher, Jan|Gentzel, Marc|Shevchenko, Andrej|Gygi, Steven|Sunyaev, Shamil', 'Division of Genetics, Brigham and Womens Hospital, Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, MA 02115, USA.|Division of Genetics, Brigham and Womens Hospital, Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, MA 02115, USA.|Division of Genetics, Brigham and Womens Hospital, Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, MA 02115, USA.|Division of Genetics, Brigham and Womens Hospital, Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, MA 02115, USA.|Division of Genetics, Brigham and Womens Hospital, Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, MA 02115, USA.|Division of Genetics, Brigham and Womens Hospital, Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, MA 02115, USA.|Division of Genetics, Brigham and Womens Hospital, Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, MA 02115, USA.', 'United States|United States|United States|United States|United States|United States|United States', 22, 'Algorithms|Animals|Data Interpretation, Statistical|Databases, Protein|Mass Spectrometry|Mice|Peptides|Proteins|Proteomics|Saccharomyces cerevisiae Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btr089', '21349864', 'Although many methods and statistical approaches have been developed for protein identification by mass spectrometry, the problem of accurate assessment of statistical significance of protein identifications remains an open question. The main issues are as follows: (i) statistical significance of inferring peptide from experimental mass spectra must be platform independent and spectrum specific and (ii) individual spectrum matches at the peptide level must be combined into a single statistical measure at the protein level.'),
(76059, 2011, 'bio', 'All-atom knowledge-based potential for RNA structure prediction and assessment', 'Capriotti, Emidio|Norambuena, Tomas|Marti-Renom, Marc A|Melo, Francisco', 'Structural Genomics Unit, Bioinformatics and Genomics Department, Centro de Investigacixc3xb3n Principe Felipe, 46012 Valencia, Spain.|Structural Genomics Unit, Bioinformatics and Genomics Department, Centro de Investigacixc3xb3n Principe Felipe, 46012 Valencia, Spain.|Structural Genomics Unit, Bioinformatics and Genomics Department, Centro de Investigacixc3xb3n Principe Felipe, 46012 Valencia, Spain.|Structural Genomics Unit, Bioinformatics and Genomics Department, Centro de Investigacixc3xb3n Principe Felipe, 46012 Valencia, Spain.', 'Spain|Spain|Spain|Spain', 0, 'Data Interpretation, Statistical|Knowledge Bases|Models, Molecular|Nucleic Acid Conformation|RNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/btr093', '21349865', 'Over the recent years, the vision that RNA simply serves as information transfer molecule has dramatically changed. The study of the sequence/structure/function relationships in RNA is becoming more important. As a direct consequence, the total number of experimentally solved RNA structures has dramatically increased and new computer tools for predicting RNA structure from sequence are rapidly emerging. Therefore, new and accurate methods for assessing the accuracy of RNA structure models are clearly needed.'),
(76060, 2011, 'bio', 'A high-throughput processing service for retention time alignment of complex proteomics and metabolomics LC-MS data', 'Ahmad, Isthiaq|Suits, Frank|Hoekman, Berend|Swertz, Morris A|Byelas, Heorhiy|Dijkstra, Martijn|Hooft, Rob|Katsubo, Dmitry|van Breukelen, Bas|Bischoff, Rainer|Horvatovich, Peter', 'Analytical Biochemistry, Department of Pharmacy, University of Groningen, Groningen, The Netherlands.|Analytical Biochemistry, Department of Pharmacy, University of Groningen, Groningen, The Netherlands.|Analytical Biochemistry, Department of Pharmacy, University of Groningen, Groningen, The Netherlands.|Analytical Biochemistry, Department of Pharmacy, University of Groningen, Groningen, The Netherlands.|Analytical Biochemistry, Department of Pharmacy, University of Groningen, Groningen, The Netherlands.|Analytical Biochemistry, Department of Pharmacy, University of Groningen, Groningen, The Netherlands.|Analytical Biochemistry, Department of Pharmacy, University of Groningen, Groningen, The Netherlands.|Analytical Biochemistry, Department of Pharmacy, University of Groningen, Groningen, The Netherlands.|Analytical Biochemistry, Department of Pharmacy, University of Groningen, Groningen, The Netherlands.|Analytical Biochemistry, Department of Pharmacy, University of Groningen, Groningen, The Netherlands.