INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78574, 2014, 'bio', 'Big data and other challenges in the quest for orthologs', 'Sonnhammer, Erik L L|Gabaldxc3xb3n, Toni|Sousa da Silva, Alan W|Martin, Maria|Robinson-Rechavi, Marc|Boeckmann, Brigitte|Thomas, Paul D|Dessimoz, Christophe|Quest for Orthologs consortium', 'Stockholm Bioinformatics Center, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden, Swedish eScience Research Center, Stockholm, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain, Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, Institucixc3xb3 Catalana de Recerca i Estudis Avanxc3xa7ats (ICREA), 08010 Barcelona, Spain, EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, UK, Department of Ecology and Evolution, University of Lausanne, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, SwissProt, Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland, Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA and Department of Genetics, Evolution and Environment, and Department of Computer Science, University College London, Gower St, London WC1E 6BT, UK Stockholm Bioinformatics Center, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden, Swedish eScience Research Center, Stockholm, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain, Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, Institucixc3xb3 Catalana de Recerca i Estudis Avanxc3xa7ats (ICREA), 08010 Barcelona, Spain, EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, UK, Department of Ecology and Evolution, University of Lausanne, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, SwissProt, Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland, Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA and Department of Genetics, Evolution and Environment, and Department of Computer Science, University College London, Gower St, London|Stockholm Bioinformatics Center, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden, Swedish eScience Research Center, Stockholm, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain, Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, Institucixc3xb3 Catalana de Recerca i Estudis Avanxc3xa7ats (ICREA), 08010 Barcelona, Spain, EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, UK, Department of Ecology and Evolution, University of Lausanne, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, SwissProt, Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland, Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA and Department of Genetics, Evolution and Environment, and Department of Computer Science, University College London, Gower St, London WC1E 6BT, UK Stockholm Bioinformatics Center, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden, Swedish eScience Research Center, Stockholm, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain, Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, Institucixc3xb3 Catalana de Recerca i Estudis Avanxc3xa7ats (ICREA), 08010 Barcelona, Spain, EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, UK, Department of Ecology and Evolution, University of Lausanne, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, SwissProt, Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland, Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA and Department of Genetics, Evolution and Environment, and Department of Computer Science, University College London, Gower St, London|Stockholm Bioinformatics Center, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden, Swedish eScience Research Center, Stockholm, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain, Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, Institucixc3xb3 Catalana de Recerca i Estudis Avanxc3xa7ats (ICREA), 08010 Barcelona, Spain, EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, UK, Department of Ecology and Evolution, University of Lausanne, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, SwissProt, Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland, Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA and Department of Genetics, Evolution and Environment, and Department of Computer Science, University College London, Gower St, London WC1E 6BT, UK.|Stockholm Bioinformatics Center, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden, Swedish eScience Research Center, Stockholm, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain, Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, Institucixc3xb3 Catalana de Recerca i Estudis Avanxc3xa7ats (ICREA), 08010 Barcelona, Spain, EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, UK, Department of Ecology and Evolution, University of Lausanne, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, SwissProt, Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland, Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA and Department of Genetics, Evolution and Environment, and Department of Computer Science, University College London, Gower St, London WC1E 6BT, UK.|Stockholm Bioinformatics Center, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden, Swedish eScience Research Center, Stockholm, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain, Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, Institucixc3xb3 Catalana de Recerca i Estudis Avanxc3xa7ats (ICREA), 08010 Barcelona, Spain, EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, UK, Department of Ecology and Evolution, University of Lausanne, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, SwissProt, Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland, Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA and Department of Genetics, Evolution and Environment, and Department of Computer Science, University College London, Gower St, London WC1E 6BT, UK Stockholm Bioinformatics Center, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden, Swedish eScience Research Center, Stockholm, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain, Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, Institucixc3xb3 Catalana de Recerca i Estudis Avanxc3xa7ats (ICREA), 08010 Barcelona, Spain, EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, UK, Department of Ecology and Evolution, University of Lausanne, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, SwissProt, Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland, Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA and Department of Genetics, Evolution and Environment, and Department of Computer Science, University College London, Gower St, London|Stockholm Bioinformatics Center, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden, Swedish eScience Research Center, Stockholm, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain, Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, Institucixc3xb3 Catalana de Recerca i Estudis Avanxc3xa7ats (ICREA), 08010 Barcelona, Spain, EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, UK, Department of Ecology and Evolution, University of Lausanne, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, SwissProt, Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland, Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA and Department of Genetics, Evolution and Environment, and Department of Computer Science, University College London, Gower St, London WC1E 6BT, UK.|Stockholm Bioinformatics Center, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden, Swedish eScience Research Center, Stockholm, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain, Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, Institucixc3xb3 Catalana de Recerca i Estudis Avanxc3xa7ats (ICREA), 08010 Barcelona, Spain, EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, UK, Department of Ecology and Evolution, University of Lausanne, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, SwissProt, Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland, Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA and Department of Genetics, Evolution and Environment, and Department of Computer Science, University College London, Gower St, London WC1E 6BT, UK.