INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76331, 2011, 'bio', 'In-depth annotation of SNPs arising from resequencing projects using NGS-SNP', 'Grant, Jason R|Arantes, Adriano S|Liao, Xiaoping|Stothard, Paul', 'Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G2P5, Canada.|Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G2P5, Canada.|Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G2P5, Canada.|Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G2P5, Canada.', 'Canada|Canada|Canada|Canada', 77, 'Genomics|High-Throughput Nucleotide Sequencing|Molecular Sequence Annotation|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btr372', '21697123', 'NGS-SNP is a collection of command-line scripts for providing rich annotations for SNPs identified by the sequencing of whole genomes from any organism with reference sequences in Ensembl. Included among the annotations, several of which are not available from any existing SNP annotation tools, are the results of detailed comparisons with orthologous sequences. These comparisons can, for example, identify SNPs that affect conserved residues, or alter residues or genes linked to phenotypes in another species.'),
(76332, 2011, 'bio', 'MetaABC--an integrated metagenomics platform for data adjustment, binning and clustering', 'Su, Chien-Hao|Hsu, Ming-Tsung|Wang, Tse-Yi|Chiang, Sufeng|Cheng, Jen-Hao|Weng, Francis C|Kao, Cheng-Yan|Wang, Daryi|Tsai, Huai-Kuang', 'Institute of Information Science, Academia Sinica, Taipei 115, Taiwan.|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan.|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan.|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan.|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan.|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan.|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan.|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan.|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan.', '-|-|-|-|-|-|-|-|-', 5, 'Cluster Analysis|Metagenomics|Software|Systems Integration', 'Journal Article', '10.1093/bioinformatics/btr376', '21697124', 'MetaABC is a metagenomic platform that integrates several binning tools coupled with methods for removing artifacts, analyzing unassigned reads and controlling sampling biases. It allows users to arrive at a better interpretation via series of distinct combinations of analysis tools. After execution, MetaABC provides outputs in various visual formats such as tables, pie and bar charts as well as clustering result diagrams.'),
(76333, 2011, 'bio', 'GeneNetWeaver: in silico benchmark generation and performance profiling of network inference methods', 'Schaffter, Thomas|Marbach, Daniel|Floreano, Dario', 'Laboratory of Intelligent Systems, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Laboratory of Intelligent Systems, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Laboratory of Intelligent Systems, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland', 279, 'Benchmarking|Escherichia coli|Gene Expression|Gene Regulatory Networks|Models, Genetic|Software', 'Journal Article', '10.1093/bioinformatics/btr373', '21697125', 'Over the last decade, numerous methods have been developed for inference of regulatory networks from gene expression data. However, accurate and systematic evaluation of these methods is hampered by the difficulty of constructing adequate benchmarks and the lack of tools for a differentiated analysis of network predictions on such benchmarks.'),
(76334, 2011, 'bio', 'ontoCAT: an R package for ontology traversal and search', 'Kurbatova, Natalja|Adamusiak, Tomasz|Kurnosov, Pavel|Swertz, Morris A|Kapushesky, Misha', 'EMBL Outstation-Hinxton, European Bioinformatics Institute, Cambridge, UK. natalja@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Cambridge, UK. natalja@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Cambridge, UK. natalja@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Cambridge, UK. natalja@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Cambridge, UK. natalja@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 9, 'Software|Terminology as Topic|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btr375', '21697126', 'There exist few simple and easily accessible methods to integrate ontologies programmatically in the R environment. We present ontoCAT-an R package to access ontologies in widely used standard formats, stored locally in the filesystem or available online. The ontoCAT package supports a number of traversal and search functions on a single ontology, as well as searching for ontology terms across multiple ontologies and in major ontology repositories.'),
(76335, 2011, 'bio', 'A procedure to statistically evaluate agreement of differential expression for cross-species genomics', 'Pounds, Stan|Gao, Cuilan Lani|Johnson, Robert A|Wright, Karen D|Poppleton, Helen|Finkelstein, David|Leary, Sarah E S|Gilbertson, Richard J', 'Department of Biostatistics, St Jude Childrens Research Hospital, Memphis, TN, USA. stanley.pounds@stjude.org|Department of Biostatistics, St Jude Childrens Research Hospital, Memphis, TN, USA. stanley.pounds@stjude.org|Department of Biostatistics, St Jude Childrens Research Hospital, Memphis, TN, USA. stanley.pounds@stjude.org|Department of Biostatistics, St Jude Childrens Research Hospital, Memphis, TN, USA. stanley.pounds@stjude.org|Department of Biostatistics, St Jude Childrens Research Hospital, Memphis, TN, USA. stanley.pounds@stjude.org|Department of Biostatistics, St Jude Childrens Research Hospital, Memphis, TN, USA. stanley.pounds@stjude.org|Department of Biostatistics, St Jude Childrens Research Hospital, Memphis, TN, USA. stanley.pounds@stjude.org|Department of Biostatistics, St Jude Childrens Research Hospital, Memphis, TN, USA. stanley.pounds@stjude.org', 'United States|United States|United States|United States|United States|United States|United States|United States', 9, 'Animals|Computational Biology|Disease Models, Animal|Ependymoma|Gene Expression Profiling|Genomics|Humans|Meta-Analysis as Topic|Mice|Models, Statistical', 'Comparative Study', '10.1093/bioinformatics/btr362', '21697127', 'Animal models play a pivotal role in translation biomedical research. The scientific value of an animal model depends on how accurately it mimics the human disease. In principle, microarrays collect the necessary data to evaluate the transcriptomic fidelity of an animal model in terms of the similarity of expression with the human disease. However, statistical methods for this purpose are lacking.'),
(76336, 2011, 'bio', 'Metab: an R package for high-throughput analysis of metabolomics data generated by GC-MS', 'Aggio, Raphael|Villas-Bôas, Silas Granato|Ruggiero, Katya', 'Centre for Microbial Innovation, School of Biological Sciences, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand.|Centre for Microbial Innovation, School of Biological Sciences, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand.|Centre for Microbial Innovation, School of Biological Sciences, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand.', 'New Zealand|New Zealand|New Zealand', 76, 'Gas Chromatography-Mass Spectrometry|Humans|Metabolomics|Software', 'Journal Article', '10.1093/bioinformatics/btr379', '21697128', 'The Automated Mass Spectral Deconvolution and Identification System (AMDIS) is freeware extensively applied in metabolomics. However, datasets processed by AMDIS require extensive data correction, filtering and reshaping to create reliable datasets for further downstream analysis. Performed manually, these processes are laborious and extremely time consuming. Furthermore, manual corrections increase the chance of human error and can introduce additional technical variability to the data. Thus, an automated pipeline for curating GC-MS data is urgently needed.'),
(76337, 2011, 'bio', 'JSBML: a flexible Java library for working with SBML', 'Dräger, Andreas|Rodriguez, Nicolas|Dumousseau, Marine|Dörr, Alexander|Wrzodek, Clemens|Le Novère, Nicolas|Zell, Andreas|Hucka, Michael', 'Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tübingen, Germany. jsbml-team@sbml.org|Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tübingen, Germany. jsbml-team@sbml.org|Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tübingen, Germany. jsbml-team@sbml.org|Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tübingen, Germany. jsbml-team@sbml.org|Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tübingen, Germany. jsbml-team@sbml.org|Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tübingen, Germany. jsbml-team@sbml.org|Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tübingen, Germany. jsbml-team@sbml.org|Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tübingen, Germany. jsbml-team@sbml.org', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Computer Simulation|Database Management Systems|Information Storage and Retrieval|Models, Biological|Programming Languages|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btr361', '21697129', 'The specifications of the Systems Biology Markup Language (SBML) define standards for storing and exchanging computer models of biological processes in text files. In order to perform model simulations, graphical visualizations and other software manipulations, an in-memory representation of SBML is required. We developed JSBML for this purpose. In contrast to prior implementations of SBML APIs, JSBML has been designed from the ground up for the Java programming language, and can therefore be used on all platforms supported by a Java Runtime Environment. This offers important benefits for Java users, including the ability to distribute software as Java Web Start applications. JSBML supports all SBML Levels and Versions through Level 3 Version 1, and we have strived to maintain the highest possible degree of compatibility with the popular library libSBML. JSBML also supports modules that can facilitate the development of plugins for end user applications, as well as ease migration from a libSBML-based backend.'),
(76338, 2011, 'bio', 'SNPman: a program for genotype calling using run data from TaqMan allelic discrimination', 'Konopac, Martin|Dusatkova, Petra|Cinek, Ondrej', 'Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno, The Czech Republic.|Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno, The Czech Republic.|Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno, The Czech Republic.', '-|-|-', 2, 'Alleles|Genotyping Techniques|Polymerase Chain Reaction|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btr383', '21697130', 'The SNPman program calls the genotypes of single nucleotide polymorphisms (SNP) from TaqMan allelic discrimination assays. It utilizes the fluorescence data collected over the whole PCR run, rather than relying on the end point fluorescence measurements that is the basis of the genotype calling process in most software solutions sold with the real-time instruments. This inspection of run data facilitates genotype calls in difficult sample sets, especially in those containing various concentrations of DNA or inhibitors, as indicated by results of a reanalysis of 3738 genotyping samples. The program works with data from three different widely used PCR instruments.'),
(76339, 2011, 'bio', 'Response to Comments on Bayesian variable selection for disease classification using gene expression data', 'Song, Xin-Yuan|Lu, Zhao-Hua', 'Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno, The Czech Republic.|Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno, The Czech Republic.', '-|-', 1, 'Bayes Theorem|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis', 'Letter', '10.1093/bioinformatics/btr334', '21697131', '-'),
(76340, 2011, 'bio', 'SEAL: a distributed short read mapping and duplicate removal tool', 'Pireddu, Luca|Leo, Simone|Zanetti, Gianluigi', 'CRS4, Polaris, Ed. 1, I-09010 Pula, Italy. luca.pireddu@crs4.it|CRS4, Polaris, Ed. 1, I-09010 Pula, Italy. luca.pireddu@crs4.it|CRS4, Polaris, Ed. 1, I-09010 Pula, Italy. luca.pireddu@crs4.it', 'Italy|Italy|Italy', 86, 'Algorithms|Computational Biology|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr325', '21697132', 'SEAL is a scalable tool for short read pair mapping and duplicate removal. It computes mappings that are consistent with those produced by BWA and removes duplicates according to the same criteria employed by Picard MarkDuplicates. On a 16-node Hadoop cluster, it is capable of processing about 13 GB per hour in map+rmdup mode, while reaching a throughput of 19 GB per hour in mapping-only mode.'),
(76341, 2011, 'bio', 'eResponseNet: a package prioritizing candidate disease genes through cellular pathways', 'Huang, Jialiang|Liu, Yi|Zhang, Wei|Yu, Hong|Han, Jing-Dong J', 'Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.|Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.|Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.|Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.|Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.', 'China|China|China|China|China', 6, 'Algorithms|Diabetes Mellitus, Type 2|Disease|Genes|Genetic Predisposition to Disease|Genome-Wide Association Study|Humans|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btr380', '21700671', 'Although genome-wide association studies (GWAS) have found many common genetic variants associated with human diseases, it remains a challenge to elucidate the functional links between associated variants and complex traits.'),
(76342, 2011, 'bio', 'Gaia: automated quality assessment of protein structure models', 'Kota, Pradeep|Ding, Feng|Ramachandran, Srinivas|Dokholyan, Nikolay V', 'Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, NC 27599-7260, USA.|Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, NC 27599-7260, USA.|Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, NC 27599-7260, USA.|Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, NC 27599-7260, USA.', 'United States|United States|United States|United States', 27, 'Models, Molecular|Protein Conformation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btr374', '21700672', 'Increasing use of structural modeling for understanding structure-function relationships in proteins has led to the need to ensure that the protein models being used are of acceptable quality. Quality of a given protein structure can be assessed by comparing various intrinsic structural properties of the protein to those observed in high-resolution protein structures.'),
(76343, 2011, 'bio', 'A rank-based statistical test for measuring synergistic effects between two gene sets', 'Shiraishi, Yuichi|Okada-Hatakeyama, Mariko|Miyano, Satoru', 'Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan. yshira@hgc.jp|Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan. yshira@hgc.jp|Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan. yshira@hgc.jp', 'Japan|Japan|Japan', 3, 'Binding Sites|Breast Neoplasms|Cell Line, Tumor|Female|Gene Expression|Genomics|Histones|Humans|Markov Chains|Models, Statistical|Monte Carlo Method|Nucleotide Motifs|Promoter Regions, Genetic|Statistics, Nonparametric|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr382', '21700673', 'Due to recent advances in high-throughput technologies, data on various types of genomic annotation have accumulated. These data will be crucially helpful for elucidating the combinatorial logic of transcription. Although several approaches have been proposed for inferring cooperativity among multiple factors, most approaches are haunted by the issues of normalization and threshold values.'),
(76344, 2011, 'bio', 'UCHIME improves sensitivity and speed of chimera detection', 'Edgar, Robert C|Haas, Brian J|Clemente, Jose C|Quince, Christopher|Knight, Rob', 'Tiburon, CA, USA. robert@drive5.com|Tiburon, CA, USA. robert@drive5.com|Tiburon, CA, USA. robert@drive5.com|Tiburon, CA, USA. robert@drive5.com|Tiburon, CA, USA. robert@drive5.com', 'United States|United States|United States|United States|United States', 7097, 'Algorithms|Artifacts|Computational Biology|Polymerase Chain Reaction|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/btr381', '21700674', 'Chimeric DNA sequences often form during polymerase chain reaction amplification, especially when sequencing single regions (e.g. 16S rRNA or fungal Internal Transcribed Spacer) to assess diversity or compare populations. Undetected chimeras may be misinterpreted as novel species, causing inflated estimates of diversity and spurious inferences of differences between populations. Detection and removal of chimeras is therefore of critical importance in such experiments.'),
(76345, 2011, 'bio', 'KEGGtranslator: visualizing and converting the KEGG PATHWAY database to various formats', 'Wrzodek, Clemens|Dräger, Andreas|Zell, Andreas', 'Center for Bioinformatics Tuebingen, University of Tuebingen, 72076 Tübingen, Germany. clemens.wrzodek@uni-tuebingen.de|Center for Bioinformatics Tuebingen, University of Tuebingen, 72076 Tübingen, Germany. clemens.wrzodek@uni-tuebingen.de|Center for Bioinformatics Tuebingen, University of Tuebingen, 72076 Tübingen, Germany. clemens.wrzodek@uni-tuebingen.de', 'Germany|Germany|Germany', 39, 'Algorithms|Computer Graphics|Databases, Factual|Metabolic Networks and Pathways|Software', 'Journal Article', '10.1093/bioinformatics/btr377', '21700675', 'The KEGG PATHWAY database provides a widely used service for metabolic and nonmetabolic pathways. It contains manually drawn pathway maps with information about the genes, reactions and relations contained therein. To store these pathways, KEGG uses KGML, a proprietary XML-format. Parsers and translators are needed to process the pathway maps for usage in other applications and algorithms. We have developed KEGGtranslator, an easy-to-use stand-alone application that can visualize and convert KGML formatted XML-files into multiple output formats. Unlike other translators, KEGGtranslator supports a plethora of output formats, is able to augment the information in translated documents (e.g. MIRIAM annotations) beyond the scope of the KGML document, and amends missing components to fragmentary reactions within the pathway to allow simulations on those.'),
(76346, 2011, 'bio', 'ODORactor: a web server for deciphering olfactory coding', 'Liu, Xinyi|Su, Xubo|Wang, Fei|Huang, Zhimin|Wang, Qi|Li, Zhen|Zhang, Ruina|Wu, Lifang|Pan, Yi|Chen, Yingyi|Zhuang, Hanyi|Chen, Guoqiang|Shi, Ting|Zhang, Jian', 'Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.|Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.|Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.|Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.|Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.|Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.|Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.|Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.|Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.|Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.|Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.|Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.|Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.|Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.', 'China|China|China|China|China|China|China|China|China|China|China|China|China|China', 0, 'Animals|Humans|Internet|Ligands|Mice|Odorants|Receptors, Odorant|Smell|Software', 'Journal Article', '10.1093/bioinformatics/btr385', '21700676', 'ODORactor is an open access web server aimed at providing a platform for identifying odorant receptors (ORs) for small molecules and for browsing existing OR-ligand pairs. It enables the prediction of ORs from the molecular structures of arbitrary chemicals by integrating two individual functionalities: odorant verification and OR recognition. The prediction of the ORs for several odorants was experimentally validated in the study. In addition, ODORactor features a comprehensive repertoire of olfactory information that has been manually curated from literature. Therefore, ODORactor may provide an effective way to decipher olfactory coding and could be a useful server tool for both basic olfaction research in academia and for odorant discovery in industry.'),
(76347, 2011, 'bio', 'Enriching targeted sequencing experiments for rare disease alleles', 'Edwards, Todd L|Song, Zhuo|Li, Chun', 'Vanderbilt Epidemiology Center, Division of Epidemiology, Department of Medicine, Vanderbilt University, Nashville, TN 37203, USA.|Vanderbilt Epidemiology Center, Division of Epidemiology, Department of Medicine, Vanderbilt University, Nashville, TN 37203, USA.|Vanderbilt Epidemiology Center, Division of Epidemiology, Department of Medicine, Vanderbilt University, Nashville, TN 37203, USA.', 'United States|United States|United States', 6, 'Algorithms|Alleles|Base Sequence|Computational Biology|Computer Simulation|Genome|Genome-Wide Association Study|Genotype|Humans|Polymorphism, Single Nucleotide|Probability|Rare Diseases|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr324', '21700677', 'Next-generation targeted resequencing of genome-wide association study (GWAS)-associated genomic regions is a common approach for follow-up of indirect association of common alleles. However, it is prohibitively expensive to sequence all the samples from a well-powered GWAS study with sufficient depth of coverage to accurately call rare genotypes. As a result, many studies may use next-generation sequencing for single nucleotide polymorphism (SNP) discovery in a smaller number of samples, with the intent to genotype candidate SNPs with rare alleles captured by resequencing. This approach is reasonable, but may be inefficient for rare alleles if samples are not carefully selected for the resequencing experiment.'),
(76348, 2011, 'bio', 'In silico analysis of phytoene synthase and its promoter reveals hints for regulation mechanisms of carotenogenesis in Duanliella bardawil', 'Lao, Yong-Min|Xiao, Lan|Ye, Zhi-Wei|Jiang, Jian-Guo|Zhou, Shi-Shui', 'College of Food and Bioengineering, South China University of Technology, Guangzhou, 510640, China.|College of Food and Bioengineering, South China University of Technology, Guangzhou, 510640, China.|College of Food and Bioengineering, South China University of Technology, Guangzhou, 510640, China.|College of Food and Bioengineering, South China University of Technology, Guangzhou, 510640, China.|College of Food and Bioengineering, South China University of Technology, Guangzhou, 510640, China.', 'China|China|China|China|China', 0, 'Alkyl and Aryl Transferases|Amino Acid Sequence|Carotenoids|Chlorophyta|DNA, Complementary|Gene Expression Regulation, Plant|Geranylgeranyl-Diphosphate Geranylgeranyltransferase|Molecular Sequence Data|Phylogeny|Plant Proteins|Promoter Regions, Genetic|Reverse Transcriptase Polymerase Chain Reaction|Terminator Regions, Genetic', 'Journal Article', '10.1093/bioinformatics/btr371', '21712245', 'Previous researches showed that phytoene synthase (Psy) from Dunaliella bardawil is the first regulatory point in carotenogenesis. We hypothesize certain interactions between the environmental stress factors and the regulatory sequences of Psy in D.bardawil (DbPsy). Consequently, LA PCR-based genomic walking approach was performed for isolation of psy promoter and terminator, respectively. The obtained nucleic acid sequences and the corresponding protein structure of DbPsy were analyzed and predicted using various bioinformatics tools. Finally, we presented some hints for the regulation mechanisms of DbPsy at the molecular level according to the computed results.'),
(76349, 2011, 'bio', 'CAMPAIGN: an open-source library of GPU-accelerated data clustering algorithms', 'Kohlhoff, Kai J|Sosnick, Marc H|Hsu, William T|Pande, Vijay S|Altman, Russ B', 'Department of Bioengineering, Stanford University, Stanford, CA 94305-5448, USA. kjk33@cantab.net|Department of Bioengineering, Stanford University, Stanford, CA 94305-5448, USA. kjk33@cantab.net|Department of Bioengineering, Stanford University, Stanford, CA 94305-5448, USA. kjk33@cantab.net|Department of Bioengineering, Stanford University, Stanford, CA 94305-5448, USA. kjk33@cantab.net|Department of Bioengineering, Stanford University, Stanford, CA 94305-5448, USA. kjk33@cantab.net', 'United States|United States|United States|United States|United States', 16, 'Algorithms|Cluster Analysis|Computer Graphics|Humans|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btr386', '21712246', 'Data clustering techniques are an essential component of a good data analysis toolbox. Many current bioinformatics applications are inherently compute-intense and work with very large datasets. Sequential algorithms are inadequate for providing the necessary performance. For this reason, we have created Clustering Algorithms for Massively Parallel Architectures, Including GPU Nodes (CAMPAIGN), a central resource for data clustering algorithms and tools that are implemented specifically for execution on massively parallel processing architectures.'),
(76350, 2011, 'bio', 'MetATT: a web-based metabolomics tool for analyzing time-series and two-factor datasets', 'Xia, Jianguo|Sinelnikov, Igor V|Wishart, David S', 'Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada. jianguox@ualberta.ca|Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada. jianguox@ualberta.ca|Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada. jianguox@ualberta.ca', 'Canada|Canada|Canada', 40, 'Bayes Theorem|Computer Graphics|Internet|Metabolomics|Software|Time Factors', 'Journal Article', '10.1093/bioinformatics/btr392', '21712247', 'Time-series and multifactor studies have become increasingly common in metabolomic studies. Common tasks for analyzing data from these relatively complex experiments include identification of major variations associated with each experimental factor, comparison of temporal profiles across different biological conditions, as well as detection and validation of the presence of interactions. Here we introduce MetATT, a web-based tool for time-series and two-factor metabolomic data analysis. MetATT offers a number of complementary approaches including 3D interactive principal component analysis, two-way heatmap visualization, two-way ANOVA, ANOVA-simultaneous component analysis and multivariate empirical Bayes time-series analysis. These procedures are presented through an intuitive web interface. At the end of each session, a detailed analysis report is generated to facilitate understanding of the results.'),
(76351, 2011, 'bio', 'BRISK--research-oriented storage kit for biology-related data', 'Tan, Alan|Tripp, Ben|Daley, Denise', 'James Hogg iCAPTURE Center, Department of Medicine, University of British Columbia, Vancouver, BC, Canada V6Z1Y6.|James Hogg iCAPTURE Center, Department of Medicine, University of British Columbia, Vancouver, BC, Canada V6Z1Y6.|James Hogg iCAPTURE Center, Department of Medicine, University of British Columbia, Vancouver, BC, Canada V6Z1Y6.', 'Canada|Canada|Canada', 14, 'Cooperative Behavior|Database Management Systems|Genome-Wide Association Study|Genomics|Information Dissemination|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btr389', '21712248', 'In genetic science, large-scale international research collaborations represent a growing trend. These collaborations have demanding and challenging database, storage, retrieval and communication needs. These studies typically involve demographic and clinical data, in addition to the results from numerous genomic studies (omics studies) such as gene expression, eQTL, genome-wide association and methylation studies, which present numerous challenges, thus the need for data integration platforms that can handle these complex data structures. Inefficient methods of data transfer and access control still plague research collaboration. As science becomes more and more collaborative in nature, the need for a system that adequately manages data sharing becomes paramount.'),
(76352, 2011, 'bio', 'CytoscapeRPC: a plugin to create, modify and query Cytoscape networks from scripting languages', 'Bot, Jan J|Reinders, Marcel J T', 'Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands. j.j.bot@tudelft.nl|Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands. j.j.bot@tudelft.nl', 'Netherlands|Netherlands', 7, 'Computer Graphics|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/btr388', '21712249', 'CytoscapeRPC is a plugin for Cytoscape which allows users to create, query and modify Cytoscape networks from any programming language which supports XML-RPC. This enables them to access Cytoscape functionality and visualize their data interactively without leaving the programming environment with which they are familiar.'),
(76353, 2011, 'bio', 'Integration and visualization of host-pathogen data related to infectious diseases', 'Driscoll, Timothy|Gabbard, Joseph L|Mao, Chunhong|Dalay, Oral|Shukla, Maulik|Freifeld, Clark C|Hoen, Anne Gatewood|Brownstein, John S|Sobral, Bruno W', 'Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 13, 'Bacteria|Bacterial Infections|Communicable Diseases|Computational Biology|Computer Graphics|Databases, Factual|Host-Pathogen Interactions|Humans|Software|Systems Integration|Virulence', 'Journal Article', '10.1093/bioinformatics/btr391', '21712250', 'Infectious disease research is generating an increasing amount of disparate data on pathogenic systems. There is a growing need for resources that effectively integrate, analyze, deliver and visualize these data, both to improve our understanding of infectious diseases and to facilitate the development of strategies for disease control and prevention.'),
(76354, 2011, 'bio', 'Paired-end RAD-seq for de novo assembly and marker design without available reference', 'Willing, Eva-Maria|Hoffmann, Margarete|Klein, Juliane D|Weigel, Detlef|Dreyer, Christine', 'Department of Molecular Biology, Max Planck Institute for Developmental Biology, University of Tübingen, Sand 14, 72076 Tübingen, Germany.|Department of Molecular Biology, Max Planck Institute for Developmental Biology, University of Tübingen, Sand 14, 72076 Tübingen, Germany.|Department of Molecular Biology, Max Planck Institute for Developmental Biology, University of Tübingen, Sand 14, 72076 Tübingen, Germany.|Department of Molecular Biology, Max Planck Institute for Developmental Biology, University of Tübingen, Sand 14, 72076 Tübingen, Germany.|Department of Molecular Biology, Max Planck Institute for Developmental Biology, University of Tübingen, Sand 14, 72076 Tübingen, Germany.', 'Germany|Germany|Germany|Germany|Germany', 69, 'Animals|Chromosome Mapping|Female|Genetic Markers|Genome|Male|Poecilia|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btr346', '21712251', 'Next-generation sequencing technologies have facilitated the study of organisms on a genome-wide scale. A recent method called restriction site associated DNA sequencing (RAD-seq) allows to sample sequence information at reduced complexity across a target genome using the Illumina platform. Single-end RAD-seq has proven to provide a large number of informative genetic markers in reference as well as non-reference organisms.'),
(76355, 2011, 'bio', 'Improving the prediction of disulfide bonds in Eukaryotes with machine learning methods and protein subcellular localization', 'Savojardo, Castrense|Fariselli, Piero|Alhamdoosh, Monther|Martelli, Pier Luigi|Pierleoni, Andrea|Casadio, Rita', 'Biocomputing Group, University of Bologna, CIRI-Life Science and Health Technologies and Department of Biology, Via San Giacomo 9/2, Bologna, Italy.|Biocomputing Group, University of Bologna, CIRI-Life Science and Health Technologies and Department of Biology, Via San Giacomo 9/2, Bologna, Italy.|Biocomputing Group, University of Bologna, CIRI-Life Science and Health Technologies and Department of Biology, Via San Giacomo 9/2, Bologna, Italy.|Biocomputing Group, University of Bologna, CIRI-Life Science and Health Technologies and Department of Biology, Via San Giacomo 9/2, Bologna, Italy.|Biocomputing Group, University of Bologna, CIRI-Life Science and Health Technologies and Department of Biology, Via San Giacomo 9/2, Bologna, Italy.|Biocomputing Group, University of Bologna, CIRI-Life Science and Health Technologies and Department of Biology, Via San Giacomo 9/2, Bologna, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy', 31, 'Artificial Intelligence|Cysteine|Disulfides|Eukaryota|Proteins', 'Journal Article', '10.1093/bioinformatics/btr387', '21715467', 'Disulfide bonds stabilize protein structures and play relevant roles in their functions. Their formation requires an oxidizing environment and their stability is consequently depending on the redox ambient potential, which may differ according to the subcellular compartment. Several methods are available to predict cysteine-bonding state and connectivity patterns. However, none of them takes into consideration the relevance of protein subcellular localization.'),
(76356, 2011, 'bio', 'Tissue-specific prediction of directly regulated genes', 'McLeay, Robert C|Leat, Chris J|Bailey, Timothy L', 'Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia.', 'Australia|Australia|Australia', 4, 'Bayes Theorem|Binding Sites|Chromatin Immunoprecipitation|Gene Expression Regulation|Promoter Regions, Genetic|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr399', '21724591', 'Direct binding by a transcription factor (TF) to the proximal promoter of a gene is a strong evidence that the TF regulates the gene. Assaying the genome-wide binding of every TF in every cell type and condition is currently impractical. Histone modifications correlate with tissue/cell/condition-specific (tissue specific) TF binding, so histone ChIP-seq data can be combined with traditional position weight matrix (PWM) methods to make tissue-specific predictions of TF-promoter interactions.'),
(76357, 2011, 'bio', 'Computational reconstruction of primordial prototypes of elementary functional loops in modern proteins', 'Goncearenco, Alexander|Berezovsky, Igor N', 'Computational Biology Unit, Uni Research, University of Bergen, N-5008 Bergen, Norway.|Computational Biology Unit, Uni Research, University of Bergen, N-5008 Bergen, Norway.', 'Norway|Norway', 11, 'Computational Biology|Cysteine|Enzymes|Evolution, Molecular|Metalloproteins|Proteomics|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btr396', '21724592', 'Enzymes are complex catalytic machines, which perform sequences of elementary chemical transformations resulting in biochemical function. The building blocks of enzymes, elementary functional loops (EFLs), possess distinct functional signatures and provide catalytic and binding amino acids to the enzymes active sites. The goal of this work is to obtain primordial prototypes of EFLs that existed before the formation of enzymatic domains and served as their building blocks.'),
(76358, 2011, 'bio', 'TotalReCaller: improved accuracy and performance via integrated alignment and base-calling', 'Menges, Fabian|Narzisi, Giuseppe|Mishra, Bud', 'Computer Science Department, Courant Institute, New York University, NY 10012, USA. fabian.menges@nyu.edu|Computer Science Department, Courant Institute, New York University, NY 10012, USA. fabian.menges@nyu.edu|Computer Science Department, Courant Institute, New York University, NY 10012, USA. fabian.menges@nyu.edu', 'United States|United States|United States', 5, 'Algorithms|Bayes Theorem|Genomics|High-Throughput Nucleotide Sequencing|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/btr393', '21724593', 'Currently, re-sequencing approaches use multiple modules serially to interpret raw sequencing data from next-generation sequencing platforms, while remaining oblivious to the genomic information until the final alignment step. Such approaches fail to exploit the full information from both raw sequencing data and the reference genome that can yield better quality sequence reads, SNP-calls, variant detection, as well as an alignment at the best possible location in the reference genome. Thus, there is a need for novel reference-guided bioinformatics algorithms for interpreting analog signals representing sequences of the bases ({A, C, G, T}), while simultaneously aligning possible sequence reads to a source reference genome whenever available.'),
(76359, 2011, 'bio', 'MethylCoder: software pipeline for bisulfite-treated sequences', 'Pedersen, Brent|Hsieh, Tzung-Fu|Ibarra, Christian|Fischer, Robert L', 'Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA. bpederse@gmail.com|Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA. bpederse@gmail.com|Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA. bpederse@gmail.com|Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA. bpederse@gmail.com', 'United States|United States|United States|United States', 48, 'Cytosine|DNA|DNA Methylation|Genomics|Sequence Alignment|Sequence Analysis, DNA|Software|Sulfites', 'Journal Article', '10.1093/bioinformatics/btr394', '21724594', 'MethylCoder is a software program that generates per-base methylation data given a set of bisulfite-treated reads. It provides the option to use either of two existing short-read aligners, each with different strengths. It accounts for soft-masked alignments and overlapping paired-end reads. MethylCoder outputs data in text and binary formats in addition to the final alignment in SAM format, so that common high-throughput sequencing tools can be used on the resulting output. It is more flexible than existing software and competitive in terms of speed and memory use.'),
(76360, 2011, 'bio', 'StochKit2: software for discrete stochastic simulation of biochemical systems with events', 'Sanft, Kevin R|Wu, Sheng|Roh, Min|Fu, Jin|Lim, Rone Kwei|Petzold, Linda R', 'Department of Computer Science, University of California Santa Barbara, Santa Barbara, CA 93106, USA.|Department of Computer Science, University of California Santa Barbara, Santa Barbara, CA 93106, USA.|Department of Computer Science, University of California Santa Barbara, Santa Barbara, CA 93106, USA.|Department of Computer Science, University of California Santa Barbara, Santa Barbara, CA 93106, USA.|Department of Computer Science, University of California Santa Barbara, Santa Barbara, CA 93106, USA.|Department of Computer Science, University of California Santa Barbara, Santa Barbara, CA 93106, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Biochemical Phenomena|Computer Simulation|Models, Biological|Software|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/btr401', '21727139', 'StochKit2 is the first major upgrade of the popular StochKit stochastic simulation software package. StochKit2 provides highly efficient implementations of several variants of Gillespies stochastic simulation algorithm (SSA), and tau-leaping with automatic step size selection. StochKit2 features include automatic selection of the optimal SSA method based on model properties, event handling, and automatic parallelism on multicore architectures. The underlying structure of the code has been completely updated to provide a flexible framework for extending its functionality.'),
(76361, 2011, 'bio', 'ModeRNA server: an online tool for modeling RNA 3D structures', 'Rother, Magdalena|Milanowska, Kaja|Puton, Tomasz|Jeleniewicz, Jaroslaw|Rother, Kristian|Bujnicki, Janusz M', 'Faculty of Biology, Adam Mickiewicz University, ul. Umultowska 89, 61-614 Poznan, Poland.|Faculty of Biology, Adam Mickiewicz University, ul. Umultowska 89, 61-614 Poznan, Poland.|Faculty of Biology, Adam Mickiewicz University, ul. Umultowska 89, 61-614 Poznan, Poland.|Faculty of Biology, Adam Mickiewicz University, ul. Umultowska 89, 61-614 Poznan, Poland.|Faculty of Biology, Adam Mickiewicz University, ul. Umultowska 89, 61-614 Poznan, Poland.|Faculty of Biology, Adam Mickiewicz University, ul. Umultowska 89, 61-614 Poznan, Poland.', 'Poland|Poland|Poland|Poland|Poland|Poland', 32, 'Internet|Models, Molecular|Nucleic Acid Conformation|RNA|RNA, Untranslated|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btr400', '21727140', 'The diverse functional roles of non-coding RNA molecules are determined by their underlying structure. ModeRNA server is an online tool for RNA 3D structure modeling by the comparative approach, based on a template RNA structure and a user-defined target-template sequence alignment. It offers an option to search for potential templates, given the target sequence. The server also provides tools for analyzing, editing and formatting of RNA structure files. It facilitates the use of the ModeRNA software and offers new options in comparison to the standalone program.'),
(76362, 2011, 'bio', 'Simple Neurite Tracer: open source software for reconstruction, visualization and analysis of neuronal processes', 'Longair, Mark H|Baker, Dean A|Armstrong, J Douglas', 'Institute of Neuroinformatics, Uni/ETH Zürich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland. longair@ini.phys.ethz.ch|Institute of Neuroinformatics, Uni/ETH Zürich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland. longair@ini.phys.ethz.ch|Institute of Neuroinformatics, Uni/ETH Zürich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland. longair@ini.phys.ethz.ch', 'Switzerland|Switzerland|Switzerland', 0, 'Animals|Computer Graphics|Humans|Image Processing, Computer-Assisted|Imaging, Three-Dimensional|Neurites|Neurons|Software', 'Journal Article', '10.1093/bioinformatics/btr390', '21727141', 'Advances in techniques to sparsely label neurons unlock the potential to reconstruct connectivity from 3D image stacks acquired by light microscopy. We present an application for semi-automated tracing of neurons to quickly annotate noisy datasets and construct complex neuronal topologies, which we call the Simple Neurite Tracer.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76363, 2011, 'bio', 'A statistical framework for biomarker discovery in metabolomic time course data', 'Berk, Maurice|Ebbels, Timothy|Montana, Giovanni', 'Statistics Section, Department of Mathematics, Imperial College London, Huxley Building, South Kensington, London SW7 2AZ, UK.|Statistics Section, Department of Mathematics, Imperial College London, Huxley Building, South Kensington, London SW7 2AZ, UK.|Statistics Section, Department of Mathematics, Imperial College London, Huxley Building, South Kensington, London SW7 2AZ, UK.', 'United Kingdom|United Kingdom|United Kingdom', 28, 'Animals|Biomarkers|Biometry|Databases as Topic|Magnetic Resonance Spectroscopy|Metabolome|Metabolomics|Models, Biological|Rats|Software', 'Journal Article', '10.1093/bioinformatics/btr289', '21729866', 'Metabolomics is the study of the complement of small molecule metabolites in cells, biofluids and tissues. Many metabolomic experiments are designed to compare changes observed over time under two experimental conditions or groups (e.g. a control and drug-treated group) with the goal of identifying discriminatory metabolites or biomarkers that characterize each condition. A common study design consists of repeated measurements taken on each experimental unit thus producing time courses of all metabolites. We describe a statistical framework for estimating time-varying metabolic profiles and their within-group variability and for detecting between-group differences. Specifically, we propose (i) a smoothing splines mixed effects (SME) model that treats each longitudinal measurement as a smooth function of time and (ii) an associated functional test statistic. Statistical significance is assessed by a non-parametric bootstrap procedure.'),
(76364, 2011, 'bio', 'spacodiR: structuring of phylogenetic diversity in ecological communities', 'Eastman, Jonathan M|Paine, C E Timothy|Hardy, Olivier J', 'Department of Biological Sciences, University of Idaho, Moscow, Idaho, USA. jonathan.eastman@gmail.com|Department of Biological Sciences, University of Idaho, Moscow, Idaho, USA. jonathan.eastman@gmail.com|Department of Biological Sciences, University of Idaho, Moscow, Idaho, USA. jonathan.eastman@gmail.com', 'United States|United States|United States', 0, 'Biota|Data Interpretation, Statistical|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btr403', '21737436', 'spacodiR is a cross-platform package, written for the R environment, for studying partitioning of diversity among natural communities in space and time. Complementing and extending existing software, spacodiR allows for hypothesis testing and parameter estimation in studying spatial structuring of species-, phylogenetic- and trait diversities.'),
(76365, 2011, 'bio', 'APCluster: an R package for affinity propagation clustering', 'Bodenhofer, Ulrich|Kothmeier, Andreas|Hochreiter, Sepp', 'Institute of Bioinformatics, Johannes Kepler University, Linz, Austria. apcluster@bioinf.jku.at|Institute of Bioinformatics, Johannes Kepler University, Linz, Austria. apcluster@bioinf.jku.at|Institute of Bioinformatics, Johannes Kepler University, Linz, Austria. apcluster@bioinf.jku.at', 'Austria|Austria|Austria', 195, 'Algorithms|Amino Acid Motifs|Cluster Analysis|Computational Biology|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btr406', '21737437', 'Affinity propagation (AP) clustering has recently gained increasing popularity in bioinformatics. AP clustering has the advantage that it allows for determining typical cluster members, the so-called exemplars. We provide an R implementation of this promising new clustering technique to account for the ubiquity of R in bioinformatics. This article introduces the package and presents an application from structural biology.'),
(76366, 2011, 'bio', 'Simulating systems genetics data with SysGenSIM', 'Pinna, Andrea|Soranzo, Nicola|Hoeschele, Ina|de la Fuente, Alberto', 'CRS4 Bioinformatica, 09010 Pula (CA), Italy.|CRS4 Bioinformatica, 09010 Pula (CA), Italy.|CRS4 Bioinformatica, 09010 Pula (CA), Italy.|CRS4 Bioinformatica, 09010 Pula (CA), Italy.', 'Italy|Italy|Italy|Italy', 0, 'Computer Simulation|Gene Expression|Gene Regulatory Networks|Genotype|Phenotype|Software', 'Journal Article', '10.1093/bioinformatics/btr407', '21737438', 'SysGenSIM is a software package to simulate Systems Genetics (SG) experiments in model organisms, for the purpose of evaluating and comparing statistical and computational methods and their implementations for analyses of SG data [e.g. methods for expression quantitative trait loci (eQTL) mapping and network inference]. SysGenSIM allows the user to select a variety of network topologies, genetic and kinetic parameters to simulate SG data ( genotyping, gene expression and phenotyping) with large gene networks with thousands of nodes. The software is encoded in MATLAB, and a user-friendly graphical user interface is provided.'),
(76367, 2011, 'bio', 'The Cardiac Atlas Project--an imaging database for computational modeling and statistical atlases of the heart', 'Fonseca, Carissa G|Backhaus, Michael|Bluemke, David A|Britten, Randall D|Chung, Jae Do|Cowan, Brett R|Dinov, Ivo D|Finn, J Paul|Hunter, Peter J|Kadish, Alan H|Lee, Daniel C|Lima, Joao A C|Medrano-Gracia, Pau|Shivkumar, Kalyanam|Suinesiaputra, Avan|Tao, Wenchao|Young, Alistair A', 'Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA.|Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA.|Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA.|Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA.|Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA.|Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA.|Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA.|Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA.|Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA.|Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA.|Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA.|Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA.|Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA.|Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA.|Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA.|Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA.|Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 162, 'Aged|Aged, 80 and over|Atlases as Topic|Cardiovascular Diseases|Computational Biology|Databases, Factual|Diagnostic Imaging|Female|Heart|Humans|Magnetic Resonance Imaging, Cine|Male|Middle Aged|Models, Cardiovascular|Models, Statistical|Myocardium|Software', 'Journal Article', '10.1093/bioinformatics/btr360', '21737439', 'Integrative mathematical and statistical models of cardiac anatomy and physiology can play a vital role in understanding cardiac disease phenotype and planning therapeutic strategies. However, the accuracy and predictive power of such models is dependent upon the breadth and depth of noninvasive imaging datasets. The Cardiac Atlas Project (CAP) has established a large-scale database of cardiac imaging examinations and associated clinical data in order to develop a shareable, web-accessible, structural and functional atlas of the normal and pathological heart for clinical, research and educational purposes. A goal of CAP is to facilitate collaborative statistical analysis of regional heart shape and wall motion and characterize cardiac function among and within population groups.'),