|Analytical Biochemistry, Department of Pharmacy, University of Groningen, Groningen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Neth', 0, 'Animals|Chromatography, Liquid|High-Throughput Screening Assays|Internet|Mass Spectrometry|Metabolomics|Mice|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/btr094', '21349866', 'Warp2D is a novel time alignment approach, which uses the overlapping peak volume of the reference and sample peak lists to correct misleading peak shifts. Here, we present an easy-to-use web interface for high-throughput Warp2D batch processing time alignment service using the Dutch Life Science Grid, reducing processing time from days to hours. This service provides the warping function, the sample chromatogram peak list with adjusted retention times and normalized quality scores based on the sum of overlapping peak volume of all peaks. Heat maps before and after time alignment are created from the arithmetic mean of the sum of overlapping peak area rearranged with hierarchical clustering, allowing the quality control of the time alignment procedure. Taverna workflow and command line tool are provided for remote processing of local user data.'),
(76061, 2011, 'bio', 'Interactive, multiscale navigation of large and complicated biological networks', 'Praneenararat, Thanet|Takagi, Toshihisa|Iwasaki, Wataru', 'Department of Computational Biology, The University of Tokyo, Kashiwa, Chiba 277-8568, Japan. thanet@cb.k.u-tokyo.ac.jp|Department of Computational Biology, The University of Tokyo, Kashiwa, Chiba 277-8568, Japan. thanet@cb.k.u-tokyo.ac.jp|Department of Computational Biology, The University of Tokyo, Kashiwa, Chiba 277-8568, Japan. thanet@cb.k.u-tokyo.ac.jp', 'Japan|Japan|Japan', 0, 'Cluster Analysis|Protein Interaction Mapping|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr083', '21349867', 'Many types of omics data are compiled as lists of connections between elements and visualized as networks or graphs where the nodes and edges correspond to the elements and the connections, respectively. However, these networks often appear as hair-balls-with a large number of extremely tangled edges-and cannot be visually interpreted.'),
(76062, 2011, 'bio', 'Gene List significance at-a-glance with GeneValorization', 'Brancotte, Bryan|Biton, Anne|Bernard-Pierrot, Isabelle|Radvanyi, François|Reyal, Fabien|Cohen-Boulakia, Sarah', 'Laboratoire de Recherche en Informatique, CNRS UMR 8623, Université Paris-Sud, F-91405 Orsay Cedex, France.|Laboratoire de Recherche en Informatique, CNRS UMR 8623, Université Paris-Sud, F-91405 Orsay Cedex, France.|Laboratoire de Recherche en Informatique, CNRS UMR 8623, Université Paris-Sud, F-91405 Orsay Cedex, France.|Laboratoire de Recherche en Informatique, CNRS UMR 8623, Université Paris-Sud, F-91405 Orsay Cedex, France.|Laboratoire de Recherche en Informatique, CNRS UMR 8623, Université Paris-Sud, F-91405 Orsay Cedex, France.|Laboratoire de Recherche en Informatique, CNRS UMR 8623, Université Paris-Sud, F-91405 Orsay Cedex, France.', 'France|France|France|France|France|France', 0, 'Genes|Genes, Neoplasm|Humans|Internet|Publications|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr073', '21349868', 'High-throughput technologies provide fundamental informations concerning thousands of genes. Many of the current research laboratories daily use one or more of these technologies and end-up with lists of genes. Assessing the originality of the results obtained includes being aware of the number of publications available concerning individual or multiple genes and accessing information about these publications. Faced with the exponential growth of publications avaliable and number of genes involved in a study, this task is becoming particularly difficult to achieve.'),
(76063, 2011, 'bio', 'R453Plus1Toolbox: an R/Bioconductor package for analyzing Roche 454 Sequencing data', 'Klein, Hans-Ulrich|Bartenhagen, Christoph|Kohlmann, Alexander|Grossmann, Vera|Ruckert, Christian|Haferlach, Torsten|Dugas, Martin', 'Department of Medical Informatics and Biomathematics, University of Münster, Münster and Munich Leukemia Laboratory, Munich, Germany. h.klein@uni-muenster.de|Department of Medical Informatics and Biomathematics, University of Münster, Münster and Munich Leukemia Laboratory, Munich, Germany. h.klein@uni-muenster.de|Department of Medical Informatics and Biomathematics, University of Münster, Münster and Munich Leukemia Laboratory, Munich, Germany. h.klein@uni-muenster.de|Department of Medical Informatics and Biomathematics, University of Münster, Münster and Munich Leukemia Laboratory, Munich, Germany. h.klein@uni-muenster.de|Department of Medical Informatics and Biomathematics, University of Münster, Münster and Munich Leukemia Laboratory, Munich, Germany. h.klein@uni-muenster.de|Department of Medical Informatics and Biomathematics, University of Münster, Münster and Munich Leukemia Laboratory, Munich, Germany. h.klein@uni-muenster.de|Department of Medical Informatics and Biomathematics, University of Münster, Münster and Munich Leukemia Laboratory, Munich, Germany. h.klein@uni-muenster.