|Stockholm Bioinformatics Center, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden, Swedish eScience Research Center, Stockholm, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain, Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, Institucixc3xb3 Catalana de Recerca i Estudis Avanxc3xa7ats (ICREA), 08010 Barcelona, Spain, EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, UK, Department of Ecology and Evolution, University of Lausanne, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, SwissProt, Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland, Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA and Department of Genetics, Evolution and Environment, and Department of Computer Science, University College London, Gower St, London WC1E 6BT, UK Stockholm Bioinformatics Center, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden, Swedish eScience Research Center, Stockholm, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain, Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, Institucixc3xb3 Catalana de Recerca i Estudis Avanxc3xa7ats (ICREA), 08010 Barcelona, Spain, EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, UK, Department of Ecology and Evolution, University of Lausanne, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, SwissProt, Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland, Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA and Department of Genetics, Evolution and Environment, and Department of Computer Science, University College London, Gower St, London|Stockholm Bioinformatics Center, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden, Swedish eScience Research Center, Stockholm, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain, Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, Institucixc3xb3 Catalana de Recerca i Estudis Avanxc3xa7ats (ICREA), 08010 Barcelona, Spain, EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, UK, Department of Ecology and Evolution, University of Lausanne, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, SwissProt, Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland, Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA and Department of Genetics, Evolution and Environment, and Department of Computer Science, University College London, Gower St, London WC1E 6BT, UK Stockholm Bioinformatics Center, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden, Swedish eScience Research Center, Stockholm, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain, Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, Institucixc3xb3 Catalana de Recerca i Estudis Avanxc3xa7ats (ICREA), 08010 Barcelona, Spain, EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, UK, Department of Ecology and Evolution, University of Lausanne, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, SwissProt, Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland, Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA and Department of Genetics, Evolution and Environment, and Department of Computer Science, University College London, Gower St, London', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Swit', 0, 'Algorithms|Genomics|Protein Structure, Tertiary|Proteome|Sequence Analysis, DNA|Sequence Analysis, Protein|Sequence Homology', 'Editorial', '10.1093/bioinformatics/btu492', '25064571', 'Given the rapid increase of species with a sequenced genome, the need to identify orthologous genes between them has emerged as a central bioinformatics task. Many different methods exist for orthology detection, which makes it difficult to decide which one to choose for a particular application. Here, we review the latest developments and issues in the orthology field, and summarize the most recent results reported at the third Quest for Orthologs meeting. We focus on community efforts such as the adoption of reference proteomes, standard file formats and benchmarking. Progress in these areas is good, and they are already beneficial to both orthology consumers and providers. However, a major current issue is that the massive increase in complete proteomes poses computational challenges to many of the ortholog database providers, as most orthology inference algorithms scale at least quadratically with the number of proteomes. The Quest for Orthologs consortium is an open community with a number of working groups that join efforts to enhance various aspects of orthology analysis, such as defining standard formats and datasets, documenting community resources and benchmarking.'),
(78575, 2014, 'bio', 'Biocellion: accelerating computer simulation of multicellular biological system models', 'Kang, Seunghwa|Kahan, Simon|McDermott, Jason|Flann, Nicholas|Shmulevich, Ilya', 'Computational Biology and Bioinformatics Group, High-performance Computing Group, Pacific Northwest National Laboratory, Richland, WA 99354, USA, Department of Computer Science, Utah State University, Logan, UT 84322, USA and Institute for Systems Biology, Seattle, WA 98109, USA.|Computational Biology and Bioinformatics Group, High-performance Computing Group, Pacific Northwest National Laboratory, Richland, WA 99354, USA, Department of Computer Science, Utah State University, Logan, UT 84322, USA and Institute for Systems Biology, Seattle, WA 98109, USA.|Computational Biology and Bioinformatics Group, High-performance Computing Group, Pacific Northwest National Laboratory, Richland, WA 99354, USA, Department of Computer Science, Utah State University, Logan, UT 84322, USA and Institute for Systems Biology, Seattle, WA 98109, USA.|Computational Biology and Bioinformatics Group, High-performance Computing Group, Pacific Northwest National Laboratory, Richland, WA 99354, USA, Department of Computer Science, Utah State University, Logan, UT 84322, USA and Institute for Systems Biology, Seattle, WA 98109, USA.|Computational Biology and Bioinformatics Group, High-performance Computing Group, Pacific Northwest National Laboratory, Richland, WA 99354, USA, Department of Computer Science, Utah State University, Logan, UT 84322, USA and Institute for Systems Biology, Seattle, WA 98109, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Bacteria|Cell Adhesion|Computational Biology|Computer Simulation|Microbial Interactions|Models, Biological|Software|Soil Microbiology|Yeasts', 'Journal Article', '10.1093/bioinformatics/btu498', '25064572', 'Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming.'),
(78576, 2014, 'bio', 'Circleator: flexible circular visualization of genome-associated data with BioPerl and SVG', 'Crabtree, Jonathan|Agrawal, Sonia|Mahurkar, Anup|Myers, Garry S|Rasko, David A|White, Owen', 'Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, i3 Institute, University of Technology, Sydney, PO Box 123 Broadway NSW 2007, Australia, Department of Microbial Pathogenesis, University of Maryland Dental School, Baltimore, MD 21201, Center for Health-Related Informatics and Bioimaging, University of Maryland, College Park, MD 20740 and Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA.|Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, i3 Institute, University of Technology, Sydney, PO Box 123 Broadway NSW 2007, Australia, Department of Microbial Pathogenesis, University of Maryland Dental School, Baltimore, MD 21201, Center for Health-Related Informatics and Bioimaging, University of Maryland, College Park, MD 20740 and Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA.|Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, i3 Institute, University of Technology, Sydney, PO Box 123 Broadway NSW 2007, Australia, Department of Microbial Pathogenesis, University of Maryland Dental School, Baltimore, MD 21201, Center for Health-Related Informatics and Bioimaging, University of Maryland, College Park, MD 20740 and Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA.|Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, i3 Institute, University of Technology, Sydney, PO Box 123 Broadway NSW 2007, Australia, Department of Microbial Pathogenesis, University of Maryland Dental School, Baltimore, MD 21201, Center for Health-Related Informatics and Bioimaging, University of Maryland, College Park, MD 20740 and Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, i3 Institute, University of Technology, Sydney, PO Box 123 Broadway NSW 2007, Australia, Department of Microbial Pathogenesis, University of Maryland Dental School, Baltimore, MD 21201, Center for Health-Related Informatics and Bioimaging, University of Maryland, College Park, MD 20740 and Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, i3 Institute, University of Technology, Sydney, PO Box 123 Broadway NSW 2007, Australia, Department of Microbial Pathogenesis, University of Maryland Dental School, Baltimore, MD 21201, Center for Health-Related Informatics and Bioimaging, University of Maryland, College Park, MD 20740 and Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, Department of Microbiology and Immunology, University of Maryland School of Medicine|Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, i3 Institute, University of Technology, Sydney, PO Box 123 Broadway NSW 2007, Australia, Department of Microbial Pathogenesis, University of Maryland Dental School, Baltimore, MD 21201, Center for Health-Related Informatics and Bioimaging, University of Maryland, College Park, MD 20740 and Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, i3 Institute, University of Technology, Sydney, PO Box 123 Broadway NSW 2007, Australia, Department of Microbial Pathogenesis, University of Maryland Dental School, Baltimore, MD 21201, Center for Health-Related Informatics and Bioimaging, University of Maryland, College Park, MD 20740 and Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, i3 Institute, University of Technology, Sydney, PO Box 123 Broadway NSW 2007, Australia, Department of Microbial Pathogenesis, University of Maryland Dental School, Baltimore, MD 21201, Center for Health-Related Informatics and Bioimaging, University of Maryland, College Park, MD 20740 and Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA.|Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, i3 Institute, University of Technology, Sydney, PO Box 123 Broadway NSW 2007, Australia, Department of Microbial Pathogenesis, University of Maryland Dental School, Baltimore, MD 21201, Center for Health-Related Informatics and Bioimaging, University of Maryland, College Park, MD 20740 and Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, i3 Institute, University of Technology, Sydney, PO Box 123 Broadway NSW 2007, Australia, Department of Microbial Pathogenesis, University of Maryland Dental School, Baltimore, MD 21201, Center for Health-Related Informatics and Bioimaging, University of Maryland, College Park, MD 20740 and Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, i3 Institute, University of Technology, Sydney, PO Box 123 Broadway NSW 2007, Australia, Department of Microbial Pathogenesis, University of Maryland Dental School, Baltimore, MD 21201, Center for Health-Related Informatics and Bioimaging, University of Maryland, College Park, MD 20740 and Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA.', 'Australia|Australia|Australia|Australia|Australia|Australia', 0, 'Computer Graphics|Gardnerella vaginalis|Genomics|Molecular Sequence Annotation|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu505', '25075113', 'Circleator is a Perl application that generates circular figures of genome-associated data. It leverages BioPerl to support standard annotation and sequence file formats and produces publication-quality SVG output. It is designed to be both flexible and easy to use. It includes a library of circular track types and predefined configuration files for common use-cases, including. (i) visualizing gene annotation and DNA sequence data from a GenBank flat file, (ii) displaying patterns of gene conservation in related microbial strains, (iii) showing Single Nucleotide Polymorphisms (SNPs) and indels relative to a reference genome and gene set and (iv) viewing RNA-Seq plots.'),
(78577, 2014, 'bio', 'Metabomxtr: an R package for mixture-model analysis of non-targeted metabolomics data', 'Nodzenski, Michael|Muehlbauer, Michael J|Bain, James R|Reisetter, Anna C|Lowe, William L|Scholtens, Denise M', 'Department of Preventive Medicine, Division of Biostatistics, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, Sarah W. Stedman Nutrition and Metabolism Center, Duke Molecular Physiology Institute and Division of Endocrinology, Metabolism, and Nutrition, Department of Medicine, Duke University Medical Center, Durham, NC 27704 and Department of Medicine, Division of Endocrinology, Metabolism, and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611.|Department of Preventive Medicine, Division of Biostatistics, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, Sarah W. Stedman Nutrition and Metabolism Center, Duke Molecular Physiology Institute and Division of Endocrinology, Metabolism, and Nutrition, Department of Medicine, Duke University Medical Center, Durham, NC 27704 and Department of Medicine, Division of Endocrinology, Metabolism, and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611.|Department of Preventive Medicine, Division of Biostatistics, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, Sarah W. Stedman Nutrition and Metabolism Center, Duke Molecular Physiology Institute and Division of Endocrinology, Metabolism, and Nutrition, Department of Medicine, Duke University Medical Center, Durham, NC 27704 and Department of Medicine, Division of Endocrinology, Metabolism, and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611 Department of Preventive Medicine, Division of Biostatistics, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, Sarah W. Stedman Nutrition and Metabolism Center, Duke Molecular Physiology Institute and Division of Endocrinology, Metabolism, and Nutrition, Department of Medicine, Duke University Medical Center, Durham, NC 27704 and Department of Medicine, Division of Endocrinology, Metabolism, and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611.|Department of Preventive Medicine, Division of Biostatistics, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, Sarah W. Stedman Nutrition and Metabolism Center, Duke Molecular Physiology Institute and Division of Endocrinology, Metabolism, and Nutrition, Department of Medicine, Duke University Medical Center, Durham, NC 27704 and Department of Medicine, Division of Endocrinology, Metabolism, and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611.|Department of Preventive Medicine, Division of Biostatistics, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, Sarah W. Stedman Nutrition and Metabolism Center, Duke Molecular Physiology Institute and Division of Endocrinology, Metabolism, and Nutrition, Department of Medicine, Duke University Medical Center, Durham, NC 27704 and Department of Medicine, Division of Endocrinology, Metabolism, and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611.|Department of Preventive Medicine, Division of Biostatistics, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, Sarah W. Stedman Nutrition and Metabolism Center, Duke Molecular Physiology Institute and Division of Endocrinology, Metabolism, and Nutrition, Department of Medicine, Duke University Medical Center, Durham, NC 27704 and Department of Medicine, Division of Endocrinology, Metabolism, and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611.', '-|-|-|-|-|-', 14, 'Female|Humans|Metabolomics|Models, Statistical|Pregnancy|Software', 'Journal Article', '10.1093/bioinformatics/btu509', '25075114', 'Non-targeted metabolomics technologies often yield data in which abundance for any given metabolite is observed and quantified for some samples and reported as missing for other samples. Apparent missingness can be due to true absence of the metabolite in the sample or presence at a level below detectability. Mixture-model analysis can formally account for metabolite missingness due to absence or undetectability, but software for this type of analysis in the high-throughput setting is limited. The R package metabomxtr has been developed to facilitate mixture-model analysis of non-targeted metabolomics data in which only a portion of samples have quantifiable abundance for certain metabolites.'),