(76368, 2011, 'bio', 'PREDA: an R-package to identify regional variations in genomic data', 'Ferrari, Francesco|Solari, Aldo|Battaglia, Cristina|Bicciato, Silvio', 'Department of Biomedical Sciences, Center for Genome Research, University of Modena and Reggio Emilia, Modena, Italy.|Department of Biomedical Sciences, Center for Genome Research, University of Modena and Reggio Emilia, Modena, Italy.|Department of Biomedical Sciences, Center for Genome Research, University of Modena and Reggio Emilia, Modena, Italy.|Department of Biomedical Sciences, Center for Genome Research, University of Modena and Reggio Emilia, Modena, Italy.', 'Italy|Italy|Italy|Italy', 0, 'Genetic Variation|Genomics|Software', 'Journal Article', '10.1093/bioinformatics/btr404', '21742634', 'Chromosomal patterns of genomic signals represent molecular fingerprints that may reveal how the local structural organization of a genome impacts the functional control mechanisms. Thus, the integrative analysis of multiple sources of genomic data and information deepens the resolution and enhances the interpretation of stand-alone high-throughput data. In this note, we present PREDA (Position RElated Data Analysis), an R package for detecting regional variations in genomics data. PREDA identifies relevant chromosomal patterns in high-throughput data using a smoothing approach that accounts for distance and density variability of genomics features. Custom-designed data structures allow efficiently managing diverse signals in different genomes. A variety of smoothing functions and statistics empower flexible and robust workflows. The modularity of package design allows an easy deployment of custom analytical pipelines. Tabular and graphical representations facilitate downstream biological interpretation of results.'),
(76369, 2011, 'bio', 'DivBayes and SubT: exploring species diversification using Bayesian statistics', 'Ryberg, Martin|Nilsson, R Henrik|Matheny, P Brandon', 'Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN 37996-1610, USA. kryberg@utk.edu|Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN 37996-1610, USA. kryberg@utk.edu|Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN 37996-1610, USA. kryberg@utk.edu', 'United States|United States|United States', 4, 'Bayes Theorem|Biodiversity|Genetic Speciation|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btr405', '21742635', 'DivBayes is a program to estimate diversification rates from species richness and ages of a set of clades. SubT estimates diversification rates from node heights within a clade. Both programs implement Bayesian statistics and provide the ability to account for uncertainty in the ages of taxa in the underlying data, an improvement over more commonly used maximum likelihood methods.'),
(76370, 2011, 'bio', 'Biologically inspired EM image alignment and neural reconstruction', 'Knowles-Barley, Seymour|Butcher, Nancy J|Meinertzhagen, Ian A|Armstrong, J Douglas', 'School of Informatics, The University of Edinburgh, Edinburgh, UK. seymour.kb@ed.ac.uk|School of Informatics, The University of Edinburgh, Edinburgh, UK. seymour.kb@ed.ac.uk|School of Informatics, The University of Edinburgh, Edinburgh, UK. seymour.kb@ed.ac.uk|School of Informatics, The University of Edinburgh, Edinburgh, UK. seymour.kb@ed.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 6, 'Algorithms|Animals|Cell Membrane|Drosophila|Imaging, Three-Dimensional|Microscopy, Electron, Transmission|Neurons', 'Journal Article', '10.1093/bioinformatics/btr378', '21742636', 'Three-dimensional reconstruction of consecutive serial-section transmission electron microscopy (ssTEM) images of neural tissue currently requires many hours of manual tracing and annotation. Several computational techniques have already been applied to ssTEM images to facilitate 3D reconstruction and ease this burden.'),
(76371, 2011, 'bio', 'Annotation concept synthesis and enrichment analysis: a logic-based approach to the interpretation of high-throughput experiments', 'Jiline, Mikhail|Matwin, Stan|Turcotte, Marcel', 'School of Information Technology and Engineering, University of Ottawa, Ottawa, Ontario, K1N 6N5 Canada. mjiline@site.uottawa.ca|School of Information Technology and Engineering, University of Ottawa, Ottawa, Ontario, K1N 6N5 Canada. mjiline@site.uottawa.ca|School of Information Technology and Engineering, University of Ottawa, Ottawa, Ontario, K1N 6N5 Canada. mjiline@site.uottawa.ca', 'Canada|Canada|Canada', 0, 'Algorithms|Gene Expression Profiling|Genomics|High-Throughput Screening Assays|Molecular Sequence Annotation|Oligonucleotide Array Sequence Analysis|Proteomics', 'Evaluation Studies', '10.1093/bioinformatics/btr337', '21743060', 'Annotation Enrichment Analysis (AEA) is a widely used analytical approach to process data generated by high-throughput genomic and proteomic experiments such as gene expression microarrays. The analysis uncovers and summarizes discriminating background information (e.g. GO annotations) for sets of genes identified by experiments (e.g. a set of differentially expressed genes, a cluster). The discovered information is utilized by human experts to find biological interpretations of the experiments. However, AEA isolates and tests for overrepresentation only individual annotation terms or groups of similar terms and is limited in its ability to uncover complex phenomena involving relationship between multiple annotation terms from various knowledge bases. Also, AEA assumes that annotations describe the whole object of interest, which makes it difficult to apply it to sets of compound objects (e.g. sets of protein-protein interactions) and to sets of objects having an internal structure (e.g. protein complexes).'),
(76372, 2011, 'bio', 'A Lasso regression model for the construction of microRNA-target regulatory networks', 'Lu, Yiming|Zhou, Yang|Qu, Wubin|Deng, Minghua|Zhang, Chenggang', 'Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Beijing 100850, PR China.|Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Beijing 100850, PR China.|Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Beijing 100850, PR China.|Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Beijing 100850, PR China.|Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Beijing 100850, PR China.', 'China|China|China|China|China', 77, 'Gene Expression Regulation|Gene Regulatory Networks|Humans|Linear Models|Male|MicroRNAs|Prostatic Neoplasms|RNA, Messenger', 'Journal Article', '10.1093/bioinformatics/btr410', '21743061', 'MicroRNAs have recently emerged as a major class of regulatory molecules involved in a broad range of biological processes and complex diseases. Construction of miRNA-target regulatory networks can provide useful information for the study and diagnosis of complex diseases. Many sequence-based and evolutionary information-based methods have been developed to identify miRNA-mRNA targeting relationships. However, as the amount of available miRNA and gene expression data grows, a more statistical and systematic method combining sequence-based binding predictions and expression-based correlation data becomes necessary for the accurate identification of miRNA-mRNA pairs.'),
(76373, 2011, 'bio', 'CSO validator: improving manual curation workflow for biological pathways', 'Jeong, Euna|Nagasaki, Masao|Ikeda, Emi|Sekiya, Yayoi|Saito, Ayumu|Miyano, Satoru', 'Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo 108-8639, Japan.|Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo 108-8639, Japan.|Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo 108-8639, Japan.|Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo 108-8639, Japan.|Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo 108-8639, Japan.|Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo 108-8639, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan', 2, 'Databases, Factual|Models, Biological|Software|Vocabulary, Controlled|Workflow', 'Journal Article', '10.1093/bioinformatics/btr395', '21743062', 'Manual curation and validation of large-scale biological pathways are required to obtain high-quality pathway databases. In a typical curation process, model validation and model update based on appropriate feedback are repeated and requires considerable cooperation of scientists. We have developed a CSO (Cell System Ontology) validator to reduce the repetition and time during the curation process. This tool assists in quickly obtaining agreement among curators and domain experts and in providing a consistent and accurate pathway database.'),
(76374, 2011, 'bio', 'A novel signal processing approach for the detection of copy number variations in the human genome', 'Stamoulis, Catherine|Betensky, Rebecca A', 'Department of Radiology, Harvard School of Public Health, Boston, MA 02115, USA. caterina@mit.edu|Department of Radiology, Harvard School of Public Health, Boston, MA 02115, USA. caterina@mit.edu', 'United States|United States', 16, 'DNA Copy Number Variations|Gene Dosage|Genome, Human|Genomics|Humans|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btr402', '21752800', 'Human genomic variability occurs at different scales, from single nucleotide polymorphisms (SNPs) to large DNA segments. Copy number variations (CNVs) represent a significant part of our genetic heterogeneity and have also been associated with many diseases and disorders. Short, localized CNVs, which may play an important role in human disease, may be undetectable in noisy genomic data. Therefore, robust methodologies are needed for their detection. Furthermore, for meaningful identification of pathological CNVs, estimation of normal allelic aberrations is necessary.'),
(76375, 2011, 'bio', 'DECOD: fast and accurate discriminative DNA motif finding', 'Huggins, Peter|Zhong, Shan|Shiff, Idit|Beckerman, Rachel|Laptenko, Oleg|Prives, Carol|Schulz, Marcel H|Simon, Itamar|Bar-Joseph, Ziv', 'Lane Center for Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.|Lane Center for Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.|Lane Center for Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.|Lane Center for Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.|Lane Center for Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.|Lane Center for Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.|Lane Center for Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.|Lane Center for Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.|Lane Center for Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Base Sequence|DNA|Nucleotide Motifs|Sequence Analysis, DNA|Tumor Suppressor Protein p53', 'Journal Article', '10.1093/bioinformatics/btr412', '21752801', 'Motif discovery is now routinely used in high-throughput studies including large-scale sequencing and proteomics. These datasets present new challenges. The first is speed. Many motif discovery methods do not scale well to large datasets. Another issue is identifying discriminative rather than generative motifs. Such discriminative motifs are important for identifying co-factors and for explaining changes in behavior between different conditions.'),
(76376, 2011, 'bio', 'RxnFinder: biochemical reaction search engines using molecular structures, molecular fragments and reaction similarity', 'Hu, Qian-Nan|Deng, Zhe|Hu, Huanan|Cao, Dong-Sheng|Liang, Yi-Zeng', 'Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan University), Ministry of Education, Wuhan University School of Pharmaceutical Sciences, Wuhan 430071, PR China.|Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan University), Ministry of Education, Wuhan University School of Pharmaceutical Sciences, Wuhan 430071, PR China.|Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan University), Ministry of Education, Wuhan University School of Pharmaceutical Sciences, Wuhan 430071, PR China.|Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan University), Ministry of Education, Wuhan University School of Pharmaceutical Sciences, Wuhan 430071, PR China.|Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan University), Ministry of Education, Wuhan University School of Pharmaceutical Sciences, Wuhan 430071, PR China.', 'China|China|China|China|China', 19, 'Biochemical Phenomena|Databases, Factual|Molecular Structure|Search Engine', 'Journal Article', '10.1093/bioinformatics/btr413', '21752802', 'Biochemical reactions play a key role to help sustain life and allow cells to grow. RxnFinder was developed to search biochemical reactions from KEGG reaction database using three search criteria: molecular structures, molecular fragments and reaction similarity. RxnFinder is helpful to get reference reactions for biosynthesis and xenobiotics metabolism.'),
(76377, 2011, 'bio', 'A Grid-enabled web portal for NMR structure refinement with AMBER', 'Bertini, Ivano|Case, David A|Ferella, Lucio|Giachetti, Andrea|Rosato, Antonio', 'Magnetic Resonance Center (CERM), University of Florence, Via L. Sacconi 6, Italy. ivanobertini@cerm.unifi.it|Magnetic Resonance Center (CERM), University of Florence, Via L. Sacconi 6, Italy. ivanobertini@cerm.unifi.it|Magnetic Resonance Center (CERM), University of Florence, Via L. Sacconi 6, Italy. ivanobertini@cerm.unifi.it|Magnetic Resonance Center (CERM), University of Florence, Via L. Sacconi 6, Italy. ivanobertini@cerm.unifi.it|Magnetic Resonance Center (CERM), University of Florence, Via L. Sacconi 6, Italy. ivanobertini@cerm.unifi.it', 'Italy|Italy|Italy|Italy|Italy', 50, 'Internet|Molecular Dynamics Simulation|Nuclear Magnetic Resonance, Biomolecular|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr415', '21757462', 'The typical workflow for NMR structure determination involves collecting thousands of conformational restraints, calculating a bundle of 20-40 conformers in agreement with them and refining the energetics of these conformers. The structure calculation step employs simulated annealing based on molecular dynamics (MD) simulations with very simplified force fields. The value of refining the calculated conformers using restrained MD (rMD) simulations with state-of-art force fields is documented. This refinement however presents various subtleties, from the proper formatting of conformational restraints to the definition of suitable protocols.'),
(76378, 2011, 'bio', 'Sufficient statistics and expectation maximization algorithms in phylogenetic tree models', 'Kiryu, Hisanori', 'Department of Computational Biology, Faculty of Frontier Science, The University of Tokyo, Kashiwa, Chiba 277-8561, Japan. kiryu-h@k.u-tokyo.ac.jp', 'Japan', 3, 'Algorithms|Evolution, Molecular|Genome, Human|Genomics|Humans|Markov Chains|Phylogeny', 'Journal Article', '10.1093/bioinformatics/btr420', '21757463', 'Measuring evolutionary conservation is a routine step in the identification of functional elements in genome sequences. Although a number of studies have proposed methods that use the continuous time Markov models (CTMMs) to find evolutionarily constrained elements, their probabilistic structures have been less frequently investigated.'),
(76379, 2011, 'bio', 'PDBpaint, a visualization webservice to tag protein structures with sequence annotations', 'Fournier, David|Andrade-Navarro, Miguel A', 'Max Delbrück Center for Molecular Medicine, Robert-Rössle-Strasse 10, 13125 Berlin, Germany. david.fournier@mdc-berlin.de|Max Delbrück Center for Molecular Medicine, Robert-Rössle-Strasse 10, 13125 Berlin, Germany. david.fournier@mdc-berlin.de', 'Germany|Germany', 3, 'Amino Acids|Internet|Protein Conformation|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btr419', '21757464', 'Protein features are often displayed along the linear sequence of amino acids that make up that protein, but in reality these features occupy a position in the folded proteins 3D space. Mapping sequence features to known or predicted protein structures is useful when trying to deduce the function of those features and when evaluating sequence or structural predictions. To facilitate this goal, we developed PDBpaint, a simple tool that displays protein sequence features gathered from bioinformatics resources on top of protein structures, which are displayed in an interactive window (using the Jmol Java viewer). PDBpaint can be used either with existing protein structures or with novel structures provided by the user. The current version of PDBpaint allows the visualization of annotations from Pfam, ARD (detection of HEAT-repeats), UniProt, TMHMM2.0 and SignalP. Users can also add other annotations manually.'),
(76380, 2011, 'bio', 'Inferring statin-induced gene regulatory relationships in primary human hepatocytes', 'Schröder, Adrian|Wollnik, Johannes|Wrzodek, Clemens|Dräger, Andreas|Bonin, Michael|Burk, Oliver|Thomas, Maria|Thasler, Wolfgang E|Zanger, Ulrich M|Zell, Andreas', 'Center for Bioinformatics Tuebingen, University of Tuebingen, Tuebingen, Germany. adrian.schroeder@uni-tuebingen.de|Center for Bioinformatics Tuebingen, University of Tuebingen, Tuebingen, Germany. adrian.schroeder@uni-tuebingen.de|Center for Bioinformatics Tuebingen, University of Tuebingen, Tuebingen, Germany. adrian.schroeder@uni-tuebingen.de|Center for Bioinformatics Tuebingen, University of Tuebingen, Tuebingen, Germany. adrian.schroeder@uni-tuebingen.de|Center for Bioinformatics Tuebingen, University of Tuebingen, Tuebingen, Germany. adrian.schroeder@uni-tuebingen.de|Center for Bioinformatics Tuebingen, University of Tuebingen, Tuebingen, Germany. adrian.schroeder@uni-tuebingen.de|Center for Bioinformatics Tuebingen, University of Tuebingen, Tuebingen, Germany. adrian.schroeder@uni-tuebingen.de|Center for Bioinformatics Tuebingen, University of Tuebingen, Tuebingen, Germany. adrian.schroeder@uni-tuebingen.de|Center for Bioinformatics Tuebingen, University of Tuebingen, Tuebingen, Germany. adrian.schroeder@uni-tuebingen.de|Center for Bioinformatics Tuebingen, University of Tuebingen, Tuebingen, Germany. adrian.schroeder@uni-tuebingen.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 15, 'Anticholesteremic Agents|Atorvastatin|Cytochrome P-450 CYP3A|Drug Interactions|Gene Expression Profiling|Gene Expression Regulation|Genes, Regulator|Hepatocytes|Heptanoic Acids|Humans|Hydroxymethylglutaryl CoA Reductases|Hydroxymethylglutaryl-CoA Reductase Inhibitors|Liver|Molecular Sequence Data|Protein Binding|Pyrroles|RNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr416', '21757465', 'Statins are the most widely used cholesterol-lowering drugs. The primary target of statins is HMG-CoA reductase, a key enzyme in cholesterol synthesis. However, statins elicit pleitropic responses including beneficial as well as adverse effects in the liver or other organs. Today, the regulatory mechanisms that cause these pleiotropic effects are not sufficiently understood.'),
(76381, 2011, 'bio', 'NASP: a parallel program for identifying evolutionarily conserved nucleic acid secondary structures from nucleotide sequence alignments', 'Semegni, J Y|Wamalwa, M|Gaujoux, R|Harkins, G W|Gray, A|Martin, D P', 'Computational Biology Group, Department of Clinical Laboratory Sciences, IIDMM, University of Cape Town, Observatory, Cape Town, South Africa. yves@cbio.uct.ac.za|Computational Biology Group, Department of Clinical Laboratory Sciences, IIDMM, University of Cape Town, Observatory, Cape Town, South Africa. yves@cbio.uct.ac.za|Computational Biology Group, Department of Clinical Laboratory Sciences, IIDMM, University of Cape Town, Observatory, Cape Town, South Africa. yves@cbio.uct.ac.za|Computational Biology Group, Department of Clinical Laboratory Sciences, IIDMM, University of Cape Town, Observatory, Cape Town, South Africa. yves@cbio.uct.ac.za|Computational Biology Group, Department of Clinical Laboratory Sciences, IIDMM, University of Cape Town, Observatory, Cape Town, South Africa. yves@cbio.uct.ac.za|Computational Biology Group, Department of Clinical Laboratory Sciences, IIDMM, University of Cape Town, Observatory, Cape Town, South Africa. yves@cbio.uct.ac.za', 'South Africa|South Africa|South Africa|South Africa|South Africa|South Africa', 6, 'DNA|Evolution, Molecular|Nucleic Acid Conformation|Nucleotides|RNA|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btr417', '21757466', 'Many natural nucleic acid sequences have evolutionarily conserved secondary structures with diverse biological functions. A reliable computational tool for identifying such structures would be very useful in guiding experimental analyses of their biological functions. NASP (Nucleic Acid Structure Predictor) is a program that takes into account thermodynamic stability, Boltzmann base pair probabilities, alignment uncertainty, covarying sites and evolutionary conservation to identify biologically relevant secondary structures within multiple sequence alignments. Unique to NASP is the consideration of all this information together with a recursive permutation-based approach to progressively identify and list the most conserved probable secondary structures that are likely to have the greatest biological relevance. By focusing on identifying only evolutionarily conserved structures, NASP forgoes the prediction of complete nucleotide folds but outperforms various other secondary structure prediction methods in its ability to selectively identify actual base pairings.'),
(76382, 2011, 'bio', 'Elemental composition determination based on MS(n)', 'Rojas-Chertó, Miguel|Kasper, Piotr T|Willighagen, Egon L|Vreeken, Rob J|Hankemeier, Thomas|Reijmers, Theo H', 'Netherlands Metabolomics Centre, Leiden/Amsterdam Center for Drug Research, Leiden, The Netherlands. m.rojas@lacdr.leidenuniv.nl|Netherlands Metabolomics Centre, Leiden/Amsterdam Center for Drug Research, Leiden, The Netherlands. m.rojas@lacdr.leidenuniv.nl|Netherlands Metabolomics Centre, Leiden/Amsterdam Center for Drug Research, Leiden, The Netherlands. m.rojas@lacdr.leidenuniv.nl|Netherlands Metabolomics Centre, Leiden/Amsterdam Center for Drug Research, Leiden, The Netherlands. m.rojas@lacdr.leidenuniv.nl|Netherlands Metabolomics Centre, Leiden/Amsterdam Center for Drug Research, Leiden, The Netherlands. m.rojas@lacdr.leidenuniv.nl|Netherlands Metabolomics Centre, Leiden/Amsterdam Center for Drug Research, Leiden, The Netherlands. m.rojas@lacdr.leidenuniv.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 51, 'Algorithms|Ions|Mass Spectrometry|Metabolomics|Software', 'Journal Article', '10.1093/bioinformatics/btr409', '21757467', 'Identification of metabolites is essential for its use as biomarkers, for research in systems biology and for drug discovery. The first step before a structure can be elucidated is to determine its elemental composition. High-resolution mass spectrometry, which provides the exact mass, together with common constraint rules, for rejecting false proposed elemental compositions, cannot always provide one unique elemental composition solution.'),
(76383, 2011, 'bio', 'IRiS: construction of ARG networks at genomic scales', 'Javed, Asif|Pybus, Marc|Melé, Marta|Utro, Filippo|Bertranpetit, Jaume|Calafell, Francesc|Parida, Laxmi', 'Computational Biology Center, IBM T J Watson Research, Yorktown Heights, NY 10598, USA.|Computational Biology Center, IBM T J Watson Research, Yorktown Heights, NY 10598, USA.|Computational Biology Center, IBM T J Watson Research, Yorktown Heights, NY 10598, USA.|Computational Biology Center, IBM T J Watson Research, Yorktown Heights, NY 10598, USA.|Computational Biology Center, IBM T J Watson Research, Yorktown Heights, NY 10598, USA.|Computational Biology Center, IBM T J Watson Research, Yorktown Heights, NY 10598, USA.|Computational Biology Center, IBM T J Watson Research, Yorktown Heights, NY 10598, USA.', 'United States|United States|United States|United States|United States|United States|United States', 9, 'Algorithms|Genome, Human|Genomics|Haplotypes|Humans|Models, Genetic|Recombination, Genetic|Software', 'Journal Article', '10.1093/bioinformatics/btr423', '21765095', 'Given a set of extant haplotypes IRiS first detects high confidence recombination events in their shared genealogy. Next using the local sequence topology defined by each detected event, it integrates these recombinations into an ancestral recombination graph. While the current system has been calibrated for human population data, it is easily extendible to other species as well.'),
(76384, 2011, 'bio', 'Stage prediction of embryonic stem cell differentiation from genome-wide expression data', 'Zagar, Lan|Mulas, Francesca|Garagna, Silvia|Zuccotti, Maurizio|Bellazzi, Riccardo|Zupan, Blaz', 'Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.|Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.|Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.|Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.|Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.|Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.', 'Slovenia|Slovenia|Slovenia|Slovenia|Slovenia|Slovenia', 14, 'Animals|Cell Differentiation|Embryonic Stem Cells|Gene Expression|Gene Expression Profiling|Genome|Genome-Wide Association Study|Humans|Mice|Rats', 'Journal Article', '10.1093/bioinformatics/btr422', '21765096', 'The developmental stage of a cell can be determined by cellular morphology or various other observable indicators. Such classical markers could be complemented with modern surrogates, like whole-genome transcription profiles, that can encode the state of the entire organism and provide increased quantitative resolution. Recent findings suggest that such profiles provide sufficient information to reliably predict the cells developmental stage.'),
(76385, 2011, 'bio', 'PGAT: a multistrain analysis resource for microbial genomes', 'Brittnacher, M J|Fong, C|Hayden, H S|Jacobs, M A|Radey, Matthew|Rohmer, L', 'Department of Microbiology, University of Washington, Seattle, WA 98195, USA. mbrittna@uw.edu|Department of Microbiology, University of Washington, Seattle, WA 98195, USA. mbrittna@uw.edu|Department of Microbiology, University of Washington, Seattle, WA 98195, USA. mbrittna@uw.edu|Department of Microbiology, University of Washington, Seattle, WA 98195, USA. mbrittna@uw.edu|Department of Microbiology, University of Washington, Seattle, WA 98195, USA. mbrittna@uw.edu|Department of Microbiology, University of Washington, Seattle, WA 98195, USA. mbrittna@uw.edu', 'United States|United States|United States|United States|United States|United States', 47, 'Data Mining|Databases, Nucleic Acid|Genes, Bacterial|Genome, Bacterial|Genomics|Internet|Metabolic Networks and Pathways|Polymorphism, Genetic|Software', 'Journal Article', '10.1093/bioinformatics/btr418', '21765097', 'The Prokaryotic-genome Analysis Tool (PGAT) is a web-based database application for comparing gene content and sequence across multiple microbial genomes facilitating the discovery of genetic differences that may explain observed phenotypes. PGAT supports database queries to identify genes that are present or absent in user-selected genomes, comparison of sequence polymorphisms in sets of orthologous genes, multigenome display of regions surrounding a query gene, comparison of the distribution of genes in metabolic pathways and manual community annotation.'),
(76386, 2011, 'bio', 'Comparative analysis of RNA-Seq alignment algorithms and the RNA-Seq unified mapper (RUM)', 'Grant, Gregory R|Farkas, Michael H|Pizarro, Angel D|Lahens, Nicholas F|Schug, Jonathan|Brunk, Brian P|Stoeckert, Christian J|Hogenesch, John B|Pierce, Eric A', 'Penn Center for Bioinformatics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA. ggrant@pcbi.upenn.edu|Penn Center for Bioinformatics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA. ggrant@pcbi.upenn.edu|Penn Center for Bioinformatics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA. ggrant@pcbi.upenn.edu|Penn Center for Bioinformatics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA. ggrant@pcbi.upenn.edu|Penn Center for Bioinformatics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA. ggrant@pcbi.upenn.edu|Penn Center for Bioinformatics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA. ggrant@pcbi.upenn.edu|Penn Center for Bioinformatics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA. ggrant@pcbi.upenn.edu|Penn Center for Bioinformatics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA. ggrant@pcbi.upenn.edu|Penn Center for Bioinformatics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA. ggrant@pcbi.upenn.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 210, 'Algorithms|Animals|Base Sequence|Benchmarking|Cluster Analysis|Exons|Gene Library|Genome|High-Throughput Nucleotide Sequencing|Mice|Models, Genetic|Molecular Sequence Data|RNA|RNA Splicing|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btr427', '21775302', 'A critical task in high-throughput sequencing is aligning millions of short reads to a reference genome. Alignment is especially complicated for RNA sequencing (RNA-Seq) because of RNA splicing. A number of RNA-Seq algorithms are available, and claim to align reads with high accuracy and efficiency while detecting splice junctions. RNA-Seq data are discrete in nature, therefore, with reasonable gene models and comparative metrics RNA-Seq data can be simulated to sufficient accuracy to enable meaningful benchmarking of alignment algorithms. The exercise to rigorously compare all viable published RNA-Seq algorithms has not been performed previously.'),
(76387, 2011, 'bio', 'miRDeep-P: a computational tool for analyzing the microRNA transcriptome in plants', 'Yang, Xiaozeng|Li, Lei', 'Department of Biology, University of Virginia, Charlottesville, VA 22904, USA.|Department of Biology, University of Virginia, Charlottesville, VA 22904, USA.', 'United States|United States', 153, 'Data Mining|Gene Expression|MicroRNAs|Models, Genetic|Plants|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btr430', '21775303', 'Ultra-deep sampling of small RNA libraries by next-generation sequencing has provided rich information on the microRNA (miRNA) transcriptome of various plant species. However, few computational tools have been developed to effectively deconvolute the complex information.'),
(76388, 2011, 'bio', 'Making whole genome multiple alignments usable for biologists', 'Blankenberg, Daniel|Taylor, James|Nekrutenko, Anton|Galaxy Team', 'The Huck Institutes for the Life Sciences and Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA, USA.|The Huck Institutes for the Life Sciences and Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA, USA.|The Huck Institutes for the Life Sciences and Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA, USA.|The Huck Institutes for the Life Sciences and Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA, USA.', 'United States|United States|United States|United States', 28, 'Genomics|Humans|Internet|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr398', '21775304', 'Here we describe a set of tools implemented within the Galaxy platform designed to make analysis of multiple genome alignments truly accessible for biologists. These tools are available through both a web-based graphical user interface and a command-line interface.'),
(76389, 2011, 'bio', 'CalcTav--integration of a spreadsheet and Taverna workbench', 'Sroka, Jacek|Krupa, xc5x81ukasz|Kierzek, Andrzej M|Tyszkiewicz, Jerzy', 'Institute of Informatics, University of Warsaw, Warsaw, Poland and School of Biomedical and Molecular Sciences, University of Surrey, Guildford GU2 7XH, UK.|Institute of Informatics, University of Warsaw, Warsaw, Poland and School of Biomedical and Molecular Sciences, University of Surrey, Guildford GU2 7XH, UK.|Institute of Informatics, University of Warsaw, Warsaw, Poland and School of Biomedical and Molecular Sciences, University of Surrey, Guildford GU2 7XH, UK.|Institute of Informatics, University of Warsaw, Warsaw, Poland and School of Biomedical and Molecular Sciences, University of Surrey, Guildford GU2 7XH, UK.', 'Poland|Poland|Poland|Poland', 1, 'Computational Biology|Internet|Software|User-Computer Interface|Workflow', 'Journal Article', '10.1093/bioinformatics/btr425', '21775305', 'Taverna workbench is an environment for construction, visualization and execution of bioinformatic workflows that integrates specialized tools available on the Internet. It already supports major bioinformatics services and is constantly gaining popularity. However, its user interface requires considerable effort to learn, and sometimes requires programming or scripting experience from its users. We have integrated Taverna with OpenOffice Calc, making the functions of the scientific workflow system available in the spreadsheet. In CalcTav, one can define workflows using the spreadsheet interface and analyze the results using the spreadsheet toolset.'),
(76390, 2011, 'bio', 'GaggleBridge: collaborative data analysis', 'Battke, Florian|Symons, Stephan|Herbig, Alexander|Nieselt, Kay', 'Integrative Transcriptomics, Center for Bioinformatics, University of Tuebingen, 72076 Tuebingen, Germany. florian.battke@uni-tuebingen.de|Integrative Transcriptomics, Center for Bioinformatics, University of Tuebingen, 72076 Tuebingen, Germany. florian.battke@uni-tuebingen.de|Integrative Transcriptomics, Center for Bioinformatics, University of Tuebingen, 72076 Tuebingen, Germany. florian.battke@uni-tuebingen.de|Integrative Transcriptomics, Center for Bioinformatics, University of Tuebingen, 72076 Tuebingen, Germany. florian.battke@uni-tuebingen.de', 'Germany|Germany|Germany|Germany', 3, 'Computer Communication Networks|Data Interpretation, Statistical|Humans|Information Storage and Retrieval|Software', 'Journal Article', '10.1093/bioinformatics/btr429', '21775306', 'Tools aiding in collaborative data analysis are becoming ever more important as researchers work together over long distances. We present an extension to the Gaggle framework, which has been widely adopted as a tool to enable data exchange between different analysis programs on one computer.'),
(76391, 2011, 'bio', 'Simple high-throughput annotation pipeline (SHAP)', 'DeMaere, Matthew Z|Lauro, Federico M|Thomas, Torsten|Yau, Sheree|Cavicchioli, Ricardo', 'School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, NSW 2052, Australia. matt.demaere@unsw.edu.au|School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, NSW 2052, Australia. matt.demaere@unsw.edu.au|School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, NSW 2052, Australia. matt.demaere@unsw.edu.au|School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, NSW 2052, Australia. matt.demaere@unsw.edu.au|School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, NSW 2052, Australia. matt.demaere@unsw.edu.au', 'Australia|Australia|Australia|Australia|Australia', 0, 'Humans|Information Storage and Retrieval|Internet|Molecular Sequence Annotation|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr411', '21775307', 'SHAP (simple high-throughput annotation pipeline) is a lightweight and scalable sequence annotation pipeline capable of supporting research efforts that generate or utilize large volumes of DNA sequence data. The software provides Grid capable analysis, relational storage and Web-based full-text searching of annotation results. Implemented in Java, SHAP recognizes the limited resources of many smaller research groups.'),
(76392, 2011, 'bio', 'Discovering novel subsystems using comparative genomics', 'Ferrer, Luciana|Shearer, Alexander G|Karp, Peter D', 'Artificial Intelligence Center, SRI International, Menlo Park, CA, USA. lferrer@ai.sri.com|Artificial Intelligence Center, SRI International, Menlo Park, CA, USA. lferrer@ai.sri.com|Artificial Intelligence Center, SRI International, Menlo Park, CA, USA. lferrer@ai.sri.com', 'United States|United States|United States', 6, 'Algorithms|Computational Biology|Escherichia coli K12|Genetic Association Studies|Genome|Metabolic Networks and Pathways|Software', 'Journal Article', '10.1093/bioinformatics/btr428', '21775308', 'Key problems for computational genomics include discovering novel pathways in genome data, and discovering functional interaction partners for genes to define new members of partially elucidated pathways.'),
(76393, 2011, 'bio', 'coMOTIF: a mixture framework for identifying transcription factor and a coregulator motif in ChIP-seq data', 'Xu, Mengyuan|Weinberg, Clarice R|Umbach, David M|Li, Leping', 'Biostatistics Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA.|Biostatistics Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA.|Biostatistics Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA.|Biostatistics Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA.', 'United States|United States|United States|United States', 6, 'Algorithms|Amino Acid Motifs|Animals|Base Sequence|Binding Sites|Chromatin Immunoprecipitation|Gene Expression Regulation|Genome|Humans|Mice|Models, Genetic|Protein Binding|Protein Structure, Tertiary|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr397', '21775309', 'ChIP-seq data are enriched in binding sites for the protein immunoprecipitated. Some sequences may also contain binding sites for a coregulator. Biologists are interested in knowing which coregulatory factor motifs may be present in the sequences bound by the protein ChIPed.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76394, 2011, 'bio', 'Identification of novel phosphorylation modification sites in human proteins that originated after the human-chimpanzee divergence', 'Kim, Dong Seon|Hahn, Yoonsoo', 'School of Biological Sciences (BK21 Program) and Research Center for Biomolecules and Biosystems, Chung-Ang University, Seoul 156-756, Korea.|School of Biological Sciences (BK21 Program) and Research Center for Biomolecules and Biosystems, Chung-Ang University, Seoul 156-756, Korea.', '-|-', 16, 'Amino Acids|Animals|Casein Kinases|Cell Division|Chromatin Assembly and Disassembly|Cyclin-Dependent Kinases|Evolution, Molecular|Humans|Pan troglodytes|Phosphorylation|Protein Interaction Maps|Protein Kinases|Proteins|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btr426', '21775310', 'Phosphorylation modifications of specific protein residues are involved in a wide range of biological processes such as modulation of intracellular signal networks. Here, we present the development and application of a bioinformatics procedure for systematic identification of human-specific phosphorylation sites in proteins that may have occurred after the human-chimpanzee divergence.'),
(76395, 2011, 'bio', 'GenSSI: a software toolbox for structural identifiability analysis of biological models', 'Chixc5x9f, Oana|Banga, Julio R|Balsa-Canto, Eva', '(Bio)Process Engineering Group, Spanish National Research Council, IIM-CSIC, 36208 Vigo, Spain.|(Bio)Process Engineering Group, Spanish National Research Council, IIM-CSIC, 36208 Vigo, Spain.|(Bio)Process Engineering Group, Spanish National Research Council, IIM-CSIC, 36208 Vigo, Spain.', 'Spain|Spain|Spain', 0, 'Models, Biological|Nonlinear Dynamics|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btr431', '21784792', 'Mathematical modeling has a key role in systems biology. Model building is often regarded as an iterative loop involving several tasks, among which the estimation of unknown parameters of the model from a certain set of experimental data is of central importance. This problem of parameter estimation has many possible pitfalls, and modelers should be very careful to avoid them. Many of such difficulties arise from a fundamental (yet often overlooked) property: the so-called structural (or a priori) identifiability, which considers the uniqueness of the estimated parameters. Obviously, the structural identifiability of any tentative model should be checked at the beginning of the model building loop. However, checking this property for arbitrary non-linear dynamic models is not an easy task. Here we present a software toolbox, GenSSI (Generating Series for testing Structural Identifiability), which enables non-expert users to carry out such analysis. The toolbox runs under the popular MATLAB environment and is accompanied by detailed documentation and relevant examples.'),
(76396, 2011, 'bio', 'Structural analysis of the hot spots in the binding between H1N1 HA and the 2D1 antibody: do mutations of H1N1 from 1918 to 2009 affect much on this binding?', 'Liu, Qian|Hoi, Steven C H|Su, Chinh T T|Li, Zhenhua|Kwoh, Chee-Keong|Wong, Limsoon|Li, Jinyan', 'School of Computer Engineering, Nanyang Technological University, Singapore.|School of Computer Engineering, Nanyang Technological University, Singapore.|School of Computer Engineering, Nanyang Technological University, Singapore.|School of Computer Engineering, Nanyang Technological University, Singapore.|School of Computer Engineering, Nanyang Technological University, Singapore.|School of Computer Engineering, Nanyang Technological University, Singapore.|School of Computer Engineering, Nanyang Technological University, Singapore.', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 7, 'Antibodies|Antibodies, Neutralizing|Binding Sites, Antibody|Cross Reactions|Epitopes|Humans|Influenza A Virus, H1N1 Subtype|Influenza, Human|Mutation|Protein Binding|Proteins|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btr437', '21784793', 'Worldwide and substantial mortality caused by the 2009 H1N1 influenza A has stimulated a new surge of research on H1N1 viruses. An epitope conservation has been learned in the HA1 protein that allows antibodies to cross-neutralize both 1918 and 2009 H1N1. However, few works have thoroughly studied the binding hot spots in those two antigen-antibody interfaces which are responsible for the antibody cross-neutralization.'),
(76397, 2011, 'bio', 'Identifying disease-associated SNP clusters via contiguous outlier detection', 'Yang, Can|Zhou, Xiaowei|Wan, Xiang|Yang, Qiang|Xue, Hong|Yu, Weichuan', 'Laboratory for Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China.|Laboratory for Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China.|Laboratory for Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China.|Laboratory for Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China.|Laboratory for Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China.|Laboratory for Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China.', 'China|China|China|China|China|China', 5, 'Algorithms|Cluster Analysis|Disease|Genetic Predisposition to Disease|Genome-Wide Association Study|Genotype|Humans|Linkage Disequilibrium|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btr424', '21784794', 'Although genome-wide association studies (GWAS) have identified many disease-susceptibility single-nucleotide polymorphisms (SNPs), these findings can only explain a small portion of genetic contributions to complex diseases, which is known as the missing heritability. A possible explanation is that genetic variants with small effects have not been detected. The chance is < 8 that a causal SNP will be directly genotyped. The effects of its neighboring SNPs may be too weak to be detected due to the effect decay caused by imperfect linkage disequilibrium. Moreover, it is still challenging to detect a causal SNP with a small effect even if it has been directly genotyped.'),
(76398, 2011, 'bio', 'Estimating classification probabilities in high-dimensional diagnostic studies', 'Appel, Inka J|Gronwald, Wolfram|Spang, Rainer', 'Institute of Functional Genomics, University of Regensburg, 93053 Regensburg, Germany. inka.appel@klinik.uni-regensburg.de|Institute of Functional Genomics, University of Regensburg, 93053 Regensburg, Germany. inka.appel@klinik.uni-regensburg.de|Institute of Functional Genomics, University of Regensburg, 93053 Regensburg, Germany. inka.appel@klinik.uni-regensburg.de', 'Germany|Germany|Germany', 4, 'Algorithms|Bayes Theorem|Humans|Kidney Diseases|Metabolome|Reproducibility of Results|Urine', 'Journal Article', '10.1093/bioinformatics/btr434', '21784795', 'Classification algorithms for high-dimensional biological data like gene expression profiles or metabolomic fingerprints are typically evaluated by the number of misclassifications across a test dataset. However, to judge the classification of a single case in the context of clinical diagnosis, we need to assess the uncertainties associated with that individual case rather than the average accuracy across many cases. Reliability of individual classifications can be expressed in terms of class probabilities. While classification algorithms are a well-developed area of research, the estimation of class probabilities is considerably less progressed in biology, with only a few classification algorithms that provide estimated class probabilities.'),
(76399, 2011, 'bio', 'phyloMeta: a program for phylogenetic comparative analyses with meta-analysis', 'Lajeunesse, Marc J', 'Department of Integrative Biology, University of South Florida, Tampa, FL 33620, USA. lajeunesse@usf.edu', 'United States', 0, 'Biological Evolution|Information Storage and Retrieval|Meta-Analysis as Topic|Phylogeny|Research Design|Software', 'Comparative Study', '10.1093/bioinformatics/btr438', '21784796', 'phyloMeta is an easy to use console program for integrating phylogenetic information into meta-analysis. It is designed to help ecologists, evolutionary biologists and conservation biologists analyze effect size data extracted from published studies in a comparative phylogenetic context. This software estimates phylogenetic versions of all the traditional meta-analytical statistics used for: pooling effect sizes with weighted regressions, evaluating the homogeneity of these effect sizes, performing moderator tests akin to ANOVA style analyses, and analyzing data with fixed- and random-effects models. phyloMeta is developed in C/C++ and can be used via command line in MS Windows environments.'),
(76400, 2011, 'bio', 'CAM-CM: a signal deconvolution tool for in vivo dynamic contrast-enhanced imaging of complex tissues', 'Chen, Li|Chan, Tsung-Han|Choyke, Peter L|Hillman, Elizabeth M C|Chi, Chong-Yung|Bhujwalla, Zaver M|Wang, Ge|Wang, Sean S|Szabo, Zsolt|Wang, Yue', 'Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, USA.|Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 17, 'Algorithms|Diagnostic Imaging|Models, Biological|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btr436', '21785131', 'In vivo dynamic contrast-enhanced imaging tools provide non-invasive methods for analyzing various functional changes associated with disease initiation, progression and responses to therapy. The quantitative application of these tools has been hindered by its inability to accurately resolve and characterize targeted tissues due to spatially mixed tissue heterogeneity. Convex Analysis of Mixtures - Compartment Modeling (CAM-CM) signal deconvolution tool has been developed to automatically identify pure-volume pixels located at the corners of the clustered pixel time series scatter simplex and subsequently estimate tissue-specific pharmacokinetic parameters. CAM-CM can dissect complex tissues into regions with differential tracer kinetics at pixel-wise resolution and provide a systems biology tool for defining imaging signatures predictive of phenotypes.'),
(76401, 2011, 'bio', 'RNAG: a new Gibbs sampler for predicting RNA secondary structure for unaligned sequences', 'Wei, Donglai|Alpert, Lauren V|Lawrence, Charles E', 'Department of Mathematics, Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA.|Department of Mathematics, Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA.|Department of Mathematics, Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA.', 'United States|United States|United States', 18, 'Algorithms|Base Sequence|Cluster Analysis|Molecular Sequence Data|Nucleic Acid Conformation|RNA|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btr421', '21788211', 'RNA secondary structure plays an important role in the function of many RNAs, and structural features are often key to their interaction with other cellular components. Thus, there has been considerable interest in the prediction of secondary structures for RNA families. In this article, we present a new global structural alignment algorithm, RNAG, to predict consensus secondary structures for unaligned sequences. It uses a blocked Gibbs sampling algorithm, which has a theoretical advantage in convergence time. This algorithm iteratively samples from the conditional probability distributions P(Structure | Alignment) and P(Alignment | Structure). Not surprisingly, there is considerable uncertainly in the high-dimensional space of this difficult problem, which has so far received limited attention in this field. We show how the samples drawn from this algorithm can be used to more fully characterize the posterior space and to assess the uncertainty of predictions.'),
(76402, 2011, 'bio', 'Alignment of distantly related protein structures: algorithm, bound and implications to homology modeling', 'Wang, Sheng|Peng, Jian|Xu, Jinbo', 'Toyota Technological Institute at Chicago, IL 60637, USA.|Toyota Technological Institute at Chicago, IL 60637, USA.|Toyota Technological Institute at Chicago, IL 60637, USA.', 'United States|United States|United States', 32, 'Algorithms|Artificial Intelligence|Protein Binding|Proteins|Sequence Alignment|Software|Structural Homology, Protein', 'Journal Article', '10.1093/bioinformatics/btr432', '21791532', 'Building an accurate alignment of a large set of distantly related protein structures is still very challenging.'),
(76403, 2011, 'bio', 'VISTA Region Viewer (RViewer)--a computational system for prioritizing genomic intervals for biomedical studies', 'Lukashin, Igor|Novichkov, Pavel|Boffelli, Dario|Paciorkowski, Alex R|Minovitsky, Simon|Yang, Song|Dubchak, Inna', 'Genomics Division, Lawrence Berkeley National Laboratory, MS 84-171, Berkeley, CA 94720, USA.|Genomics Division, Lawrence Berkeley National Laboratory, MS 84-171, Berkeley, CA 94720, USA.|Genomics Division, Lawrence Berkeley National Laboratory, MS 84-171, Berkeley, CA 94720, USA.|Genomics Division, Lawrence Berkeley National Laboratory, MS 84-171, Berkeley, CA 94720, USA.|Genomics Division, Lawrence Berkeley National Laboratory, MS 84-171, Berkeley, CA 94720, USA.|Genomics Division, Lawrence Berkeley National Laboratory, MS 84-171, Berkeley, CA 94720, USA.|Genomics Division, Lawrence Berkeley National Laboratory, MS 84-171, Berkeley, CA 94720, USA.', 'United States|United States|United States|United States|United States|United States|United States', 10, 'Animals|Data Mining|Follow-Up Studies|Gene Dosage|Genome|Genome, Human|Humans|Infant|Internet|Mice|Models, Genetic|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btr440', '21791533', 'Current genome browsers are designed for linear browsing of individual genomic regions, but the high-throughput nature of experiments aiming to elucidate the genetic component of human disease makes it very important to develop user-friendly tools for comparing several genomic regions in parallel and prioritizing them based on their functional content. We introduce VISTA Region Viewer (RViewer), an interactive online tool that allows for efficient screening and prioritization of regions of the human genome for follow-up studies. The tool takes as input genetic variation data from different biomedical studies, determines a number of various functional parameters for both coding and non-coding sequences in each region and allows for sorting and searching the results of the analysis in multiple ways.'),