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Chromosome Mapping|Genetic Variation|Polymerase Chain Reaction|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr102', '21349869', 'The R453Plus1Toolbox is an R/Bioconductor package for the analysis of 454 Sequencing data. Projects generated with Roches data analysis software can be imported into R allowing advanced and customized analyses within the R/Bioconductor environment for sequencing data. Several methods were implemented extending the current functionality of Roches software. These extensions include methods for quality assurance and annotation of detected variants. Further, a pipeline for the detection of structural variants, e.g. balanced chromosomal translocations, is provided.'),
(76064, 2011, 'bio', 'MPID-T2: a database for sequence-structure-function analyses of pMHC and TR/pMHC structures', 'Khan, Javed Mohammed|Cheruku, Harish Reddy|Tong, Joo Chuan|Ranganathan, Shoba', 'Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence in Bioinformatics, Macquarie University, Sydney, NSW, Australia.|Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence in Bioinformatics, Macquarie University, Sydney, NSW, Australia.|Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence in Bioinformatics, Macquarie University, Sydney, NSW, Australia.|Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence in Bioinformatics, Macquarie University, Sydney, NSW, Australia.', 'Australia|Australia|Australia|Australia', 0, 'Animals|Databases, Protein|Histocompatibility Antigens Class I|Histocompatibility Antigens Class II|Humans|Peptides|Protein Binding|Receptors, Antigen, T-Cell|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btr104', '21349870', 'Sequence-structure-function information is critical in understanding the mechanism of pMHC and TR/pMHC binding and recognition. A database for sequence-structure-function information on pMHC and TR/pMHC interactions, MHC-Peptide Interaction Database-TR version 2 (MPID-T2), is now available augmented with the latest PDB and IMGT/3Dstructure-DB data, advanced features and new parameters for the analysis of pMHC and TR/pMHC structures.'),
(76065, 2011, 'bio', 'FNV: light-weight flash-based network and pathway viewer', 'Dannenfelser, Ruth|Lachmann, Alexander|Szenk, Mariola|Maayan, Avi', 'Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY), Mount Sinai School of Medicine, 1425 Madison Avenue, New York, NY 10029, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY), Mount Sinai School of Medicine, 1425 Madison Avenue, New York, NY 10029, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY), Mount Sinai School of Medicine, 1425 Madison Avenue, New York, NY 10029, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY), Mount Sinai School of Medicine, 1425 Madison Avenue, New York, NY 10029, USA.', 'United States|United States|United States|United States', 4, 'Computer Graphics|Internet|Models, Biological|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/btr098', '21349871', 'Network diagrams are commonly used to visualize biochemical pathways by displaying the relationships between genes, proteins, mRNAs, microRNAs, metabolites, regulatory DNA elements, diseases, viruses and drugs. While there are several currently available web-based pathway viewers, there is still room for improvement. To this end, we have developed a flash-based network viewer (FNV) for the visualization of small to moderately sized biological networks and pathways.'),