(78578, 2014, 'bio', 'Retro: concept-based clustering of biomedical topical sets', 'Yeganova, Lana|Kim, Won|Kim, Sun|Wilbur, W John', 'National Center for Biotechnology Information, National Library of Medicine, NIH, 8600 Rockville Pike, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, NIH, 8600 Rockville Pike, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, NIH, 8600 Rockville Pike, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, NIH, 8600 Rockville Pike, Bethesda, MD 20894, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Cluster Analysis|Data Mining|Databases, Genetic|Medical Subject Headings', 'Evaluation Studies', '10.1093/bioinformatics/btu514', '25075115', 'Clustering methods can be useful for automatically grouping documents into meaningful clusters, improving human comprehension of a document collection. Although there are clustering algorithms that can achieve the goal for relatively large document collections, they do not always work well for small and homogenous datasets.'),
(78579, 2014, 'bio', 'Trowel: a fast and accurate error correction module for Illumina sequencing reads', 'Lim, Eun-Cheon|Müller, Jonas|Hagmann, Jörg|Henz, Stefan R|Kim, Sang-Tae|Weigel, Detlef', 'Department of Molecular Biology, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany.|Department of Molecular Biology, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany.|Department of Molecular Biology, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany.|Department of Molecular Biology, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany.|Department of Molecular Biology, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany.|Department of Molecular Biology, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 17, 'Algorithms|High-Throughput Nucleotide Sequencing|Software', 'Journal Article', '10.1093/bioinformatics/btu513', '25075116', 'The ability to accurately read the order of nucleotides in DNA and RNA is fundamental for modern biology. Errors in next-generation sequencing can lead to many artifacts, from erroneous genome assemblies to mistaken inferences about RNA editing. Uneven coverage in datasets also contributes to false corrections.'),
(78580, 2014, 'bio', 'Greater power and computational efficiency for kernel-based association testing of sets of genetic variants', 'Lippert, Christoph|Xiang, Jing|Horta, Danilo|Widmer, Christian|Kadie, Carl|Heckerman, David|Listgarten, Jennifer', 'eScience Research Group, Microsoft Research, Los Angeles, CA, 90024 and eScience Research Group, Microsoft Research, Redmond, WA, 98052, USA.|eScience Research Group, Microsoft Research, Los Angeles, CA, 90024 and eScience Research Group, Microsoft Research, Redmond, WA, 98052, USA.|eScience Research Group, Microsoft Research, Los Angeles, CA, 90024 and eScience Research Group, Microsoft Research, Redmond, WA, 98052, USA.|eScience Research Group, Microsoft Research, Los Angeles, CA, 90024 and eScience Research Group, Microsoft Research, Redmond, WA, 98052, USA.|eScience Research Group, Microsoft Research, Los Angeles, CA, 90024 and eScience Research Group, Microsoft Research, Redmond, WA, 98052, USA.|eScience Research Group, Microsoft Research, Los Angeles, CA, 90024 and eScience Research Group, Microsoft Research, Redmond, WA, 98052, USA.|eScience Research Group, Microsoft Research, Los Angeles, CA, 90024 and eScience Research Group, Microsoft Research, Redmond, WA, 98052, USA.', 'United States|United States|United States|United States|United States|United States|United States', 13, 'Algorithms|Data Interpretation, Statistical|Genetic Association Studies|Genetic Variation|Humans|Likelihood Functions|Phenotype|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btu504', '25075117', 'Set-based variance component tests have been identified as a way to increase power in association studies by aggregating weak individual effects. However, the choice of test statistic has been largely ignored even though it may play an important role in obtaining optimal power. We compared a standard statistical test-a score test-with a recently developed likelihood ratio (LR) test. Further, when correction for hidden structure is needed, or gene-gene interactions are sought, state-of-the art algorithms for both the score and LR tests can be computationally impractical. Thus we develop new computationally efficient methods.'),
(78581, 2014, 'bio', 'FARVAT: a family-based rare variant association test', 'Choi, Sungkyoung|Lee, Sungyoung|Cichon, Sven|Nöthen, Markus M|Lange, Christoph|Park, Taesung|Won, Sungho', 'Interdisciplinary Program in bioinformatics, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea, Institute of Human Genetics, University of Bonn, D-53127 Bonn, Germany, Department of Biostatistics, Harvard School of Public Health, 677 Huntington Avenue. Boston, MA 02115, USA, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA, Center for Genomic Medicine, Brigham and Womens Hospital, 75 Francis Street, Boston MA 02115, USA, Department of Biostatistics, Harvard School of Public Health, 667 Huntington Ave, Boston, MA 02115, USA, Institute for Genomic Mathematics, University of Bonn, D-53127 Bonn, Germany, German Center for Neurodegenerative Diseases, D-53127 Bonn, Germany, Department of Statistics, Seoul National University 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea and Department of Public Health Science, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea.|Interdisciplinary Program in bioinformatics, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea, Institute of Human Genetics, University of Bonn, D-53127 Bonn, Germany, Department of Biostatistics, Harvard School of Public Health, 677 Huntington Avenue. Boston, MA 02115, USA, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA, Center for Genomic Medicine, Brigham and Womens Hospital, 75 Francis Street, Boston MA 02115, USA, Department of Biostatistics, Harvard School of Public Health, 667 Huntington Ave, Boston, MA 02115, USA, Institute for Genomic Mathematics, University of Bonn, D-53127 Bonn, Germany, German Center for Neurodegenerative Diseases, D-53127 Bonn, Germany, Department of Statistics, Seoul National University 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea and Department of Public Health Science, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea.|Interdisciplinary Program in bioinformatics, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea, Institute of Human Genetics, University of Bonn, D-53127 Bonn, Germany, Department of Biostatistics, Harvard School of Public Health, 677 Huntington Avenue. Boston, MA 02115, USA, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA, Center for Genomic Medicine, Brigham and Womens Hospital, 75 Francis Street, Boston MA 02115, USA, Department of Biostatistics, Harvard School of Public Health, 667 Huntington Ave, Boston, MA 02115, USA, Institute for Genomic Mathematics, University of Bonn, D-53127 Bonn, Germany, German Center for Neurodegenerative Diseases, D-53127 Bonn, Germany, Department of Statistics, Seoul National University 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea and Department of Public Health Science, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea.|Interdisciplinary Program in bioinformatics, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea, Institute of Human Genetics, University of Bonn, D-53127 Bonn, Germany, Department of Biostatistics, Harvard School of Public Health, 677 Huntington Avenue. Boston, MA 02115, USA, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA, Center for Genomic Medicine, Brigham and Womens Hospital, 75 Francis Street, Boston MA 02115, USA, Department of Biostatistics, Harvard School of Public Health, 667 Huntington Ave, Boston, MA 02115, USA, Institute for Genomic Mathematics, University of Bonn, D-53127 Bonn, Germany, German Center for Neurodegenerative Diseases, D-53127 Bonn, Germany, Department of Statistics, Seoul National University 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea and Department of Public Health Science, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea.|Interdisciplinary Program in bioinformatics, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea, Institute of Human Genetics, University of Bonn, D-53127 Bonn, Germany, Department of Biostatistics, Harvard School of Public Health, 677 Huntington Avenue. Boston, MA 02115, USA, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA, Center for Genomic Medicine, Brigham and Womens Hospital, 75 Francis Street, Boston MA 02115, USA, Department of Biostatistics, Harvard School of Public Health, 667 Huntington Ave, Boston, MA 02115, USA, Institute for Genomic Mathematics, University of Bonn, D-53127 Bonn, Germany, German Center for Neurodegenerative Diseases, D-53127 Bonn, Germany, Department of Statistics, Seoul National University 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea and Department of Public Health Science, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea.|Interdisciplinary Program in bioinformatics, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea, Institute of Human Genetics, University of Bonn, D-53127 Bonn, Germany, Department of Biostatistics, Harvard School of Public Health, 677 Huntington Avenue. Boston, MA 02115, USA, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA, Center for Genomic Medicine, Brigham and Womens Hospital, 75 Francis Street, Boston MA 02115, USA, Department of Biostatistics, Harvard School of Public Health, 667 Huntington Ave, Boston, MA 02115, USA, Institute for Genomic Mathematics, University of Bonn, D-53127 Bonn, Germany, German Center for Neurodegenerative Diseases, D-53127 Bonn, Germany, Department of Statistics, Seoul National University 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea and Department of Public Health Science, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea Interdisciplinary Program in bioinformatics, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea, Institute of Human Genetics, University of Bonn, D-53127 Bonn, Germany, Department of Biostatistics, Harvard School of Public Health, 677 Huntington Avenue. Boston, MA 02115, USA, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA, Center for Genomic Medicine, Brigham and Womens Hospital, 75 Francis Street, Boston MA 02115, USA, Department of Biostatistics, Harvard School of Public Health, 667 Huntington Ave, Boston, MA 02115, USA, Institute for Genomic Mathematics, University of Bonn, D-53127 Bonn, Germany, German Center for Neurodegenerative Diseases, D-53127 Bonn, Germany, Department of Statistics, Seoul National University 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea and Department of Public Health Science, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea.|Interdisciplinary Program in bioinformatics, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea, Institute of Human Genetics, University of Bonn, D-53127 Bonn, Germany, Department of Biostatistics, Harvard School of Public Health, 677 Huntington Avenue. Boston, MA 02115, USA, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA, Center for Genomic Medicine, Brigham and Womens Hospital, 75 Francis Street, Boston MA 02115, USA, Department of Biostatistics, Harvard School of Public Health, 667 Huntington Ave, Boston, MA 02115, USA, Institute for Genomic Mathematics, University of Bonn, D-53127 Bonn, Germany, German Center for Neurodegenerative Diseases, D-53127 Bonn, Germany, Department of Statistics, Seoul National University 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea and Department of Public Health Science, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Family|Genetic Association Studies|Genetic Variation|Humans|Schizophrenia|Software', 'Journal Article', '10.1093/bioinformatics/btu496', '25075118', 'Individuals in each family are genetically more homogeneous than unrelated individuals, and family-based designs are often recommended for the analysis of rare variants. However, despite the importance of family-based samples analysis, few statistical methods for rare variant association analysis are available.'),
(78582, 2014, 'bio', 'BitPAl: a bit-parallel, general integer-scoring sequence alignment algorithm', 'Loving, Joshua|Hernandez, Yozen|Benson, Gary', 'Laboratory for Biocomputing and Informatics, Graduate Program in Bioinformatics, and Department of Computer Science, Boston University, Boston, MA 02215, USA Laboratory for Biocomputing and Informatics, Graduate Program in Bioinformatics, and Department of Computer Science, Boston University, Boston, MA 02215, USA.|Laboratory for Biocomputing and Informatics, Graduate Program in Bioinformatics, and Department of Computer Science, Boston University, Boston, MA 02215, USA Laboratory for Biocomputing and Informatics, Graduate Program in Bioinformatics, and Department of Computer Science, Boston University, Boston, MA 02215, USA.|Laboratory for Biocomputing and Informatics, Graduate Program in Bioinformatics, and Department of Computer Science, Boston University, Boston, MA 02215, USA Laboratory for Biocomputing and Informatics, Graduate Program in Bioinformatics, and Department of Computer Science, Boston University, Boston, MA 02215, USA Laboratory for Biocomputing and Informatics, Graduate Program in Bioinformatics, and Department of Computer Science, Boston University, Boston, MA 02215, USA.', 'United States|United States|United States', 0, 'Algorithms|High-Throughput Nucleotide Sequencing|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btu507', '25075119', 'Mapping of high-throughput sequencing data and other bulk sequence comparison applications have motivated a search for high-efficiency sequence alignment algorithms. The bit-parallel approach represents individual cells in an alignment scoring matrix as bits in computer words and emulates the calculation of scores by a series of logic operations composed of AND, OR, XOR, complement, shift and addition. Bit-parallelism has been successfully applied to the longest common subsequence (LCS) and edit-distance problems, producing fast algorithms in practice.'),
(78583, 2014, 'bio', 'NetPathMiner: R/Bioconductor package for network path mining through gene expression', 'Mohamed, Ahmed|Hancock, Timothy|Nguyen, Canh Hao|Mamitsuka, Hiroshi', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Japan and Department of Computing and Information Systems, The University of Melbourne, Victoria, Australia.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Japan and Department of Computing and Information Systems, The University of Melbourne, Victoria, Australia Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Japan and Department of Computing and Information Systems, The University of Melbourne, Victoria, Australia.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Japan and Department of Computing and Information Systems, The University of Melbourne, Victoria, Australia.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Japan and Department of Computing and Information Systems, The University of Melbourne, Victoria, Australia.', 'Australia|Australia|Australia|Australia', 4, 'Carbohydrate Metabolism|Cluster Analysis|Computer Graphics|Data Mining|Genomics|Metabolic Networks and Pathways|Signal Transduction|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btu501', '25075120', 'NetPathMiner is a general framework for mining, from genome-scale networks, paths that are related to specific experimental conditions. NetPathMiner interfaces with various input formats including KGML, SBML and BioPAX files and allows for manipulation of networks in three different forms: metabolic, reaction and gene representations. NetPathMiner ranks the obtained paths and applies Markov model-based clustering and classification methods to the ranked paths for easy interpretation. NetPathMiner also provides static and interactive visualizations of networks and paths to aid manual investigation.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78584, 2014, 'bio', 'Quantitative method for the assignment of hinge and shear mechanism in protein domain movements', 'Taylor, Daniel|Cawley, Gavin|Hayward, Steven', 'DArcy Thompson Centre for Computational Biology, School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, UK.|DArcy Thompson Centre for Computational Biology, School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, UK.|DArcy Thompson Centre for Computational Biology, School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, UK.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Logistic Models|Motion|Protein Structure, Tertiary|Rotation|Software', 'Journal Article', '10.1093/bioinformatics/btu506', '25078396', 'A popular method for classification of protein domain movements apportions them into two main types: those with a hinge mechanism and those with a shear mechanism. The intuitive assignment of domain movements to these classes has limited the number of domain movements that can be classified in this way. Furthermore, whether intended or not, the term shear is often interpreted to mean a relative translation of the domains.'),