(76404, 2011, 'bio', 'A dynamic programming algorithm for identification of triplex-forming sequences', 'Lexa, Matej|Martxc3xadnek, Tomxc3xa1xc5xa1|Burgetovxc3xa1, Ivana|Kopexc4x8dek, Daniel|Brxc3xa1zdovxc3xa1, Marie', 'Department of Information Technology, Faculty of Informatics, Masaryk University, 60200 Brno, Czech Republic. lexa@fi.muni.cz|Department of Information Technology, Faculty of Informatics, Masaryk University, 60200 Brno, Czech Republic. lexa@fi.muni.cz|Department of Information Technology, Faculty of Informatics, Masaryk University, 60200 Brno, Czech Republic. lexa@fi.muni.cz|Department of Information Technology, Faculty of Informatics, Masaryk University, 60200 Brno, Czech Republic. lexa@fi.muni.cz|Department of Information Technology, Faculty of Informatics, Masaryk University, 60200 Brno, Czech Republic. lexa@fi.muni.cz', '-|-|-|-|-', 17, 'Algorithms|Base Pair Mismatch|Base Sequence|DNA|Escherichia coli K12|Genome|Humans|Inverted Repeat Sequences|Likelihood Functions|Nucleic Acid Conformation|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btr439', '21791534', 'Current methods for identification of potential triplex-forming sequences in genomes and similar sequence sets rely primarily on detecting homopurine and homopyrimidine tracts. Procedures capable of detecting sequences supporting imperfect, but structurally feasible intramolecular triplex structures are needed for better sequence analysis.'),
(76405, 2011, 'bio', 'ReplacementMatrix: a web server for maximum-likelihood estimation of amino acid replacement rate matrices', 'Dang, Cuong Cao|Lefort, Vincent|Le, Vinh Sy|Le, Quang Si|Gascuel, Olivier', 'College of Technology and Information Technology Institute, Vietnam National University, Hanoi, Vietnam.|College of Technology and Information Technology Institute, Vietnam National University, Hanoi, Vietnam.|College of Technology and Information Technology Institute, Vietnam National University, Hanoi, Vietnam.|College of Technology and Information Technology Institute, Vietnam National University, Hanoi, Vietnam.|College of Technology and Information Technology Institute, Vietnam National University, Hanoi, Vietnam.', '-|-|-|-|-', 9, 'Amino Acids|Internet|Likelihood Functions|Phylogeny|Probability|Proteins|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btr435', '21791535', 'Amino acid replacement rate matrices are an essential basis of protein studies (e.g. in phylogenetics and alignment). A number of general purpose matrices have been proposed (e.g. JTT, WAG, LG) since the seminal work of Margaret Dayhoff and co-workers. However, it has been shown that matrices specific to certain protein groups (e.g. mitochondrial) or life domains (e.g. viruses) differ significantly from general average matrices, and thus perform better when applied to the data to which they are dedicated. This Web server implements the maximum-likelihood estimation procedure that was used to estimate LG, and provides a number of tools and facilities. Users upload a set of multiple protein alignments from their domain of interest and receive the resulting matrix by email, along with statistics and comparisons with other matrices. A non-parametric bootstrap is performed optionally to assess the variability of replacement rate estimates. Maximum-likelihood trees, inferred using the estimated rate matrix, are also computed optionally for each input alignment. Finely tuned procedures and up-to-date ML software (PhyML 3.0, XRATE) are combined to perform all these heavy calculations on our clusters.'),
(76406, 2011, 'bio', 'RseqFlow: workflows for RNA-Seq data analysis', 'Wang, Ying|Mehta, Gaurang|Mayani, Rajiv|Lu, Jingxi|Souaiaia, Tade|Chen, Yangho|Clark, Andrew|Yoon, Hee Jae|Wan, Lin|Evgrafov, Oleg V|Knowles, James A|Deelman, Ewa|Chen, Ting', 'Department of Biological Sciences, USC, Los Angeles, CA 90089, USA. wangying@xmu.edu.cn|Department of Biological Sciences, USC, Los Angeles, CA 90089, USA. wangying@xmu.edu.cn|Department of Biological Sciences, USC, Los Angeles, CA 90089, USA. wangying@xmu.edu.cn|Department of Biological Sciences, USC, Los Angeles, CA 90089, USA. wangying@xmu.edu.cn|Department of Biological Sciences, USC, Los Angeles, CA 90089, USA. wangying@xmu.edu.cn|Department of Biological Sciences, USC, Los Angeles, CA 90089, USA. wangying@xmu.edu.cn|Department of Biological Sciences, USC, Los Angeles, CA 90089, USA. wangying@xmu.edu.cn|Department of Biological Sciences, USC, Los Angeles, CA 90089, USA. wangying@xmu.edu.cn|Department of Biological Sciences, USC, Los Angeles, CA 90089, USA. wangying@xmu.edu.cn|Department of Biological Sciences, USC, Los Angeles, CA 90089, USA. wangying@xmu.edu.cn|Department of Biological Sciences, USC, Los Angeles, CA 90089, USA. wangying@xmu.edu.cn|Department of Biological Sciences, USC, Los Angeles, CA 90089, USA. wangying@xmu.edu.cn|Department of Biological Sciences, USC, Los Angeles, CA 90089, USA. wangying@xmu.edu.cn', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 16, 'Base Sequence|Gene Expression|Genome, Human|Humans|RNA|Sequence Analysis, RNA|Software|Workflow', 'Journal Article', '10.1093/bioinformatics/btr441', '21795323', 'We have developed an RNA-Seq analysis workflow for single-ended Illumina reads, termed RseqFlow. This workflow includes a set of analytic functions, such as quality control for sequencing data, signal tracks of mapped reads, calculation of expression levels, identification of differentially expressed genes and coding SNPs calling. This workflow is formalized and managed by the Pegasus Workflow Management System, which maps the analysis modules onto available computational resources, automatically executes the steps in the appropriate order and supervises the whole running process. RseqFlow is available as a Virtual Machine with all the necessary software, which eliminates any complex configuration and installation steps.'),
(76407, 2011, 'bio', 'A powerful approach for association analysis incorporating imprinting effects', 'Xia, Fan|Zhou, Ji-Yuan|Fung, Wing Kam', 'Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong.|Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong.|Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong.', 'Hong Kong|Hong Kong|Hong Kong', 9, 'Arthritis, Rheumatoid|Child|Genetic Testing|Genome-Wide Association Study|Genomic Imprinting|Humans|Models, Genetic|Nuclear Family|Parents|Polymorphism, Genetic|Reproducibility of Results', 'Journal Article', '10.1093/bioinformatics/btr443', '21798962', 'For a diallelic marker locus, the transmission disequilibrium test (TDT) is a simple and powerful design for genetic studies. The TDT was originally proposed for use in families with both parents available (complete nuclear families) and has further been extended to 1-TDT for use in families with only one of the parents available (incomplete nuclear families). Currently, the increasing interest of the influence of parental imprinting on heritability indicates the importance of incorporating imprinting effects into the mapping of association variants.'),
(76408, 2011, 'bio', 'Tissue-specific subnetworks and characteristics of publicly available human protein interaction databases', 'Lopes, Tiago J S|Schaefer, Martin|Shoemaker, Jason|Matsuoka, Yukiko|Fontaine, Jean-Fred|Neumann, Gabriele|Andrade-Navarro, Miguel A|Kawaoka, Yoshihiro|Kitano, Hiroaki', 'JST ERATO KAWAOKA Infection-induced Host Responses Project, Tokyo, Japan.|JST ERATO KAWAOKA Infection-induced Host Responses Project, Tokyo, Japan.|JST ERATO KAWAOKA Infection-induced Host Responses Project, Tokyo, Japan.|JST ERATO KAWAOKA Infection-induced Host Responses Project, Tokyo, Japan.|JST ERATO KAWAOKA Infection-induced Host Responses Project, Tokyo, Japan.|JST ERATO KAWAOKA Infection-induced Host Responses Project, Tokyo, Japan.|JST ERATO KAWAOKA Infection-induced Host Responses Project, Tokyo, Japan.|JST ERATO KAWAOKA Infection-induced Host Responses Project, Tokyo, Japan.|JST ERATO KAWAOKA Infection-induced Host Responses Project, Tokyo, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 33, 'Databases, Protein|Gene Expression|Humans|Protein Interaction Mapping|Proteins', 'Journal Article', '10.1093/bioinformatics/btr414', '21798963', 'Protein-protein interaction (PPI) databases are widely used tools to study cellular pathways and networks, however, there are several databases available that still do not account for cell type-specific differences. Here, we evaluated the characteristics of six interaction databases, incorporated tissue-specific gene expression information and finally, investigated if the most popular proteins of scientific literature are involved in good quality interactions.'),
(76409, 2011, 'bio', 'Dasty3, a WEB framework for DAS', 'Villaveces, Jose M|Jimenez, Rafael C|Garcia, Leyla J|Salazar, Gustavo A|Gel, Bernat|Mulder, Nicola|Martin, Maria|Garcia, Alexander|Hermjakob, Henning', 'Protein and Nucleotide Data Group, EMBL Outstation European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.|Protein and Nucleotide Data Group, EMBL Outstation European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.|Protein and Nucleotide Data Group, EMBL Outstation European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.|Protein and Nucleotide Data Group, EMBL Outstation European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.|Protein and Nucleotide Data Group, EMBL Outstation European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.|Protein and Nucleotide Data Group, EMBL Outstation European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.|Protein and Nucleotide Data Group, EMBL Outstation European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.|Protein and Nucleotide Data Group, EMBL Outstation European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.|Protein and Nucleotide Data Group, EMBL Outstation European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Computational Biology|Databases, Genetic|Databases, Protein|Internet|Registries|Software', 'Journal Article', '10.1093/bioinformatics/btr433', '21798964', 'Dasty3 is a highly interactive and extensible Web-based framework. It provides a rich Application Programming Interface upon which it is possible to develop specialized clients capable of retrieving information from DAS sources as well as from data providers not using the DAS protocol. Dasty3 provides significant improvements on previous Web-based frameworks and is implemented using the 1.6 DAS specification.'),
(76410, 2011, 'bio', 'JMassBalance: mass-balanced randomization and analysis of metabolic networks', 'Basler, Georg|Nikoloski, Zoran', 'University of Potsdam, Institute for Biochemistry and Biology, D-14476 Potsdam, Germany. basler@mpimp-golm.mpg.de|University of Potsdam, Institute for Biochemistry and Biology, D-14476 Potsdam, Germany. basler@mpimp-golm.mpg.de', 'Germany|Germany', 0, 'Cluster Analysis|Humans|Metabolic Networks and Pathways|Models, Biological|Random Allocation|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr448', '21803803', 'Analysis of biological networks requires assessing the statistical significance of network-based predictions by using a realistic null model. However, the existing network null model, switch randomization, is unsuitable for metabolic networks, as it does not include physical constraints and generates unrealistic reactions. We present JMassBalance, a tool for mass-balanced randomization and analysis of metabolic networks. The tool allows efficient generation of large sets of randomized networks under the physical constraint of mass balance. In addition, various structural properties of the original and randomized networks can be calculated, facilitating the identification of the salient properties of metabolic networks with a biologically meaningful null model.'),
(76411, 2011, 'bio', 'Bayesian prediction of tissue-regulated splicing using RNA sequence and cellular context', 'Xiong, Hui Yuan|Barash, Yoseph|Frey, Brendan J', 'Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada.|Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada.|Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada.', 'Canada|Canada|Canada', 46, 'Algorithms|Alternative Splicing|Animals|Base Sequence|Bayes Theorem|Exons|Gene Expression|Gene Expression Regulation|Humans|Mice|Models, Genetic|RNA|RNA Isoforms|RNA Splicing|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btr444', '21803804', 'Alternative splicing is a major contributor to cellular diversity in mammalian tissues and relates to many human diseases. An important goal in understanding this phenomenon is to infer a splicing code that predicts how splicing is regulated in different cell types by features derived from RNA, DNA and epigenetic modifiers.'),
(76412, 2011, 'bio', 'ContEst: estimating cross-contamination of human samples in next-generation sequencing data', 'Cibulskis, Kristian|McKenna, Aaron|Fennell, Tim|Banks, Eric|DePristo, Mark|Getz, Gad', 'Genome Sequencing Analysis Program and Platform, Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA. kcibul@broadinstitute.org|Genome Sequencing Analysis Program and Platform, Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA. kcibul@broadinstitute.org|Genome Sequencing Analysis Program and Platform, Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA. kcibul@broadinstitute.org|Genome Sequencing Analysis Program and Platform, Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA. kcibul@broadinstitute.org|Genome Sequencing Analysis Program and Platform, Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA. kcibul@broadinstitute.org|Genome Sequencing Analysis Program and Platform, Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA. kcibul@broadinstitute.org', 'United States|United States|United States|United States|United States|United States', 0, 'Base Sequence|Bayes Theorem|False Positive Reactions|Genotype|Humans|Models, Genetic|Neoplasms|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr446', '21803805', 'Here, we present ContEst, a tool for estimating the level of cross-individual contamination in next-generation sequencing data. We demonstrate the accuracy of ContEst across a range of contamination levels, sources and read depths using sequencing data mixed in silico at known concentrations. We applied our tool to published cancer sequencing datasets and report their estimated contamination levels.'),
(76413, 2011, 'bio', 'Gee Fu: a sequence version and web-services database tool for genomic assembly, genome feature and NGS data', 'Ramirez-Gonzalez, Ricardo|Caccamo, Mario|MacLean, Daniel', 'The Genome Analysis Centre, Norwich Research Park, Colney Lane, Norwich, UK, NR4 7UH.|The Genome Analysis Centre, Norwich Research Park, Colney Lane, Norwich, UK, NR4 7UH.|The Genome Analysis Centre, Norwich Research Park, Colney Lane, Norwich, UK, NR4 7UH.', '-|-|-', 2, 'Animals|Base Sequence|Databases, Genetic|Electronic Data Processing|Genome|Genomics|Humans|Information Storage and Retrieval|Internet|Microarray Analysis|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btr442', '21803806', 'Scientists now use high-throughput sequencing technologies and short-read assembly methods to create draft genome assemblies in just days. Tools and pipelines like the assembler, and the workflow management environments make it easy for a non-specialist to implement complicated pipelines to produce genome assemblies and annotations very quickly. Such accessibility results in a proliferation of assemblies and associated files, often for many organisms. These assemblies get used as a working reference by lots of different workers, from a bioinformatician doing gene prediction or a bench scientist designing primers for PCR. Here we describe Gee Fu, a database tool for genomic assembly and feature data, including next-generation sequence alignments. Gee Fu is an instance of a Ruby-On-Rails web application on a feature database that provides web and console interfaces for input, visualization of feature data via AnnoJ, access to data through a web-service interface, an API for direct data access by Ruby scripts and access to feature data stored in BAM files. Gee Fu provides a platform for storing and sharing different versions of an assembly and associated features that can be accessed and updated by bench biologists and bioinformaticians in ways that are easy and useful for each.'),
(76414, 2011, 'bio', 'Penalized regression elucidates aberration hotspots mediating subtype-specific transcriptional responses in breast cancer', 'Yuan, Yinyin|Rueda, Oscar M|Curtis, Christina|Markowetz, Florian', 'Cambridge Research Institute, Cancer Research UK, Li Ka Shing Centre, Cambridge CB2 0RE, UK. yinyin.yuan@cancer.org.uk|Cambridge Research Institute, Cancer Research UK, Li Ka Shing Centre, Cambridge CB2 0RE, UK. yinyin.yuan@cancer.org.uk|Cambridge Research Institute, Cancer Research UK, Li Ka Shing Centre, Cambridge CB2 0RE, UK. yinyin.yuan@cancer.org.uk|Cambridge Research Institute, Cancer Research UK, Li Ka Shing Centre, Cambridge CB2 0RE, UK. yinyin.yuan@cancer.org.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 2, 'Breast Neoplasms|DNA Copy Number Variations|Female|Gene Expression|Gene Expression Regulation|Genomic Instability|Humans|Models, Genetic|Phenotype|Software|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btr450', '21804112', 'Copy number alterations (CNAs) associated with cancer are known to contribute to genomic instability and gene deregulation. Integrating CNAs with gene expression helps to elucidate the mechanisms by which CNAs act and to identify the transcriptional downstream targets of CNAs. Such analyses can help to sort functional driver events from the many accompanying passenger alterations. However, the way CNAs affect gene expression can vary in different cellular contexts, for example between different subtypes of the same cancer. Thus, it is important to develop computational approaches capable of inferring differential connectivity of regulatory networks in different cellular contexts.'),
(76415, 2011, 'bio', 'SEED: efficient clustering of next-generation sequences', 'Bao, Ergude|Jiang, Tao|Kaloshian, Isgouhi|Girke, Thomas', 'Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.|Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.|Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.|Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.', 'United States|United States|United States|United States', 37, 'Algorithms|Base Sequence|Cluster Analysis|Genome|MicroRNAs|Sequence Analysis|Sequence Analysis, RNA|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btr447', '21810899', 'Similarity clustering of next-generation sequences (NGS) is an important computational problem to study the population sizes of DNA/RNA molecules and to reduce the redundancies in NGS data. Currently, most sequence clustering algorithms are limited by their speed and scalability, and thus cannot handle data with tens of millions of reads.'),
(76416, 2011, 'bio', 'A powerful and flexible approach to the analysis of RNA sequence count data', 'Zhou, Yi-Hui|Xia, Kai|Wright, Fred A', 'Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. yzhou@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. yzhou@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. yzhou@bios.unc.edu', 'United States|United States|United States', 73, 'Base Sequence|Gene Expression|Gene Expression Profiling|Models, Genetic|Models, Statistical|Sequence Analysis, RNA|Software|Transcription, Genetic|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btr449', '21810900', 'A number of penalization and shrinkage approaches have been proposed for the analysis of microarray gene expression data. Similar techniques are now routinely applied to RNA sequence transcriptional count data, although the value of such shrinkage has not been conclusively established. If penalization is desired, the explicit modeling of mean-variance relationships provides a flexible testing regimen that borrows information across genes, while easily incorporating design effects and additional covariates.'),
(76417, 2011, 'bio', 'Mauve assembly metrics', 'Darling, Aaron E|Tritt, Andrew|Eisen, Jonathan A|Facciotti, Marc T', 'Genome Center, University of California-Davis, Davis, CA 95616, USA. aarondarling@ucdavis.edu|Genome Center, University of California-Davis, Davis, CA 95616, USA. aarondarling@ucdavis.edu|Genome Center, University of California-Davis, Davis, CA 95616, USA. aarondarling@ucdavis.edu|Genome Center, University of California-Davis, Davis, CA 95616, USA. aarondarling@ucdavis.edu', 'United States|United States|United States|United States', 53, 'Algorithms|Base Sequence|Genome|Haloferax volcanii|High-Throughput Nucleotide Sequencing|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btr451', '21810901', 'High-throughput DNA sequencing technologies have spurred the development of numerous novel methods for genome assembly. With few exceptions, these algorithms are heuristic and require one or more parameters to be manually set by the user. One approach to parameter tuning involves assembling data from an organism with an available high-quality reference genome, and measuring assembly accuracy using some metrics. We developed a system to measure assembly quality under several scoring metrics, and to compare assembly quality across a variety of assemblers, sequence data types, and parameter choices. When used in conjunction with training data such as a high-quality reference genome and sequence reads from the same organism, our program can be used to manually identify an optimal sequencing and assembly strategy for de novo sequencing of related organisms.'),
(76418, 2011, 'bio', 'The GNAT library for local and remote gene mention normalization', 'Hakenberg, Jörg|Gerner, Martin|Haeussler, Maximilian|Solt, Illés|Plake, Conrad|Schroeder, Michael|Gonzalez, Graciela|Nenadic, Goran|Bergman, Casey M', 'Pharma Research and Early Development, Hoffmann-La Roche Inc., Nutley, NJ 07110, USA. jorg.hakenberg@roche.com|Pharma Research and Early Development, Hoffmann-La Roche Inc., Nutley, NJ 07110, USA. jorg.hakenberg@roche.com|Pharma Research and Early Development, Hoffmann-La Roche Inc., Nutley, NJ 07110, USA. jorg.hakenberg@roche.com|Pharma Research and Early Development, Hoffmann-La Roche Inc., Nutley, NJ 07110, USA. jorg.hakenberg@roche.com|Pharma Research and Early Development, Hoffmann-La Roche Inc., Nutley, NJ 07110, USA. jorg.hakenberg@roche.com|Pharma Research and Early Development, Hoffmann-La Roche Inc., Nutley, NJ 07110, USA. jorg.hakenberg@roche.com|Pharma Research and Early Development, Hoffmann-La Roche Inc., Nutley, NJ 07110, USA. jorg.hakenberg@roche.com|Pharma Research and Early Development, Hoffmann-La Roche Inc., Nutley, NJ 07110, USA. jorg.hakenberg@roche.com|Pharma Research and Early Development, Hoffmann-La Roche Inc., Nutley, NJ 07110, USA. jorg.hakenberg@roche.com', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 40, 'Data Mining|Electronic Data Processing|Gene Library|Genes|Internet|Proteins|Publishing|Terminology as Topic', 'Journal Article', '10.1093/bioinformatics/btr455', '21813477', 'Identifying mentions of named entities, such as genes or diseases, and normalizing them to database identifiers have become an important step in many text and data mining pipelines. Despite this need, very few entity normalization systems are publicly available as source code or web services for biomedical text mining. Here we present the Gnat Java library for text retrieval, named entity recognition, and normalization of gene and protein mentions in biomedical text. The library can be used as a component to be integrated with other text-mining systems, as a framework to add user-specific extensions, and as an efficient stand-alone application for the identification of gene and protein names for data analysis. On the BioCreative III test data, the current version of Gnat achieves a Tap-20 score of 0.1987.'),
(76419, 2011, 'bio', 'GlobalMIT: learning globally optimal dynamic bayesian network with the mutual information test criterion', 'Vinh, Nguyen Xuan|Chetty, Madhu|Coppel, Ross|Wangikar, Pramod P', 'Gippsland School of Information Technology, Faculty of IT, Monash University, Victoria, Australia. vinh.nguyen@monash.edu|Gippsland School of Information Technology, Faculty of IT, Monash University, Victoria, Australia. vinh.nguyen@monash.edu|Gippsland School of Information Technology, Faculty of IT, Monash University, Victoria, Australia. vinh.nguyen@monash.edu|Gippsland School of Information Technology, Faculty of IT, Monash University, Victoria, Australia. vinh.nguyen@monash.edu', 'Australia|Australia|Australia|Australia', 55, 'Algorithms|Bayes Theorem|Gene Expression|Gene Expression Regulation|Gene Regulatory Networks|Information Storage and Retrieval|Metabolic Networks and Pathways|Models, Biological|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btr457', '21813478', 'Dynamic Bayesian networks (DBN) are widely applied in modeling various biological networks including the gene regulatory network (GRN). Due to the NP-hard nature of learning static Bayesian network structure, most methods for learning DBN also employ either local search such as hill climbing, or a meta stochastic global optimization framework such as genetic algorithm or simulated annealing.'),
(76420, 2011, 'bio', 'Large-scale dynamic gene regulatory network inference combining differential equation models with local dynamic Bayesian network analysis', 'Li, Zheng|Li, Ping|Krishnan, Arun|Liu, Jingdong', 'Monsanto Company, Mail zone CC1A, Chesterfield, MO 63017, USA. zheng.li@monsanto.com|Monsanto Company, Mail zone CC1A, Chesterfield, MO 63017, USA. zheng.li@monsanto.com|Monsanto Company, Mail zone CC1A, Chesterfield, MO 63017, USA. zheng.li@monsanto.com|Monsanto Company, Mail zone CC1A, Chesterfield, MO 63017, USA. zheng.li@monsanto.com', 'United States|United States|United States|United States', 0, 'Algorithms|Bayes Theorem|Gene Expression Profiling|Gene Expression Regulation|Gene Regulatory Networks|Genes, BRCA1|HeLa Cells|Humans|Models, Genetic|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/btr454', '21816876', 'Reverse engineering gene regulatory networks, especially large size networks from time series gene expression data, remain a challenge to the systems biology community. In this article, a new hybrid algorithm integrating ordinary differential equation models with dynamic Bayesian network analysis, called Differential Equation-based Local Dynamic Bayesian Network (DELDBN), was proposed and implemented for gene regulatory network inference.'),
(76421, 2011, 'bio', 'Automatic extraction of angiogenesis bioprocess from text', 'Wang, Xinglong|McKendrick, Iain|Barrett, Ian|Dix, Ian|French, Tim|Tsujii, Junichi|Ananiadou, Sophia', 'National Centre for Text Mining, University of Manchester, Manchester, AstraZeneca, Alderley Park, UK. xinglong.wang@gmail.com|National Centre for Text Mining, University of Manchester, Manchester, AstraZeneca, Alderley Park, UK. xinglong.wang@gmail.com|National Centre for Text Mining, University of Manchester, Manchester, AstraZeneca, Alderley Park, UK. xinglong.wang@gmail.com|National Centre for Text Mining, University of Manchester, Manchester, AstraZeneca, Alderley Park, UK. xinglong.wang@gmail.com|National Centre for Text Mining, University of Manchester, Manchester, AstraZeneca, Alderley Park, UK. xinglong.wang@gmail.com|National Centre for Text Mining, University of Manchester, Manchester, AstraZeneca, Alderley Park, UK. xinglong.wang@gmail.com|National Centre for Text Mining, University of Manchester, Manchester, AstraZeneca, Alderley Park, UK. xinglong.wang@gmail.com', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 9, 'Angiogenesis Inhibitors|Artificial Intelligence|Biological Phenomena|Data Mining|Documentation|Models, Statistical|Natural Language Processing|Neovascularization, Pathologic|Neovascularization, Physiologic|Software|Vocabulary', 'Journal Article', '10.1093/bioinformatics/btr460', '21821664', 'Understanding key biological processes (bioprocesses) and their relationships with constituent biological entities and pharmaceutical agents is crucial for drug design and discovery. One way to harvest such information is searching the literature. However, bioprocesses are difficult to capture because they may occur in text in a variety of textual expressions. Moreover, a bioprocess is often composed of a series of bioevents, where a bioevent denotes changes to one or a group of cells involved in the bioprocess. Such bioevents are often used to refer to bioprocesses in text, which current techniques, relying solely on specialized lexicons, struggle to find.'),
(76422, 2011, 'bio', 'Tree-structured algorithm for long weak motif discovery', 'Sun, He Quan|Low, Malcolm Yoke Hean|Hsu, Wen Jing|Tan, Ching Wai|Rajapakse, Jagath C', 'Department of Computer Science, School of Computer Engineering, Nanyang Technological University, Singapore 639798. sunh0013@e.ntu.edu.sg|Department of Computer Science, School of Computer Engineering, Nanyang Technological University, Singapore 639798. sunh0013@e.ntu.edu.sg|Department of Computer Science, School of Computer Engineering, Nanyang Technological University, Singapore 639798. sunh0013@e.ntu.edu.sg|Department of Computer Science, School of Computer Engineering, Nanyang Technological University, Singapore 639798. sunh0013@e.ntu.edu.sg|Department of Computer Science, School of Computer Engineering, Nanyang Technological University, Singapore 639798. sunh0013@e.ntu.edu.sg', 'Singapore|Singapore|Singapore|Singapore|Singapore', 14, 'Algorithms|Amino Acid Motifs|Base Sequence|Gene Expression Regulation|Models, Genetic|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr459', '21821665', 'Motifs in DNA sequences often appear in degenerate form, so there has been an increased interest in computational algorithms for weak motif discovery. Probabilistic algorithms are unable to detect weak motifs while exact methods have been able to detect only short weak motifs. This article proposes an exact tree-based motif detection (TreeMotif) algorithm capable of discovering longer and weaker motifs than by the existing methods.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76423, 2011, 'bio', 'NeuroPedia: neuropeptide database and spectral library', 'Kim, Yoona|Bark, Steven|Hook, Vivian|Bandeira, Nuno', 'Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, California 92093-0744, USA.|Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, California 92093-0744, USA.|Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, California 92093-0744, USA.|Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, California 92093-0744, USA.', 'United States|United States|United States|United States', 0, 'Amino Acid Sequence|Animals|Databases, Protein|High-Throughput Screening Assays|Humans|Internet|Mass Spectrometry|Neuropeptides|Peptide Library|Peptides|Sensitivity and Specificity|Tandem Mass Spectrometry', 'Journal Article', '10.1093/bioinformatics/btr445', '21821666', 'Neuropeptides are essential for cell-cell communication in neurological and endocrine physiological processes in health and disease. While many neuropeptides have been identified in previous studies, the resulting data has not been structured to facilitate further analysis by tandem mass spectrometry (MS/MS), the main technology for high-throughput neuropeptide identification. Many neuropeptides are difficult to identify when searching MS/MS spectra against large protein databases because of their atypical lengths (e.g. shorter/longer than common tryptic peptides) and lack of tryptic residues to facilitate peptide ionization/fragmentation. NeuroPedia is a neuropeptide encyclopedia of peptide sequences (including genomic and taxonomic information) and spectral libraries of identified MS/MS spectra of homolog neuropeptides from multiple species. Searching neuropeptide MS/MS data against known NeuroPedia sequences will improve the sensitivity of database search tools. Moreover, the availability of neuropeptide spectral libraries will also enable the utilization of spectral library search tools, which are known to further improve the sensitivity of peptide identification. These will also reinforce the confidence in peptide identifications by enabling visual comparisons between new and previously identified neuropeptide MS/MS spectra.'),
(76424, 2011, 'bio', 'Inferring disease and gene set associations with rank coherence in networks', 'Hwang, TaeHyun|Zhang, Wei|Xie, Maoqiang|Liu, Jinfeng|Kuang, Rui', 'Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN 55455, USA.|Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN 55455, USA.|Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN 55455, USA.|Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN 55455, USA.|Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN 55455, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|DNA Copy Number Variations|Databases, Genetic|Disease|Gene Expression Profiling|Gene Regulatory Networks|Genes|Genome-Wide Association Study|Genomics|Humans|Models, Genetic|Phenotype|Reproducibility of Results', 'Journal Article', '10.1093/bioinformatics/btr463', '21824970', 'To validate the candidate disease genes identified from high-throughput genomic studies, a necessary step is to elucidate the associations between the set of candidate genes and disease phenotypes. The conventional gene set enrichment analysis often fails to reveal associations between disease phenotypes and the gene sets with a short list of poorly annotated genes, because the existing annotations of disease-causative genes are incomplete. This article introduces a network-based computational approach called rcNet to discover the associations between gene sets and disease phenotypes. A learning framework is proposed to maximize the coherence between the predicted phenotype-gene set relations and the known disease phenotype-gene associations. An efficient algorithm coupling ridge regression with label propagation and two variants are designed to find the optimal solution to the objective functions of the learning framework.'),
(76425, 2011, 'bio', 'FDM: a graph-based statistical method to detect differential transcription using RNA-seq data', 'Singh, Darshan|Orellana, Christian F|Hu, Yin|Jones, Corbin D|Liu, Yufeng|Chiang, Derek Y|Liu, Jinze|Prins, Jan F', 'Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. darshan@email.unc.edu|Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. darshan@email.unc.edu|Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. darshan@email.unc.edu|Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. darshan@email.unc.edu|Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. darshan@email.unc.edu|Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. darshan@email.unc.edu|Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. darshan@email.unc.edu|Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. darshan@email.unc.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 38, 'Alternative Splicing|Gene Expression Profiling|Genome|Humans|Models, Genetic|Protein Isoforms|RNA|Sequence Analysis, RNA|Transcription, Genetic|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btr458', '21824971', 'In eukaryotic cells, alternative splicing expands the diversity of RNA transcripts and plays an important role in tissue-specific differentiation, and can be misregulated in disease. To understand these processes, there is a great need for methods to detect differential transcription between samples. Our focus is on samples observed using short-read RNA sequencing (RNA-seq).'),
(76426, 2011, 'bio', 'Metannogen: annotation of biological reaction networks', 'Gille, Christoph|Hübner, Katrin|Hoppe, Andreas|Holzhütter, Hermann-Georg', 'Institute of Biochemistry, Computational Systems Biochemistry Group, Universitätsmedizin Berlin (Charité), Reinickendorfer Strasse 61, D-13347 Berlin, Germany. christoph.gille@charite.de|Institute of Biochemistry, Computational Systems Biochemistry Group, Universitätsmedizin Berlin (Charité), Reinickendorfer Strasse 61, D-13347 Berlin, Germany. christoph.gille@charite.de|Institute of Biochemistry, Computational Systems Biochemistry Group, Universitätsmedizin Berlin (Charité), Reinickendorfer Strasse 61, D-13347 Berlin, Germany. christoph.gille@charite.de|Institute of Biochemistry, Computational Systems Biochemistry Group, Universitätsmedizin Berlin (Charité), Reinickendorfer Strasse 61, D-13347 Berlin, Germany. christoph.gille@charite.de', 'Germany|Germany|Germany|Germany', 4, 'Biological Phenomena|Database Management Systems|Metabolic Networks and Pathways|Models, Biological|Software Design', 'Journal Article', '10.1093/bioinformatics/btr456', '21824972', 'Semantic annotations of the biochemical entities constituting a biological reaction network are indispensable to create biologically meaningful networks. They further heighten efficient exchange, reuse and merging of existing models which concern present-day systems biology research more often. Two types of tools for the reconstruction of biological networks currently exist: (i) several sophisticated programs support graphical network editing and visualization. (ii) Data management systems permit reconstruction and curation of huge networks in a team of scientists including data integration, annotation and cross-referencing. We seeked ways to combine the advantages of both approaches.'),
(76427, 2011, 'bio', 'A biclustering algorithm for extracting bit-patterns from binary datasets', 'Rodriguez-Baena, Domingo S|Perez-Pulido, Antonio J|Aguilar-Ruiz, Jesus S', 'School of Engineering, Pablo de Olavide University, Seville, Spain. dsrodbae@upo.es|School of Engineering, Pablo de Olavide University, Seville, Spain. dsrodbae@upo.es|School of Engineering, Pablo de Olavide University, Seville, Spain. dsrodbae@upo.es', 'Spain|Spain|Spain', 0, 'Algorithms|Central Nervous System Neoplasms|Cluster Analysis|Computational Biology|Data Mining|Databases, Factual|Gene Expression|Humans|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btr464', '21824973', 'Binary datasets represent a compact and simple way to store data about the relationships between a group of objects and their possible properties. In the last few years, different biclustering algorithms have been specially developed to be applied to binary datasets. Several approaches based on matrix factorization, suffix trees or divide-and-conquer techniques have been proposed to extract useful biclusters from binary data, and these approaches provide information about the distribution of patterns and intrinsic correlations.'),
(76428, 2011, 'bio', 'NetDS: a Cytoscape plugin to analyze the robustness of dynamics and feedforward/feedback loop structures of biological networks', 'Le, Duc-Hau|Kwon, Yung-Keun', 'School of Electrical Engineering, University of Ulsan, 93, Daehak-ro, Nam-gu, Ulsan 680-749.|School of Electrical Engineering, University of Ulsan, 93, Daehak-ro, Nam-gu, Ulsan 680-749.', '-|-', 20, 'Algorithms|Feedback, Physiological|Metabolic Networks and Pathways|Models, Biological|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/btr466', '21828085', 'NetDS is a novel Cytoscape plugin that conveniently simulates dynamics related to robustness, and examines structural properties with respect to feedforward/feedback loops. It can evaluate how robustly a network sustains a stable state against mutations by employing a Boolean network model. In addition, the plugin can examine all feedforward/feedback loops appearing in a network and determine whether or not a pair of loops is coupled. Random networks can also be generated to evaluate whether or not an interesting finding in real biological networks is significantly random.'),
(76429, 2011, 'bio', 'Exome sequencing-based copy-number variation and loss of heterozygosity detection: ExomeCNV', 'Sathirapongsasuti, Jarupon Fah|Lee, Hane|Horst, Basil A J|Brunner, Georg|Cochran, Alistair J|Binder, Scott|Quackenbush, John|Nelson, Stanley F', 'Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. fsathira@fas.harvard.edu|Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. fsathira@fas.harvard.edu|Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. fsathira@fas.harvard.edu|Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. fsathira@fas.harvard.edu|Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. fsathira@fas.harvard.edu|Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. fsathira@fas.harvard.edu|Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. fsathira@fas.harvard.edu|Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. fsathira@fas.harvard.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 266, 'Algorithms|Base Sequence|DNA Copy Number Variations|Exome|Genotype|Humans|Loss of Heterozygosity|Melanoma|Models, Genetic|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Skin Neoplasms', 'Journal Article', '10.1093/bioinformatics/btr462', '21828086', 'The ability to detect copy-number variation (CNV) and loss of heterozygosity (LOH) from exome sequencing data extends the utility of this powerful approach that has mainly been used for point or small insertion/deletion detection.'),
(76430, 2011, 'bio', 'OrganismTagger: detection, normalization and grounding of organism entities in biomedical documents', 'Naderi, Nona|Kappler, Thomas|Baker, Christopher J O|Witte, René', 'Department of Computer Science and Software Engineering, Concordia University, Montréal, Québec, Canada.|Department of Computer Science and Software Engineering, Concordia University, Montréal, Québec, Canada.|Department of Computer Science and Software Engineering, Concordia University, Montréal, Québec, Canada.|Department of Computer Science and Software Engineering, Concordia University, Montréal, Québec, Canada.', 'Canada|Canada|Canada|Canada', 0, 'Algorithms|Artificial Intelligence|Classification|Data Mining|Humans|Natural Language Processing|Publications|Semantics|Terminology as Topic|Unified Medical Language System', 'Journal Article', '10.1093/bioinformatics/btr452', '21828087', 'Semantic tagging of organism mentions in full-text articles is an important part of literature mining and semantic enrichment solutions. Tagged organism mentions also play a pivotal role in disambiguating other entities in a text, such as proteins. A high-precision organism tagging system must be able to detect the numerous forms of organism mentions, including common names as well as the traditional taxonomic groups: genus, species and strains. In addition, such a system must resolve abbreviations and acronyms, assign the scientific name and if possible link the detected mention to the NCBI Taxonomy database for further semantic queries and literature navigation.'),
(76431, 2011, 'bio', 'Automatic detection of changes in the dynamics of delayed stochastic gene networks and in vivo production of RNA molecules in Escherichia coli', 'Mäkelä, Jarno|Huttunen, Heikki|Kandhavelu, Meenakshisundaram|Yli-Harja, Olli|Ribeiro, Andre S', 'Computational Systems Biology Research Group, Department of Signal Processing, Tampere University of Technology, FI-33101 Tampere, Finland.|Computational Systems Biology Research Group, Department of Signal Processing, Tampere University of Technology, FI-33101 Tampere, Finland.|Computational Systems Biology Research Group, Department of Signal Processing, Tampere University of Technology, FI-33101 Tampere, Finland.|Computational Systems Biology Research Group, Department of Signal Processing, Tampere University of Technology, FI-33101 Tampere, Finland.|Computational Systems Biology Research Group, Department of Signal Processing, Tampere University of Technology, FI-33101 Tampere, Finland.', 'Finland|Finland|Finland|Finland|Finland', 0, 'Algorithms|Escherichia coli|Gene Expression Regulation|Gene Regulatory Networks|Gene Silencing|Humans|Models, Genetic|Proteins|RNA|Saccharomyces cerevisiae|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/btr471', '21835771', 'Production and degradation of RNA and proteins are stochastic processes, difficulting the distinction between spurious fluctuations in their numbers and changes in the dynamics of a genetic circuit. An accurate method of change detection is key to analyze plasticity and robustness of stochastic genetic circuits.'),
(76432, 2011, 'bio', 'Contextual analysis of RNAi-based functional screens using interaction networks', 'Gonzalez, Orland|Zimmer, Ralf', 'Institut für Informatik, Ludwig-Maximilians-Universität München, 80333 München, Germany. gonzalez@bio.ifi.lmu.de|Institut für Informatik, Ludwig-Maximilians-Universität München, 80333 München, Germany. gonzalez@bio.ifi.lmu.de', 'Germany|Germany', 10, 'Gene Expression Profiling|Gene Regulatory Networks|Genome|Hepacivirus|Hepatitis C|Humans|RNA Interference', 'Journal Article', '10.1093/bioinformatics/btr469', '21835772', 'Considerable attention has been directed in recent years toward the development of methods for the contextual analysis of expression data using interaction networks. Of particular interest has been the identification of active subnetworks by detecting regions enriched with differential expression. In contrast, however, very little effort has been made toward the application of comparable methods to other types of high-throughput data.'),
(76433, 2011, 'bio', 'Conserved and differential gene interactions in dynamical biological systems', 'Ouyang, Zhengyu|Song, Mingzhou|Güth, Robert|Ha, Thomas J|Larouche, Matt|Goldowitz, Dan', 'Department of Computer Science, New Mexico State University, Las Cruces, NM 88003, USA.|Department of Computer Science, New Mexico State University, Las Cruces, NM 88003, USA.|Department of Computer Science, New Mexico State University, Las Cruces, NM 88003, USA.|Department of Computer Science, New Mexico State University, Las Cruces, NM 88003, USA.|Department of Computer Science, New Mexico State University, Las Cruces, NM 88003, USA.|Department of Computer Science, New Mexico State University, Las Cruces, NM 88003, USA.', 'Mexico|Mexico|Mexico|Mexico|Mexico|Mexico', 7, 'Animals|Cerebellum|Gene Expression|Gene Expression Profiling|Gene Expression Regulation|Gene Regulatory Networks|Mice|Models, Biological', 'Journal Article', '10.1093/bioinformatics/btr472', '21840874', 'While biological systems operated from a common genome can be conserved in various ways, they can also manifest highly diverse dynamics and functions. This is because the same set of genes can interact differentially across specific molecular contexts. For example, differential gene interactions give rise to various stages of morphogenesis during cerebellar development. However, after over a decade of efforts toward reverse engineering biological networks from high-throughput omic data, gene networks of most organisms remain sketchy. This hindrance has motivated us to develop comparative modeling to highlight conserved and differential gene interactions across experimental conditions, without reconstructing complete gene networks first.'),
(76434, 2011, 'bio', 'Absynte: a web tool to analyze the evolution of orthologous archaeal and bacterial gene clusters', 'Despalins, Arnaud|Marsit, Souhir|Oberto, Jacques', 'Université Paris-Sud 11, CNRS, UMR8621, Institut de Génétique et Microbiologie, 91405 Orsay Cedex, France.|Université Paris-Sud 11, CNRS, UMR8621, Institut de Génétique et Microbiologie, 91405 Orsay Cedex, France.|Université Paris-Sud 11, CNRS, UMR8621, Institut de Génétique et Microbiologie, 91405 Orsay Cedex, France.', 'France|France|France', 31, 'Cluster Analysis|Evolution, Molecular|Genes, Archaeal|Genes, Bacterial|Genome, Archaeal|Genome, Bacterial|Genomics|Internet|Multigene Family|Software|Synteny', 'Journal Article', '10.1093/bioinformatics/btr473', '21840875', 'Absynte (Archaeal and Bacterial Synteny Explorer) is a web-based service designed to display local syntenies in completely sequenced prokaryotic chromosomes. The genomic contexts are determined with a multiple center star clustering topology on the basis of a user-provided protein sequence and all (or a set of) chromosomes from the publicly available archaeal and bacterial genomes. The results consist in a dynamic web page where a consistent color-coding permits a rapid visual evaluation of the relative positioning of genes with similar sequences within the synteny. Each gene composing the synteny can be further queried interactively using either local or remote databases. Absynte results can be exported in .CSV or high-resolution, .PDF formats for printing, archival, further editing or publication purposes. Performance, real-time computation, user-friendliness and daily database updates constitute the principal advantages of Absynte over similar web services.'),