(76066, 2011, 'bio', 'The MEMPACK alpha-helical transmembrane protein structure prediction server', 'Nugent, Timothy|Ward, Sean|Jones, David T', 'Department of Computer Science, University College London, London, UK. t.nugent@cs.ucl.ac.uk|Department of Computer Science, University College London, London, UK. t.nugent@cs.ucl.ac.uk|Department of Computer Science, University College London, London, UK. t.nugent@cs.ucl.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Archaeal Proteins|Artificial Intelligence|Membrane Proteins|Protein Structure, Secondary', 'Journal Article', '10.1093/bioinformatics/btr096', '21349872', 'The experimental difficulties of alpha-helical transmembrane protein structure determination make this class of protein an important target for sequence-based structure prediction tools. The MEMPACK prediction server allows users to submit a transmembrane protein sequence and returns transmembrane topology, lipid exposure, residue contacts, helix-helix interactions and helical packing arrangement predictions in both plain text and graphical formats using a number of novel machine learning-based algorithms.'),
(76067, 2011, 'bio', 'AGRA: analysis of gene ranking algorithms', 'Kocbek, Simon|Sætre, Rune|Stiglic, Gregor|Kim, Jin-Dong|Pernek, Igor|Tsuruoka, Yoshimasa|Kokol, Peter|Ananiadou, Sophia|Tsujii, Junichi', 'Faculty of Health Sciences, University of Maribor, Maribor, Slovenia. simon.kocbek@uni-mb.si|Faculty of Health Sciences, University of Maribor, Maribor, Slovenia. simon.kocbek@uni-mb.si|Faculty of Health Sciences, University of Maribor, Maribor, Slovenia. simon.kocbek@uni-mb.si|Faculty of Health Sciences, University of Maribor, Maribor, Slovenia. simon.kocbek@uni-mb.si|Faculty of Health Sciences, University of Maribor, Maribor, Slovenia. simon.kocbek@uni-mb.si|Faculty of Health Sciences, University of Maribor, Maribor, Slovenia. simon.kocbek@uni-mb.si|Faculty of Health Sciences, University of Maribor, Maribor, Slovenia. simon.kocbek@uni-mb.si|Faculty of Health Sciences, University of Maribor, Maribor, Slovenia. simon.kocbek@uni-mb.si|Faculty of Health Sciences, University of Maribor, Maribor, Slovenia. simon.kocbek@uni-mb.si', 'Slovenia|Slovenia|Slovenia|Slovenia|Slovenia|Slovenia|Slovenia|Slovenia|Slovenia', 0, 'Algorithms|Data Mining|Genes|Software', 'Journal Article', '10.1093/bioinformatics/btr097', '21349873', 'Often, the most informative genes have to be selected from different gene sets and several computer gene ranking algorithms have been developed to cope with the problem. To help researchers decide which algorithm to use, we developed the analysis of gene ranking algorithms (AGRA) system that offers a novel technique for comparing ranked lists of genes. The most important feature of AGRA is that no previous knowledge of gene ranking algorithms is needed for their comparison. Using the text mining system finding-associated concepts with text analysis. AGRA defines what we call biomedical concept space (BCS) for each gene list and offers a comparison of the gene lists in six different BCS categories. The uploaded gene lists can be compared using two different methods. In the first method, the overlap between each pair of two gene lists of BCSs is calculated. The second method offers a text field where a specific biomedical concept can be entered. AGRA searches for this concept in each gene lists BCS, highlights the rank of the concept and offers a visual representation of concepts ranked above and below it.'),
(76068, 2011, 'bio', 'aCGHSpline--an R package for aCGH dye bias normalization', 'Fitzgerald, Tomas W|Larcombe, Lee D|Le Scouarnec, Solena|Clayton, Stephen|Rajan, Diana|Carter, Nigel P|Redon, Richard', 'Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK. tf2@sanger.ac.uk|Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK. tf2@sanger.ac.uk|Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK. tf2@sanger.ac.uk|Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK. tf2@sanger.ac.uk|Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK. tf2@sanger.ac.uk|Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK. tf2@sanger.ac.uk|Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK. tf2@sanger.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Carbocyanines|Comparative Genomic Hybridization|DNA Copy Number Variations|Fluorescent Dyes|Software', 'Journal Article', '10.1093/bioinformatics/btr107', '21357574', 'The careful normalization of array-based comparative genomic hybridization (aCGH) data is of critical importance for the accurate detection of copy number changes. The difference in labelling affinity between the two fluorophores used in aCGH-usually Cy5 and Cy3-can be observed as a bias within the intensity distributions. If left unchecked, this bias is likely to skew data interpretation during downstream analysis and lead to an increased number of false discoveries.'),