(78585, 2014, 'bio', 'Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases', 'Smedley, Damian|Kxc3xb6hler, Sebastian|Czeschik, Johanna Christina|Amberger, Joanna|Bocchini, Carol|Hamosh, Ada|Veldboer, Julian|Zemojtel, Tomasz|Robinson, Peter N', 'Mouse Informatics Group, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, Institute for Medical Genetics and Human Genetics, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Genome Informatics Department, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45122 Essen, Germany, McKusick-Nathans Institute of Genetic Medicine, John Hopkins University School of Medicine, Baltimore, MD 21205, USA, Department of Mathematics and Computer Science, Institute for Bioinformatics, Freie Universitxc3xa4t Berlin, Takustrasse 9, 14195 Berlin, Germany, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-701 Poznan, Poland, Berlin-Brandenburg Center for Regenerative Therapies, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin and Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany.|Mouse Informatics Group, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, Institute for Medical Genetics and Human Genetics, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Genome Informatics Department, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45122 Essen, Germany, McKusick-Nathans Institute of Genetic Medicine, John Hopkins University School of Medicine, Baltimore, MD 21205, USA, Department of Mathematics and Computer Science, Institute for Bioinformatics, Freie Universitxc3xa4t Berlin, Takustrasse 9, 14195 Berlin, Germany, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-701 Poznan, Poland, Berlin-Brandenburg Center for Regenerative Therapies, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin and Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany.|Mouse Informatics Group, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, Institute for Medical Genetics and Human Genetics, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Genome Informatics Department, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45122 Essen, Germany, McKusick-Nathans Institute of Genetic Medicine, John Hopkins University School of Medicine, Baltimore, MD 21205, USA, Department of Mathematics and Computer Science, Institute for Bioinformatics, Freie Universitxc3xa4t Berlin, Takustrasse 9, 14195 Berlin, Germany, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-701 Poznan, Poland, Berlin-Brandenburg Center for Regenerative Therapies, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin and Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany.|Mouse Informatics Group, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, Institute for Medical Genetics and Human Genetics, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Genome Informatics Department, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45122 Essen, Germany, McKusick-Nathans Institute of Genetic Medicine, John Hopkins University School of Medicine, Baltimore, MD 21205, USA, Department of Mathematics and Computer Science, Institute for Bioinformatics, Freie Universitxc3xa4t Berlin, Takustrasse 9, 14195 Berlin, Germany, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-701 Poznan, Poland, Berlin-Brandenburg Center for Regenerative Therapies, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin and Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany.|Mouse Informatics Group, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, Institute for Medical Genetics and Human Genetics, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Genome Informatics Department, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45122 Essen, Germany, McKusick-Nathans Institute of Genetic Medicine, John Hopkins University School of Medicine, Baltimore, MD 21205, USA, Department of Mathematics and Computer Science, Institute for Bioinformatics, Freie Universitxc3xa4t Berlin, Takustrasse 9, 14195 Berlin, Germany, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-701 Poznan, Poland, Berlin-Brandenburg Center for Regenerative Therapies, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin and Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany.|Mouse Informatics Group, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, Institute for Medical Genetics and Human Genetics, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Genome Informatics Department, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45122 Essen, Germany, McKusick-Nathans Institute of Genetic Medicine, John Hopkins University School of Medicine, Baltimore, MD 21205, USA, Department of Mathematics and Computer Science, Institute for Bioinformatics, Freie Universitxc3xa4t Berlin, Takustrasse 9, 14195 Berlin, Germany, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-701 Poznan, Poland, Berlin-Brandenburg Center for Regenerative Therapies, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin and Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany.|Mouse Informatics Group, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, Institute for Medical Genetics and Human Genetics, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Genome Informatics Department, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45122 Essen, Germany, McKusick-Nathans Institute of Genetic Medicine, John Hopkins University School of Medicine, Baltimore, MD 21205, USA, Department of Mathematics and Computer Science, Institute for Bioinformatics, Freie Universitxc3xa4t Berlin, Takustrasse 9, 14195 Berlin, Germany, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-701 Poznan, Poland, Berlin-Brandenburg Center for Regenerative Therapies, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin and Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany Mouse Informatics Group, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, Institute for Medical Genetics and Human Genetics, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Genome Informatics Department, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45122 Essen, Germany, McKusick-Nathans Institute of Genetic Medicine, John Hopkins University School of Medicine, Baltimore, MD 21205, USA, Department of Mathematics and Computer Science, Institute for Bioinformatics, Freie Universitxc3xa4t Berlin, Takustrasse 9, 14195 Berlin, Germany, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-701 Poznan, Poland, Berlin-Brandenburg Center for Regenerative Therapies, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin and Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany.|Mouse Informatics Group, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, Institute for Medical Genetics and Human Genetics, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Genome Informatics Department, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45122 Essen, Germany, McKusick-Nathans Institute of Genetic Medicine, John Hopkins University School of Medicine, Baltimore, MD 21205, USA, Department of Mathematics and Computer Science, Institute for Bioinformatics, Freie Universitxc3xa4t Berlin, Takustrasse 9, 14195 Berlin, Germany, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-701 Poznan, Poland, Berlin-Brandenburg Center for Regenerative Therapies, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin and Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany Mouse Informatics Group, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, Institute for Medical Genetics and Human Genetics, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Genome Informatics Department, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45122 Essen, Germany, McKusick-Nathans Institute of Genetic Medicine, John Hopkins University School of Medicine, Baltimore, MD 21205, USA, Department of Mathematics and Computer Science, Institute for Bioinformatics, Freie Universitxc3xa4t Berlin, Takustrasse 9, 14195 Berlin, Germany, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-701 Poznan, Poland, Berlin-Brandenburg Center for Regenerative Therapies, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin and Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany.|Mouse Informatics Group, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, Institute for Medical Genetics and Human Genetics, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Genome Informatics Department, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45122 Essen, Germany, McKusick-Nathans Institute of Genetic Medicine, John Hopkins University School of Medicine, Baltimore, MD 21205, USA, Department of Mathematics and Computer Science, Institute for Bioinformatics, Freie Universitxc3xa4t Berlin, Takustrasse 9, 14195 Berlin, Germany, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-701 Poznan, Poland, Berlin-Brandenburg Center for Regenerative Therapies, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin and Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany Mouse Informatics Group, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, Institute for Medical Genetics and Human Genetics, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Genome Informatics Department, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45122 Essen, Germany, McKusick-Nathans Institute of Genetic Medicine, John Hopkins University School of Medicine, Baltimore, MD 21205, USA, Department of Mathematics and Computer Science, Institute for Bioinformatics, Freie Universitxc3xa4t Berlin, Takustrasse 9, 14195 Berlin, Germany, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-701 Poznan, Poland, Berlin-Brandenburg Center for Regenerative Therapies, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin and Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany Mouse Informatics Group, The Wellcome Trust Sang', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 43, 'Algorithms|Disease|Exome|Genes|Humans|Protein Interaction Mapping|Proteins|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu508', '25078397', 'Whole-exome sequencing (WES) has opened up previously unheard of possibilities for identifying novel disease genes in Mendelian disorders, only about half of which have been elucidated to date. However, interpretation of WES data remains challenging.'),
(78586, 2014, 'bio', 'Basic4Cseq: an R/Bioconductor package for analyzing 4C-seq data', 'Walter, Carolin|Schuetzmann, Daniel|Rosenbauer, Frank|Dugas, Martin', 'Institute of Medical Informatics, University of Münster, 48149 Münster, Germany, and Institute of Molecular Tumorbiology, University of Münster, 48149 Münster, Germany.|Institute of Medical Informatics, University of Münster, 48149 Münster, Germany, and Institute of Molecular Tumorbiology, University of Münster, 48149 Münster, Germany.|Institute of Medical Informatics, University of Münster, 48149 Münster, Germany, and Institute of Molecular Tumorbiology, University of Münster, 48149 Münster, Germany.|Institute of Medical Informatics, University of Münster, 48149 Münster, Germany, and Institute of Molecular Tumorbiology, University of Münster, 48149 Münster, Germany.', 'Germany|Germany|Germany|Germany', 13, 'Chromosomes|High-Throughput Nucleotide Sequencing|Software', 'Journal Article', '10.1093/bioinformatics/btu497', '25078398', 'Basic4Cseq is an R/Bioconductor package for basic filtering, analysis and subsequent near-cis visualization of 4C-seq data. The package processes aligned 4C-seq raw data stored in binary alignment/map (BAM) format and maps the short reads to a corresponding virtual fragment library. Functions are included to create virtual fragment libraries providing chromosome position and further information on 4C-seq fragments (length and uniqueness of the fragment ends, and blindness of a fragment) for any BSGenome package. An optional filter is included for BAM files to remove invalid 4C-seq reads, and further filter functions are offered for 4C-seq fragments. Additionally, basic quality controls based on the read distribution are included. Fragment data in the vicinity of the experiments viewpoint are visualized as coverage plot based on a running median approach and a multi-scale contact profile. Wig files or csv files of the fragment data can be exported for further analyses and visualizations of interactions with other programs.'),
(78587, 2014, 'bio', 'Network-based analysis of genotype-phenotype correlations between different inheritance modes', 'Hao, Dapeng|Li, Chuanxing|Zhang, Shaojun|Lu, Jianping|Jiang, Yongshuai|Wang, Shiyuan|Zhou, Meng', 'College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, P.R. China and Institute for Systems Biology, Seattle 98109, USA.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, P.R. China and Institute for Systems Biology, Seattle 98109, USA College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, P.R. China and Institute for Systems Biology, Seattle 98109, USA.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, P.R. China and Institute for Systems Biology, Seattle 98109, USA.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, P.R. China and Institute for Systems Biology, Seattle 98109, USA.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, P.R. China and Institute for Systems Biology, Seattle 98109, USA.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, P.R. China and Institute for Systems Biology, Seattle 98109, USA.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, P.R. China and Institute for Systems Biology, Seattle 98109, USA.', 'China|China|China|China|China|China|China', 0, 'Disease|Genetic Association Studies|Genotype|Humans|Inheritance Patterns|Mutation|Phenotype|Protein Interaction Mapping', 'Journal Article', '10.1093/bioinformatics/btu482', '25078399', 'Recent studies on human disease have revealed that aberrant interaction between proteins probably underlies a substantial number of human genetic diseases. This suggests a need to investigate disease inheritance mode using interaction, and based on which to refresh our conceptual understanding of a series of properties regarding inheritance mode of human disease.'),