(76435, 2011, 'bio', 'A phylogenetic mixture model for the identification of functionally divergent protein residues', 'Gaston, Daniel|Susko, Edward|Roger, Andrew J', 'Centre for Comparative Genomics and Evolutionary Bioinformatics, Dalhousie University, Halifax, Canada, B3H 1X5.|Centre for Comparative Genomics and Evolutionary Bioinformatics, Dalhousie University, Halifax, Canada, B3H 1X5.|Centre for Comparative Genomics and Evolutionary Bioinformatics, Dalhousie University, Halifax, Canada, B3H 1X5.', 'Canada|Canada|Canada', 18, 'Amino Acids|Evolution, Molecular|Models, Genetic|Phylogeny|Protein Binding|Proteins', 'Journal Article', '10.1093/bioinformatics/btr470', '21840876', 'To understand the evolution of molecular function within protein families, it is important to identify those amino acid residues responsible for functional divergence, i.e. those sites in a protein family that affect cofactor, protein or substrate binding preferences, affinity, catalysis, flexibility, or folding. Type I functional divergence (FD) results from changes in conservation (evolutionary rate) at a site between protein subfamilies, whereas type II FD occurs when there has been a shift in preferences for different amino acid chemical properties. A variety of methods have been developed for identifying both site types in protein subfamilies, both from phylogenetic and information-theoretic angles. However, evaluation of the performance of these methods has typically relied upon a handful of reasonably well-characterized biological datasets or analyses of a single biological example. While experimental validation of many truly functionally divergent sites (true positives) can be relatively straightforward, determining that particular sites do not contribute to functional divergence (i.e. false positives and true negatives) is much more difficult, resulting in noisy gold standard examples.'),
(76436, 2011, 'bio', 'ChimeraScan: a tool for identifying chimeric transcription in sequencing data', 'Iyer, Matthew K|Chinnaiyan, Arul M|Maher, Christopher A', 'Michigan Center for Translational Pathology, University of Michigan Medical School, Ann Arbor, MI 48109, USA.|Michigan Center for Translational Pathology, University of Michigan Medical School, Ann Arbor, MI 48109, USA.|Michigan Center for Translational Pathology, University of Michigan Medical School, Ann Arbor, MI 48109, USA.', 'United States|United States|United States', 175, 'Cell Line, Tumor|Gene Expression Profiling|Gene Fusion|High-Throughput Nucleotide Sequencing|Humans|Neoplasms|Sequence Analysis, RNA|Software|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btr467', '21840877', 'Next generation sequencing (NGS) technologies have enabled de novo gene fusion discovery that could reveal candidates with therapeutic significance in cancer. Here we present an open-source software package, ChimeraScan, for the discovery of chimeric transcription between two independent transcripts in high-throughput transcriptome sequencing data.'),
(76437, 2011, 'bio', 'A framework for analytical characterization of monoclonal antibodies based on reactivity profiles in different tissues', 'Rossin, Elizabeth|Lin, Tsung-I|Ho, Hsiu J|Mentzer, Steven J|Pyne, Saumyadipta', 'Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA.|Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA.|Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA.|Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA.|Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA.', 'United States|United States|United States|United States|United States', 10, 'Algorithms|Animals|Antibodies, Monoclonal|Antigen-Antibody Reactions|Cells|Cluster Analysis|Flow Cytometry|Mice|Models, Biological|Sheep|Software', 'Journal Article', '10.1093/bioinformatics/btr468', '21846734', 'Monoclonal antibodies (mAbs) are among the most powerful and important tools in biology and medicine. MAb development is of great significance to many research and clinical applications. Therefore, objective mAb classification is essential for categorizing and comparing mAb panels based on their reactivity patterns in different cellular species. However, typical flow cytometric mAb profiles present unique modeling challenges with their non-Gaussian features and intersample variations. It makes accurate mAb classification difficult to do with the currently used kernel-based or hierarchical clustering techniques.'),
(76438, 2011, 'bio', 'Reconstructing the architecture of the ancestral amniote genome', 'Ouangraoua, Aïda|Tannier, Eric|Chauve, Cedric', 'INRIA Lille-Nord-Europe, Université Lille 1, LIFL, UMR CNRS 8022, Villeneuve dAscq, Villeurbanne, France.|INRIA Lille-Nord-Europe, Université Lille 1, LIFL, UMR CNRS 8022, Villeneuve dAscq, Villeurbanne, France.|INRIA Lille-Nord-Europe, Université Lille 1, LIFL, UMR CNRS 8022, Villeneuve dAscq, Villeurbanne, France.', 'France|France|France', 21, 'Animals|Biological Evolution|Birds|Chromosomes|Evolution, Molecular|Genetic Linkage|Genome|Mammals|Synteny|Vertebrates', 'Journal Article', '10.1093/bioinformatics/btr461', '21846735', 'The ancestor of birds and mammals lived approximately 300 million years ago. Inferring its genome organization is key to understanding the differentiated evolution of these two lineages. However, detecting traces of its chromosomal organization in its extant descendants is difficult due to the accumulation of molecular evolution since birds and mammals lineages diverged.'),
(76439, 2011, 'bio', 'The use of semiparametric mixed models to analyze PamChip(R) peptide array data: an application to an oncology experiment', 'Thilakarathne, Pushpike J|Clement, Lieven|Lin, Dan|Shkedy, Ziv|Kasim, Adetayo|Talloen, Willem|Versele, Matthias|Verbeke, Geert', 'Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Katholieke Universiteit Leuven, B3000 Leuven, Belgium. pushpike@med.kuleuven.be|Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Katholieke Universiteit Leuven, B3000 Leuven, Belgium. pushpike@med.kuleuven.be|Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Katholieke Universiteit Leuven, B3000 Leuven, Belgium. pushpike@med.kuleuven.be|Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Katholieke Universiteit Leuven, B3000 Leuven, Belgium. pushpike@med.kuleuven.be|Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Katholieke Universiteit Leuven, B3000 Leuven, Belgium. pushpike@med.kuleuven.be|Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Katholieke Universiteit Leuven, B3000 Leuven, Belgium. pushpike@med.kuleuven.be|Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Katholieke Universiteit Leuven, B3000 Leuven, Belgium. pushpike@med.kuleuven.be|Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Katholieke Universiteit Leuven, B3000 Leuven, Belgium. pushpike@med.kuleuven.be', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 4, 'Cell Line, Tumor|Confidence Intervals|Humans|Microarray Analysis|Models, Statistical|Peptides|Phosphorylation|Protein Kinase Inhibitors|Protein Kinases', 'Journal Article', '10.1093/bioinformatics/btr475', '21846736', 'Phosphorylation by protein kinases is a central theme in biological systems. Aberrant protein kinase activity has been implicated in a variety of human diseases (e.g. cancer). Therefore, modulation of kinase activity represents an attractive therapeutic approach for the treatment of human illnesses. Thus, identification of signature peptides is crucial for protein kinase targeting and can be achieved by using PamChip(®) microarray technology. We propose a flexible semiparametric mixed model for analyzing PamChip(®) data. This approach enables the estimation of the phosphorylation rate (Velocity) as a function of time together with pointwise confidence intervals.'),
(76440, 2011, 'bio', 'cSSMD: assessing collective activity for addressing off-target effects in genome-scale RNA interference screens', 'Zhang, Xiaohua Douglas|Santini, Francesca|Lacson, Raul|Marine, Shane D|Wu, Qian|Benetti, Luca|Yang, Ruojing|McCampbell, Alex|Berger, Joel P|Toolan, Dawn M|Stec, Erica M|Holder, Daniel J|Soper, Keith A|Heyse, Joseph F|Ferrer, Marc', 'Biometrics Research, Merck Research Laboratories, West Point, PA 19486, USA. xiaohua_zhang@merck.com|Biometrics Research, Merck Research Laboratories, West Point, PA 19486, USA. xiaohua_zhang@merck.com|Biometrics Research, Merck Research Laboratories, West Point, PA 19486, USA. xiaohua_zhang@merck.com|Biometrics Research, Merck Research Laboratories, West Point, PA 19486, USA. xiaohua_zhang@merck.com|Biometrics Research, Merck Research Laboratories, West Point, PA 19486, USA. xiaohua_zhang@merck.com|Biometrics Research, Merck Research Laboratories, West Point, PA 19486, USA. xiaohua_zhang@merck.com|Biometrics Research, Merck Research Laboratories, West Point, PA 19486, USA. xiaohua_zhang@merck.com|Biometrics Research, Merck Research Laboratories, West Point, PA 19486, USA. xiaohua_zhang@merck.com|Biometrics Research, Merck Research Laboratories, West Point, PA 19486, USA. xiaohua_zhang@merck.com|Biometrics Research, Merck Research Laboratories, West Point, PA 19486, USA. xiaohua_zhang@merck.com|Biometrics Research, Merck Research Laboratories, West Point, PA 19486, USA. xiaohua_zhang@merck.com|Biometrics Research, Merck Research Laboratories, West Point, PA 19486, USA. xiaohua_zhang@merck.com|Biometrics Research, Merck Research Laboratories, West Point, PA 19486, USA. xiaohua_zhang@merck.com|Biometrics Research, Merck Research Laboratories, West Point, PA 19486, USA. xiaohua_zhang@merck.com|Biometrics Research, Merck Research Laboratories, West Point, PA 19486, USA. xiaohua_zhang@merck.com', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 14, 'Alzheimer Disease|Data Interpretation, Statistical|Diabetes Mellitus|Gene Knockdown Techniques|Genomics|Herpesvirus 3, Human|High-Throughput Screening Assays|Humans|RNA Interference|RNA, Small Interfering', 'Evaluation Studies', '10.1093/bioinformatics/btr474', '21846737', 'Off-target activity commonly exists in RNA interference (RNAi) screens and often generates false positives. Existing analytic methods for addressing the off-target effects are demonstrably inadequate in RNAi confirmatory screens.'),
(76441, 2011, 'bio', 'Identifying associations between amino acid changes and meta information in alignments', 'Spangenberg, L|Battke, F|Graña, M|Nieselt, K|Naya, H', 'Bioinformatics Unit, Institut Pasteur Montevideo, 11400 Montevideo, Uruguay.|Bioinformatics Unit, Institut Pasteur Montevideo, 11400 Montevideo, Uruguay.|Bioinformatics Unit, Institut Pasteur Montevideo, 11400 Montevideo, Uruguay.|Bioinformatics Unit, Institut Pasteur Montevideo, 11400 Montevideo, Uruguay.|Bioinformatics Unit, Institut Pasteur Montevideo, 11400 Montevideo, Uruguay.', 'Uruguay|Uruguay|Uruguay|Uruguay|Uruguay', 2, 'Bacterial Proteins|Genomics|Linear Models|Phylogeny|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sigma Factor', 'Journal Article', '10.1093/bioinformatics/btr476', '21846738', 'We present a method that identifies associations between amino acid changes in potentially significant sites in an alignment (taking into account several amino acid properties) with phenotypic data, through the phylogenetic mixed model. The latter accounts for the dependency of the observations (organisms). It is known from previous studies that the pathogenic aspect of many organisms may be associated with a single or just few changes in amino acids, which have a strong structural and/or functional impact on the protein. Discovering these sites is a big step toward understanding pathogenicity. Our method is able to discover such sites in proteins responsible for the pathogenic character of a group of bacteria.'),
(76442, 2011, 'bio', 'Robust synthetic gene network design via library-based search method', 'Wu, Chih-Hung|Lee, Hsiao-Ching|Chen, Bor-Sen', 'Lab of Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan 30013. g883743@alumni.nthu.edu.tw|Lab of Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan 30013. g883743@alumni.nthu.edu.tw|Lab of Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan 30013. g883743@alumni.nthu.edu.tw', '-|-|-', 18, 'Gene Expression Regulation|Gene Library|Gene Regulatory Networks|Genes, Synthetic|Models, Genetic|Promoter Regions, Genetic|Synthetic Biology', 'Journal Article', '10.1093/bioinformatics/btr465', '21849394', 'Synthetic biology aims to develop the artificial gene networks with desirable behaviors using systematic method. These networks with desired behaviors could be constructed using diverse biological parts, which may limit the development to complex synthetic gene networks. Fortunately, some well-characterized promoter libraries for engineering gene networks are widely available. Thus, a synthetic gene network can be constructed by selecting adequate promoters from promoter libraries to achieve the desired behaviors. However, the present promoter libraries cannot be directly applied to engineer a synthetic gene network. In order to efficiently select adequate promoters from promoter libraries for a synthetic gene network, promoter libraries are needed to be redefined based on the dynamic gene regulation.'),
(76443, 2011, 'bio', 'Simultaneous recognition and segmentation of cells: application in Celegans', 'Qu, Lei|Long, Fuhui|Liu, Xiao|Kim, Stuart|Myers, Eugene|Peng, Hanchuan', 'Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.|Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.|Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.|Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.|Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.|Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.', 'United States|United States|United States|United States|United States|United States', 20, 'Algorithms|Animals|Caenorhabditis elegans|Imaging, Three-Dimensional|Single-Cell Analysis', 'Journal Article', '10.1093/bioinformatics/btr480', '21849395', 'Automatic recognition of cell identities is critical for quantitative measurement, targeting and manipulation of cells of model animals at single-cell resolution. It has been shown to be a powerful tool for studying gene expression and regulation, cell lineages and cell fates. Existing methods first segment cells, before applying a recognition algorithm in the second step. As a result, the segmentation errors in the first step directly affect and complicate the subsequent cell recognition step. Moreover, in new experimental settings, some of the image features that have been previously relied upon to recognize cells may not be easy to reproduce, due to limitations on the number of color channels available for fluorescent imaging or to the cost of building transgenic animals. An approach that is more accurate and relies on only a single signal channel is clearly desirable.'),
(76444, 2011, 'bio', 'Improved quality control processing of peptide-centric LC-MS proteomics data', 'Matzke, Melissa M|Waters, Katrina M|Metz, Thomas O|Jacobs, Jon M|Sims, Amy C|Baric, Ralph S|Pounds, Joel G|Webb-Robertson, Bobbie-Jo M', 'Pacific Northwest National Laboratory, Richland, WA 99352, USA.|Pacific Northwest National Laboratory, Richland, WA 99352, USA.|Pacific Northwest National Laboratory, Richland, WA 99352, USA.|Pacific Northwest National Laboratory, Richland, WA 99352, USA.|Pacific Northwest National Laboratory, Richland, WA 99352, USA.|Pacific Northwest National Laboratory, Richland, WA 99352, USA.|Pacific Northwest National Laboratory, Richland, WA 99352, USA.|Pacific Northwest National Laboratory, Richland, WA 99352, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 50, 'Chromatography, Liquid|Data Interpretation, Statistical|Mass Spectrometry|Peptides|Proteome|Proteomics|Quality Control|Software', 'Journal Article', '10.1093/bioinformatics/btr479', '21852304', 'In the analysis of differential peptide peak intensities (i.e. abundance measures), LC-MS analyses with poor quality peptide abundance data can bias downstream statistical analyses and hence the biological interpretation for an otherwise high-quality dataset. Although considerable effort has been placed on assuring the quality of the peptide identification with respect to spectral processing, to date quality assessment of the subsequent peptide abundance data matrix has been limited to a subjective visual inspection of run-by-run correlation or individual peptide components. Identifying statistical outliers is a critical step in the processing of proteomics data as many of the downstream statistical analyses [e.g. analysis of variance (ANOVA)] rely upon accurate estimates of sample variance, and their results are influenced by extreme values.'),
(76445, 2011, 'bio', 'A deeper look into transcription regulatory code by preferred pair distance templates for transcription factor binding sites', 'Kulakovskiy, I V|Belostotsky, A A|Kasianov, A S|Esipova, N G|Medvedeva, Y A|Eliseeva, I A|Makeev, V J', 'Laboratory of Bioinformatics and System Biology, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia. ivan.kulakovskiy@gmail.com|Laboratory of Bioinformatics and System Biology, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia. ivan.kulakovskiy@gmail.com|Laboratory of Bioinformatics and System Biology, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia. ivan.kulakovskiy@gmail.com|Laboratory of Bioinformatics and System Biology, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia. ivan.kulakovskiy@gmail.com|Laboratory of Bioinformatics and System Biology, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia. ivan.kulakovskiy@gmail.com|Laboratory of Bioinformatics and System Biology, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia. ivan.kulakovskiy@gmail.com|Laboratory of Bioinformatics and System Biology, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia. ivan.kulakovskiy@gmail.com', '-|-|-|-|-|-|-', 5, 'Amino Acid Motifs|Binding Sites|DNA|Erythropoietin|Gene Expression Regulation|Genome|Humans|Hypoxia-Inducible Factor 1, alpha Subunit|Nucleotide Motifs|Protein Binding|Proteins|Regulatory Sequences, Nucleic Acid|Transcription Factors|Transcription Initiation Site', 'Journal Article', '10.1093/bioinformatics/btr453', '21852305', 'Modern experimental methods provide substantial information on protein-DNA recognition. Studying arrangements of transcription factor binding sites (TFBSs) of interacting transcription factors (TFs) advances understanding of the transcription regulatory code.'),
(76446, 2011, 'bio', 'PTPan--overcoming memory limitations in oligonucleotide string matching for primer/probe design', 'Eissler, Tilo|Hodges, Christopher P|Meier, Harald', 'Department of Informatics, Technische Universität München, Boltzmannstrasse 3, 85748 Garching, Germany.|Department of Informatics, Technische Universität München, Boltzmannstrasse 3, 85748 Garching, Germany.|Department of Informatics, Technische Universität München, Boltzmannstrasse 3, 85748 Garching, Germany.', 'Germany|Germany|Germany', 2, 'Algorithms|DNA Primers|Oligonucleotide Probes|Sequence Analysis, DNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btr483', '21856736', 'Nucleic acid diagnostics has high demands for non-heuristic exact and approximate oligonucleotide string matching concerning in silico primer/probe design in huge nucleic acid sequence collections. Unfortunately, public sequence repositories grow much faster than computer hardware performance and main memory capacity do. This growth imposes severe problems on existing oligonucleotide primer/probe design applications necessitating new approaches based on space-efficient indexing structures.'),
(76447, 2011, 'bio', 'Comparative analysis of algorithms for next-generation sequencing read alignment', 'Ruffalo, Matthew|LaFramboise, Thomas|Koyutürk, Mehmet', 'Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA. matthew.ruffalo@case.edu|Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA. matthew.ruffalo@case.edu|Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA. matthew.ruffalo@case.edu', 'United States|United States|United States', 138, 'Algorithms|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|INDEL Mutation|Sequence Alignment|Software', 'Comparative Study', '10.1093/bioinformatics/btr477', '21856737', 'The advent of next-generation sequencing (NGS) techniques presents many novel opportunities for many applications in life sciences. The vast number of short reads produced by these techniques, however, pose significant computational challenges. The first step in many types of genomic analysis is the mapping of short reads to a reference genome, and several groups have developed dedicated algorithms and software packages to perform this function. As the developers of these packages optimize their algorithms with respect to various considerations, the relative merits of different software packages remain unclear. However, for scientists who generate and use NGS data for their specific research projects, an important consideration is choosing the software that is most suitable for their application.'),
(76448, 2011, 'bio', 'Detecting biological network organization and functional gene orthologs', 'Cui, Jike|DeLuca, Todd F|Jung, Jae-Yoon|Wall, Dennis P', 'The Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.|The Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.|The Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.|The Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.', 'United States|United States|United States|United States', 1, 'Databases, Genetic|Evolution, Molecular|Genes, Bacterial|Genome, Bacterial|Genomics|Models, Biological|Phylogeny|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btr485', '21856738', 'We developed a package TripletSearch to compute relationships within triplets of genes based on Roundup, an orthologous gene database containing >1500 genomes. These relationships, derived from the coevolution of genes, provide valuable information in the detection of biological network organization from the local to the system level, in the inference of protein functions and in the identification of functional orthologs. To run the computation, users need to provide the GI IDs of the genes of interest.'),
(76449, 2011, 'bio', 'Integration of SNP genotyping confidence scores in IBD inference', 'Markus, Barak|Birk, Ohad S|Geiger, Dan', 'The Morris Kahn Laboratory of Human Genetics, Department of Virology and Developmental Genetics, NIBN, Ben Gurion University, Israel. markusb@bgu.ac.il|The Morris Kahn Laboratory of Human Genetics, Department of Virology and Developmental Genetics, NIBN, Ben Gurion University, Israel. markusb@bgu.ac.il|The Morris Kahn Laboratory of Human Genetics, Department of Virology and Developmental Genetics, NIBN, Ben Gurion University, Israel. markusb@bgu.ac.il', 'Israel|Israel|Israel', 9, 'Algorithms|Genotype|Genotyping Techniques|Humans|Markov Chains|Models, Statistical|Pedigree|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btr486', '21862568', 'High-throughput single nucleotide polymorphism (SNP) arrays have become the standard platform for linkage and association analyses. The high SNP density of these platforms allows high-resolution identification of ancestral recombination events even for distant relatives many generations apart. However, such inference is sensitive to marker mistyping and current error detection methods rely on the genotyping of additional close relatives. Genotyping algorithms provide a confidence score for each marker call that is currently not integrated in existing methods. There is a need for a model that incorporates this prior information within the standard identical by descent (IBD) and association analyses.'),
(76450, 2011, 'bio', 'SDRS--an algorithm for analyzing large-scale dose-response data', 'Ji, Rui-Ru|Siemers, Nathan O|Lei, Ming|Schweizer, Liang|Bruccoleri, Robert E', 'Department of Applied Genomics, Bristol-Myers Squibb, Princeton, NJ 08543, USA. ruiruji@gmail.com|Department of Applied Genomics, Bristol-Myers Squibb, Princeton, NJ 08543, USA. ruiruji@gmail.com|Department of Applied Genomics, Bristol-Myers Squibb, Princeton, NJ 08543, USA. ruiruji@gmail.com|Department of Applied Genomics, Bristol-Myers Squibb, Princeton, NJ 08543, USA. ruiruji@gmail.com|Department of Applied Genomics, Bristol-Myers Squibb, Princeton, NJ 08543, USA. ruiruji@gmail.com', 'United States|United States|United States|United States|United States', 5, 'Algorithms|Dose-Response Relationship, Drug|Gene Expression Profiling|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btr489', '21865301', 'Dose-response information is critical to understanding drug effects, yet analytical methods for dose-response assays cannot cope with the dimensionality of large-scale screening data such as the microarray profiling data. To overcome this limitation, we developed and implemented the Sigmoidal Dose Response Search (SDRS) algorithm, a grid search-based method designed to handle large-scale dose-response data. This method not only calculates the pharmacological parameters for every assay, but also provides built-in statistic that enables downstream systematic analyses, such as characterizing dose response at the transcriptome level.'),
(76451, 2011, 'bio', 'Finding recurrent copy number alterations preserving within-sample homogeneity', 'Morganella, Sandro|Pagnotta, Stefano Maria|Ceccarelli, Michele', 'Department of Science, University of Sannio, 82100, Benevento, Italy. morganella@unisannio.it|Department of Science, University of Sannio, 82100, Benevento, Italy. morganella@unisannio.it|Department of Science, University of Sannio, 82100, Benevento, Italy. morganella@unisannio.it', 'Italy|Italy|Italy', 18, 'Algorithms|Comparative Genomic Hybridization|Genomic Structural Variation|Genomics|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis', 'Evaluation Studies', '10.1093/bioinformatics/btr488', '21873327', 'Copy number alterations (CNAs) represent an important component of genetic variation and play a significant role in many human diseases. Development of array comparative genomic hybridization (aCGH) technology has made it possible to identify CNAs. Identification of recurrent CNAs represents the first fundamental step to provide a list of genomic regions which form the basis for further biological investigations. The main problem in recurrent CNAs discovery is related to the need to distinguish between functional changes and random events without pathological relevance. Within-sample homogeneity represents a common feature of copy number profile in cancer, so it can be used as additional source of information to increase the accuracy of the results. Although several algorithms aimed at the identification of recurrent CNAs have been proposed, no attempt of a comprehensive comparison of different approaches has yet been published.'),
(76452, 2011, 'bio', 'iMod: multipurpose normal mode analysis in internal coordinates', 'Lopéz-Blanco, José Ramón|Garzón, José Ignacio|Chacón, Pablo', 'Department of Biological Chemical Physics, Rocasolano Physical Chemistry Institute, CSIC, Serrano 119, Madrid 28006, Spain.|Department of Biological Chemical Physics, Rocasolano Physical Chemistry Institute, CSIC, Serrano 119, Madrid 28006, Spain.|Department of Biological Chemical Physics, Rocasolano Physical Chemistry Institute, CSIC, Serrano 119, Madrid 28006, Spain.', 'Spain|Spain|Spain', 74, 'Models, Molecular|Monte Carlo Method|Nucleic Acid Conformation|Protein Conformation|Software', 'Journal Article', '10.1093/bioinformatics/btr497', '21873636', 'Dynamic simulations of systems with biologically relevant sizes and time scales are critical for understanding macromolecular functioning. Coarse-grained representations combined with normal mode analysis (NMA) have been established as an alternative to atomistic simulations. The versatility and efficiency of current approaches normally based on Cartesian coordinates can be greatly enhanced with internal coordinates (IC).');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76453, 2011, 'bio', 'Spatial clustering of protein binding sites for template based protein docking', 'Ghoorah, Anisah W|Devignes, Marie-Dominique|Smaïl-Tabbone, Malika|Ritchie, David W', 'INRIA, LORIA, Campus Scientifique, BP 239, 54506 Vandoeuvre-lès-Nancy, France.|INRIA, LORIA, Campus Scientifique, BP 239, 54506 Vandoeuvre-lès-Nancy, France.|INRIA, LORIA, Campus Scientifique, BP 239, 54506 Vandoeuvre-lès-Nancy, France.|INRIA, LORIA, Campus Scientifique, BP 239, 54506 Vandoeuvre-lès-Nancy, France.', 'France|France|France|France', 24, 'Binding Sites|Databases, Protein|Humans|Models, Molecular|Multiprotein Complexes|Protein Interaction Domains and Motifs|Protein Interaction Mapping', 'Journal Article', '10.1093/bioinformatics/btr493', '21873637', 'In recent years, much structural information on protein domains and their pair-wise interactions has been made available in public databases. However, it is not yet clear how best to use this information to discover general rules or interaction patterns about structural protein-protein interactions. Improving our ability to detect and exploit structural interaction patterns will help to provide a better 3D picture of the known protein interactome, and will help to guide docking-based predictions of the 3D structures of unsolved protein complexes.'),
(76454, 2011, 'bio', 'Feature-based 3D motif filtering for ribosomal RNA', 'Shen, Ying|Wong, Hau-San|Zhang, Shaohong|Yu, Zhiwen', 'Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong.|Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong.|Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong.|Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong.', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong', 3, 'Algorithms|Models, Molecular|Nucleotide Motifs|RNA, Ribosomal|Ribosome Subunits, Large, Archaeal', 'Journal Article', '10.1093/bioinformatics/btr495', '21873638', 'RNA 3D motifs are recurrent substructures in an RNA subunit and are building blocks of the RNA architecture. They play an important role in binding proteins and consolidating RNA tertiary structures. RNA 3D motif searching consists of two steps: candidate generation and candidate filtering. We proposed a novel method, known as Feature-based RNA Motif Filtering (FRMF), for identifying motifs based on a set of moment invariants and the Earth Movers Distance in the second step.'),
(76455, 2011, 'bio', 'SCLpred: protein subcellular localization prediction by N-to-1 neural networks', 'Mooney, Catherine|Wang, Yong-Hong|Pollastri, Gianluca', 'School of Computer Science and Informatics, University College Dublin, Belfield, Ireland.|School of Computer Science and Informatics, University College Dublin, Belfield, Ireland.|School of Computer Science and Informatics, University College Dublin, Belfield, Ireland.', 'Ireland|Ireland|Ireland', 35, 'Algorithms|Animals|Artificial Intelligence|Chloroplast Proteins|Cytoplasm|Fungal Proteins|Mitochondrial Proteins|Neural Networks (Computer)|Nuclear Proteins|Plant Proteins|Proteins|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/btr494', '21873639', 'Knowledge of the subcellular location of a protein provides valuable information about its function and possible interaction with other proteins. In the post-genomic era, fast and accurate predictors of subcellular location are required if this abundance of sequence data is to be fully exploited. We have developed a subcellular localization predictor (SCLpred), which predicts the location of a protein into four classes for animals and fungi and five classes for plants (secreted, cytoplasm, nucleus, mitochondrion and chloroplast) using machine learning models trained on large non-redundant sets of protein sequences. The algorithm powering SCLpred is a novel Neural Network (N-to-1 Neural Network, or N1-NN) we have developed, which is capable of mapping whole sequences into single properties (a functional class, in this work) without resorting to predefined transformations, but rather by adaptively compressing the sequence into a hidden feature vector. We benchmark SCLpred against other publicly available predictors using two benchmarks including a new subset of Swiss-Prot Release 2010_06. We show that SCLpred surpasses the state of the art. The N1-NN algorithm is fully general and may be applied to a host of problems of similar shape, that is, in which a whole sequence needs to be mapped into a fixed-size array of properties, and the adaptive compression it operates may shed light on the space of protein sequences.'),
(76456, 2011, 'bio', 'Fast and accurate prediction of protein side-chain conformations', 'Liang, Shide|Zheng, Dandan|Zhang, Chi|Standley, Daron M', 'Systems Immunology Lab, Immunology Frontier Research Center, Osaka University, Suita, Osaka 565-0871, Japan.|Systems Immunology Lab, Immunology Frontier Research Center, Osaka University, Suita, Osaka 565-0871, Japan.|Systems Immunology Lab, Immunology Frontier Research Center, Osaka University, Suita, Osaka 565-0871, Japan.|Systems Immunology Lab, Immunology Frontier Research Center, Osaka University, Suita, Osaka 565-0871, Japan.', 'Japan|Japan|Japan|Japan', 31, 'Algorithms|Models, Molecular|Protein Conformation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btr482', '21873640', 'We developed a fast and accurate side-chain modeling program [Optimized Side Chain Atomic eneRgy (OSCAR)-star] based on orientation-dependent energy functions and a rigid rotamer model. The average computing time was 18 s per protein for 218 test proteins with higher prediction accuracy (1.1% increase for xcfx87(1) and 0.8% increase for xcfx87(1+2)) than the best performing program developed by other groups. We show that the energy functions, which were calibrated to tolerate the discrete errors of rigid rotamers, are appropriate for protein loop selection, especially for decoys without extensive structural refinement.'),
(76457, 2011, 'bio', 'Extending KNIME for next-generation sequencing data analysis', 'Jagla, Bernd|Wiswedel, Bernd|Coppée, Jean-Yves', 'Departement Génomes et Génétique, Institut Pasteur, Plate-forme Transcriptome et Epigénome, 25 Rue du Docteur Roux, F-75015 Paris, France. bernd.jagla@pasteur.fr|Departement Génomes et Génétique, Institut Pasteur, Plate-forme Transcriptome et Epigénome, 25 Rue du Docteur Roux, F-75015 Paris, France. bernd.jagla@pasteur.fr|Departement Génomes et Génétique, Institut Pasteur, Plate-forme Transcriptome et Epigénome, 25 Rue du Docteur Roux, F-75015 Paris, France. bernd.jagla@pasteur.fr', 'France|France|France', 22, 'High-Throughput Nucleotide Sequencing|Software|Workflow', 'Journal Article', '10.1093/bioinformatics/btr478', '21873641', 'KNIME (Konstanz Information Miner) is a user-friendly and comprehensive open-source data integration, processing, analysis and exploration platform. We present here new functionality and workflows that open the door to performing next-generation sequencing analysis using the KNIME framework.'),
(76458, 2011, 'bio', 'COCOMAPS: a web application to analyze and visualize contacts at the interface of biomolecular complexes', 'Vangone, Anna|Spinelli, Raffaele|Scarano, Vittorio|Cavallo, Luigi|Oliva, Romina', 'Department of Chemistry and Biology, University of Salerno, 84084 Fisciano, Italy.|Department of Chemistry and Biology, University of Salerno, 84084 Fisciano, Italy.|Department of Chemistry and Biology, University of Salerno, 84084 Fisciano, Italy.|Department of Chemistry and Biology, University of Salerno, 84084 Fisciano, Italy.|Department of Chemistry and Biology, University of Salerno, 84084 Fisciano, Italy.', 'Italy|Italy|Italy|Italy|Italy', 0, 'DNA-Binding Proteins|Internet|Multiprotein Complexes|Nucleic Acid Conformation|Protein Conformation|Protein Interaction Mapping|Protein Interaction Maps|RNA-Binding Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btr484', '21873642', 'Herein we present COCOMAPS, a novel tool for analyzing, visualizing and comparing the interface in protein-protein and protein-nucleic acids complexes. COCOMAPS combines traditional analyses and 3D visualization of the interface with the effectiveness of intermolecular contact maps.'),
(76459, 2011, 'bio', 'Robustness portraits of diverse biological networks conserved despite order-of-magnitude parameter uncertainty', 'Soltis, Anthony R|Saucerman, Jeffrey J', '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', 0, 'Chemotaxis|Escherichia coli|Kinetics|Models, Biological|Myocardium|Receptors, Adrenergic, beta|Signal Transduction|Uncertainty', 'Journal Article', '10.1093/bioinformatics/btr496', '21880701', 'Biological networks are robust to a wide variety of internal and external perturbations, yet fragile or sensitive to a small minority of perturbations. Due to this rare sensitivity of networks to certain perturbations, it is unclear how precisely biochemical parameters must be experimentally measured in order to accurately predict network function.'),
(76460, 2011, 'bio', 'PepCrawler: a fast RRT-based algorithm for high-resolution refinement and binding affinity estimation of peptide inhibitors', 'Donsky, Elad|Wolfson, Haim J', 'Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. eladdons@tau.ac.il|Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. eladdons@tau.ac.il', 'Israel|Israel', 51, 'Algorithms|Drug Design|Models, Molecular|Multiprotein Complexes|Peptides|Protein Conformation|Protein Interaction Mapping', 'Journal Article', '10.1093/bioinformatics/btr498', '21880702', 'Design of protein-protein interaction (PPI) inhibitors is a key challenge in structural bioinformatics and computer-aided drug design. Peptides, which partially mimic the interface area of one of the interacting proteins, are natural candidates to form protein-peptide complexes competing with the original PPI. The prediction of such complexes is especially challenging due to the high flexibility of peptide conformations.'),
(76461, 2011, 'bio', 'AluHunter: a database of potentially polymorphic Alu insertions for use in primate phylogeny and population genetics', 'Bergey, Christina M', 'Department of Anthropology, New York University, New York, NY 10003, USA. cmb433@nyu.edu', 'United States', 0, 'Alu Elements|Animals|Databases, Nucleic Acid|Genetics, Population|Genomics|Phylogeny|Polymorphism, Genetic|Primates', 'Journal Article', '10.1093/bioinformatics/btr491', '21880703', 'AluHunter is a database of taxon-specific primate Alu elements for use in phylogeny and population genetics. The software automatically isolates potentially polymorphic Alu insertions in sequences submitted to GenBank by screening the elements against reference genomes. The resultant database of variable markers is a valuable resource for researchers interested in characterizing Alu elements in their primate taxon of interest.'),
(76462, 2011, 'bio', 'Gaussian interaction profile kernels for predicting drug-target interaction', 'van Laarhoven, Twan|Nabuurs, Sander B|Marchiori, Elena', 'Department of Computer Science, Radboud University Nijmegen, Nijmegen, The Netherlands. tvanlaarhoven@cs.ru.nl|Department of Computer Science, Radboud University Nijmegen, Nijmegen, The Netherlands. tvanlaarhoven@cs.ru.nl|Department of Computer Science, Radboud University Nijmegen, Nijmegen, The Netherlands. tvanlaarhoven@cs.ru.nl', 'Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Artificial Intelligence|Drug Delivery Systems|Drug Discovery|Genomics', 'Journal Article', '10.1093/bioinformatics/btr500', '21893517', 'The in silico prediction of potential interactions between drugs and target proteins is of core importance for the identification of new drugs or novel targets for existing drugs. However, only a tiny portion of all drug-target pairs in current datasets are experimentally validated interactions. This motivates the need for developing computational methods that predict true interaction pairs with high accuracy.'),
(76463, 2011, 'bio', 'SiTaR: a novel tool for transcription factor binding site prediction', 'Fazius, Eugen|Shelest, Vladimir|Shelest, Ekaterina', 'Research Group Systems Biology/Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology, Hans Knöll Institute, 07745 Jena, Germany.|Research Group Systems Biology/Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology, Hans Knöll Institute, 07745 Jena, Germany.|Research Group Systems Biology/Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology, Hans Knöll Institute, 07745 Jena, Germany.', 'Germany|Germany|Germany', 13, 'Binding Sites|Nucleotide Motifs|Promoter Regions, Genetic|Sensitivity and Specificity|Sequence Analysis, DNA|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr492', '21893518', 'Prediction of transcription factor binding sites (TFBSs) is crucial for promoter modeling and network inference. Quality of the predictions is spoiled by numerous false positives, which persist as the main problem for all presently available TFBS search methods.'),
(76464, 2011, 'bio', 'Integrated pathway-level analysis of transcriptomics and metabolomics data with IMPaLA', 'Kamburov, Atanas|Cavill, Rachel|Ebbels, Timothy M D|Herwig, Ralf|Keun, Hector C', 'Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany. kamburov@molgen.mpg.de|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany. kamburov@molgen.mpg.de|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany. kamburov@molgen.mpg.de|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany. kamburov@molgen.mpg.de|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany. kamburov@molgen.mpg.de', 'Germany|Germany|Germany|Germany|Germany', 0, 'Databases, Factual|Gene Expression Profiling|Internet|Metabolomics|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/btr499', '21893519', 'Pathway-level analysis is a powerful approach enabling interpretation of post-genomic data at a higher level than that of individual biomolecules. Yet, it is currently hard to integrate more than one type of omics data in such an approach. Here, we present a web tool IMPaLA for the joint pathway analysis of transcriptomics or proteomics and metabolomics data. It performs over-representation or enrichment analysis with user-specified lists of metabolites and genes using over 3000 pre-annotated pathways from 11 databases. As a result, pathways can be identified that may be disregulated on the transcriptional level, the metabolic level or both. Evidence of pathway disregulation is combined, allowing for the identification of additional pathways with changed activity that would not be highlighted when analysis is applied to any of the functional levels alone. The tool has been implemented both as an interactive website and as a web service to allow a programming interface.'),
(76465, 2011, 'bio', 'Semi-supervised learning improves gene expression-based prediction of cancer recurrence', 'Shi, Mingguang|Zhang, Bing', 'Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.', 'United States|United States', 41, 'Artificial Intelligence|Breast Neoplasms|Colonic Neoplasms|Disease-Free Survival|Female|Gene Expression Profiling|Humans|Neoplasm Recurrence, Local|Support Vector Machine', 'Evaluation Studies', '10.1093/bioinformatics/btr502', '21893520', 'Gene expression profiling has shown great potential in outcome prediction for different types of cancers. Nevertheless, small sample size remains a bottleneck in obtaining robust and accurate classifiers. Traditional supervised learning techniques can only work with labeled data. Consequently, a large number of microarray data that do not have sufficient follow-up information are disregarded. To fully leverage all of the precious data in public databases, we turned to a semi-supervised learning technique, low density separation (LDS).'),
(76466, 2011, 'bio', 'wapRNA: a web-based application for the processing of RNA sequences', 'Zhao, Wenming|Liu, Wanfei|Tian, Dongmei|Tang, Bixia|Wang, Yanqing|Yu, Caixia|Li, Rujiao|Ling, Yunchao|Wu, Jiayan|Song, Shuhui|Hu, Songnian', 'Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, PR China.|Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, PR China.|Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, PR China.|Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, PR China.|Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, PR China.|Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, PR China.|Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, PR China.|Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, PR China.|Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, PR China.|Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, PR China.|Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, PR China.', 'China|China|China|China|China|China|China|China|China|China|China', 0, 'Internet|MicroRNAs|RNA, Messenger|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btr504', '21896507', 'mRNA/miRNA-seq technology is becoming the leading technology to globally profile gene expression and elucidate the transcriptional regulation mechanisms in living cells. Although there are many tools available for analyzing RNA-seq data, few of them are available as easy accessible online web tools for processing both mRNA and miRNA data for the RNA-seq based user community. As such, we have developed a comprehensive web application tool for processing mRNA-seq and miRNA-seq data. Our web tool wapRNA includes four different modules: mRNA-seq and miRNA-seq sequenced from SOLiD or Solexa platform and all the modules were tested on previously published experimental data. We accept raw sequence data with an optional reads filter, followed by mapping and gene annotation or miRNA prediction. wapRNA also integrates downstream functional analyses such as Gene Ontology, KEGG pathway, miRNA targets prediction and comparison of genes or miRNAs different expression in different samples. Moreover, we provide the executable packages for installation on users local server.'),
(76467, 2011, 'bio', 'Correlated evolution of transcription factors and their binding sites', 'Yang, Shu|Yalamanchili, Hari Krishna|Li, Xinran|Yao, Kwok-Ming|Sham, Pak Chung|Zhang, Michael Q|Wang, Junwen', 'Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.|Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.|Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.|Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.|Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.|Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.|Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.', 'China|China|China|China|China|China|China', 17, 'Base Sequence|Binding Sites|DNA|Evolution, Molecular|Humans|Regulatory Elements, Transcriptional|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr503', '21896508', 'The interaction between transcription factor (TF) and transcription factor binding site (TFBS) is essential for gene regulation. Mutation in either the TF or the TFBS may weaken their interaction and thus result in abnormalities. To maintain such vital interaction, a mutation in one of the interacting partners might be compensated by a corresponding mutation in its binding partner during the course of evolution. Confirming this co-evolutionary relationship will guide us in designing protein sequences to target a specific DNA sequence or in predicting TFBS for poorly studied proteins, or even correcting and rescuing disease mutations in clinical applications.'),
(76468, 2011, 'bio', 'SpliceTrap: a method to quantify alternative splicing under single cellular conditions', 'Wu, Jie|Akerman, Martin|Sun, Shuying|McCombie, W Richard|Krainer, Adrian R|Zhang, Michael Q', 'Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Alternative Splicing|Bayes Theorem|Exons|Humans|Sequence Analysis, RNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/btr508', '21896509', 'Alternative splicing (AS) is a pre-mRNA maturation process leading to the expression of multiple mRNA variants from the same primary transcript. More than 90% of human genes are expressed via AS. Therefore, quantifying the inclusion level of every exon is crucial for generating accurate transcriptomic maps and studying the regulation of AS.'),
(76469, 2011, 'bio', 'Robust relative compression of genomes with random access', 'Deorowicz, Sebastian|Grabowski, Szymon', 'Institute of Informatics, Silesian University of Technology, 44-100 Gliwice, Poland. sebastian.deorowicz@polsl.pl|Institute of Informatics, Silesian University of Technology, 44-100 Gliwice, Poland. sebastian.deorowicz@polsl.pl', 'Poland|Poland', 71, 'Algorithms|Data Compression|Databases, Nucleic Acid|Genome, Human|Genomics|Humans|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btr505', '21896510', 'Storing, transferring and maintaining genomic databases becomes a major challenge because of the rapid technology progress in DNA sequencing and correspondingly growing pace at which the sequencing data are being produced. Efficient compression, with support for extraction of arbitrary snippets of any sequence, is the key to maintaining those huge amounts of data.'),
(76470, 2011, 'bio', 'Finding stable local optimal RNA secondary structures', 'Li, Yuan|Zhang, Shaojie', 'Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816, USA.|Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816, USA.', 'United States|United States', 0, 'Algorithms|Base Sequence|Molecular Sequence Data|Nucleic Acid Conformation|RNA|Riboswitch', 'Journal Article', '10.1093/bioinformatics/btr510', '21903624', 'Many RNAs, such as riboswitches, can fold into multiple alternate structures and perform different biological functions. These biologically functional structures usually have low free energies in their local energy landscapes and are very stable such that they cannot easily jump out of the current states and fold into other stable conformations. The conformational space of feasible RNA secondary structures is prohibitively large, and accurate prediction of functional structure conformations is challenging. Because the stability of an RNA secondary structure is determined predominantly by energetically favorable helical regions (stacks), we propose to use configurations of putative stacks to represent RNA secondary structures. By considering a reduced conformational space of local optimal stack configurations instead of all feasible RNA structures, we first present an algorithm for enumerating all possible local optimal stack configurations. In addition, we present a fast heuristic algorithm for approximating energy barriers encountered during folding pathways between each pair of local optimal stack configurations and finding all the stable local optimal structures.'),