(76069, 2011, 'bio', 'STOCHSIMGPU: parallel stochastic simulation for the Systems Biology Toolbox 2 for MATLAB', 'Klingbeil, Guido|Erban, Radek|Giles, Mike|Maini, Philip K', 'Centre for Mathematical Biology, Oxford-Man Institute of Quantitative Finance, University of Oxford, Oxford OX1 3LB, UK. klingbeil@maths.ox.ac.uk|Centre for Mathematical Biology, Oxford-Man Institute of Quantitative Finance, University of Oxford, Oxford OX1 3LB, UK. klingbeil@maths.ox.ac.uk|Centre for Mathematical Biology, Oxford-Man Institute of Quantitative Finance, University of Oxford, Oxford OX1 3LB, UK. klingbeil@maths.ox.ac.uk|Centre for Mathematical Biology, Oxford-Man Institute of Quantitative Finance, University of Oxford, Oxford OX1 3LB, UK. klingbeil@maths.ox.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Computer Simulation|Software|Stochastic Processes|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btr068', '21357575', 'The importance of stochasticity in biological systems is becoming increasingly recognized and the computational cost of biologically realistic stochastic simulations urgently requires development of efficient software. We present a new software tool STOCHSIMGPU that exploits graphics processing units (GPUs) for parallel stochastic simulations of biological/chemical reaction systems and show that significant gains in efficiency can be made. It is integrated into MATLAB and works with the Systems Biology Toolbox 2 (SBTOOLBOX2) for MATLAB.'),
(76070, 2011, 'bio', 'Automatically identifying and annotating mouse embryo gene expression patterns', 'Han, Liangxiu|van Hemert, Jano I|Baldock, Richard A', 'School of Informatics, University of Edinburgh, Informatics Forum, 10 Crichton Street, Edinburgh EH8 9AB, UK. l.han@mmu.ac.uk|School of Informatics, University of Edinburgh, Informatics Forum, 10 Crichton Street, Edinburgh EH8 9AB, UK. l.han@mmu.ac.uk|School of Informatics, University of Edinburgh, Informatics Forum, 10 Crichton Street, Edinburgh EH8 9AB, UK. l.han@mmu.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 12, 'Animals|Artificial Intelligence|Embryo, Mammalian|Gene Expression|Gene Expression Regulation, Developmental|Image Processing, Computer-Assisted|In Situ Hybridization|Mice|RNA', 'Evaluation Studies', '10.1093/bioinformatics/btr105', '21357576', 'Deciphering the regulatory and developmental mechanisms for multicellular organisms requires detailed knowledge of gene interactions and gene expressions. The availability of large datasets with both spatial and ontological annotation of the spatio-temporal patterns of gene expression in mouse embryo provides a powerful resource to discover the biological function of embryo organization. Ontological annotation of gene expressions consists of labelling images with terms from the anatomy ontology for mouse development. If the spatial genes of an anatomical component are expressed in an image, the image is then tagged with a term of that anatomical component. The current annotation is done manually by domain experts, which is both time consuming and costly. In addition, the level of detail is variable, and inevitably errors arise from the tedious nature of the task. In this article, we present a new method to automatically identify and annotate gene expression patterns in the mouse embryo with anatomical terms.'),
(76071, 2011, 'bio', 'eCEO: an efficient Cloud Epistasis cOmputing model in genome-wide association study', 'Wang, Zhengkui|Wang, Yue|Tan, Kian-Lee|Wong, Limsoon|Agrawal, Divyakant', 'NUS Graduate School for Integrative Sciences and Engineering, Department of Computer Science, School of Computing, National University of Singapore, Singapore and Department of Computer Science, University of California, Santa Barbara, 93106-5110, USA. wangzhengkui@nus.edu.sg|NUS Graduate School for Integrative Sciences and Engineering, Department of Computer Science, School of Computing, National University of Singapore, Singapore and Department of Computer Science, University of California, Santa Barbara, 93106-5110, USA. wangzhengkui@nus.edu.sg|NUS Graduate School for Integrative Sciences and Engineering, Department of Computer Science, School of Computing, National University of Singapore, Singapore and Department of Computer Science, University of California, Santa Barbara, 93106-5110, USA. wangzhengkui@nus.edu.sg|NUS Graduate School for Integrative Sciences and Engineering, Department of Computer Science, School of Computing, National University of Singapore, Singapore and Department of Computer Science, University of California, Santa Barbara, 93106-5110, USA. wangzhengkui@nus.edu.sg|NUS Graduate School for Integrative Sciences and Engineering, Department of Computer Science, School of Computing, National University of Singapore, Singapore and Department of Computer Science, University of California, Santa Barbara, 93106-5110, USA. wangzhengkui@nus.edu.sg', 'Singapore|Singapore|Singapore|Singapore|Singapore', 24, 'Epistasis, Genetic|Genome-Wide Association Study|Models, Statistical|Phenotype|Polymorphism, Single Nucleotide|Software', 'Evaluation Studies', '10.1093/bioinformatics/btr091', '21367868', 'Recent studies suggested that a combination of multiple single nucleotide polymorphisms (SNPs) could have more significant associations with a specific phenotype. However, to discover epistasis, the epistatic interactions of SNPs, in a large number of SNPs, is a computationally challenging task. We are, therefore, motivated to develop efficient and effective solutions for identifying epistatic interactions of SNPs.'),
(76072, 2011, 'bio', 'MemLoci: predicting subcellular localization of membrane proteins in eukaryotes', 'Pierleoni, Andrea|Martelli, Pier Luigi|Casadio, Rita', 'Biocomputing Group, Computational Biology Network, via San Giacomo 9/2, Bologna, Italy.|Biocomputing Group, Computational Biology Network, via San Giacomo 9/2, Bologna, Italy.|Biocomputing Group, Computational Biology Network, via San Giacomo 9/2, Bologna, Italy.', 'Italy|Italy|Italy', 38, 'Computational Biology|Databases, Protein|Eukaryotic Cells|Membrane Proteins|Organelles|Protein Sorting Signals|Protein Transport|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btr108', '21367869', 'Subcellular localization is a key feature in the process of functional annotation of both globular and membrane proteins. In the absence of experimental data, protein localization is inferred on the basis of annotation transfer upon sequence similarity search. However, predictive tools are necessary when the localization of homologs is not known. This is so particularly for membrane proteins. Furthermore, most of the available predictors of subcellular localization are specifically trained on globular proteins and poorly perform on membrane proteins.'),
(76073, 2011, 'bio', 'Large-scale learning of combinatorial transcriptional dynamics from gene expression', 'Asif, H M Shahzad|Sanguinetti, Guido', 'School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh, UK.|School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh, UK.', 'United Kingdom|United Kingdom', 20, 'Artificial Intelligence|Bayes Theorem|Computational Biology|Gene Expression Profiling|Gene Expression Regulation|Gene Regulatory Networks|Likelihood Functions|Markov Chains|Models, Genetic|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr113', '21367870', 'Knowledge of the activation patterns of transcription factors (TFs) is fundamental to elucidate the dynamics of gene regulation in response to environmental conditions. Direct experimental measurement of TFs activities is, however, challenging, resulting in a need to develop statistical tools to infer TF activities from mRNA expression levels of target genes. Current models, however, neglect important features of transcriptional regulation, in particular, the combinatorial nature of regulation, which is fundamental for signal integration, is not accounted for.'),
(76074, 2011, 'bio', 'Connectedness of PPI network neighborhoods identifies regulatory hub proteins', 'Fox, Andrew D|Hescott, Benjamin J|Blumer, Anselm C|Slonim, Donna K', 'Department of Computer Science, Tufts University, Medford, MA 02155, USA. fox.andrew.d@gmail.com|Department of Computer Science, Tufts University, Medford, MA 02155, USA. fox.andrew.d@gmail.com|Department of Computer Science, Tufts University, Medford, MA 02155, USA. fox.andrew.d@gmail.com|Department of Computer Science, Tufts University, Medford, MA 02155, USA. fox.andrew.d@gmail.com', 'United States|United States|United States|United States', 0, 'Algorithms|Anti-Bacterial Agents|Disease|Drug Resistance, Fungal|Gene Expression Profiling|Gentamicins|Humans|Models, Statistical|Protein Interaction Mapping|Saccharomyces cerevisiae Proteins|Yeasts', 'Journal Article', '10.1093/bioinformatics/btr099', '21367871', 'With the growing availability of high-throughput protein-protein interaction (PPI) data, it has become possible to consider how a proteins local or global network characteristics predict its function.');