(76471, 2011, 'bio', 'Comparing bioassay response and similarity ensemble approaches to probing protein pharmacology', 'Chen, Bin|McConnell, Kevin J|Wale, Nikil|Wild, David J|Gifford, Eric M', 'School of Informatics and Computing, Indiana University at Bloomington, Indiana, USA.|School of Informatics and Computing, Indiana University at Bloomington, Indiana, USA.|School of Informatics and Computing, Indiana University at Bloomington, Indiana, USA.|School of Informatics and Computing, Indiana University at Bloomington, Indiana, USA.|School of Informatics and Computing, Indiana University at Bloomington, Indiana, USA.', 'India|India|India|India|India', 12, 'Biological Assay|Cluster Analysis|Drug Design|Ligands|Protein Interaction Maps|Proteins', 'Journal Article', '10.1093/bioinformatics/btr506', '21903625', 'Networks to predict protein pharmacology can be created using ligand similarity or using known bioassay response profiles of ligands. Recent publications indicate that similarity methods can be highly accurate, but it has been unclear how similarity methods compare to methods that use bioassay response data directly.'),
(76472, 2011, 'bio', 'TopiaryExplorer: visualizing large phylogenetic trees with environmental metadata', 'Pirrung, Meg|Kennedy, Ryan|Caporaso, J Gregory|Stombaugh, Jesse|Wendel, Doug|Knight, Rob', 'Department of Pharmacology, University of Colorado Denver, Aurora, CO 80045, USA.|Department of Pharmacology, University of Colorado Denver, Aurora, CO 80045, USA.|Department of Pharmacology, University of Colorado Denver, Aurora, CO 80045, USA.|Department of Pharmacology, University of Colorado Denver, Aurora, CO 80045, USA.|Department of Pharmacology, University of Colorado Denver, Aurora, CO 80045, USA.|Department of Pharmacology, University of Colorado Denver, Aurora, CO 80045, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Environment|Phylogeny|Proteobacteria|Software', 'Journal Article', '10.1093/bioinformatics/btr517', '21903626', 'Microbial community profiling is a highly active area of research, but tools that facilitate visualization of phylogenetic trees and associated environmental data have not kept up with the increasing quantity of data generated in these studies.'),
(76473, 2011, 'bio', 'A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data', 'Li, Heng', 'Medical Population Genetics Program, Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA. hengli@broadinstitute.org', 'United States', 1655, 'Alleles|Data Interpretation, Statistical|Gene Frequency|Genetic Association Studies|Genetics, Population|Genotype|Humans|Mutation|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btr509', '21903627', 'Most existing methods for DNA sequence analysis rely on accurate sequences or genotypes. However, in applications of the next-generation sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample low-coverage sequencing or somatic mutation discovery). These applications press for the development of new methods for analyzing sequence data with uncertainty.'),
(76474, 2011, 'bio', 'An empirical comparison of several recent epistatic interaction detection methods', 'Wang, Yue|Liu, Guimei|Feng, Mengling|Wong, Limsoon', 'NUS Graduate School for Integrative Sciences and Engineering, Department of Computer Science, School of Computing, National University of Singapore and Data Mining Department, Institute for Infocomm Research, Singapore. wangyue@nus.edu.sg|NUS Graduate School for Integrative Sciences and Engineering, Department of Computer Science, School of Computing, National University of Singapore and Data Mining Department, Institute for Infocomm Research, Singapore. wangyue@nus.edu.sg|NUS Graduate School for Integrative Sciences and Engineering, Department of Computer Science, School of Computing, National University of Singapore and Data Mining Department, Institute for Infocomm Research, Singapore. wangyue@nus.edu.sg|NUS Graduate School for Integrative Sciences and Engineering, Department of Computer Science, School of Computing, National University of Singapore and Data Mining Department, Institute for Infocomm Research, Singapore. wangyue@nus.edu.sg', 'Singapore|Singapore|Singapore|Singapore', 48, 'Epistasis, Genetic|Genome-Wide Association Study|Polymorphism, Single Nucleotide|Software', 'Comparative Study', '10.1093/bioinformatics/btr512', '21903628', 'Many new methods have recently been proposed for detecting epistatic interactions in GWAS data. There is, however, no in-depth independent comparison of these methods yet.'),
(76475, 2011, 'bio', 'FLASH: fast length adjustment of short reads to improve genome assemblies', 'Magoxc4x8d, Tanja|Salzberg, Steven L', 'McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA. t.magoc@gmail.com|McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA. t.magoc@gmail.com', 'United States|United States', 0, 'Chromosomes, Human, Pair 14|Genome|Genomics|Humans|Sequence Analysis, DNA|Software|Staphylococcus aureus', 'Evaluation Studies', '10.1093/bioinformatics/btr507', '21903629', 'Next-generation sequencing technologies generate very large numbers of short reads. Even with very deep genome coverage, short read lengths cause problems in de novo assemblies. The use of paired-end libraries with a fragment size shorter than twice the read length provides an opportunity to generate much longer reads by overlapping and merging read pairs before assembling a genome.'),
(76476, 2011, 'bio', 'survcomp: an R/Bioconductor package for performance assessment and comparison of survival models', 'Schröder, Markus S|Culhane, Aedín C|Quackenbush, John|Haibe-Kains, Benjamin', 'Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. mschroed@jimmy.harvard.edu|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. mschroed@jimmy.harvard.edu|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. mschroed@jimmy.harvard.edu|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. mschroed@jimmy.harvard.edu', 'United States|United States|United States|United States', 0, 'Breast Neoplasms|Female|Humans|Meta-Analysis as Topic|Models, Statistical|Software|Survival Analysis', 'Journal Article', '10.1093/bioinformatics/btr511', '21903630', 'The survcomp package provides functions to assess and statistically compare the performance of survival/risk prediction models. It implements state-of-the-art statistics to (i) measure the performance of risk prediction models, (ii) combine these statistical estimates from multiple datasets using a meta-analytical framework, and (iii) statistically compare the performance of competitive models.'),
(76477, 2011, 'bio', 'Reconstructing transcription factor activities in hierarchical transcription network motifs', 'Ocone, Andrea|Sanguinetti, Guido', 'School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK.|School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK.', 'United Kingdom|United Kingdom', 0, 'Cell Line, Tumor|Gene Expression Regulation|Gene Regulatory Networks|Humans|Markov Chains|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr487', '21903631', 'A knowledge of the dynamics of transcription factors is fundamental to understand the transcriptional regulation mechanism. Nowadays, an experimental measure of transcription factor activities in vivo represents a challenge. Several methods have been developed to infer these activities from easily measurable quantities such as mRNA expression of target genes. A limitation of these methods is represented by the fact that they rely on very simple single-layer structures, typically consisting of one or more transcription factors regulating a number of target genes.'),
(76478, 2011, 'bio', 'Protein-protein binding affinity prediction on a diverse set of structures', 'Moal, Iain H|Agius, Rudi|Bates, Paul A', 'Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London WC2A 3LY, UK.|Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London WC2A 3LY, UK.|Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London WC2A 3LY, UK.', 'United Kingdom|United Kingdom|United Kingdom', 72, 'Artificial Intelligence|Multiprotein Complexes|Protein Binding|Protein Interaction Mapping', 'Journal Article', '10.1093/bioinformatics/btr513', '21903632', 'Accurate binding free energy functions for protein-protein interactions are imperative for a wide range of purposes. Their construction is predicated upon ascertaining the factors that influence binding and their relative importance. A recent benchmark of binding affinities has allowed, for the first time, the evaluation and construction of binding free energy models using a diverse set of complexes, and a systematic assessment of our ability to model the energetics of conformational changes.'),
(76479, 2011, 'bio', 'Revisiting the negative example sampling problem for predicting protein-protein interactions', 'Park, Yungki|Marcotte, Edward M', 'Center for Systems and Synthetic Biology, Institute of Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas 78712, USA. yungki@mail.utexas.edu|Center for Systems and Synthetic Biology, Institute of Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas 78712, USA. yungki@mail.utexas.edu', 'United States|United States', 46, 'Algorithms|Computational Biology|Humans|Protein Interaction Mapping|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btr514', '21908540', 'A number of computational methods have been proposed that predict protein-protein interactions (PPIs) based on protein sequence features. Since the number of potential non-interacting protein pairs (negative PPIs) is very high both in absolute terms and in comparison to that of interacting protein pairs (positive PPIs), computational prediction methods rely upon subsets of negative PPIs for training and validation. Hence, the need arises for subset sampling for negative PPIs.'),
(76480, 2011, 'bio', 'AUC-based biomarker ensemble with an application on gene scores predicting low bone mineral density', 'Zhao, X G|Dai, W|Li, Y|Tian, L', 'Department of Bone and Joint Surgery, The First Affiliated Hospital of Xian Medical University, Xian 710077, Shaanxi Province, PR China.|Department of Bone and Joint Surgery, The First Affiliated Hospital of Xian Medical University, Xian 710077, Shaanxi Province, PR China.|Department of Bone and Joint Surgery, The First Affiliated Hospital of Xian Medical University, Xian 710077, Shaanxi Province, PR China.|Department of Bone and Joint Surgery, The First Affiliated Hospital of Xian Medical University, Xian 710077, Shaanxi Province, PR China.', 'China|China|China|China', 9, 'Aged|Algorithms|Area Under Curve|Biomarkers|Bone Density|Female|Gene Expression|Humans|ROC Curve', 'Journal Article', '10.1093/bioinformatics/btr516', '21908541', 'The area under the receiver operating characteristic (ROC) curve (AUC), long regarded as a golden measure for the predictiveness of a continuous score, has propelled the need to develop AUC-based predictors. However, the AUC-based ensemble methods are rather scant, largely due to the fact that the associated objective function is neither continuous nor concave. Indeed, there is no reliable numerical algorithm identifying optimal combination of a set of biomarkers to maximize the AUC, especially when the number of biomarkers is large.'),
(76481, 2011, 'bio', 'HIV Therapy Simulator: a graphical user interface for comparing the effectiveness of novel therapy regimens', 'Lim, Huat Chye|Curlin, Marcel E|Mittler, John E', 'Department of Microbiology, University of Washington, Seattle, WA 98195, USA.|Department of Microbiology, University of Washington, Seattle, WA 98195, USA.|Department of Microbiology, University of Washington, Seattle, WA 98195, USA.', 'United States|United States|United States', 3, 'Anti-HIV Agents|Computer Graphics|Computer Simulation|HIV Infections|Humans|Models, Biological|Nevirapine|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr515', '21908542', 'Computer simulation models can be useful in exploring the efficacy of HIV therapy regimens in preventing the evolution of drug-resistant viruses. Current modeling programs, however, were designed by researchers with expertise in computational biology, limiting their accessibility to those who might lack such a background. We have developed a user-friendly graphical program, HIV Therapy Simulator (HIVSIM), that is accessible to non-technical users. The program allows clinicians and researchers to explore the effectiveness of various therapeutic strategies, such as structured treatment interruptions, booster therapies and induction-maintenance therapies. We anticipate that HIVSIM will be useful for evaluating novel drug-based treatment concepts in clinical research, and as an educational tool.'),
(76482, 2011, 'bio', 'Metavir: a web server dedicated to virome analysis', 'Roux, Simon|Faubladier, Michaël|Mahul, Antoine|Paulhe, Nils|Bernard, Aurélien|Debroas, Didier|Enault, François', 'Laboratoire Microorganismes: Génome et Environnement, Clermont Université, Université Blaise Pascal, BP 10448, F-63000 Clermont-Ferrand, France. simon.roux@univ-bpclermont.fr|Laboratoire Microorganismes: Génome et Environnement, Clermont Université, Université Blaise Pascal, BP 10448, F-63000 Clermont-Ferrand, France. simon.roux@univ-bpclermont.fr|Laboratoire Microorganismes: Génome et Environnement, Clermont Université, Université Blaise Pascal, BP 10448, F-63000 Clermont-Ferrand, France. simon.roux@univ-bpclermont.fr|Laboratoire Microorganismes: Génome et Environnement, Clermont Université, Université Blaise Pascal, BP 10448, F-63000 Clermont-Ferrand, France. simon.roux@univ-bpclermont.fr|Laboratoire Microorganismes: Génome et Environnement, Clermont Université, Université Blaise Pascal, BP 10448, F-63000 Clermont-Ferrand, France. simon.roux@univ-bpclermont.fr|Laboratoire Microorganismes: Génome et Environnement, Clermont Université, Université Blaise Pascal, BP 10448, F-63000 Clermont-Ferrand, France. simon.roux@univ-bpclermont.fr|Laboratoire Microorganismes: Génome et Environnement, Clermont Université, Université Blaise Pascal, BP 10448, F-63000 Clermont-Ferrand, France. simon.roux@univ-bpclermont.fr', 'France|France|France|France|France|France|France', 0, 'Genome, Viral|Internet|Metagenomics|Phylogeny|Software|Viruses', 'Journal Article', '10.1093/bioinformatics/btr519', '21911332', 'Metavir is a web server dedicated to the analysis of viral metagenomes (viromes). In addition to classical approaches for analyzing metagenomes (general sequence characteristics, taxonomic composition), new tools developed specifically for viral sequence analysis make it possible to: (i) explore viral diversity through automatically constructed phylogenies for selected marker genes, (ii) estimate gene richness through rarefaction curves and (iii) perform cross-comparison against other viromes using sequence similarities. Metavir is thus unique as a platform that allows a comprehensive virome analysis.'),
(76483, 2011, 'bio', 'SPREAD: spatial phylogenetic reconstruction of evolutionary dynamics', 'Bielejec, Filip|Rambaut, Andrew|Suchard, Marc A|Lemey, Philippe', 'Rega Institute for Medical Research, Clinical and Epidemiological Virology Section, Katholieke Universiteit Leuven, Leuven, Belgium. filip.bielejec@rega.kuleuven.be|Rega Institute for Medical Research, Clinical and Epidemiological Virology Section, Katholieke Universiteit Leuven, Leuven, Belgium. filip.bielejec@rega.kuleuven.be|Rega Institute for Medical Research, Clinical and Epidemiological Virology Section, Katholieke Universiteit Leuven, Leuven, Belgium. filip.bielejec@rega.kuleuven.be|Rega Institute for Medical Research, Clinical and Epidemiological Virology Section, Katholieke Universiteit Leuven, Leuven, Belgium. filip.bielejec@rega.kuleuven.be', 'Belgium|Belgium|Belgium|Belgium', 318, 'Bayes Theorem|Biological Evolution|Computer Graphics|Phylogeny|Phylogeography|Software', 'Journal Article', '10.1093/bioinformatics/btr481', '21911333', 'SPREAD is a user-friendly, cross-platform application to analyze and visualize Bayesian phylogeographic reconstructions incorporating spatial-temporal diffusion. The software maps phylogenies annotated with both discrete and continuous spatial information and can export high-dimensional posterior summaries to keyhole markup language (KML) for animation of the spatial diffusion through time in virtual globe software. In addition, SPREAD implements Bayes factor calculation to evaluate the support for hypotheses of historical diffusion among pairs of discrete locations based on Bayesian stochastic search variable selection estimates. SPREAD takes advantage of multicore architectures to process large joint posterior distributions of phylogenies and their spatial diffusion and produces visualizations as compelling and interpretable statistical summaries for the different spatial projections.'),
(76484, 2011, 'bio', 'High-dimensional bolstered error estimation', 'Sima, Chao|Braga-Neto, Ulisses M|Dougherty, Edward R', 'Computational Biology Division, Translational Genomics Research Institute, Phoenix, AZ, USA.|Computational Biology Division, Translational Genomics Research Institute, Phoenix, AZ, USA.|Computational Biology Division, Translational Genomics Research Institute, Phoenix, AZ, USA.', 'United States|United States|United States', 4, 'Algorithms|Breast Neoplasms|Data Interpretation, Statistical|Female|Gene Expression Profiling|Humans|Multiple Myeloma|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sample Size', 'Journal Article', '10.1093/bioinformatics/btr518', '21914630', 'In small-sample settings, bolstered error estimation has been shown to perform better than cross-validation and competitively with bootstrap with regard to various criteria. The key issue for bolstering performance is the variance setting for the bolstering kernel. Heretofore, this variance has been determined in a non-parametric manner from the data. Although bolstering based on this variance setting works well for small feature sets, results can deteriorate for high-dimensional feature spaces.'),
(76485, 2011, 'bio', 'MapReduce implementation of a hybrid spectral library-database search method for large-scale peptide identification', 'Kalyanaraman, Ananth|Cannon, William R|Latt, Benjamin|Baxter, Douglas J', 'School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99164-2752, USA. ananth@eecs.wsu.edu|School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99164-2752, USA. ananth@eecs.wsu.edu|School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99164-2752, USA. ananth@eecs.wsu.edu|School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99164-2752, USA. ananth@eecs.wsu.edu', 'United States|United States|United States|United States', 0, 'Databases, Protein|Mass Spectrometry|Peptides|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btr523', '21926122', 'A MapReduce-based implementation called MR-MSPolygraph for parallelizing peptide identification from mass spectrometry data is presented. The underlying serial method, MSPolygraph, uses a novel hybrid approach to match an experimental spectrum against a combination of a protein sequence database and a spectral library. Our MapReduce implementation can run on any Hadoop cluster environment. Experimental results demonstrate that, relative to the serial version, MR-MSPolygraph reduces the time to solution from weeks to hours, for processing tens of thousands of experimental spectra. Speedup and other related performance studies are also reported on a 400-core Hadoop cluster using spectral datasets from environmental microbial communities as inputs.'),
(76486, 2011, 'bio', 'Bambus 2: scaffolding metagenomes', 'Koren, Sergey|Treangen, Todd J|Pop, Mihai', 'Department of Computer Science, University of Maryland, College Park, MD 20742, USA.|Department of Computer Science, University of Maryland, College Park, MD 20742, USA.|Department of Computer Science, University of Maryland, College Park, MD 20742, USA.', 'United States|United States|United States', 83, 'Algorithms|Metagenome|Metagenomics|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/btr520', '21926123', 'Sequencing projects increasingly target samples from non-clonal sources. In particular, metagenomics has enabled scientists to begin to characterize the structure of microbial communities. The software tools developed for assembling and analyzing sequencing data for clonal organisms are, however, unable to adequately process data derived from non-clonal sources.'),
(76487, 2011, 'bio', 'adegenet 13-1: new tools for the analysis of genome-wide SNP data', 'Jombart, Thibaut|Ahmed, Ismaxc3xafl', 'MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College, Norfolk Place, London W2 1PG, UK. t.jombart@imperial.ac.uk|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College, Norfolk Place, London W2 1PG, UK. t.jombart@imperial.ac.uk', 'United Kingdom|United Kingdom', 941, 'Genetics, Population|Genome|Genome-Wide Association Study|Genomics|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btr521', '21926124', 'While the R software is becoming a standard for the analysis of genetic data, classical population genetics tools are being challenged by the increasing availability of genomic sequences. Dedicated tools are needed for harnessing the large amount of information generated by next-generation sequencing technologies. We introduce new tools implemented in the adegenet 1.3-1 package for handling and analyzing genome-wide single nucleotide polymorphism (SNP) data. Using a bit-level coding scheme for SNP data and parallelized computation, adegenet enables the analysis of large genome-wide SNPs datasets using standard personal computers.'),
(76488, 2011, 'bio', 'Discovering relational-based association rules with multiple minimum supports on microarray datasets', 'Liu, Yu-Cheng|Cheng, Chun-Pei|Tseng, Vincent S', 'Department of Computer Science and Information Engineering and Institute of Medical Informatics, National Cheng Kung University, Taiwan.|Department of Computer Science and Information Engineering and Institute of Medical Informatics, National Cheng Kung University, Taiwan.|Department of Computer Science and Information Engineering and Institute of Medical Informatics, National Cheng Kung University, Taiwan.', '-|-|-', 0, 'Algorithms|Gene Expression Profiling|Gene Expression Regulation|Gene Regulatory Networks|Oligonucleotide Array Sequence Analysis|Protein Interaction Maps|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1093/bioinformatics/btr526', '21926125', 'Association rule analysis methods are important techniques applied to gene expression data for finding expression relationships between genes. However, previous methods implicitly assume that all genes have similar importance, or they ignore the individual importance of each gene. The relation intensity between any two items has never been taken into consideration. Therefore, we proposed a technique named REMMAR (RElational-based Multiple Minimum supports Association Rules) algorithm to tackle this problem. This method adjusts the minimum relation support (MRS) for each gene pair depending on the regulatory relation intensity to discover more important association rules with stronger biological meaning.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76489, 2011, 'bio', 'Computational prediction of eukaryotic phosphorylation sites', 'Trost, Brett|Kusalik, Anthony', 'Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5C9, Canada. brett.trost@usask.ca|Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5C9, Canada. brett.trost@usask.ca', 'Canada|Canada', 105, 'Artificial Intelligence|Computational Biology|Eukaryota|Humans|Phosphorylation|Protein Kinases|Protein Processing, Post-Translational', 'Journal Article', '10.1093/bioinformatics/btr525', '21926126', 'Kinase-mediated phosphorylation is the central mechanism of post-translational modification to regulate cellular responses and phenotypes. Signaling defects associated with protein phosphorylation are linked to many diseases, particularly cancer. Characterizing protein kinases and their substrates enhances our ability to understand and treat such diseases and broadens our knowledge of signaling networks in general. While most or all protein kinases have been identified in well-studied eukaryotes, the sites that they phosphorylate have been only partially elucidated. Experimental methods for identifying phosphorylation sites are resource intensive, so the ability to computationally predict potential sites has considerable value.'),
(76490, 2011, 'bio', 'An efficient network querying method based on conditional random fields', 'Huang, Qiang|Wu, Ling-Yun|Zhang, Xiang-Sun', 'National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.|National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.|National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.', 'China|China|China', 11, 'Algorithms|Computational Biology|Gene Regulatory Networks|Metabolic Networks and Pathways|Protein Interaction Mapping|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btr524', '21926127', 'A large amount of biomolecular network data for multiple species have been generated by high-throughput experimental techniques, including undirected and directed networks such as protein-protein interaction networks, gene regulatory networks and metabolic networks. There are many conserved functionally similar modules and pathways among multiple biomolecular networks in different species, therefore, it is important to analyze the similarity between the biomolecular networks. Network querying approaches aim at efficiently discovering the similar subnetworks among different species. However, many existing methods only partially solve this problem.'),
(76491, 2011, 'bio', 'Population length variability and nucleoid numbers in Escherichia coli', 'Athale, Chaitanya A|Chaudhari, Hemangi', 'Division of Biology, IISER Pune, Central Tower, Sai Trinity, Pashan, Pune 411021, India. cathale@iiserpune.ac.in|Division of Biology, IISER Pune, Central Tower, Sai Trinity, Pashan, Pune 411021, India. cathale@iiserpune.ac.in', 'India|India', 7, 'Algorithms|DNA, Bacterial|Escherichia coli|Microscopy, Interference', 'Journal Article', '10.1093/bioinformatics/btr501', '21930671', 'Cell sizes and shapes are a fundamental defining characteristic of all cellular life. In bacteria like Escherichia coli, the machinery that determines cell length is complex and interconnected, spanning extracellular cues, biosynthesis and cell division. Few tools exist to study cell lengths in a population. We have developed and tested three automated image analysis routines on growing E.coli cultures to simultaneously measure cell lengths and nucleoid numbers in populations of bacteria. We find population profiles changing with culture density-higher density of culture leads to fewer long cells. Additionally, lab strains mutant for recA show a correlation between the number of nucleoids and cell length.'),
(76492, 2011, 'bio', 'Sparse non-negative generalized PCA with applications to metabolomics', 'Allen, Genevera I|Maletixc4x87-Savatixc4x87, Mirjana', 'Department of Pediatrics-Neurology, Baylor College of Medicine, Jan and Dan Duncan Neurological Research Institute at Texas Childrens Hospital, Houston, TX 77030, USA. gallen@rice.edu|Department of Pediatrics-Neurology, Baylor College of Medicine, Jan and Dan Duncan Neurological Research Institute at Texas Childrens Hospital, Houston, TX 77030, USA. gallen@rice.edu', 'United States|United States', 0, 'Algorithms|Magnetic Resonance Spectroscopy|Metabolomics|Principal Component Analysis', 'Evaluation Studies', '10.1093/bioinformatics/btr522', '21930672', 'Nuclear magnetic resonance (NMR) spectroscopy has been used to study mixtures of metabolites in biological samples. This technology produces a spectrum for each sample depicting the chemical shifts at which an unknown number of latent metabolites resonate. The interpretation of this data with common multivariate exploratory methods such as principal components analysis (PCA) is limited due to high-dimensionality, non-negativity of the underlying spectra and dependencies at adjacent chemical shifts.'),
(76493, 2011, 'bio', 'inSilicoDb: an R/Bioconductor package for accessing human Affymetrix expert-curated datasets from GEO', 'Taminau, Jonatan|Steenhoff, David|Coletta, Alain|Meganck, Stijn|Lazar, Cosmin|de Schaetzen, Virginie|Duque, Robin|Molter, Colin|Bersini, Hugues|Nowé, Ann|Weiss Solís, David Y', 'CoMo, Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. jtaminau@vub.ac.be|CoMo, Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. jtaminau@vub.ac.be|CoMo, Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. jtaminau@vub.ac.be|CoMo, Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. jtaminau@vub.ac.be|CoMo, Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. jtaminau@vub.ac.be|CoMo, Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. jtaminau@vub.ac.be|CoMo, Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. jtaminau@vub.ac.be|CoMo, Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. jtaminau@vub.ac.be|CoMo, Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. jtaminau@vub.ac.be|CoMo, Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. jtaminau@vub.ac.be|CoMo, Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. jtaminau@vub.ac.be', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 29, 'Databases, Genetic|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btr529', '21937664', 'Microarray technology has become an integral part of biomedical research and increasing amounts of datasets become available through public repositories. However, re-use of these datasets is severely hindered by unstructured, missing or incorrect biological samples information, as well as the wide variety of preprocessing methods in use. The inSilicoDb R/Bioconductor package is a command-line front-end to the InSilico DB, a web-based database currently containing 86 104 expert-curated human Affymetrix expression profiles compiled from 1937 GEO repository series. The use of this package builds on the Bioconductor projects focus on reproducibility by enabling a clear workflow in which not only analysis, but also the retrieval of verified data is supported.'),
(76494, 2011, 'bio', 'Weakly supervised learning of information structure of scientific abstracts--is it accurate enough to benefit real-world tasks in biomedicine?', 'Guo, Yufan|Korhonen, Anna|Silins, Ilona|Stenius, Ulla', 'Computer Laboratory, University of Cambridge, Cambridge CB3 0FD, UK.|Computer Laboratory, University of Cambridge, Cambridge CB3 0FD, UK.|Computer Laboratory, University of Cambridge, Cambridge CB3 0FD, UK.|Computer Laboratory, University of Cambridge, Cambridge CB3 0FD, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 10, 'Abstracting and Indexing as Topic|Artificial Intelligence|Data Mining|Humans|Neoplasms|Risk Assessment', 'Evaluation Studies', '10.1093/bioinformatics/btr536', '21949269', 'Many practical tasks in biomedicine require accessing specific types of information in scientific literature, e.g. information about the methods, results or conclusions of the study in question. Several approaches have been developed to identify such information in scientific journal articles. The best of these have yielded promising results and proved useful for biomedical text mining tasks. However, relying on fully supervised machine learning (ml) and a large body of annotated data, existing approaches are expensive to develop and port to different tasks. A potential solution to this problem is to employ weakly supervised learning instead. In this article, we investigate a weakly supervised approach to identifying information structure according to a scheme called Argumentative Zoning (az). We apply four weakly supervised classifiers to biomedical abstracts and evaluate their performance both directly and in a real-life scenario in the context of cancer risk assessment.'),
(76495, 2011, 'bio', 'PIDO: the primary immunodeficiency disease ontology', 'Adams, Nico|Hoehndorf, Robert|Gkoutos, Georgios V|Hansen, Gesine|Hennig, Christian', 'Department of Genetics, University of Cambridge, Downing Street, Cambridge CB2 3EH, UK. nico.adams@csiro.au|Department of Genetics, University of Cambridge, Downing Street, Cambridge CB2 3EH, UK. nico.adams@csiro.au|Department of Genetics, University of Cambridge, Downing Street, Cambridge CB2 3EH, UK. nico.adams@csiro.au|Department of Genetics, University of Cambridge, Downing Street, Cambridge CB2 3EH, UK. nico.adams@csiro.au|Department of Genetics, University of Cambridge, Downing Street, Cambridge CB2 3EH, UK. nico.adams@csiro.au', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Biomarkers|Humans|Immunologic Deficiency Syndromes|Phenotype|Software|Terminology as Topic|Wiskott-Aldrich Syndrome', 'Journal Article', '10.1093/bioinformatics/btr531', '21949270', 'Primary immunodeficiency diseases (PIDs) are Mendelian conditions of high phenotypic complexity and low incidence. They usually manifest in toddlers and infants, although they can also occur much later in life. Information about PIDs is often widely scattered throughout the clinical as well as the research literature and hard to find for both generalists as well as experienced clinicians. Semantic Web technologies coupled to clinical information systems can go some way toward addressing this problem. Ontologies are a central component of such a system, containing and centralizing knowledge about primary immunodeficiencies in both a human- and computer-comprehensible form. The development of an ontology of PIDs is therefore a central step toward developing informatics tools, which can support the clinician in the diagnosis and treatment of these diseases.'),
(76496, 2011, 'bio', 'Pybedtools: a flexible Python library for manipulating genomic datasets and annotations', 'Dale, Ryan K|Pedersen, Brent S|Quinlan, Aaron R', 'Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA. dalerr@niddk.nih.gov|Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA. dalerr@niddk.nih.gov|Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA. dalerr@niddk.nih.gov', 'United States|United States|United States', 0, 'Animals|Computational Biology|Genomics|Molecular Sequence Annotation|Software', 'Journal Article', '10.1093/bioinformatics/btr539', '21949271', 'pybedtools is a flexible Python software library for manipulating and exploring genomic datasets in many common formats. It provides an intuitive Python interface that extends upon the popular BEDTools genome arithmetic tools. The library is well documented and efficient, and allows researchers to quickly develop simple, yet powerful scripts that enable complex genomic analyses.'),
(76497, 2011, 'bio', 'RASP: rapid modeling of protein side chain conformations', 'Miao, Zhichao|Cao, Yang|Jiang, Taijiao', 'National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.|National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.|National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.', 'China|China|China', 37, 'Algorithms|Models, Molecular|Protein Conformation|Proteins|Software', 'Evaluation Studies', '10.1093/bioinformatics/btr538', '21949272', 'Modeling of side chain conformations constitutes an indispensable effort in protein structure modeling, protein-protein docking and protein design. Thanks to an intensive attention to this field, many of the existing programs can achieve reasonably good and comparable prediction accuracy. Moreover, in our previous work on CIS-RR, we argued that the prediction with few atomic clashes can complement the current existing methods for subsequent analysis and refinement of protein structures. However, these recent efforts to enhance the quality of predicted side chains have been accompanied by a significant increase of computational cost.'),
(76498, 2011, 'bio', 'ISPyB: an information management system for synchrotron macromolecular crystallography', 'Delagenière, Solange|Brenchereau, Patrice|Launer, Ludovic|Ashton, Alun W|Leal, Ricardo|Veyrier, Stéphanie|Gabadinho, José|Gordon, Elspeth J|Jones, Samuel D|Levik, Karl Erik|McSweeney, Seán M|Monaco, Stéphanie|Nanao, Max|Spruce, Darren|Svensson, Olof|Walsh, Martin A|Leonard, Gordon A', 'European Synchrotron Radiation Facility, 38043 Grenoble, France.|European Synchrotron Radiation Facility, 38043 Grenoble, France.|European Synchrotron Radiation Facility, 38043 Grenoble, France.|European Synchrotron Radiation Facility, 38043 Grenoble, France.|European Synchrotron Radiation Facility, 38043 Grenoble, France.|European Synchrotron Radiation Facility, 38043 Grenoble, France.|European Synchrotron Radiation Facility, 38043 Grenoble, France.|European Synchrotron Radiation Facility, 38043 Grenoble, France.|European Synchrotron Radiation Facility, 38043 Grenoble, France.|European Synchrotron Radiation Facility, 38043 Grenoble, France.|European Synchrotron Radiation Facility, 38043 Grenoble, France.|European Synchrotron Radiation Facility, 38043 Grenoble, France.|European Synchrotron Radiation Facility, 38043 Grenoble, France.|European Synchrotron Radiation Facility, 38043 Grenoble, France.|European Synchrotron Radiation Facility, 38043 Grenoble, France.|European Synchrotron Radiation Facility, 38043 Grenoble, France.|European Synchrotron Radiation Facility, 38043 Grenoble, France.', 'France|France|France|France|France|France|France|France|France|France|France|France|France|France|Fr', 0, 'Crystallography, X-Ray|Data Collection|Macromolecular Substances|Management Information Systems|Proteins|Synchrotrons|X-Ray Diffraction', 'Journal Article', '10.1093/bioinformatics/btr535', '21949273', 'Individual research groups now analyze thousands of samples per year at synchrotron macromolecular crystallography (MX) resources. The efficient management of experimental data is thus essential if the best possible experiments are to be performed and the best possible data used in downstream processes in structure determination pipelines. Information System for Protein crystallography Beamlines (ISPyB), a Laboratory Information Management System (LIMS) with an underlying data model allowing for the integration of analyses down-stream of the data collection experiment was developed to facilitate such data management.'),
(76499, 2011, 'bio', 'A wide repertoire of miRNA binding sites: prediction and functional implications', 'Elefant, Naama|Altuvia, Yael|Margalit, Hanah', 'Department of Microbiology and Molecular Genetics, IMRIC, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 91120, Israel.|Department of Microbiology and Molecular Genetics, IMRIC, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 91120, Israel.|Department of Microbiology and Molecular Genetics, IMRIC, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 91120, Israel.', 'Israel|Israel|Israel', 23, '3 Untranslated Regions|Algorithms|Animals|Binding Sites|Herpesviridae|Humans|Mice|MicroRNAs|RNA, Messenger|RNA, Viral|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btr534', '21953484', 'Over the past decade, deciphering the roles of microRNAs (miRNAs) has relied heavily upon the identification of their targets. Most of the targets that were computationally and experimentally characterized were evolutionarily conserved seed targets, containing a perfect 6-8 nt match between the miRNA 5()-region and the messenger RNA (mRNA). Gradually, it has become evident that other types of miRNA binding can confer target regulation, but their characterization has been lagging behind.'),
(76500, 2011, 'bio', 'TFRank: network-based prioritization of regulatory associations underlying transcriptional responses', 'Gonçalves, Joana P|Francisco, Alexandre P|Mira, Nuno P|Teixeira, Miguel C|Sá-Correia, Isabel|Oliveira, Arlindo L|Madeira, Sara C', 'Knowledge Discovery and Bioinformatics group, INESC-ID, Portugal. jpg@kdbio.inesc-id.pt|Knowledge Discovery and Bioinformatics group, INESC-ID, Portugal. jpg@kdbio.inesc-id.pt|Knowledge Discovery and Bioinformatics group, INESC-ID, Portugal. jpg@kdbio.inesc-id.pt|Knowledge Discovery and Bioinformatics group, INESC-ID, Portugal. jpg@kdbio.inesc-id.pt|Knowledge Discovery and Bioinformatics group, INESC-ID, Portugal. jpg@kdbio.inesc-id.pt|Knowledge Discovery and Bioinformatics group, INESC-ID, Portugal. jpg@kdbio.inesc-id.pt|Knowledge Discovery and Bioinformatics group, INESC-ID, Portugal. jpg@kdbio.inesc-id.pt', 'Portugal|Portugal|Portugal|Portugal|Portugal|Portugal|Portugal', 0, 'Acetic Acid|Binding Sites|Gene Expression Regulation|Gene Regulatory Networks|Humans|Neoplasm Metastasis|Quinine|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btr546', '21965816', 'Uncovering mechanisms underlying gene expression control is crucial to understand complex cellular responses. Studies in gene regulation often aim to identify regulatory players involved in a biological process of interest, either transcription factors coregulating a set of target genes or genes eventually controlled by a set of regulators. These are frequently prioritized with respect to a context-specific relevance score. Current approaches rely on relevance measures accounting exclusively for direct transcription factor-target interactions, namely overrepresentation of binding sites or target ratios. Gene regulation has, however, intricate behavior with overlapping, indirect effect that should not be neglected. In addition, the rapid accumulation of regulatory data already enables the prediction of large-scale networks suitable for higher level exploration by methods based on graph theory. A paradigm shift is thus emerging, where isolated and constrained analyses will likely be replaced by whole-network, systemic-aware strategies.'),
(76501, 2011, 'bio', 'Supporting tool suite for production proteomics', 'Ma, Ze-Qiang|Tabb, David L|Burden, Joseph|Chambers, Matthew C|Cox, Matthew B|Cantrell, Michael J|Ham, Amy-Joan L|Litton, Michael D|Oreto, Michael R|Schultz, William C|Sobecki, Scott M|Tsui, Tina Y|Wernke, Gregory R|Liebler, Daniel C', 'Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.|Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 25, 'Mass Spectrometry|Proteome|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/btr544', '21965817', 'The large amount of data produced by proteomics experiments requires effective bioinformatics tools for the integration of data management and data analysis. Here we introduce a suite of tools developed at Vanderbilt University to support production proteomics. We present the Backup Utility Service tool for automated instrument file backup and the ScanSifter tool for data conversion. We also describe a queuing system to coordinate identification pipelines and the File Collector tool for batch copying analytical results. These tools are individually useful but collectively reinforce each other. They are particularly valuable for proteomics core facilities or research institutions that need to manage multiple mass spectrometers. With minor changes, they could support other types of biomolecular resource facilities.'),
(76502, 2011, 'bio', 'Fast filtering for RNA homology search', 'Kolbe, Diana L|Eddy, Sean R', 'Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA.|Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA.', 'United States|United States', 21, 'Algorithms|Base Sequence|Consensus Sequence|Humans|Nucleic Acid Conformation|RNA|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1093/bioinformatics/btr545', '21965818', 'Homology search for RNAs can use secondary structure information to increase power by modeling base pairs, as in covariance models, but the resulting computational costs are high. Typical acceleration strategies rely on at least one filtering stage using sequence-only search.'),
(76503, 2011, 'bio', 'Unsupervised detection of genes of influence in lung cancer using biological networks', 'Goldenberg, Anna|Mostafavi, Sara|Quon, Gerald|Boutros, Paul C|Morris, Quaid D', 'Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada. goldenberg@utoronto.ca|Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada. goldenberg@utoronto.ca|Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada. goldenberg@utoronto.ca|Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada. goldenberg@utoronto.ca|Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada. goldenberg@utoronto.ca', 'Canada|Canada|Canada|Canada|Canada', 9, 'Carcinoma, Non-Small-Cell Lung|Gene Expression Profiling|Gene Regulatory Networks|Genes, Neoplasm|Humans|Lung Neoplasms|Protein Interaction Maps', 'Journal Article', '10.1093/bioinformatics/btr533', '21965819', 'Lung cancer is often discovered long after its onset, making identifying genes important in its initiation and progression a challenge. By the time the tumors are discovered, we only observe the final sum of changes of the few genes that initiated cancer and thousands of genes that they have influenced. Gene interactions and heterogeneity of samples make it difficult to identify genes consistent between different cohorts. Using gene and gene-product interaction networks, we propose a principled approach to identify a small subset of genes whose network neighbors exhibit consistently high expression change (in cancerous tissue versus normal) regardless of their own expression. We hypothesize that these genes can shed light on the larger scale perturbations in the overall landscape of expression levels.'),
(76504, 2011, 'bio', 'Lower confidence bounds for prediction accuracy in high dimensions via AROHIL Monte Carlo', 'Dobbin, Kevin K|Cooke, Stephanie', 'Department of Epidemiology and Biostatistics and Institute of Bioinformatics, University of Georgia, Athens, GA, USA. dobbinke@uga.edu|Department of Epidemiology and Biostatistics and Institute of Bioinformatics, University of Georgia, Athens, GA, USA. dobbinke@uga.edu', 'Georgia|Georgia', 0, 'Algorithms|Computer Simulation|Humans|Models, Statistical|Monte Carlo Method|Oligonucleotide Array Sequence Analysis|Reproducibility of Results', 'Journal Article', '10.1093/bioinformatics/btr542', '21965820', 'Implementation and development of statistical methods for high-dimensional data often require high-dimensional Monte Carlo simulations. Simulations are used to assess performance, evaluate robustness, and in some cases for implementation of algorithms. But simulation in high dimensions is often very complex, cumbersome and slow. As a result, performance evaluations are often limited, robustness minimally investigated and dissemination impeded by implementation challenges. This article presents a method for converting complex, slow high-dimensional Monte Carlo simulations into simpler, faster lower dimensional simulations.'),
(76505, 2011, 'bio', 'HHfrag: HMM-based fragment detection using HHpred', 'Kalev, Ivan|Habeck, Michael', 'Department of Protein Evolution and Department of Empirical Inference, Max Planck Institute for Intelligent Systems, Tübingen, Germany.|Department of Protein Evolution and Department of Empirical Inference, Max Planck Institute for Intelligent Systems, Tübingen, Germany.', 'Germany|Germany', 20, 'Markov Chains|Protein Conformation|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btr541', '21965821', 'Over the last decade, both static and dynamic fragment libraries for protein structure prediction have been introduced. The former are built from clusters in either sequence or structure space and aim to extract a universal structural alphabet. The latter are tailored for a particular query protein sequence and aim to provide local structural templates that need to be assembled in order to build the full-length structure.'),
(76506, 2011, 'bio', 'Kaviar: an accessible system for testing SNV novelty', 'Glusman, Gustavo|Caballero, Juan|Mauldin, Denise E|Hood, Leroy|Roach, Jared C', 'Institute for Systems Biology, Seattle, WA 98109, USA. gustavo@systemsbiology.org|Institute for Systems Biology, Seattle, WA 98109, USA. gustavo@systemsbiology.org|Institute for Systems Biology, Seattle, WA 98109, USA. gustavo@systemsbiology.org|Institute for Systems Biology, Seattle, WA 98109, USA. gustavo@systemsbiology.org|Institute for Systems Biology, Seattle, WA 98109, USA. gustavo@systemsbiology.org', 'United States|United States|United States|United States|United States', 89, 'Databases, Nucleic Acid|Genetic Variation|Genomics|Humans|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btr540', '21965822', 'With the rapidly expanding availability of data from personal genomes, exomes and transcriptomes, medical researchers will frequently need to test whether observed genomic variants are novel or known. This task requires downloading and handling large and diverse datasets from a variety of sources, and processing them with bioinformatics tools and pipelines. Alternatively, researchers can upload data to online tools, which may conflict with privacy requirements. We present here Kaviar, a tool that greatly simplifies the assessment of novel variants. Kaviar includes: (i) an integrated and growing database of genomic variation from diverse sources, including over 55 million variants from personal genomes, family genomes, transcriptomes, SNV databases and population surveys, and (ii) software for querying the database efficiently.'),
(76507, 2011, 'bio', 'ProfileChaser: searching microarray repositories based on genome-wide patterns of differential expression', 'Engreitz, Jesse M|Chen, Rong|Morgan, Alexander A|Dudley, Joel T|Mallelwar, Rohan|Butte, Atul J', 'Division of Systems Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA.|Division of Systems Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA.|Division of Systems Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA.|Division of Systems Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA.|Division of Systems Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA.|Division of Systems Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA.', 'United States|United States|United States|United States|United States|United States', 38, 'Animals|Breast Neoplasms|Cell Line, Tumor|Databases, Genetic|Female|Forkhead Box Protein O3|Forkhead Transcription Factors|Gene Expression Profiling|Genome-Wide Association Study|Humans|Internet|Male|Oligonucleotide Array Sequence Analysis|Prostatic Neoplasms|Receptors, Estrogen|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr548', '21967760', 'We introduce ProfileChaser, a web server that allows for querying the Gene Expression Omnibus based on genome-wide patterns of differential expression. Using a novel, content-based approach, ProfileChaser retrieves expression profiles that match the differentially regulated transcriptional programs in a user-supplied experiment. This analysis identifies statistical links to similar expression experiments from the vast array of publicly available data on diseases, drugs, phenotypes and other experimental conditions.'),
(76508, 2011, 'bio', 'MDpocket: open-source cavity detection and characterization on molecular dynamics trajectories', 'Schmidtke, Peter|Bidon-Chanal, Axel|Luque, F Javier|Barril, Xavier', 'Departament de Fisicoquímica and Institut de Biomedicina, Universitat de Barcelona, 08028 Barcelona, Spain. pschmidtke@ub.edu|Departament de Fisicoquímica and Institut de Biomedicina, Universitat de Barcelona, 08028 Barcelona, Spain. pschmidtke@ub.edu|Departament de Fisicoquímica and Institut de Biomedicina, Universitat de Barcelona, 08028 Barcelona, Spain. pschmidtke@ub.edu|Departament de Fisicoquímica and Institut de Biomedicina, Universitat de Barcelona, 08028 Barcelona, Spain. pschmidtke@ub.edu', 'Spain|Spain|Spain|Spain', 152, 'Algorithms|Animals|Binding Sites|Computational Biology|HSP90 Heat-Shock Proteins|Models, Molecular|Molecular Dynamics Simulation|Protein Conformation|Proteins|Software|p38 Mitogen-Activated Protein Kinases', 'Journal Article', '10.1093/bioinformatics/btr550', '21967761', 'A variety of pocket detection algorithms are now freely or commercially available to the scientific community for the analysis of static protein structures. However, since proteins are dynamic entities, enhancing the capabilities of these programs for the straightforward detection and characterization of cavities taking into account protein conformational ensembles should be valuable for capturing the plasticity of pockets, and therefore allow gaining insight into structure-function relationships.'),
(76509, 2011, 'bio', 'Improving the detection of transmembrane xcexb2-barrel chains with N-to-1 extreme learning machines', 'Savojardo, Castrense|Fariselli, Piero|Casadio, Rita', 'Biocomputing Group, Department of Biology, University of Bologna CIRI-Health Science and Technology, 40126 Bologna, Italy.|Biocomputing Group, Department of Biology, University of Bologna CIRI-Health Science and Technology, 40126 Bologna, Italy.|Biocomputing Group, Department of Biology, University of Bologna CIRI-Health Science and Technology, 40126 Bologna, Italy.', 'Italy|Italy|Italy', 15, 'Artificial Intelligence|Bacterial Outer Membrane Proteins|Cell Membrane|Chloroplast Proteins|Membrane Proteins|Mitochondrial Proteins|Neural Networks (Computer)|Protein Structure, Secondary|Sequence Analysis, Protein|Software', 'Evaluation Studies', '10.1093/bioinformatics/btr549', '21967762', 'Transmembrane xcexb2-barrels (TMBBs) are extremely important proteins that play key roles in several cell functions. They cross the lipid bilayer with xcexb2-barrel structures. TMBBs are presently found in the outer membranes of Gram-negative bacteria and of mitochondria and chloroplasts. Loop exposure outside the bacterial cell membranes makes TMBBs important targets for vaccine or drug therapies. In genomes, they are not highly represented and are difficult to identify with experimental approaches. Several computational methods have been developed to discriminate TMBBs from other types of proteins. However, the best performing approaches have a high fraction of false positive predictions.'),
(76510, 2011, 'bio', 'RNA-Seq analysis in MeV', 'Howe, Eleanor A|Sinha, Raktim|Schlauch, Daniel|Quackenbush, John', 'Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.', 'United States|United States|United States|United States', 191, 'Computer Graphics|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btr490', '21976420', 'RNA-Seq is an exciting methodology that leverages the power of high-throughput sequencing to measure RNA transcript counts at an unprecedented accuracy. However, the data generated from this process are extremely large and biologist-friendly tools with which to analyze it are sorely lacking. MultiExperiment Viewer (MeV) is a Java-based desktop application that allows advanced analysis of gene expression data through an intuitive graphical user interface. Here, we report a significant enhancement to MeV that allows analysis of RNA-Seq data with these familiar, powerful tools. We also report the addition to MeV of several RNA-Seq-specific functions, addressing the differences in analysis requirements between this data type and traditional gene expression data. These tools include automatic conversion functions from raw count data to processed RPKM or FPKM values and differential expression detection and functional annotation enrichment detection based on published methods.'),
(76511, 2011, 'bio', 'A non-biased framework for the annotation and classification of the non-miRNA small RNA transcriptome', 'Pantano, Lorena|Estivill, Xavier|Martí, Eulalia', 'Genetic Causes of Disease, Genes and Disease Programme, Centre for Genomic Regulation (CRG) and UPF, Barcelona, Spain.|Genetic Causes of Disease, Genes and Disease Programme, Centre for Genomic Regulation (CRG) and UPF, Barcelona, Spain.|Genetic Causes of Disease, Genes and Disease Programme, Centre for Genomic Regulation (CRG) and UPF, Barcelona, Spain.', 'Spain|Spain|Spain', 25, 'Animals|Humans|Mice|MicroRNAs|Molecular Sequence Annotation|RNA, Small Untranslated|Sequence Analysis, RNA|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btr527', '21976421', 'Recent progress in high-throughput sequencing technologies has largely contributed to reveal a highly complex landscape of small non-coding RNAs (sRNAs), including novel non-canonical sRNAs derived from long non-coding RNA, repeated elements, transcription start sites and splicing site regions among others. The published frameworks for sRNA data analysis are focused on miRNA detection and prediction, ignoring further information in the dataset. As a consequence, tools for the identification and classification of the sRNAs not belonging to miRNA family are currently lacking.'),
(76512, 2011, 'bio', 'Probabilistic alignments with quality scores: an application to short-read mapping toward accurate SNP/indel detection', 'Hamada, Michiaki|Wijaya, Edward|Frith, Martin C|Asai, Kiyoshi', 'Graduate School of Frontier Sciences, University of Tokyo, Kashiwa 277-8562, Japan. mhamada@k.u-tokyo.ac.jp|Graduate School of Frontier Sciences, University of Tokyo, Kashiwa 277-8562, Japan. mhamada@k.u-tokyo.ac.jp|Graduate School of Frontier Sciences, University of Tokyo, Kashiwa 277-8562, Japan. mhamada@k.u-tokyo.ac.jp|Graduate School of Frontier Sciences, University of Tokyo, Kashiwa 277-8562, Japan. mhamada@k.u-tokyo.ac.jp', 'Japan|Japan|Japan|Japan', 12, 'Algorithms|Humans|INDEL Mutation|Models, Statistical|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btr537', '21976422', 'Recent studies have revealed the importance of considering quality scores of reads generated by next-generation sequence (NGS) platforms in various downstream analyses. It is also known that probabilistic alignments based on marginal probabilities (e.g. aligned-column and/or gap probabilities) provide more accurate alignment than conventional maximum score-based alignment. There exists, however, no study about probabilistic alignment that considers quality scores explicitly, although the method is expected to be useful in SNP/indel callers and bisulfite mapping, because accurate estimation of aligned columns or gaps is important in those analyses.'),
(76513, 2011, 'bio', 'DroPhEA: Drosophila phenotype enrichment analysis for insect functional genomics', 'Weng, Meng-Pin|Liao, Ben-Yang', 'Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County 350, Taiwan, R.O.C.|Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County 350, Taiwan, R.O.C.', '-|-', 7, 'Animals|Anopheles|Drosophila melanogaster|Evolution, Molecular|Feeding Behavior|Genes, Insect|Genome, Insect|Genomics|Mutation|Phenotype|Software', 'Journal Article', '10.1093/bioinformatics/btr530', '21976423', 'DroPhEA is a core module of a web application that facilitates research in insect functional genomics through enrichment analysis on mutant phenotypes of fruit fly (Drosophila melanogaster). The phenotypes investigated in the analyses can be predefined by FlyBase or customized by users. DroPhEA allows users to specify mutation or ortholog types, displays enriched term results in a hierarchical structure and supports analyses on gene sets of all insect species with a fully sequenced genome.'),
(76514, 2011, 'bio', 'FastSP: linear time calculation of alignment accuracy', 'Mirarab, Siavash|Warnow, Tandy', 'Department of Computer Science, The University of Texas at Austin, Austin, TX 78701, USA.|Department of Computer Science, The University of Texas at Austin, Austin, TX 78701, USA.', 'United States|United States', 22, 'Algorithms|Base Sequence|Proteins|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btr553', '21984754', 'Multiple sequence alignment is a basic part of much biological research, including phylogeny estimation and protein structure and function prediction. Different alignments on the same set of unaligned sequences are often compared, sometimes in order to assess the accuracy of alignment methods or to infer a consensus alignment from a set of estimated alignments. Three of the standard techniques for comparing alignments, Developer, Modeler and Total Column (TC) scores can be derived through calculations of the set of homologies that the alignments share. However, the brute-force technique for calculating this set is quadratic in the input size. The remaining standard technique, Cline Shift Score, inherently requires quadratic time.'),
(76515, 2011, 'bio', 'Computational network analysis of the anatomical and genetic organizations in the mouse brain', 'Ji, Shuiwang', 'Department of Computer Science, Old Dominion University, Norfolk, VA 23529, USA. sji@cs.odu.edu', 'United States', 12, 'Algorithms|Animals|Brain|Brain Mapping|Gene Expression Regulation|Gene Regulatory Networks|Mice', 'Journal Article', '10.1093/bioinformatics/btr558', '21984755', 'The mammalian central nervous system (CNS) generates high-level behavior and cognitive functions. Elucidating the anatomical and genetic organizations in the CNS is a key step toward understanding the functional brain circuitry. The CNS contains an enormous number of cell types, each with unique gene expression patterns. Therefore, it is of central importance to capture the spatial expression patterns in the brain. Currently, genome-wide atlas of spatial expression patterns in the mouse brain has been made available, and the data are in the form of aligned 3D data arrays. The sheer volume and complexity of these data pose significant challenges for efficient computational analysis.'),
(76516, 2011, 'bio', 'Visual DSD: a design and analysis tool for DNA strand displacement systems', 'Lakin, Matthew R|Youssef, Simon|Polo, Filippo|Emmott, Stephen|Phillips, Andrew', 'Biological Computation Group, Microsoft Research, Cambridge CB3 0FB, UK.|Biological Computation Group, Microsoft Research, Cambridge CB3 0FB, UK.|Biological Computation Group, Microsoft Research, Cambridge CB3 0FB, UK.|Biological Computation Group, Microsoft Research, Cambridge CB3 0FB, UK.|Biological Computation Group, Microsoft Research, Cambridge CB3 0FB, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 119, 'Computer Graphics|Computers, Molecular|DNA|Nucleic Acid Hybridization|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/btr543', '21984756', 'The Visual DSD (DNA Strand Displacement) tool allows rapid prototyping and analysis of computational devices implemented using DNA strand displacement, in a convenient web-based graphical interface. It is an implementation of the DSD programming language and compiler described by Lakin et al. (2011) with additional features such as support for polymers of unbounded length. It also supports stochastic and deterministic simulation, construction of continuous-time Markov chains and various export formats which allow models to be analysed using third-party tools.'),
(76517, 2011, 'bio', 'miREnvironment database: providing a bridge for microRNAs, environmental factors and phenotypes', 'Yang, Qingqing|Qiu, Chengxiang|Yang, Jie|Wu, Qing|Cui, Qinghua', 'Department of Biomedical Informatics, Peking University Health Science Center, Beijing 100191, China.|Department of Biomedical Informatics, Peking University Health Science Center, Beijing 100191, China.|Department of Biomedical Informatics, Peking University Health Science Center, Beijing 100191, China.|Department of Biomedical Informatics, Peking University Health Science Center, Beijing 100191, China.|Department of Biomedical Informatics, Peking University Health Science Center, Beijing 100191, China.', 'China|China|China|China|China', 55, 'Animals|Databases, Nucleic Acid|Environment|Humans|Mice|MicroRNAs|Phenotype|Rats', 'Journal Article', '10.1093/bioinformatics/btr556', '21984757', 'The interaction between genetic factors and environmental factors has critical roles in determining the phenotype of an organism. In recent years, a number of studies have reported that the dysfunctions on microRNA (miRNAs), environmental factors and their interactions have strong effects on phenotypes and even may result in abnormal phenotypes and diseases, whereas there has been no a database linking miRNAs, environmental factors and phenotypes. Such a resource platform is believed to be of great value in the understanding of miRNAs, environmental factors, especially drugs and diseases. In this study, we constructed the miREnvironment database, which contains a comprehensive collection and curation of experimentally supported interactions among miRNAs, environmental factors and phenotypes. The names of miRNAs, phenotypes, environmental factors, conditions of environmental factors, samples, species, evidence and references were further annotated. miREnvironment represents a biomedical resource for researches on miRNAs, environmental factors and diseases.'),
(76518, 2011, 'bio', 'Sparse distance-based learning for simultaneous multiclass classification and feature selection of metagenomic data', 'Liu, Zhenqiu|Hsiao, William|Cantarel, Brandi L|Drábek, Elliott Franco|Fraser-Liggett, Claire', 'Department of Epidemiology and Public Health, University of Maryland Greenebaum Cancer Center, University of Maryland School of Medicine, Baltimore, MD 21201, USA. zliu@umm.edu|Department of Epidemiology and Public Health, University of Maryland Greenebaum Cancer Center, University of Maryland School of Medicine, Baltimore, MD 21201, USA. zliu@umm.edu|Department of Epidemiology and Public Health, University of Maryland Greenebaum Cancer Center, University of Maryland School of Medicine, Baltimore, MD 21201, USA. zliu@umm.edu|Department of Epidemiology and Public Health, University of Maryland Greenebaum Cancer Center, University of Maryland School of Medicine, Baltimore, MD 21201, USA. zliu@umm.edu|Department of Epidemiology and Public Health, University of Maryland Greenebaum Cancer Center, University of Maryland School of Medicine, Baltimore, MD 21201, USA. zliu@umm.edu', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Artificial Intelligence|Bacteria|Humans|Metagenome|Metagenomics|Sample Size|Skin', 'Journal Article', '10.1093/bioinformatics/btr547', '21984758', 'Direct sequencing of microbes in human ecosystems (the human microbiome) has complemented single genome cultivation and sequencing to understand and explore the impact of commensal microbes on human health. As sequencing technologies improve and costs decline, the sophistication of data has outgrown available computational methods. While several existing machine learning methods have been adapted for analyzing microbiome data recently, there is not yet an efficient and dedicated algorithm available for multiclass classification of human microbiota.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76519, 2011, 'bio', 'Distance-based differential analysis of gene curves', 'Minas, Christopher|Waddell, Simon J|Montana, Giovanni', 'Statistics Section, Department of Mathematics, Imperial College London, London, UK.|Statistics Section, Department of Mathematics, Imperial College London, London, UK.|Statistics Section, Department of Mathematics, Imperial College London, London, UK.', 'United Kingdom|United Kingdom|United Kingdom', 15, 'Data Interpretation, Statistical|Gene Expression|Gene Expression Profiling|Humans|Kinetics|Mycobacterium tuberculosis|Oligonucleotide Array Sequence Analysis|Phagocytes', 'Journal Article', '10.1093/bioinformatics/btr528', '21984759', 'Time course gene expression experiments are performed to study time-varying changes in mRNA levels of thousands of genes. Statistical methods from functional data analysis (FDA) have recently gained popularity for modelling and exploring such time courses. Each temporal profile is treated as the realization of a smooth function of time, or curve, and the inferred curve becomes the basic unit of statistical analysis. The task of identifying genes with differential temporal profiles then consists of detecting statistically significant differences between curves, where such differences are commonly quantified by computing the area between the curves or the lxe2x82x82 distance.'),
(76520, 2011, 'bio', 'MyBioNet: interactively visualize, edit and merge biological networks on the web', 'Huang, Donglin|Huang, Yiling|Bai, Youhuang|Chen, Dijun|Hofestädt, Ralf|Klukas, Christian|Chen, Ming', 'Department of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.|Department of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.|Department of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.|Department of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.|Department of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.|Department of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.|Department of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.', 'China|China|China|China|China|China|China', 1, 'Algorithms|Computational Biology|Databases, Factual|Humans|Internet|Metabolic Networks and Pathways|Oryza|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr557', '21984760', 'MyBioNet is a web-based application for biological network analysis, which provides user-friendly web interfaces to visualize, edit and merge biological networks. In addition, MyBioNet integrated KEGG metabolic network data from 1366 organisms and allows users to search and navigate interesting networks.'),
(76521, 2011, 'bio', 'Knime4Bio: a set of custom nodes for the interpretation of next-generation sequencing data with KNIME', 'Lindenbaum, Pierre|Le Scouarnec, Solena|Portero, Vincent|Redon, Richard', 'Institut du thorax, Inserm UMR 915, Centre Hospitalier Universitaire de Nantes, 44000 Nantes, France.|Institut du thorax, Inserm UMR 915, Centre Hospitalier Universitaire de Nantes, 44000 Nantes, France.|Institut du thorax, Inserm UMR 915, Centre Hospitalier Universitaire de Nantes, 44000 Nantes, France.|Institut du thorax, Inserm UMR 915, Centre Hospitalier Universitaire de Nantes, 44000 Nantes, France.', 'France|France|France|France', 0, 'Hajdu-Cheney Syndrome|High-Throughput Nucleotide Sequencing|Humans|Software', 'Journal Article', '10.1093/bioinformatics/btr554', '21984761', 'Analysing large amounts of data generated by next-generation sequencing (NGS) technologies is difficult for researchers or clinicians without computational skills. They are often compelled to delegate this task to computer biologists working with command line utilities. The availability of easy-to-use tools will become essential with the generalization of NGS in research and diagnosis. It will enable investigators to handle much more of the analysis. Here, we describe Knime4Bio, a set of custom nodes for the KNIME (The Konstanz Information Miner) interactive graphical workbench, for the interpretation of large biological datasets. We demonstrate that this tool can be utilized to quickly retrieve previously published scientific findings.'),
(76522, 2011, 'bio', 'KABOOM! A new suffix array based algorithm for clustering expression data', 'Hazelhurst, Scott|Lipták, Zsuzsanna', 'Wits Bioinformatics, School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, Private Bag 3, 2050 Wits, South Africa. scott.hazelhurst@wits.ac.za|Wits Bioinformatics, School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, Private Bag 3, 2050 Wits, South Africa. scott.hazelhurst@wits.ac.za', 'South Africa|South Africa', 0, 'Algorithms|Artificial Intelligence|Cluster Analysis|Computational Biology|Gene Expression Profiling|Humans|Software', 'Journal Article', '10.1093/bioinformatics/btr560', '21984769', 'Second-generation sequencing technology has reinvigorated research using expression data, and clustering such data remains a significant challenge, with much larger datasets and with different error profiles. Algorithms that rely on all-versus-all comparison of sequences are not practical for large datasets.'),
(76523, 2011, 'bio', 'CAMBerVis: visualization software to support comparative analysis of multiple bacterial strains', 'Woxc5xbaniak, Michaxc5x82|Wong, Limsoon|Tiuryn, Jerzy', 'Informatics and Mechanics, University of Warsaw, Warsaw, Poland. m.wozniak@mimuw.edu.pl|Informatics and Mechanics, University of Warsaw, Warsaw, Poland. m.wozniak@mimuw.edu.pl|Informatics and Mechanics, University of Warsaw, Warsaw, Poland. m.wozniak@mimuw.edu.pl', 'Poland|Poland|Poland', 0, 'Bacteria|Genome, Bacterial|Molecular Sequence Annotation|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btr561', '21984770', 'A number of inconsistencies in genome annotations are documented among bacterial strains. Visualization of the differences may help biologists to make correct decisions in spurious cases.'),
(76524, 2011, 'bio', 'The Infobiotics Workbench: an integrated in silico modelling platform for Systems and Synthetic Biology', 'Blakes, Jonathan|Twycross, Jamie|Romero-Campero, Francisco Jose|Krasnogor, Natalio', 'Automated Scheduling, Optimisation and Planning Group, School of Computer Science, University of Nottingham, Nottingham, NG8 1BB, UK.|Automated Scheduling, Optimisation and Planning Group, School of Computer Science, University of Nottingham, Nottingham, NG8 1BB, UK.|Automated Scheduling, Optimisation and Planning Group, School of Computer Science, University of Nottingham, Nottingham, NG8 1BB, UK.|Automated Scheduling, Optimisation and Planning Group, School of Computer Science, University of Nottingham, Nottingham, NG8 1BB, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Computer Simulation|Humans|Models, Biological|Models, Statistical|Programming Languages|Software|Synthetic Biology|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btr571', '21994219', 'The Infobiotics Workbench is an integrated software suite incorporating model specification, simulation, parameter optimization and model checking for Systems and Synthetic Biology. A modular model specification allows for straightforward creation of large-scale models containing many compartments and reactions. Models are simulated either using stochastic simulation or numerical integration, and visualized in time and space. Model parameters and structure can be optimized with evolutionary algorithms, and model properties calculated using probabilistic model checking.'),
(76525, 2011, 'bio', 'FlyExpress: visual mining of spatiotemporal patterns for genes and publications in Drosophila embryogenesis', 'Kumar, Sudhir|Konikoff, Charlotte|Van Emden, Bernard|Busick, Christopher|Davis, Kailah T|Ji, Shuiwang|Wu, Lin-Wei|Ramos, Hector|Brody, Thomas|Panchanathan, Sethuraman|Ye, Jieping|Karr, Timothy L|Gerold, Kristyn|McCutchan, Michael|Newfeld, Stuart J', 'Center for Evolutionary Medicine and Informatics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA. s.kumar@asu.edu|Center for Evolutionary Medicine and Informatics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA. s.kumar@asu.edu|Center for Evolutionary Medicine and Informatics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA. s.kumar@asu.edu|Center for Evolutionary Medicine and Informatics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA. s.kumar@asu.edu|Center for Evolutionary Medicine and Informatics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA. s.kumar@asu.edu|Center for Evolutionary Medicine and Informatics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA. s.kumar@asu.edu|Center for Evolutionary Medicine and Informatics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA. s.kumar@asu.edu|Center for Evolutionary Medicine and Informatics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA. s.kumar@asu.edu|Center for Evolutionary Medicine and Informatics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA. s.kumar@asu.edu|Center for Evolutionary Medicine and Informatics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA. s.kumar@asu.edu|Center for Evolutionary Medicine and Informatics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA. s.kumar@asu.edu|Center for Evolutionary Medicine and Informatics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA. s.kumar@asu.edu|Center for Evolutionary Medicine and Informatics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA. s.kumar@asu.edu|Center for Evolutionary Medicine and Informatics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA. s.kumar@asu.edu|Center for Evolutionary Medicine and Informatics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA. s.kumar@asu.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Animals|Audiovisual Aids|Data Mining|Drosophila Proteins|Drosophila melanogaster|Embryonic Development|Gene Expression Profiling|Gene Expression Regulation, Developmental', 'Journal Article', '10.1093/bioinformatics/btr567', '21994220', 'Images containing spatial expression patterns illuminate the roles of different genes during embryogenesis. In order to generate initial clues to regulatory interactions, biologists frequently need to know the set of genes expressed at the same time at specific locations in a developing embryo, as well as related research publications. However, text-based mining of image annotations and research articles cannot produce all relevant results, because the primary data are images that exist as graphical objects. We have developed a unique knowledge base (FlyExpress) to facilitate visual mining of images from Drosophila melanogaster embryogenesis. By clicking on specific locations in pictures of fly embryos from different stages of development and different visual projections, users can produce a list of genes and publications instantly. In FlyExpress, each queryable embryo picture is a heat-map that captures the expression patterns of more than 4500 genes and more than 2600 published articles. In addition, one can view spatial patterns for particular genes over time as well as find other genes with similar expression patterns at a given developmental stage. Therefore, FlyExpress is a unique tool for mining spatiotemporal expression patterns in a format readily accessible to the scientific community.'),
(76526, 2011, 'bio', 'Automatic generation of protein structure cartoons with Pro-origami', 'Stivala, Alex|Wybrow, Michael|Wirth, Anthony|Whisstock, James C|Stuckey, Peter J', 'Department of Computer Science and Software Engineering, The University of Melbourne Parkville Campus, Victoria 3010, Australia. a.stivala@pgrad.unimelb.edu.au|Department of Computer Science and Software Engineering, The University of Melbourne Parkville Campus, Victoria 3010, Australia. a.stivala@pgrad.unimelb.edu.au|Department of Computer Science and Software Engineering, The University of Melbourne Parkville Campus, Victoria 3010, Australia. a.stivala@pgrad.unimelb.edu.au|Department of Computer Science and Software Engineering, The University of Melbourne Parkville Campus, Victoria 3010, Australia. a.stivala@pgrad.unimelb.edu.au|Department of Computer Science and Software Engineering, The University of Melbourne Parkville Campus, Victoria 3010, Australia. a.stivala@pgrad.unimelb.edu.au', 'Australia|Australia|Australia|Australia|Australia', 101, 'Automation|Models, Molecular|Protein Structure, Secondary|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btr575', '21994221', 'Protein topology diagrams are 2D representations of protein structure that are particularly useful in understanding and analysing complex protein folds. Generating such diagrams presents a major problem in graph drawing, with automatic approaches often resulting in errors or uninterpretable results. Here we apply a breakthrough in diagram layout to protein topology cartoons, providing clear, accurate, interactive and editable diagrams, which are also an interface to a structural search method.'),
(76527, 2011, 'bio', 'SVseq: an approach for detecting exact breakpoints of deletions with low-coverage sequence data', 'Zhang, Jin|Wu, Yufeng', 'Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269, USA. jinzhang@engr.uconn.edu|Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269, USA. jinzhang@engr.uconn.edu', 'United States|United States', 0, 'Chromosome Deletion|Chromosomes, Human, Pair 15|Gene Deletion|Humans|INDEL Mutation|Software', 'Journal Article', '10.1093/bioinformatics/btr563', '21994222', 'Structural variation (SV), such as deletion, is an important type of genetic variation and may be associated with diseases. While there are many existing methods for detecting SVs, finding deletions is still challenging with low-coverage short sequence reads. Existing deletion finding methods for sequence reads either use the so-called split reads mapping for detecting deletions with exact breakpoints, or rely on discordant insert sizes to estimate approximate positions of deletions. Neither is completely satisfactory with low-coverage sequence reads.'),
(76528, 2011, 'bio', 'An automatic method for CASP9 free modeling structure prediction assessment', 'Cong, Qian|Kinch, Lisa N|Pei, Jimin|Shi, Shuoyong|Grishin, Vyacheslav N|Li, Wenlin|Grishin, Nick V', 'Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.|Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.|Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.|Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.|Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.|Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.|Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.', 'United States|United States|United States|United States|United States|United States|United States', 17, 'Automation|Computational Biology|Models, Molecular|Protein Conformation|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1093/bioinformatics/btr572', '21994223', 'Manual inspection has been applied to and is well accepted for assessing critical assessment of protein structure prediction (CASP) free modeling (FM) category predictions over the years. Such manual assessment requires expertise and significant time investment, yet has the problems of being subjective and unable to differentiate models of similar quality. It is beneficial to incorporate the ideas behind manual inspection to an automatic score system, which could provide objective and reproducible assessment of structure models.'),
(76529, 2011, 'bio', 'Pyicos: a versatile toolkit for the analysis of high-throughput sequencing data', 'Althammer, Sonja|González-Vallinas, Juan|Ballaré, Cecilia|Beato, Miguel|Eyras, Eduardo', 'Universitat Pompeu Fabra, E08003 Barcelona, Spain.|Universitat Pompeu Fabra, E08003 Barcelona, Spain.|Universitat Pompeu Fabra, E08003 Barcelona, Spain.|Universitat Pompeu Fabra, E08003 Barcelona, Spain.|Universitat Pompeu Fabra, E08003 Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain', 0, 'Chromatin Immunoprecipitation|Computational Biology|Computers|Gene Expression Regulation|High-Throughput Nucleotide Sequencing|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btr570', '21994224', 'High-throughput sequencing (HTS) has revolutionized gene regulation studies and is now fundamental for the detection of protein-DNA and protein-RNA binding, as well as for measuring RNA expression. With increasing variety and sequencing depth of HTS datasets, the need for more flexible and memory-efficient tools to analyse them is growing.'),
(76530, 2011, 'bio', 'Pico-inplace-inversions between human and chimpanzee', 'Hou, Minmei|Yao, Ping|Antonou, Angela|Johns, Mitrick A', 'Department of Computer Science, Northern Illinois University, DeKalb, IL 60115, USA. mhou@cs.niu.edu|Department of Computer Science, Northern Illinois University, DeKalb, IL 60115, USA. mhou@cs.niu.edu|Department of Computer Science, Northern Illinois University, DeKalb, IL 60115, USA. mhou@cs.niu.edu|Department of Computer Science, Northern Illinois University, DeKalb, IL 60115, USA. mhou@cs.niu.edu', 'United States|United States|United States|United States', 0, 'Animals|Chromosome Inversion|Evolution, Molecular|Genome|Humans|Pan troglodytes|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btr566', '21994225', 'There have been several studies on the micro-inversions between human and chimpanzee, but there are large discrepancies among their results. Furthermore, all of them rely on alignment procedures or existing alignment results to identify inversions. However, the core alignment procedures do not take very small inversions into consideration. Therefore, their analyses cannot find inversions that are too small to be detected by a classic aligner. We call such inversions pico-inversions.'),
(76531, 2011, 'bio', 'The strength of intron donor splice sites in human genes displays a bell-shaped pattern', 'Wang, Kai|Wernersson, Rasmus|Brunak, Søren', 'Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, DK-2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, DK-2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, DK-2800 Lyngby, Denmark.', 'Denmark|Denmark|Denmark', 0, 'Alternative Splicing|Animals|Humans|Introns|Mice|RNA Precursors|RNA Splice Sites|RNA, Messenger', 'Journal Article', '10.1093/bioinformatics/btr532', '21994226', 'The gene concept has recently changed from the classical one protein notion into a much more diverse picture, where overlapping or fused transcripts, alternative transcription initiation, and genes within genes, add to the complexity generated by alternative splicing. Increased understanding of the mechanisms controlling pre-mRNA splicing is thus important for a wide range of aspects relating to gene expression.'),
(76532, 2011, 'bio', 'BioTextQuest: a web-based biomedical text mining suite for concept discovery', 'Papanikolaou, Nikolas|Pafilis, Evangelos|Nikolaou, Stavros|Ouzounis, Christos A|Iliopoulos, Ioannis|Promponas, Vasilis J', 'Bioinformatics Research Laboratory, Department of Biological Sciences, University of Cyprus, CY 1678, Nicosia, Cyprus, Greece.|Bioinformatics Research Laboratory, Department of Biological Sciences, University of Cyprus, CY 1678, Nicosia, Cyprus, Greece.|Bioinformatics Research Laboratory, Department of Biological Sciences, University of Cyprus, CY 1678, Nicosia, Cyprus, Greece.|Bioinformatics Research Laboratory, Department of Biological Sciences, University of Cyprus, CY 1678, Nicosia, Cyprus, Greece.|Bioinformatics Research Laboratory, Department of Biological Sciences, University of Cyprus, CY 1678, Nicosia, Cyprus, Greece.|Bioinformatics Research Laboratory, Department of Biological Sciences, University of Cyprus, CY 1678, Nicosia, Cyprus, Greece.', 'Cyprus|Cyprus|Cyprus|Cyprus|Cyprus|Cyprus', 0, 'Algorithms|Animals|Cluster Analysis|Data Mining|Drosophila|Internet|Natural Language Processing', 'Journal Article', '10.1093/bioinformatics/btr564', '21994227', 'BioTextQuest combines automated discovery of significant terms in article clusters with structured knowledge annotation, via Named Entity Recognition services, offering interactive user-friendly visualization. A tag-cloud-based illustration of terms labeling each document cluster are semantically annotated according to the biological entity, and a list of document titles enable users to simultaneously compare terms and documents of each cluster, facilitating concept association and hypothesis generation. BioTextQuest allows customization of analysis parameters, e.g. clustering/stemming algorithms, exclusion of documents/significant terms, to better match the biological question addressed.'),
(76533, 2011, 'bio', 'Visualization and quality assessment of de novo genome assemblies', 'Riba-Grognuz, Oksana|Keller, Laurent|Falquet, Laurent|Xenarios, Ioannis|Wurm, Yannick', 'Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland. oksana.ribagrognuz@unil.ch|Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland. oksana.ribagrognuz@unil.ch|Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland. oksana.ribagrognuz@unil.ch|Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland. oksana.ribagrognuz@unil.ch|Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland. oksana.ribagrognuz@unil.ch', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 6, 'Chromosome Mapping|Computational Biology|Genome|Sequence Analysis, DNA|Software|Synteny', 'Journal Article', '10.1093/bioinformatics/btr569', '21994228', 'Recent technological progress has greatly facilitated de novo genome sequencing. However, de novo assemblies consist in many pieces of contiguous sequence (contigs) arranged in thousands of scaffolds instead of small numbers of chromosomes. Confirming and improving the quality of such assemblies is critical for subsequent analysis. We present a method to evaluate genome scaffolding by aligning independently obtained transcriptome sequences to the genome and visually summarizing the alignments using the Cytoscape software. Applying this method to the genome of the red fire ant Solenopsis invicta allowed us to identify inconsistencies in 7%, confirm contig order in 20% and extend 16% of scaffolds.'),
(76534, 2011, 'bio', 'Gathering insights on disease etiology from gene expression profiles of healthy tissues', 'Silva, A Sofia|Wood, Shona H|van Dam, Sipko|Berres, Sven|McArdle, Anne|de Magalhães, João Pedro', 'Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK.|Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK.|Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK.|Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK.|Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK.|Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Cell Transformation, Neoplastic|Female|Gene Expression Profiling|Gene Expression Regulation|Genome-Wide Association Study|Humans|Male|Neoplasms|Organ Specificity', 'Journal Article', '10.1093/bioinformatics/btr559', '21994229', 'Gene expression profiles have been widely used to study disease states. It may be possible, however, to gather insights into human diseases by comparing gene expression profiles of healthy organs with different disease incidence or severity. We tested this hypothesis and developed an approach to identify candidate genes associated with disease development by focusing on cancer incidence since it varies greatly across human organs.'),
(76535, 2011, 'bio', 'The design of optimal therapeutic small interfering RNA molecules targeting diverse strains of influenza A virus', 'ElHefnawi, Mahmoud|Hassan, Nafisa|Kamar, Mona|Siam, Rania|Remoli, Anna Lisa|El-Azab, Iman|AlAidy, Osama|Marsili, Giulia|Sgarbanti, Marco', 'Informatics and Systems Department, Division of Engineering Research, National Research Centre, Egypt. mahef@aucegypt.edu|Informatics and Systems Department, Division of Engineering Research, National Research Centre, Egypt. mahef@aucegypt.edu|Informatics and Systems Department, Division of Engineering Research, National Research Centre, Egypt. mahef@aucegypt.edu|Informatics and Systems Department, Division of Engineering Research, National Research Centre, Egypt. mahef@aucegypt.edu|Informatics and Systems Department, Division of Engineering Research, National Research Centre, Egypt. mahef@aucegypt.edu|Informatics and Systems Department, Division of Engineering Research, National Research Centre, Egypt. mahef@aucegypt.edu|Informatics and Systems Department, Division of Engineering Research, National Research Centre, Egypt. mahef@aucegypt.edu|Informatics and Systems Department, Division of Engineering Research, National Research Centre, Egypt. mahef@aucegypt.edu|Informatics and Systems Department, Division of Engineering Research, National Research Centre, Egypt. mahef@aucegypt.edu', 'Egypt|Egypt|Egypt|Egypt|Egypt|Egypt|Egypt|Egypt|Egypt', 0, 'HEK293 Cells|Humans|Influenza A Virus, H5N1 Subtype|Influenza A virus|Influenza, Human|RNA, Small Interfering|Software', 'Journal Article', '10.1093/bioinformatics/btr555', '21994230', 'There is an urgent need for new medications to combat influenza pandemics.'),
(76536, 2011, 'bio', 'Neural fate decisions mediated by trans-activation and cis-inhibition in Notch signaling', 'Wang, Ruiqi|Liu, Kaihui|Chen, Luonan|Aihara, Kazuyuki', 'Institute of Systems Biology, Shanghai University, Shanghai 200444, China. rqwang@shu.edu.cn|Institute of Systems Biology, Shanghai University, Shanghai 200444, China. rqwang@shu.edu.cn|Institute of Systems Biology, Shanghai University, Shanghai 200444, China. rqwang@shu.edu.cn|Institute of Systems Biology, Shanghai University, Shanghai 200444, China. rqwang@shu.edu.cn', 'China|China|China|China', 29, 'Basic Helix-Loop-Helix Transcription Factors|Cell Differentiation|Gene Expression Regulation|Intracellular Signaling Peptides and Proteins|Membrane Proteins|Models, Biological|Neural Stem Cells|Neurons|Receptors, Notch|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btr551', '21994231', 'In the developing nervous system, the expression of proneural genes, i.e. Hes1, Neurogenin-2 (Ngn2) and Deltalike-1 (Dll1), oscillates in neural progenitors with a period of 2-3 h, but is persistent in post-mitotic neurons. Unlike the synchronization of segmentation clocks, oscillations in neural progenitors are asynchronous between cells. It is known that Notch signaling, in which Notch in a cell can be activated by Dll1 in neighboring cells (trans-activation) and can also be inhibited by Dll1 within the same cell (cis-inhibition), is important for neural fate decisions. There have been extensive studies of trans-activation, but the operating mechanisms and potential implications of cis-inhibition are less clear and need to be further investigated.'),
(76537, 2011, 'bio', 'Fast scaffolding with small independent mixed integer programs', 'Salmela, Leena|Mäkinen, Veli|Välimäki, Niko|Ylinen, Johannes|Ukkonen, Esko', 'Department of Computer Science, Helsinki Institute for Information Technology, University of Helsinki, Helsinki, Finland. leena.salmela@cs.helsinki.fi|Department of Computer Science, Helsinki Institute for Information Technology, University of Helsinki, Helsinki, Finland. leena.salmela@cs.helsinki.fi|Department of Computer Science, Helsinki Institute for Information Technology, University of Helsinki, Helsinki, Finland. leena.salmela@cs.helsinki.fi|Department of Computer Science, Helsinki Institute for Information Technology, University of Helsinki, Helsinki, Finland. leena.salmela@cs.helsinki.fi|Department of Computer Science, Helsinki Institute for Information Technology, University of Helsinki, Helsinki, Finland. leena.salmela@cs.helsinki.fi', 'Finland|Finland|Finland|Finland|Finland', 0, 'Algorithms|Animals|Caenorhabditis elegans|Escherichia coli|Genome|High-Throughput Nucleotide Sequencing|Pseudomonas syringae|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr562', '21998153', 'Assembling genomes from short read data has become increasingly popular, but the problem remains computationally challenging especially for larger genomes. We study the scaffolding phase of sequence assembly where preassembled contigs are ordered based on mate pair data.'),
(76538, 2011, 'bio', 'Sequential Monte Carlo multiple testing', 'Sandve, Geir Kjetil|Ferkingstad, Egil|Nygård, Ståle', 'Department of Informatics, University of Oslo, Oslo, Norway. geirksa@ifi.uio.no|Department of Informatics, University of Oslo, Oslo, Norway. geirksa@ifi.uio.no|Department of Informatics, University of Oslo, Oslo, Norway. geirksa@ifi.uio.no', 'Norway|Norway|Norway', 17, 'Algorithms|Computer Simulation|Genome-Wide Association Study|Genomics|Histone Code|Monte Carlo Method', 'Journal Article', '10.1093/bioinformatics/btr568', '21998154', 'In molecular biology, as in many other scientific fields, the scale of analyses is ever increasing. Often, complex Monte Carlo simulation is required, sometimes within a large-scale multiple testing setting. The resulting computational costs may be prohibitively high.'),
(76539, 2011, 'bio', 'Protein stability: a single recorded mutation aids in predicting the effects of other mutations in the same amino acid site', 'Wainreb, Gilad|Wolf, Lior|Ashkenazy, Haim|Dehouck, Yves|Ben-Tal, Nir', 'Department of Biochemistry and Molecular Biology, Tel-Aviv University, Ramat Aviv 69978, Israel.|Department of Biochemistry and Molecular Biology, Tel-Aviv University, Ramat Aviv 69978, Israel.|Department of Biochemistry and Molecular Biology, Tel-Aviv University, Ramat Aviv 69978, Israel.|Department of Biochemistry and Molecular Biology, Tel-Aviv University, Ramat Aviv 69978, Israel.|Department of Biochemistry and Molecular Biology, Tel-Aviv University, Ramat Aviv 69978, Israel.', 'Israel|Israel|Israel|Israel|Israel', 0, 'Algorithms|Amino Acid Substitution|Amino Acids|Chymotrypsin|Hordeum|Mutation|Protein Stability|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btr576', '21998155', 'Accurate prediction of protein stability is important for understanding the molecular underpinnings of diseases and for the design of new proteins. We introduce a novel approach for the prediction of changes in protein stability that arise from a single-site amino acid substitution, the approach uses available data on mutations occurring in the same position and in other positions. Our algorithm, named Pro-Maya (Protein Mutant stAbilitY Analyzer), combines a collaborative filtering baseline model, Random Forests regression and a diverse set of features. Pro-Maya predicts the stability free energy difference of mutant versus wild type, denoted as xcex94xcex94G.'),
(76540, 2011, 'bio', 'Extraction of data deposition statements from the literature: a method for automatically tracking research results', 'Névéol, Aurélie|Wilbur, W John|Lu, Zhiyong', 'National Center for Biotechnology Information, National Library of Medicine, Bethesda, Maryland 20894, USA. aurelie.neveol@nih.gov|National Center for Biotechnology Information, National Library of Medicine, Bethesda, Maryland 20894, USA. aurelie.neveol@nih.gov|National Center for Biotechnology Information, National Library of Medicine, Bethesda, Maryland 20894, USA. aurelie.neveol@nih.gov', 'United States|United States|United States', 21, 'Algorithms|Artificial Intelligence|Automation|Databases, Genetic|MEDLINE|Molecular Sequence Data|National Library of Medicine (U.S.)|PubMed|Support Vector Machine|United States', 'Journal Article', '10.1093/bioinformatics/btr573', '21998156', 'Research in the biomedical domain can have a major impact through open sharing of the data produced. For this reason, it is important to be able to identify instances of data production and deposition for potential re-use. Herein, we report on the automatic identification of data deposition statements in research articles.'),
(76541, 2011, 'bio', 'BDTcomparator: a program for comparing binary classifiers', 'Fijorek, Kamil|Fijorek, Damian|Wisniowska, Barbara|Polak, Sebastian', 'Department of Statistics, Cracow University of Economics, 31-510 Cracow, Poland. kamil.fijorek@uek.krakow.pl|Department of Statistics, Cracow University of Economics, 31-510 Cracow, Poland. kamil.fijorek@uek.krakow.pl|Department of Statistics, Cracow University of Economics, 31-510 Cracow, Poland. kamil.fijorek@uek.krakow.pl|Department of Statistics, Cracow University of Economics, 31-510 Cracow, Poland. kamil.fijorek@uek.krakow.pl', 'Poland|Poland|Poland|Poland', 0, 'Computational Biology|Drug-Related Side Effects and Adverse Reactions|Humans|Predictive Value of Tests|Sensitivity and Specificity|Software', 'Journal Article', '10.1093/bioinformatics/btr574', '21998157', 'The BDTcomparator facilitates the selection of the best performing binary classification model or binary diagnostic procedure from the many possible alternatives by comparing their predictions with a known output, measured with the use of a system recognized as the gold standard. The program calculates the estimates of accuracy, sensitivity, specificity, predictive values and diagnostic likelihood ratios along with appropriate confidence intervals. Furthermore, all pairwise comparisons with respect to the above-mentioned measures are calculated. The formatted results can be exported to a text-file.'),
(76542, 2011, 'bio', 'An assessment of substitution scores for protein profile-profile comparison', 'Ye, Xugang|Wang, Guoli|Altschul, Stephen F', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.', 'United States|United States|United States', 6, 'Amino Acid Sequence|Computational Biology|Eukaryota|Probability|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btr565', '21998158', 'Pairwise protein sequence alignments are generally evaluated using scores defined as the sum of substitution scores for aligning amino acids to one another, and gap scores for aligning runs of amino acids in one sequence to null characters inserted into the other. Protein profiles may be abstracted from multiple alignments of protein sequences, and substitution and gap scores have been generalized to the alignment of such profiles either to single sequences or to other profiles. Although there is widespread agreement on the general form substitution scores should take for profile-sequence alignment, little consensus has been reached on how best to construct profile-profile substitution scores, and a large number of these scoring systems have been proposed. Here, we assess a variety of such substitution scores. For this evaluation, given a gold standard set of multiple alignments, we calculate the probability that a profile column yields a higher substitution score when aligned to a related than to an unrelated column. We also generalize this measure to sets of two or three adjacent columns. This simple approach has the advantages that it does not depend primarily upon the gold-standard alignment columns with the weakest empirical support, and that it does not need to fit gap and offset costs for use with each substitution score studied.'),
(76543, 2011, 'bio', 'Mapping personal functional data to personal genomes', 'Rivas-Astroza, Marcelo|Xie, Dan|Cao, Xiaoyi|Zhong, Sheng', 'Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.', 'United States|United States|United States|United States', 5, 'DNA Copy Number Variations|Genome, Human|Genomics|Humans|Individuality|Oligonucleotide Array Sequence Analysis|Polymorphism, Genetic|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btr578', '22006915', 'The sequencing of personal genomes enabled analysis of variation in transcription factor (TF) binding, chromatin structure and gene expression and indicated how they contribute to phenotypic variation. It is hypothesized that using the reference genome for mapping ChIP-seq or RNA-seq reads may introduce errors, especially at polymorphic genomic regions.'),
(76544, 2011, 'bio', 'Enrich: software for analysis of protein function by enrichment and depletion of variants', 'Fowler, Douglas M|Araya, Carlos L|Gerard, Wayne|Fields, Stanley', 'Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. dfowler@uw.edu|Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. dfowler@uw.edu|Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. dfowler@uw.edu|Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. dfowler@uw.edu', 'United States|United States|United States|United States', 0, 'Computational Biology|DNA Mutational Analysis|Genome|High-Throughput Nucleotide Sequencing|Mutation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btr577', '22006916', 'Measuring the consequences of mutation in proteins is critical to understanding their function. These measurements are essential in such applications as protein engineering, drug development, protein design and genome sequence analysis. Recently, high-throughput sequencing has been coupled to assays of protein activity, enabling the analysis of large numbers of mutations in parallel. We present Enrich, a tool for analyzing such deep mutational scanning data. Enrich identifies all unique variants (mutants) of a protein in high-throughput sequencing datasets and can correct for sequencing errors using overlapping paired-end reads. Enrich uses the frequency of each variant before and after selection to calculate an enrichment ratio, which is used to estimate fitness. Enrich provides an interactive interface to guide users. It generates user-accessible output for downstream analyses as well as several visualizations of the effects of mutation on function, thereby allowing the user to rapidly quantify and comprehend sequence-function relationships.'),
(76545, 2011, 'bio', 'MetaRank: a rank conversion scheme for comparative analysis of microbial community compositions', 'Wang, Tse-Yi|Su, Chien-Hao|Tsai, Huai-Kuang', 'Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan.|Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan.|Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan.', '-|-|-', 1, 'Adult|Bacteria|Computational Biology|DNA, Bacterial|Gastrointestinal Tract|Humans|Infant|Metagenome|Metagenomics|Obesity|Phylogeny|RNA, Ribosomal, 16S|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btr583', '22016405', 'Metagenomics involves sampling and studying the genetic materials in microbial communities. Several statistical methods have been proposed for comparative analysis of microbial community compositions. Most of the methods are based on the estimated abundances of taxonomic units or functional groups from metagenomic samples. However, such estimated abundances might deviate from the true abundances in habitats due to sampling biases and other systematic artifacts in metagenomic data processing.'),
(76546, 2011, 'bio', 'Predicting residue-residue contacts using random forest models', 'Li, Yunqi|Fang, Yaping|Fang, Jianwen', 'Applied Bioinformatics Laboratory, The University of Kansas, Lawrence, KS 66047, USA.|Applied Bioinformatics Laboratory, The University of Kansas, Lawrence, KS 66047, USA.|Applied Bioinformatics Laboratory, The University of Kansas, Lawrence, KS 66047, USA.', 'United States|United States|United States', 37, 'Algorithms|Amino Acids|Artificial Intelligence|Computational Biology|Models, Molecular|Proteins', 'Journal Article', '10.1093/bioinformatics/btr579', '22016406', 'Protein residue-residue contact prediction can be useful in predicting protein 3D structures. Current algorithms for such a purpose leave room for improvement.'),
(76547, 2011, 'bio', 'PRINCIPLE: a tool for associating genes with diseases via network propagation', 'Gottlieb, Assaf|Magger, Oded|Berman, Igor|Ruppin, Eytan|Sharan, Roded', 'The Balavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. assafgot@tau.ac.il|The Balavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. assafgot@tau.ac.il|The Balavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. assafgot@tau.ac.il|The Balavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. assafgot@tau.ac.il|The Balavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. assafgot@tau.ac.il', 'Israel|Israel|Israel|Israel|Israel', 28, 'Algorithms|Disease|Genetic Predisposition to Disease|Humans|Protein Interaction Maps|Software', 'Journal Article', '10.1093/bioinformatics/btr584', '22016407', 'PRINCIPLE is a Java application implemented as a Cytoscape plug-in, based on a previously published algorithm, PRINCE. Given a query disease, it prioritizes disease-related genes based on their closeness in a protein-protein interaction network to genes causing phenotypically similar disorders to the query disease.'),
(76548, 2011, 'bio', 'A system-level approach for deciphering the transcriptional response to prion infection', 'Zampieri, Mattia|Legname, Giuseppe|Segrè, Daniel|Altafini, Claudio', 'Institute of Molecular Systems Biology, ETH, Wolfgang-Pauli-Strasse 16, 8093 Zurich, Switzerland.|Institute of Molecular Systems Biology, ETH, Wolfgang-Pauli-Strasse 16, 8093 Zurich, Switzerland.|Institute of Molecular Systems Biology, ETH, Wolfgang-Pauli-Strasse 16, 8093 Zurich, Switzerland.|Institute of Molecular Systems Biology, ETH, Wolfgang-Pauli-Strasse 16, 8093 Zurich, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Animals|Computational Biology|Gene Expression Profiling|Gene Expression Regulation|Humans|Mice|Models, Genetic|Prion Diseases|Prions|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btr580', '22016408', 'Deciphering the response of a complex biological system to an insulting event, at the gene expression level, requires adopting theoretical models that are more sophisticated than a one-to-one comparison (i.e. t-test). Here, we investigate the ability of a novel reverse engineering approach (System Response Inference) to unveil non-obvious transcriptional signatures of the system response induced by prion infection.'),
(76549, 2011, 'bio', 'VizPrimer: a web server for visualized PCR primer design based on known gene structure', 'Zhou, Yang|Qu, Wubin|Lu, Yiming|Zhang, Yanchun|Wang, Xiaolei|Zhao, Dongsheng|Yang, Yi|Zhang, Chenggang', 'Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Cognitive and Mental Health Research Center, Beijing 100850, China.|Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Cognitive and Mental Health Research Center, Beijing 100850, China.|Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Cognitive and Mental Health Research Center, Beijing 100850, China.|Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Cognitive and Mental Health Research Center, Beijing 100850, China.|Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Cognitive and Mental Health Research Center, Beijing 100850, China.|Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Cognitive and Mental Health Research Center, Beijing 100850, China.|Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Cognitive and Mental Health Research Center, Beijing 100850, China.|Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Cognitive and Mental Health Research Center, Beijing 100850, China.', 'China|China|China|China|China|China|China|China', 3, 'Animals|DNA Primers|Exons|Humans|Membrane Proteins|Mice|Nerve Tissue Proteins|Open Reading Frames|Polymerase Chain Reaction|Polymorphism, Single Nucleotide|Protein Isoforms', 'Journal Article', '10.1093/bioinformatics/btr582', '22016409', 'The visualization of gene structure plays an important role in polymerase chain reaction (PCR) primer design, especially for eukaryotic genes with a number of splice variants that users need to distinguish between via PCR. Here, we describe a visualized web server for primer design named VizPrimer. It utilizes the new information technology (IT) tools, HTML5 to display gene structure and JavaScript to interact with the users. In VizPrimer, the users can focus their attention on the gene structure and primer design strategy, without wasting time calculating the exon positions of splice variants or manually configuring complicated parameters. In addition, VizPrimer is also suitable for the design of PCR primers for amplifying open reading frames and detecting single nucleotide polymorphisms (SNPs).');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76550, 2011, 'bio', 'BioPAX support in CellDesigner', 'Mi, Huaiyu|Muruganujan, Anushya|Demir, Emek|Matsuoka, Yukiko|Funahashi, Akira|Kitano, Hiroaki|Thomas, Paul D', 'Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA. huaiyumi@usc.edu|Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA. huaiyumi@usc.edu|Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA. huaiyumi@usc.edu|Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA. huaiyumi@usc.edu|Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA. huaiyumi@usc.edu|Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA. huaiyumi@usc.edu|Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA. huaiyumi@usc.edu', 'United States|United States|United States|United States|United States|United States|United States', 13, 'Animals|Computational Biology|Databases, Factual|Humans|Metabolic Networks and Pathways|Models, Biological|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/btr586', '22021903', 'BioPAX is a standard language for representing and exchanging models of biological processes at the molecular and cellular levels. It is widely used by different pathway databases and genomics data analysis software. Currently, the primary source of BioPAX data is direct exports from the curated pathway databases. It is still uncommon for wet-lab biologists to share and exchange pathway knowledge using BioPAX. Instead, pathways are usually represented as informal diagrams in the literature. In order to encourage formal representation of pathways, we describe a software package that allows users to create pathway diagrams using CellDesigner, a user-friendly graphical pathway-editing tool and save the pathway data in BioPAX Level 3 format.'),
(76551, 2011, 'bio', 'PoPoolation2: identifying differentiation between populations using sequencing of pooled DNA samples (Pool-Seq)', 'Kofler, Robert|Pandey, Ram Vinay|Schlötterer, Christian', 'Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz 1, A-1210 Wien, Austria.|Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz 1, A-1210 Wien, Austria.|Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz 1, A-1210 Wien, Austria.', 'Austria|Austria|Austria', 0, 'Animals|Arabidopsis|Drosophila melanogaster|Genetics, Population|Genomics|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr589', '22025480', 'Sequencing pooled DNA samples (Pool-Seq) is the most cost-effective approach for the genome-wide comparison of population samples. Here, we introduce PoPoolation2, the first software tool specifically designed for the comparison of populations with Pool-Seq data. PoPoolation2 implements a range of commonly used measures of differentiation (F(ST), Fishers exact test and Cochran-Mantel-Haenszel test) that can be applied on different scales (windows, genes, exons, SNPs). The result may be visualized with the widely used Integrated Genomics Viewer.'),
(76552, 2012, 'bio', 'Graph accordance of next-generation sequence assemblies', 'Yao, Guohui|Ye, Liang|Gao, Hongyu|Minx, Patrick|Warren, Wesley C|Weinstock, George M', 'The Genome Institute, Washington University School of Medicine, 4444 Forest Park Avenue, St Louis, MO 63108, USA.|The Genome Institute, Washington University School of Medicine, 4444 Forest Park Avenue, St Louis, MO 63108, USA.|The Genome Institute, Washington University School of Medicine, 4444 Forest Park Avenue, St Louis, MO 63108, USA.|The Genome Institute, Washington University School of Medicine, 4444 Forest Park Avenue, St Louis, MO 63108, USA.|The Genome Institute, Washington University School of Medicine, 4444 Forest Park Avenue, St Louis, MO 63108, USA.|The Genome Institute, Washington University School of Medicine, 4444 Forest Park Avenue, St Louis, MO 63108, USA.', 'United States|United States|United States|United States|United States|United States', 35, 'Algorithms|Animals|Chickens|Contig Mapping|Genome|High-Throughput Nucleotide Sequencing|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btr588', '22025481', 'No individual assembly algorithm addresses all the known limitations of assembling short-length sequences. Overall reduced sequence contig length is the major problem that challenges the usage of these assemblies. We describe an algorithm to take advantages of different assembly algorithms or sequencing platforms to improve the quality of next-generation sequence (NGS) assemblies.'),
(76553, 2012, 'bio', 'SVGMap: configurable image browser for experimental data', 'Rafael-Palou, Xavier|Schroeder, Michael P|Lopez-Bigas, Nuria', 'Department of Experimental and Health Sciences, Research Unit on Biomedical Informatics (GRIB), Universitat Pompeu Fabra-IMIM, Dr Aiguader 88, Barcelona, Spain.|Department of Experimental and Health Sciences, Research Unit on Biomedical Informatics (GRIB), Universitat Pompeu Fabra-IMIM, Dr Aiguader 88, Barcelona, Spain.|Department of Experimental and Health Sciences, Research Unit on Biomedical Informatics (GRIB), Universitat Pompeu Fabra-IMIM, Dr Aiguader 88, Barcelona, Spain.', 'Spain|Spain|Spain', 0, 'Arabidopsis|Color|Computer Graphics|Gene Expression Profiling|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr581', '22034520', 'Spatial data visualization is very useful to represent biological data and quickly interpret the results. For instance, to show the expression pattern of a gene in different tissues of a fly, an intuitive approach is to draw the fly with the corresponding tissues and color the expression of the gene in each of them. However, the creation of these visual representations may be a burdensome task. Here we present SVGMap, a java application that automatizes the generation of high-quality graphics for singular data items (e.g. genes) and biological conditions. SVGMap contains a browser that allows the user to navigate the different images created and can be used as a web-based results publishing tool.'),
(76554, 2011, 'bio', 'Automatic rebuilding and optimization of crystallographic structures in the Protein Data Bank', 'Joosten, Robbie P|Joosten, Krista|Cohen, Serge X|Vriend, Gert|Perrakis, Anastassis', 'Department of Biochemistry, NKI, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands. r.joosten@nki.nl|Department of Biochemistry, NKI, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands. r.joosten@nki.nl|Department of Biochemistry, NKI, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands. r.joosten@nki.nl|Department of Biochemistry, NKI, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands. r.joosten@nki.nl|Department of Biochemistry, NKI, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands. r.joosten@nki.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Computational Biology|Crystallography, X-Ray|Databases, Protein|Peptides|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btr590', '22034521', 'Macromolecular crystal structures in the Protein Data Bank (PDB) are a key source of structural insight into biological processes. These structures, some >30 years old, were constructed with methods of their era. With PDB_REDO, we aim to automatically optimize these structures to better fit their corresponding experimental data, passing the benefits of new methods in crystallography on to a wide base of non-crystallographer structure users.'),
(76555, 2012, 'bio', 'RAPSearch2: a fast and memory-efficient protein similarity search tool for next-generation sequencing data', 'Zhao, Yongan|Tang, Haixu|Ye, Yuzhen', 'School of Informatics and Computing, Indiana University, Bloomington, IN 47404, USA.|School of Informatics and Computing, Indiana University, Bloomington, IN 47404, USA.|School of Informatics and Computing, Indiana University, Bloomington, IN 47404, USA.', 'India|India|India', 233, 'Algorithms|Databases, Protein|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Programming Languages|Proteins|Search Engine|Software', 'Journal Article', '10.1093/bioinformatics/btr595', '22039206', 'With the wide application of next-generation sequencing (NGS) techniques, fast tools for protein similarity search that scale well to large query datasets and large databases are highly desirable. In a previous work, we developed RAPSearch, an algorithm that achieved a ~20-90-fold speedup relative to BLAST while still achieving similar levels of sensitivity for short protein fragments derived from NGS data. RAPSearch, however, requires a substantial memory footprint to identify alignment seeds, due to its use of a suffix array data structure. Here we present RAPSearch2, a new memory-efficient implementation of the RAPSearch algorithm that uses a collision-free hash table to index a similarity search database. The utilization of an optimized data structure further speeds up the similarity search-another 2-3 times. We also implemented multi-threading in RAPSearch2, and the multi-thread modes achieve significant acceleration (e.g. 3.5X for 4-thread mode). RAPSearch2 requires up to 2G memory when running in single thread mode, or up to 3.5G memory when running in 4-thread mode.'),
(76556, 2011, 'bio', 'STRIKE: evaluation of protein MSAs using a single 3D structure', 'Kemena, Carsten|Taly, Jean-Francois|Kleinjung, Jens|Notredame, Cedric', 'Bioinformatics and Genomics Program, Centre for Genomic Regulation and UPF, Aiguader, 88, 08003 Barcelona, Spain.|Bioinformatics and Genomics Program, Centre for Genomic Regulation and UPF, Aiguader, 88, 08003 Barcelona, Spain.|Bioinformatics and Genomics Program, Centre for Genomic Regulation and UPF, Aiguader, 88, 08003 Barcelona, Spain.|Bioinformatics and Genomics Program, Centre for Genomic Regulation and UPF, Aiguader, 88, 08003 Barcelona, Spain.', 'Spain|Spain|Spain|Spain', 0, 'Computational Biology|Internet|Proteins|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btr587', '22039207', 'Evaluating alternative multiple protein sequence alignments is an important unsolved problem in Biology. The most accurate way of doing this is to use structural information. Unfortunately, most methods require at least two structures to be embedded in the alignment, a condition rarely met when dealing with standard datasets.'),
(76557, 2012, 'bio', 'Comments on An empirical comparison of several recent epistatic interaction detection methods', 'Wan, Xiang|Yang, Can|Yu, Weichuan', 'Bioinformatics and Genomics Program, Centre for Genomic Regulation and UPF, Aiguader, 88, 08003 Barcelona, Spain.|Bioinformatics and Genomics Program, Centre for Genomic Regulation and UPF, Aiguader, 88, 08003 Barcelona, Spain.|Bioinformatics and Genomics Program, Centre for Genomic Regulation and UPF, Aiguader, 88, 08003 Barcelona, Spain.', 'Spain|Spain|Spain', 0, 'Epistasis, Genetic|Genome-Wide Association Study|Polymorphism, Single Nucleotide|Software', 'Letter', '10.1093/bioinformatics/btr596', '22039208', '-'),
(76558, 2012, 'bio', 'Correcting for cancer genome size and tumour cell content enables better estimation of copy number alterations from next-generation sequence data', 'Gusnanto, Arief|Wood, Henry M|Pawitan, Yudi|Rabbitts, Pamela|Berri, Stefano', 'Department of Statistics, University of Leeds, Leeds LS2 9JT, UK.|Department of Statistics, University of Leeds, Leeds LS2 9JT, UK.|Department of Statistics, University of Leeds, Leeds LS2 9JT, UK.|Department of Statistics, University of Leeds, Leeds LS2 9JT, UK.|Department of Statistics, University of Leeds, Leeds LS2 9JT, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Cell Line, Tumor|Computer Simulation|DNA Copy Number Variations|Genome Size|High-Throughput Nucleotide Sequencing|Humans|Lung Neoplasms|Neoplasms|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr593', '22039209', 'Comparison of read depths from next-generation sequencing between cancer and normal cells makes the estimation of copy number alteration (CNA) possible, even at very low coverage. However, estimating CNA from patients tumour samples poses considerable challenges due to infiltration with normal cells and aneuploid cancer genomes. Here we provide a method that corrects contamination with normal cells and adjusts for genomes of different sizes so that the actual copy number of each region can be estimated.'),
(76559, 2012, 'bio', 'Determining the evolutionary history of gene families', 'Ames, Ryan M|Money, Daniel|Ghatge, Vikramsinh P|Whelan, Simon|Lovell, Simon C', 'Faculty of Life Sciences, University of Manchester, Oxford Road, Manchester M13 9PL, UK.|Faculty of Life Sciences, University of Manchester, Oxford Road, Manchester M13 9PL, UK.|Faculty of Life Sciences, University of Manchester, Oxford Road, Manchester M13 9PL, UK.|Faculty of Life Sciences, University of Manchester, Oxford Road, Manchester M13 9PL, UK.|Faculty of Life Sciences, University of Manchester, Oxford Road, Manchester M13 9PL, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 23, 'Animals|Computer Simulation|Drosophila|Evolution, Molecular|Genome, Insect|Likelihood Functions|Markov Chains|Models, Genetic', 'Journal Article', '10.1093/bioinformatics/btr592', '22039210', 'Recent large-scale studies of individuals within a population have demonstrated that there is widespread variation in copy number in many gene families. In addition, there is increasing evidence that the variation in gene copy number can give rise to substantial phenotypic effects. In some cases, these variations have been shown to be adaptive. These observations show that a full understanding of the evolution of biological function requires an understanding of gene gain and gene loss. Accurate, robust evolutionary models of gain and loss events are, therefore, required.'),
(76560, 2011, 'bio', 'Cascade detection for the extraction of localized sequence features, specificity results for HIV-1 protease and structure-function results for the Schellman loop', 'Newell, Nicholas E', 'nacnewell@comcast.net', '-', 7, 'Algorithms|Amino Acid Motifs|Computational Biology|HIV Protease|HIV-1|Humans|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1093/bioinformatics/btr594', '22039211', 'The extraction of the set of features most relevant to function from classified biological sequence sets is still a challenging problem. A central issue is the determination of expected counts for higher order features so that artifact features may be screened.'),
(76561, 2012, 'bio', 'MissForest--non-parametric missing value imputation for mixed-type data', 'Stekhoven, Daniel J|Bühlmann, Peter', 'Seminar for Statistics, Department of Mathematics, ETH Zurich, Zurich, Switzerland.|Seminar for Statistics, Department of Mathematics, ETH Zurich, Zurich, Switzerland.', 'Switzerland|Switzerland', 825, 'Algorithms|Arabidopsis|Data Interpretation, Statistical|Escherichia coli|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btr597', '22039212', 'Modern data acquisition based on high-throughput technology is often facing the problem of missing data. Algorithms commonly used in the analysis of such large-scale data often depend on a complete set. Missing value imputation offers a solution to this problem. However, the majority of available imputation methods are restricted to one type of variable only: continuous or categorical. For mixed-type data, the different types are usually handled separately. Therefore, these methods ignore possible relations between variable types. We propose a non-parametric method which can cope with different types of variables simultaneously.'),
(76562, 2011, 'bio', 'TIP: a probabilistic method for identifying transcription factor target genes from ChIP-seq binding profiles', 'Cheng, Chao|Min, Renqiang|Gerstein, Mark', 'Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA.|Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA.|Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA.', 'United States|United States|United States', 0, 'Amino Acid Motifs|Animals|Binding Sites|Chromatin Immunoprecipitation|Estrogen Receptor alpha|Gene Expression Regulation|Mice|Models, Statistical|Oligonucleotide Array Sequence Analysis|Protein Binding|STAT4 Transcription Factor|Sequence Analysis, DNA|Transcription Factors|Transcription Initiation Site', 'Journal Article', '10.1093/bioinformatics/btr552', '22039215', 'ChIP-seq and ChIP-chip experiments have been widely used to identify transcription factor (TF) binding sites and target genes. Conventionally, a fairly simple approach is employed for target gene identification e.g. finding genes with binding sites within 2 kb of a transcription start site (TSS). However, this does not take into account the number of sites upstream of the TSS, their exact positioning or the fact that different TFs appear to act at different characteristic distances from the TSS.'),
(76563, 2012, 'bio', 'deepBlockAlign: a tool for aligning RNA-seq profiles of read block patterns', 'Langenberger, David|Pundhir, Sachin|Ekstrøm, Claus T|Stadler, Peter F|Hoffmann, Steve|Gorodkin, Jan', 'Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, Universität Leipzig, Philipp-Rosenthal-Strasse 27, D-04107 Leipzig, Germany.|Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, Universität Leipzig, Philipp-Rosenthal-Strasse 27, D-04107 Leipzig, Germany.|Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, Universität Leipzig, Philipp-Rosenthal-Strasse 27, D-04107 Leipzig, Germany.|Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, Universität Leipzig, Philipp-Rosenthal-Strasse 27, D-04107 Leipzig, Germany.|Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, Universität Leipzig, Philipp-Rosenthal-Strasse 27, D-04107 Leipzig, Germany.|Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, Universität Leipzig, Philipp-Rosenthal-Strasse 27, D-04107 Leipzig, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Base Sequence|High-Throughput Nucleotide Sequencing|Humans|MicroRNAs|RNA, Untranslated|Sequence Alignment|Sequence Analysis, RNA|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btr598', '22053076', 'High-throughput sequencing methods allow whole transcriptomes to be sequenced fast and cost-effectively. Short RNA sequencing provides not only quantitative expression data but also an opportunity to identify novel coding and non-coding RNAs. Many long transcripts undergo post-transcriptional processing that generates short RNA sequence fragments. Mapped back to a reference genome, they form distinctive patterns that convey information on both the structure of the parent transcript and the modalities of its processing. The miR-miR* pattern from microRNA precursors is the best-known, but by no means singular, example.'),
(76564, 2012, 'bio', 'AMPA: an automated web server for prediction of protein antimicrobial regions', 'Torrent, Marc|Di Tommaso, Paolo|Pulido, David|Nogués, M Victòria|Notredame, Cedric|Boix, Ester|Andreu, David', 'Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Dr Aiguader 88, Barcelona, Spain.|Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Dr Aiguader 88, Barcelona, Spain.|Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Dr Aiguader 88, Barcelona, Spain.|Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Dr Aiguader 88, Barcelona, Spain.|Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Dr Aiguader 88, Barcelona, Spain.|Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Dr Aiguader 88, Barcelona, Spain.|Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Dr Aiguader 88, Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain', 0, 'Algorithms|Anti-Infective Agents|Antimicrobial Cationic Peptides|Internet|Peptides|Programming Languages|Protein Structure, Tertiary|Software', 'Journal Article', '10.1093/bioinformatics/btr604', '22053077', 'AMPA is a web application for assessing the antimicrobial domains of proteins, with a focus on the design on new antimicrobial drugs. The application provides fast discovery of antimicrobial patterns in proteins that can be used to develop new peptide-based drugs against pathogens. Results are shown in a user-friendly graphical interface and can be downloaded as raw data for later examination.'),
(76565, 2012, 'bio', 'Detecting genome-wide epistases based on the clustering of relatively frequent items', 'Xie, Minzhu|Li, Jing|Jiang, Tao', 'Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.|Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.|Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.', 'United States|United States|United States', 41, 'Algorithms|Cluster Analysis|Epistasis, Genetic|Genetic Predisposition to Disease|Genome-Wide Association Study|Humans|Macular Degeneration|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btr603', '22053078', 'In genome-wide association studies (GWAS), up to millions of single nucleotide polymorphisms (SNPs) are genotyped for thousands of individuals. However, conventional single locus-based approaches are usually unable to detect gene-gene interactions underlying complex diseases. Due to the huge search space for complicated high order interactions, many existing multi-locus approaches are slow and may suffer from low detection power for GWAS.'),
(76566, 2012, 'bio', 'AURA: Atlas of UTR Regulatory Activity', 'Dassi, E|Malossini, A|Re, A|Mazza, T|Tebaldi, T|Caputi, L|Quattrone, A', 'Laboratory of Translational Genomics - Centre for Integrative Biology, University of Trento, Via delle Regole, 101, 38123 Mattarello (TN), Italy.|Laboratory of Translational Genomics - Centre for Integrative Biology, University of Trento, Via delle Regole, 101, 38123 Mattarello (TN), Italy.|Laboratory of Translational Genomics - Centre for Integrative Biology, University of Trento, Via delle Regole, 101, 38123 Mattarello (TN), Italy.|Laboratory of Translational Genomics - Centre for Integrative Biology, University of Trento, Via delle Regole, 101, 38123 Mattarello (TN), Italy.|Laboratory of Translational Genomics - Centre for Integrative Biology, University of Trento, Via delle Regole, 101, 38123 Mattarello (TN), Italy.|Laboratory of Translational Genomics - Centre for Integrative Biology, University of Trento, Via delle Regole, 101, 38123 Mattarello (TN), Italy.|Laboratory of Translational Genomics - Centre for Integrative Biology, University of Trento, Via delle Regole, 101, 38123 Mattarello (TN), Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy', 16, 'Databases, Genetic|Humans|Internet|Phylogeny|RNA, Messenger|Software|Untranslated Regions', 'Journal Article', '10.1093/bioinformatics/btr608', '22057158', 'The Atlas of UTR Regulatory Activity (AURA) is a manually curated and comprehensive catalog of human mRNA untranslated regions (UTRs) and UTR regulatory annotations. Through its intuitive web interface, it provides full access to a wealth of information on UTRs that integrates phylogenetic conservation, RNA sequence and structure data, single nucleotide variation, gene expression and gene functional descriptions from literature and specialized databases.'),
(76567, 2012, 'bio', 'Gene Ontology-driven inference of protein-protein interactions using inducers', 'Maetschke, Stefan R|Simonsen, Martin|Davis, Melissa J|Ragan, Mark A', 'Institute for Molecular Bioscience, The University of Queensland, Brisbane QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane QLD 4072, Australia.', 'Australia|Australia|Australia|Australia', 0, 'Algorithms|Databases, Protein|Humans|Molecular Sequence Annotation|Protein Interaction Maps|Proteins|ROC Curve|Software|Vocabulary, Controlled|Yeasts', 'Journal Article', '10.1093/bioinformatics/btr610', '22057159', 'Protein-protein interactions (PPIs) are pivotal for many biological processes and similarity in Gene Ontology (GO) annotation has been found to be one of the strongest indicators for PPI. Most GO-driven algorithms for PPI inference combine machine learning and semantic similarity techniques. We introduce the concept of inducers as a method to integrate both approaches more effectively, leading to superior prediction accuracies.'),
(76568, 2012, 'bio', 'Large-scale motif discovery using DNA Gray code and equiprobable oligomers', 'Ichinose, Natsuhiro|Yada, Tetsushi|Gotoh, Osamu', 'Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan.|Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan.|Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan.', 'Japan|Japan|Japan', 12, 'Algorithms|Cluster Analysis|Genome|Humans|Nucleotide Motifs|Promoter Regions, Genetic|RNA, Untranslated|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btr606', '22057160', 'How to find motifs from genome-scale functional sequences, such as all the promoters in a genome, is a challenging problem. Word-based methods count the occurrences of oligomers to detect excessively represented ones. This approach is known to be fast and accurate compared with other methods. However, two problems have hampered the application of such methods to large-scale data. One is the computational cost necessary for clustering similar oligomers, and the other is the bias in the frequency of fixed-length oligomers, which complicates the detection of significant words.'),
(76569, 2012, 'bio', 'Detecting differential binding of transcription factors with ChIP-seq', 'Liang, Kun|Keles, Sündüz', 'Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706, USA.|Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706, USA.', 'United States|United States', 54, 'Animals|Caenorhabditis elegans|Chromatin Immunoprecipitation|Oligonucleotide Array Sequence Analysis|Protein Binding|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr605', '22057161', 'Increasing number of ChIP-seq experiments are investigating transcription factor binding under multiple experimental conditions, for example, various treatment conditions, several distinct time points and different treatment dosage levels. Hence, identifying differential binding sites across multiple conditions is of practical importance in biological and medical research. To this end, we have developed a powerful and flexible program, called DBChIP, to detect differentially bound sharp binding sites across multiple conditions, with or without matching control samples. By assigning uncertainty measure to the putative differential binding sites, DBChIP facilitates downstream analysis. DBChIP is implemented in R programming language and can work with a wide range of sequencing file formats.'),
(76570, 2012, 'bio', 'A robust clustering algorithm for identifying problematic samples in genome-wide association studies', 'Bellenguez, Céline|Strange, Amy|Freeman, Colin|Wellcome Trust Case Control Consortium|Donnelly, Peter|Spencer, Chris C A', 'Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK.|Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK.|Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK.|Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK.|Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK.|Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 27, 'Algorithms|Cluster Analysis|Cohort Studies|Female|Genome-Wide Association Study|Humans|Male|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btr599', '22057162', 'High-throughput genotyping arrays provide an efficient way to survey single nucleotide polymorphisms (SNPs) across the genome in large numbers of individuals. Downstream analysis of the data, for example in genome-wide association studies (GWAS), often involves statistical models of genotype frequencies across individuals. The complexities of the sample collection process and the potential for errors in the experimental assay can lead to biases and artefacts in an individuals inferred genotypes. Rather than attempting to model these complications, it has become a standard practice to remove individuals whose genome-wide data differ from the sample at large. Here we describe a simple, but robust, statistical algorithm to identify samples with atypical summaries of genome-wide variation. Its use as a semi-automated quality control tool is demonstrated using several summary statistics, selected to identify different potential problems, and it is applied to two different genotyping platforms and sample collections.'),
(76571, 2012, 'bio', 'A novel structural position-specific scoring matrix for the prediction of protein secondary structures', 'Li, Dapeng|Li, Tonghua|Cong, Peisheng|Xiong, Wenwei|Sun, Jiangming', 'Department of Chemistry, Tongji University, Shanghai 200092, China.|Department of Chemistry, Tongji University, Shanghai 200092, China.|Department of Chemistry, Tongji University, Shanghai 200092, China.|Department of Chemistry, Tongji University, Shanghai 200092, China.|Department of Chemistry, Tongji University, Shanghai 200092, China.', 'China|China|China|China|China', 27, 'Animals|Humans|Position-Specific Scoring Matrices|Protein Structure, Secondary|Proteins|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/bioinformatics/btr611', '22065541', 'The precise prediction of protein secondary structure is of key importance for the prediction of 3D structure and biological function. Although the development of many excellent methods over the last few decades has allowed the achievement of prediction accuracies of up to 80%, progress seems to have reached a bottleneck, and further improvements in accuracy have proven difficult.'),
(76572, 2012, 'bio', 'Epigenetic priors for identifying active transcription factor binding sites', 'Cuellar-Partida, Gabriel|Buske, Fabian A|McLeay, Robert C|Whitington, Tom|Noble, William Stafford|Bailey, Timothy L', 'Institute for Molecular Bioscience, The University of Queensland, Brisbane QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane QLD 4072, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia', 61, 'Animals|DNA|Epigenomics|Gene Expression Regulation|Histone Code|Humans|Models, Statistical|Nucleotide Motifs|Sequence Analysis, DNA|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr614', '22072382', 'Accurate knowledge of the genome-wide binding of transcription factors in a particular cell type or under a particular condition is necessary for understanding transcriptional regulation. Using epigenetic data such as histone modification and DNase I, accessibility data has been shown to improve motif-based in silico methods for predicting such binding, but this approach has not yet been fully explored.'),
(76573, 2012, 'bio', 'NARWHAL, a primary analysis pipeline for NGS data', 'Brouwer, R W W|van den Hout, M C G N|Grosveld, F G|van Ijcken, W F J', 'Center for Biomics, Department of Cell Biology, Erasmus Medical Center, Rotterdam, The Netherlands.|Center for Biomics, Department of Cell Biology, Erasmus Medical Center, Rotterdam, The Netherlands.|Center for Biomics, Department of Cell Biology, Erasmus Medical Center, Rotterdam, The Netherlands.|Center for Biomics, Department of Cell Biology, Erasmus Medical Center, Rotterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands', 32, 'High-Throughput Nucleotide Sequencing|Humans|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr613', '22072383', 'The NARWHAL software pipeline has been developed to automate the primary analysis of Illumina sequencing data. This pipeline combines a new and flexible de-multiplexing tool with open-source aligners and automated quality assessment. The entire pipeline can be run using only one simple sample-sheet for diverse sequencing applications. NARWHAL creates a sample-oriented data structure and outperforms existing tools in speed.'),
(76574, 2012, 'bio', 'Using Poisson mixed-effects model to quantify transcript-level gene expression in RNA-Seq', 'Hu, Ming|Zhu, Yu|Taylor, Jeremy M G|Liu, Jun S|Qin, Zhaohui S', 'Department of Statistics, Harvard University, Cambridge, MA 02138, USA.|Department of Statistics, Harvard University, Cambridge, MA 02138, USA.|Department of Statistics, Harvard University, Cambridge, MA 02138, USA.|Department of Statistics, Harvard University, Cambridge, MA 02138, USA.|Department of Statistics, Harvard University, Cambridge, MA 02138, USA.', 'United States|United States|United States|United States|United States', 26, 'Cell Line, Tumor|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Male|Microarray Analysis|Models, Statistical|Prostatic Neoplasms|Sequence Analysis, RNA|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btr616', '22072384', 'RNA sequencing (RNA-Seq) is a powerful new technology for mapping and quantifying transcriptomes using ultra high-throughput next-generation sequencing technologies. Using deep sequencing, gene expression levels of all transcripts including novel ones can be quantified digitally. Although extremely promising, the massive amounts of data generated by RNA-Seq, substantial biases and uncertainty in short read alignment pose challenges for data analysis. In particular, large base-specific variation and between-base dependence make simple approaches, such as those that use averaging to normalize RNA-Seq data and quantify gene expressions, ineffective.'),
(76575, 2012, 'bio', 'MR-Tandem: parallel X!Tandem using Hadoop MapReduce on Amazon Web Services', 'Pratt, Brian|Howbert, J Jeffry|Tasman, Natalie I|Nilsson, Erik J', 'Insilicos LLC, Seattle WA, USA.|Insilicos LLC, Seattle WA, USA.|Insilicos LLC, Seattle WA, USA.|Insilicos LLC, Seattle WA, USA.', 'United States|United States|United States|United States', 31, 'Cluster Analysis|Programming Languages|Protein Processing, Post-Translational|Proteins|Search Engine|Software', 'Journal Article', '10.1093/bioinformatics/btr615', '22072385', 'MR-Tandem adapts the popular X!Tandem peptide search engine to work with Hadoop MapReduce for reliable parallel execution of large searches. MR-Tandem runs on any Hadoop cluster but offers special support for Amazon Web Services for creating inexpensive on-demand Hadoop clusters, enabling search volumes that might not otherwise be feasible with the compute resources a researcher has at hand. MR-Tandem is designed to drop in wherever X!Tandem is already in use and requires no modification to existing X!Tandem parameter files, and only minimal modification to X!Tandem-based workflows.'),
(76576, 2012, 'bio', 'Wavelet-based image fusion in multi-view three-dimensional microscopy', 'Rubio-Guivernau, Jose L|Gurchenkov, Vasily|Luengo-Oroz, Miguel A|Duloquin, Louise|Bourgine, Paul|Santos, Andres|Peyrieras, Nadine|Ledesma-Carbayo, Maria J', 'Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politénica de Madrid, Madrid, Spain. jlrubio@die.upm.es|Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politénica de Madrid, Madrid, Spain. jlrubio@die.upm.es|Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politénica de Madrid, Madrid, Spain. jlrubio@die.upm.es|Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politénica de Madrid, Madrid, Spain. jlrubio@die.upm.es|Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politénica de Madrid, Madrid, Spain. jlrubio@die.upm.es|Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politénica de Madrid, Madrid, Spain. jlrubio@die.upm.es|Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politénica de Madrid, Madrid, Spain. jlrubio@die.upm.es|Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politénica de Madrid, Madrid, Spain. jlrubio@die.upm.es', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain', 18, 'Animals|Humans|Image Processing, Computer-Assisted|Microscopy, Fluorescence|Sea Urchins|Software|Zebrafish', 'Journal Article', '10.1093/bioinformatics/btr609', '22072386', 'Multi-view microscopy techniques such as Light-Sheet Fluorescence Microscopy (LSFM) are powerful tools for 3D + time studies of live embryos in developmental biology. The sample is imaged from several points of view, acquiring a set of 3D views that are then combined or fused in order to overcome their individual limitations. Views fusion is still an open problem despite recent contributions in the field.'),
(76577, 2012, 'bio', 'Fast computation of minimum hybridization networks', 'Albrecht, Benjamin|Scornavacca, Celine|Cenci, Alberto|Huson, Daniel H', 'Department of Computer Science, Center for Bioinformatics (ZBIT), Tübingen University, Sand 14, 72076 Tübingen, Germany.|Department of Computer Science, Center for Bioinformatics (ZBIT), Tübingen University, Sand 14, 72076 Tübingen, Germany.|Department of Computer Science, Center for Bioinformatics (ZBIT), Tübingen University, Sand 14, 72076 Tübingen, Germany.|Department of Computer Science, Center for Bioinformatics (ZBIT), Tübingen University, Sand 14, 72076 Tübingen, Germany.', 'Germany|Germany|Germany|Germany', 32, 'Algorithms|Biological Evolution|Genetic Speciation|Hybridization, Genetic|Ploidies|Poaceae|Software|Triticum', 'Journal Article', '10.1093/bioinformatics/btr618', '22072387', 'Hybridization events in evolution may lead to incongruent gene trees. One approach to determining possible interspecific hybridization events is to compute a hybridization network that attempts to reconcile incongruent gene trees using a minimum number of hybridization events.'),
(76578, 2012, 'bio', 'Decompositions of large-scale biological systems based on dynamical properties', 'Soranzo, Nicola|Ramezani, Fahimeh|Iacono, Giovanni|Altafini, Claudio', 'CRS4 Bioinformatica, Loc. Piscina Manna, 09010 Pula (CA), Italy.|CRS4 Bioinformatica, Loc. Piscina Manna, 09010 Pula (CA), Italy.|CRS4 Bioinformatica, Loc. Piscina Manna, 09010 Pula (CA), Italy.|CRS4 Bioinformatica, Loc. Piscina Manna, 09010 Pula (CA), Italy.', 'Italy|Italy|Italy|Italy', 5, 'Artificial Intelligence|Computational Biology|Escherichia coli|Models, Biological|Saccharomyces cerevisiae|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btr620', '22072388', 'Given a large-scale biological network represented as an influence graph, in this article we investigate possible decompositions of the network aimed at highlighting specific dynamical properties.'),
(76579, 2012, 'bio', 'Multifunctional proteins revealed by overlapping clustering in protein interaction network', 'Becker, Emmanuelle|Robisson, Benoît|Chapple, Charles E|Guénoche, Alain|Brun, Christine', 'INSERM, U928, TAGC, France.|INSERM, U928, TAGC, France.|INSERM, U928, TAGC, France.|INSERM, U928, TAGC, France.|INSERM, U928, TAGC, France.', 'France|France|France|France|France', 98, 'Cluster Analysis|Computational Biology|Humans|Protein Interaction Maps|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btr621', '22080466', 'Multifunctional proteins perform several functions. They are expected to interact specifically with distinct sets of partners, simultaneously or not, depending on the function performed. Current graph clustering methods usually allow a protein to belong to only one cluster, therefore impeding a realistic assignment of multifunctional proteins to clusters.'),
(76580, 2012, 'bio', 'Expression2Kinases: mRNA profiling linked to multiple upstream regulatory layers', 'Chen, Edward Y|Xu, Huilei|Gordonov, Simon|Lim, Maribel P|Perkins, Matthew H|Maayan, Avi', 'Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York, New York, NY, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York, New York, NY, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York, New York, NY, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York, New York, NY, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York, New York, NY, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York, New York, NY, USA.', 'United States|United States|United States|United States|United States|United States', 78, 'Animals|Cell Differentiation|Chromatin Immunoprecipitation|Gene Expression Profiling|Genome-Wide Association Study|Humans|Oligonucleotide Array Sequence Analysis|Regulatory Sequences, Nucleic Acid|Signal Transduction|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr625', '22080467', 'Genome-wide mRNA profiling provides a snapshot of the global state of cells under different conditions. However, mRNA levels do not provide direct understanding of upstream regulatory mechanisms. Here, we present a new approach called Expression2Kinases (X2K) to identify upstream regulators likely responsible for observed patterns in genome-wide gene expression. By integrating chromatin immuno-precipitation (ChIP)-seq/chip and position weight matrices (PWMs) data, protein-protein interactions and kinase-substrate phosphorylation reactions, we can better identify regulatory mechanisms upstream of genome-wide differences in gene expression. We validated X2K by applying it to recover drug targets of food and drug administration (FDA)-approved drugs from drug perturbations followed by mRNA expression profiling, to map the regulatory landscape of 44 stem cells and their differentiating progeny, to profile upstream regulatory mechanisms of 327 breast cancer tumors, and to detect pathways from profiled hepatic stellate cells and hippocampal neurons. The X2K approach can advance our understanding of cell signaling and unravel drugs mechanisms of action.'),
(76581, 2012, 'bio', 'BadiRate: estimating family turnover rates by likelihood-based methods', 'Librado, P|Vieira, F G|Rozas, J', 'Departament de Genètica and Institut de Recerca de la Biodiversitat (IRBio), Universitat de Barcelona, Diagonal 645, 08028 Barcelona, Spain.|Departament de Genètica and Institut de Recerca de la Biodiversitat (IRBio), Universitat de Barcelona, Diagonal 645, 08028 Barcelona, Spain.|Departament de Genètica and Institut de Recerca de la Biodiversitat (IRBio), Universitat de Barcelona, Diagonal 645, 08028 Barcelona, Spain.', 'Spain|Spain|Spain', 60, 'Algorithms|Animals|Computer Simulation|Drosophila|Drosophila melanogaster|Evolution, Molecular|Genome|Likelihood Functions|MicroRNAs|Phylogeny|Regression Analysis|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr623', '22080468', 'The comparative analysis of gene gain and loss rates is critical for understanding the role of natural selection and adaptation in shaping gene family sizes. Studying complete genome data from closely related species allows accurate estimation of gene family turnover rates. Current methods and software tools, however, are not well designed for dealing with certain kinds of functional elements, such as microRNAs or transcription factor binding sites.'),
(76582, 2012, 'bio', 'rNA: a fast and accurate short reads numerical aligner', 'Vezzi, Francesco|Del Fabbro, Cristian|Tomescu, Alexandru I|Policriti, Alberto', 'Department of Mathematics and Computer Science, University of Udine, Udine, Italy.|Department of Mathematics and Computer Science, University of Udine, Udine, Italy.|Department of Mathematics and Computer Science, University of Udine, Udine, Italy.|Department of Mathematics and Computer Science, University of Udine, Udine, Italy.', 'Italy|Italy|Italy|Italy', 0, 'High-Throughput Nucleotide Sequencing|Humans|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr617', '22084252', 'The advent of high-throughput sequencers (HTS) introduced the need of new tools in order to analyse the large amount of data that those machines are able to produce. The mandatory first step for a wide range of analyses is the alignment of the sequences against a reference genome. We present a major update to our rNA (randomized Numerical Aligner) tool. The main feature of rNA is the fact that it achieves an accuracy greater than the majority of other tools in a feasible amount of time. rNA executables and source codes are freely downloadable at http://iga-rna.sourceforge.net/.'),
(76583, 2012, 'bio', 'Feature-based classifiers for somatic mutation detection in tumour-normal paired sequencing data', 'Ding, Jiarui|Bashashati, Ali|Roth, Andrew|Oloumi, Arusha|Tse, Kane|Zeng, Thomas|Haffari, Gholamreza|Hirst, Martin|Marra, Marco A|Condon, Anne|Aparicio, Samuel|Shah, Sohrab P', 'Department of Molecular Oncology, BC Cancer Agency, Vancouver, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, Vancouver, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, Vancouver, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, Vancouver, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, Vancouver, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, Vancouver, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, Vancouver, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, Vancouver, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, Vancouver, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, Vancouver, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, Vancouver, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, Vancouver, BC, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 87, 'Algorithms|Artificial Intelligence|Bayes Theorem|Breast Neoplasms|Cluster Analysis|Exome|Female|Genome|Humans|Models, Genetic|Mutation|Neoplasms|Polymorphism, Single Nucleotide|Software|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btr629', '22084253', 'The study of cancer genomes now routinely involves using next-generation sequencing technology (NGS) to profile tumours for single nucleotide variant (SNV) somatic mutations. However, surprisingly few published bioinformatics methods exist for the specific purpose of identifying somatic mutations from NGS data and existing tools are often inaccurate, yielding intolerably high false prediction rates. As such, the computational problem of accurately inferring somatic mutations from paired tumour/normal NGS data remains an unsolved challenge.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76584, 2012, 'bio', 'Gene set analysis in the cloud', 'Zhang, Lu|Gu, Shengchang|Liu, Yuan|Wang, Bingqiang|Azuaje, Francisco', 'Laboratory of Cardiovascular research, CRP-Santé, Luxembourg L-1150, Luxembourg.|Laboratory of Cardiovascular research, CRP-Santé, Luxembourg L-1150, Luxembourg.|Laboratory of Cardiovascular research, CRP-Santé, Luxembourg L-1150, Luxembourg.|Laboratory of Cardiovascular research, CRP-Santé, Luxembourg L-1150, Luxembourg.|Laboratory of Cardiovascular research, CRP-Santé, Luxembourg L-1150, Luxembourg.', 'Luxembourg|Luxembourg|Luxembourg|Luxembourg|Luxembourg', 28, 'Algorithms|Computational Biology|Information Storage and Retrieval|Internet|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/btr630', '22084254', 'Cloud computing offers low cost and highly flexible opportunities in bioinformatics. Its potential has already been demonstrated in high-throughput sequence data analysis. Pathway-based or gene set analysis of expression data has received relatively less attention. We developed a gene set analysis algorithm for biomarker identification in the cloud. The resulting tool, YunBe, is ready to use on Amazon Web Services. Moreover, here we compare its performance to those obtained with desktop and computing cluster solutions.'),
(76585, 2012, 'bio', 'PubChem promiscuity: a web resource for gathering compound promiscuity data from PubChem', 'Canny, Stephanie A|Cruz, Yasel|Southern, Mark R|Griffin, Patrick R', 'Translational Research Institute and Molecular Therapeutics, The Scripps Research Institute, Scripps Florida, 130 Scripps Way, Jupiter, FL 33458, USA.|Translational Research Institute and Molecular Therapeutics, The Scripps Research Institute, Scripps Florida, 130 Scripps Way, Jupiter, FL 33458, USA.|Translational Research Institute and Molecular Therapeutics, The Scripps Research Institute, Scripps Florida, 130 Scripps Way, Jupiter, FL 33458, USA.|Translational Research Institute and Molecular Therapeutics, The Scripps Research Institute, Scripps Florida, 130 Scripps Way, Jupiter, FL 33458, USA.', 'United States|United States|United States|United States', 0, 'Data Collection|Databases, Factual|Internet|Pharmaceutical Preparations|Protein Binding|Search Engine', 'Journal Article', '10.1093/bioinformatics/btr622', '22084255', 'Promiscuity counts allow for a better understanding of a compounds assay activity profile and drug potential. Although PubChem contains a vast amount of compound and assay data, it currently does not have a convenient or efficient method to obtain in-depth promiscuity counts for compounds. PubChem promiscuity fills this gap. It is a Java servlet that uses NCBI Entrez (eUtils) web services to interact with PubChem and provide promiscuity counts in a variety of categories along with compound descriptors, including PAINS-based functional group detection.'),
(76586, 2012, 'bio', 'Discovering transcription factor regulatory targets using gene expression and binding data', 'Maienschein-Cline, Mark|Zhou, Jie|White, Kevin P|Sciammas, Roger|Dinner, Aaron R', 'Department of Chemistry, The University of Chicago, Chicago, IL 60637, USA.|Department of Chemistry, The University of Chicago, Chicago, IL 60637, USA.|Department of Chemistry, The University of Chicago, Chicago, IL 60637, USA.|Department of Chemistry, The University of Chicago, Chicago, IL 60637, USA.|Department of Chemistry, The University of Chicago, Chicago, IL 60637, USA.', 'United States|United States|United States|United States|United States', 27, 'Algorithms|Artificial Intelligence|Estrogen Receptor alpha|Gene Expression Profiling|Gene Expression Regulation|Humans|Oligonucleotide Array Sequence Analysis|Promoter Regions, Genetic|Protein Binding|Receptors, Retinoic Acid|Regulatory Sequences, Nucleic Acid|Retinoic Acid Receptor alpha|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr628', '22084256', 'Identifying the target genes regulated by transcription factors (TFs) is the most basic step in understanding gene regulation. Recent advances in high-throughput sequencing technology, together with chromatin immunoprecipitation (ChIP), enable mapping TF binding sites genome wide, but it is not possible to infer function from binding alone. This is especially true in mammalian systems, where regulation often occurs through long-range enhancers in gene-rich neighborhoods, rather than proximal promoters, preventing straightforward assignment of a binding site to a target gene.'),
(76587, 2012, 'bio', 'NoRSE: noise reduction and state evaluator for high-frequency single event traces', 'Reuel, Nigel F|Bojo, Peter|Zhang, Jingqing|Boghossian, Ardemis A|Ahn, Jin-Ho|Kim, Jong-Ho|Strano, Michael S', 'Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.|Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.|Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.|Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.|Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.|Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.|Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.', 'United States|United States|United States|United States|United States|United States|United States', 7, 'Algorithms|Biosensing Techniques|Nanotechnology|Nanotubes, Carbon', 'Journal Article', '10.1093/bioinformatics/btr632', '22088841', 'NoRSE was developed to analyze high-frequency datasets collected from multistate, dynamic experiments, such as molecular adsorption and desorption onto carbon nanotubes. As technology improves sampling frequency, these stochastic datasets become increasingly large with faster dynamic events. More efficient algorithms are needed to accurately locate the unique states in each time trace. NoRSE adapts and optimizes a previously published noise reduction algorithm and uses a custom peak flagging routine to rapidly identify unique event states. The algorithm is explained using experimental data from our lab and its fitting accuracy and efficiency are then shown with a generalized model of stochastic datasets. The algorithm is compared to another recently published state finding algorithm and is found to be 27 times faster and more accurate over 55% of the generalized experimental space. NoRSE is written as an M-file for Matlab.'),
(76588, 2012, 'bio', 'Dragon PolyA Spotter: predictor of poly(A) motifs within human genomic DNA sequences', 'Kalkatawi, Manal|Rangkuti, Farania|Schramm, Michael|Jankovic, Boris R|Kamau, Allan|Chowdhary, Rajesh|Archer, John A C|Bajic, Vladimir B', 'Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia.|Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia.|Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia.|Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia.|Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia.|Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia.|Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia.|Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia.', 'Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Ara', 0, 'Algorithms|Genome, Human|Humans|Internet|Neural Networks (Computer)|Poly A|Sensitivity and Specificity|Software', 'Journal Article', '10.1093/bioinformatics/btr602', '22088842', 'Recognition of poly(A) signals in mRNA is relatively straightforward due to the presence of easily recognizable polyadenylic acid tail. However, the task of identifying poly(A) motifs in the primary genomic DNA sequence that correspond to poly(A) signals in mRNA is a far more challenging problem. Recognition of poly(A) signals is important for better gene annotation and understanding of the gene regulation mechanisms. In this work, we present one such poly(A) motif prediction method based on properties of human genomic DNA sequence surrounding a poly(A) motif. These properties include thermodynamic, physico-chemical and statistical characteristics. For predictions, we developed Artificial Neural Network and Random Forest models. These models are trained to recognize 12 most common poly(A) motifs in human DNA. Our predictors are available as a free web-based tool accessible at http://cbrc.kaust.edu.sa/dps. Compared with other reported predictors, our models achieve higher sensitivity and specificity and furthermore provide a consistent level of accuracy for 12 poly(A) motif variants.'),
(76589, 2012, 'bio', 'Inferring gene regulatory networks from gene expression data by path consistency algorithm based on conditional mutual information', 'Zhang, Xiujun|Zhao, Xing-Ming|He, Kun|Lu, Le|Cao, Yongwei|Liu, Jingdong|Hao, Jin-Kao|Liu, Zhi-Ping|Chen, Luonan', 'Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.', 'China|China|China|China|China|China|China|China|China', 168, 'Algorithms|Escherichia coli|Gene Expression Profiling|Gene Regulatory Networks|Principal Component Analysis|SOS Response (Genetics)', 'Journal Article', '10.1093/bioinformatics/btr626', '22088843', 'Reconstruction of gene regulatory networks (GRNs), which explicitly represent the causality of developmental or regulatory process, is of utmost interest and has become a challenging computational problem for understanding the complex regulatory mechanisms in cellular systems. However, all existing methods of inferring GRNs from gene expression profiles have their strengths and weaknesses. In particular, many properties of GRNs, such as topology sparseness and non-linear dependence, are generally in regulation mechanism but seldom are taken into account simultaneously in one computational method.'),
(76590, 2012, 'bio', 'Time-course network analysis reveals TNF-xcexb1 can promote G1/S transition of cell cycle in vascular endothelial cells', 'Chen, Yang|Gu, Jin|Li, Dan|Li, Shao', 'MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST, Department of Automation, Tsinghua University, Beijing 100084, China.|MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST, Department of Automation, Tsinghua University, Beijing 100084, China.|MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST, Department of Automation, Tsinghua University, Beijing 100084, China.|MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST, Department of Automation, Tsinghua University, Beijing 100084, China.', 'China|China|China|China', 13, 'Cell Cycle|Cell Cycle Proteins|Cell Division|Cells, Cultured|Cyclin D1|Cyclin-Dependent Kinase Inhibitor p21|Cyclin-Dependent Kinase Inhibitor p27|Endothelial Cells|Human Umbilical Vein Endothelial Cells|Humans|Protein Binding|Protein Interaction Maps|Tumor Necrosis Factor-alpha|Vascular Endothelial Growth Factor A', 'Journal Article', '10.1093/bioinformatics/btr619', '22088844', 'Tumor necrosis factor-alpha (TNF-xcexb1), a major inflammatory cytokine, is closely related to several cardiovascular pathological processes. However, its effects on the cell cycle of vascular endothelial cells (VECs) have been the subject of some controversy. To investigate the molecular mechanism underlying this process, we constructed time-course protein-protein interaction (PPI) networks of TNF-xcexb1 induced regulation of cell cycle in VECs using microarray datasets and genome-wide PPI datasets. Then, we analyzed the topological properties of the responsive PPI networks and calculated the node degree and node betweenness centralization of each gene in the networks. We found that p21, p27 and cyclinD1, key genes of the G1/S checkpoint, are in the center of responsive PPI networks and their roles in PPI networks are significantly altered with induction of TNF-xcexb1. According to the following biological experiments, we proved that TNF-xcexb1 can promote G(1)/S transition of cell cycle in VECs and facilitate the cell cycle activation induced by vascular endothelial growth factor.'),
(76591, 2012, 'bio', 'TREAT: a bioinformatics tool for variant annotations and visualizations in targeted and exome sequencing data', 'Asmann, Yan W|Middha, Sumit|Hossain, Asif|Baheti, Saurabh|Li, Ying|Chai, High-Seng|Sun, Zhifu|Duffy, Patrick H|Hadad, Ahmed A|Nair, Asha|Liu, Xiaoyu|Zhang, Yuji|Klee, Eric W|Kalari, Krishna R|Kocher, Jean-Pierre A', 'Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo College of Medicine, Rochester, MN, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo College of Medicine, Rochester, MN, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo College of Medicine, Rochester, MN, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo College of Medicine, Rochester, MN, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo College of Medicine, Rochester, MN, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo College of Medicine, Rochester, MN, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo College of Medicine, Rochester, MN, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo College of Medicine, Rochester, MN, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo College of Medicine, Rochester, MN, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo College of Medicine, Rochester, MN, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo College of Medicine, Rochester, MN, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo College of Medicine, Rochester, MN, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo College of Medicine, Rochester, MN, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo College of Medicine, Rochester, MN, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo College of Medicine, Rochester, MN, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Computational Biology|Exome|Humans|Molecular Sequence Annotation|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btr612', '22088845', 'TREAT (Targeted RE-sequencing Annotation Tool) is a tool for facile navigation and mining of the variants from both targeted resequencing and whole exome sequencing. It provides a rich integration of publicly available as well as in-house developed annotations and visualizations for variants, variant-hosting genes and host-gene pathways.'),
(76592, 2012, 'bio', 'QuRe: software for viral quasispecies reconstruction from next-generation sequencing data', 'Prosperi, Mattia C F|Salemi, Marco', 'Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610-3633, USA.|Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610-3633, USA.', 'United States|United States', 81, 'Algorithms|Cluster Analysis|Genome, Viral|High-Throughput Nucleotide Sequencing|Humans|Sequence Alignment|Software|Viruses', 'Journal Article', '10.1093/bioinformatics/btr627', '22088846', 'Next-generation sequencing (NGS) is an ideal framework for the characterization of highly variable pathogens, with a deep resolution able to capture minority variants. However, the reconstruction of all variants of a viral population infecting a host is a challenging task for genome regions larger than the average NGS read length. QuRe is a program for viral quasispecies reconstruction, specifically developed to analyze long read (>100 bp) NGS data. The software performs alignments of sequence fragments against a reference genome, finds an optimal division of the genome into sliding windows based on coverage and diversity and attempts to reconstruct all the individual sequences of the viral quasispecies--along with their prevalence--using a heuristic algorithm, which matches multinomial distributions of distinct viral variants overlapping across the genome division. QuRe comes with a built-in Poisson error correction method and a post-reconstruction probabilistic clustering, both parameterized on given error rates in homopolymeric and non-homopolymeric regions.'),
(76593, 2012, 'bio', 'Protein subcellular localization of fluorescence imagery using spatial and transform domain features', 'Tahir, Muhammad|Khan, Asifullah|Majid, Abdul', 'Department of Computer and Information Sciences, PIEAS, Islamabad, Pakistan.|Department of Computer and Information Sciences, PIEAS, Islamabad, Pakistan.|Department of Computer and Information Sciences, PIEAS, Islamabad, Pakistan.', 'Pakistan|Pakistan|Pakistan', 25, 'HeLa Cells|Humans|Microscopy, Fluorescence|Proteins|Software|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btr624', '22088847', 'Subcellular localization of proteins is one of the most significant characteristics of living cells. Prediction of protein subcellular locations is crucial to the understanding of various protein functions. Therefore, an accurate, computationally efficient and reliable prediction system is required.'),
(76594, 2011, 'bio', 'The rise and fall of supervised machine learning techniques', 'Jensen, Lars Juhl|Bateman, Alex', 'Department of Computer and Information Sciences, PIEAS, Islamabad, Pakistan.|Department of Computer and Information Sciences, PIEAS, Islamabad, Pakistan.', 'Pakistan|Pakistan', 23, 'Algorithms|Artificial Intelligence|Computational Biology|Humans|Neural Networks (Computer)|Support Vector Machine', 'Editorial', '10.1093/bioinformatics/btr585', '22101152', '-'),
(76595, 2012, 'bio', 'PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments', 'Jones, David T|Buchan, Daniel W A|Cozzetto, Domenico|Pontil, Massimiliano', 'Department of Computer Science, Bioinformatics Group, Centre for Computational Statistics and Machine Learning, University College London, Malet Place, London WC1E 6BT, UK. d.jones@cs.ucl.ac.uk|Department of Computer Science, Bioinformatics Group, Centre for Computational Statistics and Machine Learning, University College London, Malet Place, London WC1E 6BT, UK. d.jones@cs.ucl.ac.uk|Department of Computer Science, Bioinformatics Group, Centre for Computational Statistics and Machine Learning, University College London, Malet Place, London WC1E 6BT, UK. d.jones@cs.ucl.ac.uk|Department of Computer Science, Bioinformatics Group, Centre for Computational Statistics and Machine Learning, University College London, Malet Place, London WC1E 6BT, UK. d.jones@cs.ucl.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 412, 'Algorithms|Bayes Theorem|Mutation|Phylogeny|Proteins|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btr638', '22101153', 'The accurate prediction of residue-residue contacts, critical for maintaining the native fold of a protein, remains an open problem in the field of structural bioinformatics. Interest in this long-standing problem has increased recently with algorithmic improvements and the rapid growth in the sizes of sequence families. Progress could have major impacts in both structure and function prediction to name but two benefits. Sequence-based contact predictions are usually made by identifying correlated mutations within multiple sequence alignments (MSAs), most commonly through the information-theoretic approach of calculating mutual information between pairs of sites in proteins. These predictions are often inaccurate because the true covariation signal in the MSA is often masked by biases from many ancillary indirect-coupling or phylogenetic effects. Here we present a novel method, PSICOV, which introduces the use of sparse inverse covariance estimation to the problem of protein contact prediction. Our method builds on work which had previously demonstrated corrections for phylogenetic and entropic correlation noise and allows accurate discrimination of direct from indirectly coupled mutation correlations in the MSA.'),
(76596, 2012, 'bio', 'Identification of context-specific gene regulatory networks with GEMULA--gene expression modeling using LAsso', 'Geeven, Geert|van Kesteren, Ronald E|Smit, August B|de Gunst, Mathisca C M', 'Department of Mathematics, Faculty of Sciences, Neuroscience Campus Amsterdam, VU University, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands. g.geeven@hubrecht.eu|Department of Mathematics, Faculty of Sciences, Neuroscience Campus Amsterdam, VU University, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands. g.geeven@hubrecht.eu|Department of Mathematics, Faculty of Sciences, Neuroscience Campus Amsterdam, VU University, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands. g.geeven@hubrecht.eu|Department of Mathematics, Faculty of Sciences, Neuroscience Campus Amsterdam, VU University, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands. g.geeven@hubrecht.eu', 'Netherlands|Netherlands|Netherlands|Netherlands', 28, 'Animals|Gene Expression Regulation|Gene Regulatory Networks|Humans|Linear Models|Models, Genetic|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr641', '22106333', 'Gene regulatory networks, in which edges between nodes describe interactions between transcriptional regulators and their target genes, determine the coordinated spatiotemporal expression of genes. Especially in higher organisms, context-specific combinatorial regulation by transcription factors (TFs) is believed to determine cellular states and fates. TF-target gene interactions can be studied using high-throughput techniques such as ChIP-chip or ChIP-Seq. These experiments are time and cost intensive, and further limited by, for instance, availability of high affinity TF antibodies. Hence, there is a practical need for methods that can predict TF-TF and TF-target gene interactions in silico, i.e. from gene expression and DNA sequence data alone. We propose GEMULA, a novel approach based on linear models to predict TF-gene expression associations and TF-TF interactions from experimental data. GEMULA is based on linear models, fast and considers a wide range of biologically plausible models that describe gene expression data as a function of predicted TF binding to gene promoters.'),
(76597, 2012, 'bio', 'Addendum: 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, Faculty of Sciences, Neuroscience Campus Amsterdam, VU University, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands. g.geeven@hubrecht.eu|Department of Mathematics, Faculty of Sciences, Neuroscience Campus Amsterdam, VU University, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands. g.geeven@hubrecht.eu|Department of Mathematics, Faculty of Sciences, Neuroscience Campus Amsterdam, VU University, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands. g.geeven@hubrecht.eu|Department of Mathematics, Faculty of Sciences, Neuroscience Campus Amsterdam, VU University, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands. g.geeven@hubrecht.eu|Department of Mathematics, Faculty of Sciences, Neuroscience Campus Amsterdam, VU University, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands. g.geeven@hubrecht.eu|Department of Mathematics, Faculty of Sciences, Neuroscience Campus Amsterdam, VU University, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands. g.geeven@hubrecht.eu', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 1, 'Algorithms|Nucleic Acid Conformation|RNA|RNA Folding|Sequence Analysis, RNA|Software', 'Letter', '10.1093/bioinformatics/btr643', '22106334', '-'),
(76598, 2012, 'bio', 'Data-driven information retrieval in heterogeneous collections of transcriptomics data links SIM2s to malignant pleural mesothelioma', 'Caldas, José|Gehlenborg, Nils|Kettunen, Eeva|Faisal, Ali|Rönty, Mikko|Nicholson, Andrew G|Knuutila, Sakari|Brazma, Alvis|Kaski, Samuel', 'Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Helsinki, Finland.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Helsinki, Finland.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Helsinki, Finland.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Helsinki, Finland.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Helsinki, Finland.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Helsinki, Finland.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Helsinki, Finland.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Helsinki, Finland.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Helsinki, Finland.', 'Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland', 11, 'Animals|Gene Expression Profiling|Humans|Information Storage and Retrieval|Mesothelioma|Mice|Pleural Neoplasms|Programming Languages|Rats', 'Journal Article', '10.1093/bioinformatics/btr634', '22106335', 'Genome-wide measurement of transcript levels is an ubiquitous tool in biomedical research. As experimental data continues to be deposited in public databases, it is becoming important to develop search engines that enable the retrieval of relevant studies given a query study. While retrieval systems based on meta-data already exist, data-driven approaches that retrieve studies based on similarities in the expression data itself have a greater potential of uncovering novel biological insights.'),
(76599, 2012, 'bio', 'Integrating human and murine anatomical gene expression data for improved comparisons', 'Jiménez-Lozano, Natalia|Segura, Joan|Macías, José Ramón|Vega, Juanjo|Carazo, José María', 'GN7 of the National Institute for Bioinformatics, Darwin, 3, 28049 Madrid, Spain. natalia@cnb.csic.es|GN7 of the National Institute for Bioinformatics, Darwin, 3, 28049 Madrid, Spain. natalia@cnb.csic.es|GN7 of the National Institute for Bioinformatics, Darwin, 3, 28049 Madrid, Spain. natalia@cnb.csic.es|GN7 of the National Institute for Bioinformatics, Darwin, 3, 28049 Madrid, Spain. natalia@cnb.csic.es|GN7 of the National Institute for Bioinformatics, Darwin, 3, 28049 Madrid, Spain. natalia@cnb.csic.es', 'Spain|Spain|Spain|Spain|Spain', 1, 'Algorithms|Animals|Brain|Gene Expression Profiling|Gene Expression Regulation, Developmental|Humans|Huntington Disease|Mice|Organ Specificity', 'Journal Article', '10.1093/bioinformatics/btr639', '22106336', 'Information concerning the gene expression pattern in four dimensions (species, genes, anatomy and developmental stage) is crucial for unraveling the roles of genes through time. There are a variety of anatomical gene expression databases, but extracting information from them can be hampered by their diversity and heterogeneity.'),
(76600, 2012, 'bio', 'MetalionRNA: computational predictor of metal-binding sites in RNA structures', 'Philips, Anna|Milanowska, Kaja|Lach, Grzegorz|Boniecki, Michal|Rother, Kristian|Bujnicki, Janusz M', 'Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, ul. Ks. Trojdena 4, 02-109 Warsaw, Poland.|Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, ul. Ks. Trojdena 4, 02-109 Warsaw, Poland.|Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, ul. Ks. Trojdena 4, 02-109 Warsaw, Poland.|Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, ul. Ks. Trojdena 4, 02-109 Warsaw, Poland.|Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, ul. Ks. Trojdena 4, 02-109 Warsaw, Poland.|Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, ul. Ks. Trojdena 4, 02-109 Warsaw, Poland.', 'Poland|Poland|Poland|Poland|Poland|Poland', 22, 'Binding Sites|Ions|Metals|Models, Molecular|Nucleic Acid Conformation|RNA|RNA, Catalytic|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btr636', '22110243', 'Metal ions are essential for the folding of RNA molecules into stable tertiary structures and are often involved in the catalytic activity of ribozymes. However, the positions of metal ions in RNA 3D structures are difficult to determine experimentally. This motivated us to develop a computational predictor of metal ion sites for RNA structures.'),
(76601, 2012, 'bio', 'FSR: feature set reduction for scalable and accurate multi-class cancer subtype classification based on copy number', 'Wong, Gerard|Leckie, Christopher|Kowalczyk, Adam', 'National ICT Australia, Victoria Research Laboratory, Parkville, Australia. gwong@csse.unimelb.edu.au|National ICT Australia, Victoria Research Laboratory, Parkville, Australia. gwong@csse.unimelb.edu.au|National ICT Australia, Victoria Research Laboratory, Parkville, Australia. gwong@csse.unimelb.edu.au', 'Australia|Australia|Australia', 12, 'Algorithms|Artificial Intelligence|DNA Copy Number Variations|Humans|Neoplasms', 'Journal Article', '10.1093/bioinformatics/btr644', '22110244', 'Feature selection is a key concept in machine learning for microarray datasets, where features represented by probesets are typically several orders of magnitude larger than the available sample size. Computational tractability is a key challenge for feature selection algorithms in handling very high-dimensional datasets beyond a hundred thousand features, such as in datasets produced on single nucleotide polymorphism microarrays. In this article, we present a novel feature set reduction approach that enables scalable feature selection on datasets with hundreds of thousands of features and beyond. Our approach enables more efficient handling of higher resolution datasets to achieve better disease subtype classification of samples for potentially more accurate diagnosis and prognosis, which allows clinicians to make more informed decisions in regards to patient treatment options.'),
(76602, 2012, 'bio', 'PGDSpider: an automated data conversion tool for connecting population genetics and genomics programs', 'Lischer, H E L|Excoffier, L', 'Computational and Molecular Population Genetics (CMPG) laboratory, Institute of Ecology and Evolution, University of Berne, Baltzerstrasse 6, 3012 Berne, Switzerland. heidi.lischer@iee.unibe.ch|Computational and Molecular Population Genetics (CMPG) laboratory, Institute of Ecology and Evolution, University of Berne, Baltzerstrasse 6, 3012 Berne, Switzerland. heidi.lischer@iee.unibe.ch', 'Switzerland|Switzerland', 433, 'Genetics, Population|Genomics|Information Storage and Retrieval|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr642', '22110245', 'The analysis of genetic data often requires a combination of several approaches using different and sometimes incompatible programs. In order to facilitate data exchange and file conversions between population genetics programs, we introduce PGDSpider, a Java program that can read 27 different file formats and export data into 29, partially overlapping, other file formats. The PGDSpider package includes both an intuitive graphical user interface and a command-line version allowing its integration in complex data analysis pipelines.'),
(76603, 2012, 'bio', 'GenomicTools: a computational platform for developing high-throughput analytics in genomics', 'Tsirigos, Aristotelis|Haiminen, Niina|Bilal, Erhan|Utro, Filippo', 'Computational Biology Center, IBM T.J. Watson Research Center, Yorktown Heights, NY 10598, USA. atsirigo@us.ibm.com|Computational Biology Center, IBM T.J. Watson Research Center, Yorktown Heights, NY 10598, USA. atsirigo@us.ibm.com|Computational Biology Center, IBM T.J. Watson Research Center, Yorktown Heights, NY 10598, USA. atsirigo@us.ibm.com|Computational Biology Center, IBM T.J. Watson Research Center, Yorktown Heights, NY 10598, USA. atsirigo@us.ibm.com', 'United States|United States|United States|United States', 27, 'Computational Biology|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|Software', 'Journal Article', '10.1093/bioinformatics/btr646', '22113082', 'Recent advances in sequencing technology have resulted in the dramatic increase of sequencing data, which, in turn, requires efficient management of computational resources, such as computing time, memory requirements as well as prototyping of computational pipelines.'),
(76604, 2012, 'bio', 'A novel and versatile computational tool to model translation', 'Chu, Dominique|Zabet, Nicolae|von der Haar, Tobias', 'School of Computing, University of Kent, Kent CT2 7NF, UK. d.f.chu@kent.ac.uk|School of Computing, University of Kent, Kent CT2 7NF, UK. d.f.chu@kent.ac.uk|School of Computing, University of Kent, Kent CT2 7NF, UK. d.f.chu@kent.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 17, 'Codon|Open Reading Frames|Protein Biosynthesis|RNA, Messenger|RNA, Transfer|Ribosomes|Software', 'Journal Article', '10.1093/bioinformatics/btr650', '22113083', 'Much is now known about the mechanistic details of gene translation. There are also rapid advances in high-throughput technologies to determine quantitative aspects of the system. As a consequence-realistic and system-wide simulation models of translation are now feasible. Such models are also needed as devices to integrate a large volume of highly fragmented data known about translation. Software: In this application note, we present a novel, highly efficient software tool to model translation. The tool represents the main aspects of translation. Features include a representation of exhaustible tRNA pools, ribosome-ribosome interactions and differential initiation rates for different mRNA species. The tool is written in Java, and is hence portable and can be parameterized for any organism.'),
(76605, 2012, 'bio', 'FTSite: high accuracy detection of ligand binding sites on unbound protein structures', 'Ngan, Chi-Ho|Hall, David R|Zerbe, Brandon|Grove, Laurie E|Kozakov, Dima|Vajda, Sandor', 'Department of Biomedical Engineering, Boston University, Boston, MA 02115, USA.|Department of Biomedical Engineering, Boston University, Boston, MA 02115, USA.|Department of Biomedical Engineering, Boston University, Boston, MA 02115, USA.|Department of Biomedical Engineering, Boston University, Boston, MA 02115, USA.|Department of Biomedical Engineering, Boston University, Boston, MA 02115, USA.|Department of Biomedical Engineering, Boston University, Boston, MA 02115, USA.', 'United States|United States|United States|United States|United States|United States', 102, 'Algorithms|Binding Sites|Crystallography, X-Ray|Drug Design|HIV|HIV Protease|Ligands|Nuclear Magnetic Resonance, Biomolecular|Proteins|Soybeans|beta-Amylase', 'Journal Article', '10.1093/bioinformatics/btr651', '22113084', 'Binding site identification is a classical problem that is important for a range of applications, including the structure-based prediction of function, the elucidation of functional relationships among proteins, protein engineering and drug design. We describe an accurate method of binding site identification, namely FTSite. This method is based on experimental evidence that ligand binding sites also bind small organic molecules of various shapes and polarity. The FTSite algorithm does not rely on any evolutionary or statistical information, but achieves near experimental accuracy: it is capable of identifying the binding sites in over 94% of apo proteins from established test sets that have been used to evaluate many other binding site prediction methods.'),
(76606, 2012, 'bio', 'MSnbase-an R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation', 'Gatto, Laurent|Lilley, Kathryn S', 'Cambridge Centre for Proteomics, Cambridge Systems Biology Centre, Department of Biochemistry, University of Cambridge, Tennis Court Road, CB2 1QR, Cambridge, UK. lg390@cam.ac.uk|Cambridge Centre for Proteomics, Cambridge Systems Biology Centre, Department of Biochemistry, University of Cambridge, Tennis Court Road, CB2 1QR, Cambridge, UK. lg390@cam.ac.uk', 'United Kingdom|United Kingdom', 89, 'Mass Spectrometry|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/btr645', '22113085', 'MSnbase is an R/Bioconductor package for the analysis of quantitative proteomics experiments that use isobaric tagging. It provides an exploratory data analysis framework for reproducible research, allowing raw data import, quality control, visualization, data processing and quantitation. MSnbase allows direct integration of quantitative proteomics data with additional facilities for statistical analysis provided by the Bioconductor project.'),
(76607, 2012, 'bio', 'Using Sybil for interactive comparative genomics of microbes on the web', 'Riley, David R|Angiuoli, Samuel V|Crabtree, Jonathan|Dunning Hotopp, Julie C|Tettelin, Hervé', 'Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA. driley@som.umaryland.edu|Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA. driley@som.umaryland.edu|Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA. driley@som.umaryland.edu|Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA. driley@som.umaryland.edu|Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA. driley@som.umaryland.edu', 'United States|United States|United States|United States|United States', 38, 'Databases, Factual|Genome|Genomics|Humans|Internet|Pneumococcal Infections|Software|Streptococcus pneumoniae', 'Journal Article', '10.1093/bioinformatics/btr652', '22121156', 'Analysis of multiple genomes requires sophisticated tools that provide search, visualization, interactivity and data export. Comparative genomics datasets tend to be large and complex, making development of these tools difficult. In addition to scalability, comparative genomics tools must also provide user-friendly interfaces such that the research scientist can explore complex data with minimal technical expertise.'),
(76608, 2012, 'bio', 'CellAnimation: an open source MATLAB framework for microscopy assays', 'Georgescu, Walter|Wikswo, John P|Quaranta, Vito', 'Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, TN, USA.|Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, TN, USA.|Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, TN, USA.', 'United States|United States|United States', 13, 'Algorithms|Cytological Techniques|Image Processing, Computer-Assisted|Internet|Microscopy|Software', 'Journal Article', '10.1093/bioinformatics/btr633', '22121157', 'Advances in microscopy technology have led to the creation of high-throughput microscopes that are capable of generating several hundred gigabytes of images in a few days. Analyzing such wealth of data manually is nearly impossible and requires an automated approach. There are at present a number of open-source and commercial software packages that allow the user to apply algorithms of different degrees of sophistication to the images and extract desired metrics. However, the types of metrics that can be extracted are severely limited by the specific image processing algorithms that the application implements, and by the expertise of the user. In most commercial software, code unavailability prevents implementation by the end user of newly developed algorithms better suited for a particular type of imaging assay. While it is possible to implement new algorithms in open-source software, rewiring an image processing application requires a high degree of expertise. To obviate these limitations, we have developed an open-source high-throughput application that allows implementation of different biological assays such as cell tracking or ancestry recording, through the use of small, relatively simple image processing modules connected into sophisticated imaging pipelines. By connecting modules, non-expert users can apply the particular combination of well-established and novel algorithms developed by us and others that are best suited for each individual assay type. In addition, our data exploration and visualization modules make it easy to discover or select specific cell phenotypes from a heterogeneous population.'),
(76609, 2012, 'bio', 'Inferring sequence regions under functional divergence in duplicate genes', 'Huang, Yi-Fei|Golding, G Brian', 'Department of Biology, McMaster University, Hamilton, ON, Canada.|Department of Biology, McMaster University, Hamilton, ON, Canada.', 'Canada|Canada', 9, 'Animals|Evolution, Molecular|Genes, Duplicate|Markov Chains|Phylogeny|Protein Structure, Tertiary', 'Journal Article', '10.1093/bioinformatics/btr635', '22121158', 'A number of statistical phylogenetic methods have been proposed to identify type-I functional divergence in duplicate genes by detecting heterogeneous substitution rates in phylogenetic trees. A common disadvantage of the existing methods is that autocorrelation of substitution rates along sequences is not modeled. This reduces the power of existing methods to identify regions under functional divergence.'),
(76610, 2012, 'bio', 'Modelling time course gene expression data with finite mixtures of linear additive models', 'Grün, Bettina|Scharl, Theresa|Leisch, Friedrich', 'Department of Applied Statistics, Johannes Kepler University Linz, Altenbergerstrasse 69, 4040 Linz, Austria. Bettina.Gruen@jku.at|Department of Applied Statistics, Johannes Kepler University Linz, Altenbergerstrasse 69, 4040 Linz, Austria. Bettina.Gruen@jku.at|Department of Applied Statistics, Johannes Kepler University Linz, Altenbergerstrasse 69, 4040 Linz, Austria. Bettina.Gruen@jku.at', 'Austria|Austria|Austria', 4, 'Algorithms|Cell Cycle|Gene Expression Profiling|Humans|Likelihood Functions|Linear Models|Models, Genetic|Regression Analysis|Saccharomyces cerevisiae|Time Factors', 'Journal Article', '10.1093/bioinformatics/btr653', '22121159', 'A model class of finite mixtures of linear additive models is presented. The component-specific parameters in the regression models are estimated using regularized likelihood methods. The advantages of the regularization are that (i) the pre-specified maximum degrees of freedom for the splines is less crucial than for unregularized estimation and that (ii) for each component individually a suitable degree of freedom is selected in an automatic way. The performance is evaluated in a simulation study with artificial data as well as on a yeast cell cycle dataset of gene expression levels over time.'),
(76611, 2012, 'bio', 'A novel specific edge effect correction method for RNA interference screenings', 'Carralot, Jean-Philippe|Ogier, Arnaud|Boese, Annette|Genovesio, Auguste|Brodin, Priscille|Sommer, Peter|Dorval, Thierry', 'Biology of Intracellular Pathogens, Inserm Avenir Team, Institut Pasteur Korea, Seongnam-si, Korea. jean-philippe.carralot@roche.com|Biology of Intracellular Pathogens, Inserm Avenir Team, Institut Pasteur Korea, Seongnam-si, Korea. jean-philippe.carralot@roche.com|Biology of Intracellular Pathogens, Inserm Avenir Team, Institut Pasteur Korea, Seongnam-si, Korea. jean-philippe.carralot@roche.com|Biology of Intracellular Pathogens, Inserm Avenir Team, Institut Pasteur Korea, Seongnam-si, Korea. jean-philippe.carralot@roche.com|Biology of Intracellular Pathogens, Inserm Avenir Team, Institut Pasteur Korea, Seongnam-si, Korea. jean-philippe.carralot@roche.com|Biology of Intracellular Pathogens, Inserm Avenir Team, Institut Pasteur Korea, Seongnam-si, Korea. jean-philippe.carralot@roche.com|Biology of Intracellular Pathogens, Inserm Avenir Team, Institut Pasteur Korea, Seongnam-si, Korea. jean-philippe.carralot@roche.com', '-|-|-|-|-|-|-', 17, 'Algorithms|Artifacts|Drug Discovery|Genome-Wide Association Study|HIV|Humans|RNA Interference|RNA, Small Interfering', 'Journal Article', '10.1093/bioinformatics/btr648', '22121160', 'High-throughput screening (HTS) is an important method in drug discovery in which the activities of a large number of candidate chemicals or genetic materials are rapidly evaluated. Data are usually obtained by measurements on samples in microwell plates and are often subjected to artefacts that can bias the result selection. We report here a novel edge effect correction algorithm suitable for RNA interference (RNAi) screening, because its normalization does not rely on the entire dataset and takes into account the specificities of such a screening process. The proposed method is able to estimate the edge effects for each assay plate individually using the data from a single control column based on diffusion model, and thus targeting a specific but recurrent well-known HTS artefact. This method was first developed and validated using control plates and was then applied to the correction of experimental data generated during a genome-wide siRNA screen aimed at studying HIV-host interactions. The proposed algorithm was able to correct the edge effect biasing the control data and thus improve assay quality and, consequently, the hit-selection step.');