(78588, 2014, 'bio', 'Detection of active transcription factor binding sites with the combination of DNase hypersensitivity and histone modifications', 'Gusmao, Eduardo G|Dieterich, Christoph|Zenke, Martin|Costa, Ivan G', 'IZKF Computational Biology Research Group, Institute for Biomedical Engineering, RWTH Aachen University Medical School, 52074 Aachen, Computational RNA Biology Lab and Bioinformatics Core, Max Planck Institute for Biology of Ageing, 50931 Cologne, Department of Cell Biology, Institute for Biomedical Engineering, RWTH Aachen University Medical School, 52074, Helmholtz Institute for Biomedical Engineering, 52074, Aachen Institute for Advanced Study in Computational Engineering Science (AICES), RWTH Aachen University, 52062 Aachen, Germany and Center of Informatics, Federal University of Pernambuco, 50740560 Recife-PE, Brazil.|IZKF Computational Biology Research Group, Institute for Biomedical Engineering, RWTH Aachen University Medical School, 52074 Aachen, Computational RNA Biology Lab and Bioinformatics Core, Max Planck Institute for Biology of Ageing, 50931 Cologne, Department of Cell Biology, Institute for Biomedical Engineering, RWTH Aachen University Medical School, 52074, Helmholtz Institute for Biomedical Engineering, 52074, Aachen Institute for Advanced Study in Computational Engineering Science (AICES), RWTH Aachen University, 52062 Aachen, Germany and Center of Informatics, Federal University of Pernambuco, 50740560 Recife-PE, Brazil.|IZKF Computational Biology Research Group, Institute for Biomedical Engineering, RWTH Aachen University Medical School, 52074 Aachen, Computational RNA Biology Lab and Bioinformatics Core, Max Planck Institute for Biology of Ageing, 50931 Cologne, Department of Cell Biology, Institute for Biomedical Engineering, RWTH Aachen University Medical School, 52074, Helmholtz Institute for Biomedical Engineering, 52074, Aachen Institute for Advanced Study in Computational Engineering Science (AICES), RWTH Aachen University, 52062 Aachen, Germany and Center of Informatics, Federal University of Pernambuco, 50740560 Recife-PE, Brazil IZKF Computational Biology Research Group, Institute for Biomedical Engineering, RWTH Aachen University Medical School, 52074 Aachen, Computational RNA Biology Lab and Bioinformatics Core, Max Planck Institute for Biology of Ageing, 50931 Cologne, Department of Cell Biology, Institute for Biomedical Engineering, RWTH Aachen University Medical School, 52074, Helmholtz Institute for Biomedical Engineering, 52074, Aachen Institute for Advanced Study in Computational Engineering Science (AICES), RWTH Aachen University, 52062 Aachen, Germany and Center of Informatics, Federal University of Pernambuco, 50740560 Recife-PE, Brazil.|IZKF Computational Biology Research Group, Institute for Biomedical Engineering, RWTH Aachen University Medical School, 52074 Aachen, Computational RNA Biology Lab and Bioinformatics Core, Max Planck Institute for Biology of Ageing, 50931 Cologne, Department of Cell Biology, Institute for Biomedical Engineering, RWTH Aachen University Medical School, 52074, Helmholtz Institute for Biomedical Engineering, 52074, Aachen Institute for Advanced Study in Computational Engineering Science (AICES), RWTH Aachen University, 52062 Aachen, Germany and Center of Informatics, Federal University of Pernambuco, 50740560 Recife-PE, Brazil IZKF Computational Biology Research Group, Institute for Biomedical Engineering, RWTH Aachen University Medical School, 52074 Aachen, Computational RNA Biology Lab and Bioinformatics Core, Max Planck Institute for Biology of Ageing, 50931 Cologne, Department of Cell Biology, Institute for Biomedical Engineering, RWTH Aachen University Medical School, 52074, Helmholtz Institute for Biomedical Engineering, 52074, Aachen Institute for Advanced Study in Computational Engineering Science (AICES), RWTH Aachen University, 52062 Aachen, Germany and Center of Informatics, Federal University of Pernambuco, 50740560 Recife-PE, Brazil IZKF Computational Biology Research Group, Institute for Biomedical Engineering, RWTH Aachen University Medical School, 52074 Aachen, Computational RNA Biology Lab and Bioinformatics Core, Max Planck Institute for Biology of Ageing, 50931 Cologne, Department of Cell Biology, Institute for Biomedical Engineering, RWTH Aachen University Medical School, 52074, Helmholtz Institute for Biomedical Engineering, 52074, Aachen Institute for Advanced Study in Computational Engineering Science (AICES), RWTH Aachen University, 52062 Aachen, Germany and Center of Informatics, Federal University of Pernambuco, 50740560 Recife-PE, Brazil.', 'Brazil|Brazil|Brazil|Brazil', 32, 'Binding Sites|Chromatin Immunoprecipitation|Deoxyribonuclease I|Genomics|Histones|Humans|K562 Cells|Markov Chains|Protein Footprinting|Regulatory Elements, Transcriptional|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btu519', '25086003', 'The identification of active transcriptional regulatory elements is crucial to understand regulatory networks driving cellular processes such as cell development and the onset of diseases. It has recently been shown that chromatin structure information, such as DNase I hypersensitivity (DHS) or histone modifications, significantly improves cell-specific predictions of transcription factor binding sites. However, no method has so far successfully combined both DHS and histone modification data to perform active binding site prediction.'),
(78589, 2014, 'bio', 'Bias correction for selecting the minimal-error classifier from many machine learning models', 'Ding, Ying|Tang, Shaowu|Liao, Serena G|Jia, Jia|Oesterreich, Steffi|Lin, Yan|Tseng, George C', 'Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA and Magee-Womens Research Institute, Pittsburgh, PA 15213, USA Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA and Magee-Womens Research Institute, Pittsburgh, PA 15213, USA.|Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA and Magee-Womens Research Institute, Pittsburgh, PA 15213, USA.|Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA and Magee-Womens Research Institute, Pittsburgh, PA 15213, USA.|Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA and Magee-Womens Research Institute, Pittsburgh, PA 15213, USA.|Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA and Magee-Womens Research Institute, Pittsburgh, PA 15213, USA.|Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA and Magee-Womens Research Institute, Pittsburgh, PA 15213, USA.|Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA and Magee-Womens Research Institute, Pittsburgh, PA 15213, USA Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA and Magee-Womens Research Institute, Pittsburgh, PA 15213, USA.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Artificial Intelligence|Breast Neoplasms|Data Interpretation, Statistical|Female|Gene Expression Profiling|Genomics|Humans|Models, Theoretical|Sample Size', 'Journal Article', '10.1093/bioinformatics/btu520', '25086004', 'Supervised machine learning is commonly applied in genomic research to construct a classifier from the training data that is generalizable to predict independent testing data. When test datasets are not available, cross-validation is commonly used to estimate the error rate. Many machine learning methods are available, and it is well known that no universally best method exists in general. It has been a common practice to apply many machine learning methods and report the method that produces the smallest cross-validation error rate. Theoretically, such a procedure produces a selection bias. Consequently, many clinical studies with moderate sample sizes (e.g. n = 30-60) risk reporting a falsely small cross-validation error rate that could not be validated later in independent cohorts.'),
(78590, 2014, 'bio', 'APPEX: analysis platform for the identification of prognostic gene expression signatures in cancer', 'Kim, Seon-Kyu|Hwan Kim, Jong|Yun, Seok-Joong|Kim, Wun-Jae|Kim, Seon-Young', 'Medical Genomics Research Center, Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Department of Functional Genomics, University of Science and Technology, Daejeon 305-806, Korea and Department of Urology, Chungbuk National University College of Medicine, Cheongju 360-100, Korea Medical Genomics Research Center, Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Department of Functional Genomics, University of Science and Technology, Daejeon 305-806, Korea and Department of Urology, Chungbuk National University College of Medicine, Cheongju 360-100, Korea.|Medical Genomics Research Center, Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Department of Functional Genomics, University of Science and Technology, Daejeon 305-806, Korea and Department of Urology, Chungbuk National University College of Medicine, Cheongju 360-100, Korea Medical Genomics Research Center, Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Department of Functional Genomics, University of Science and Technology, Daejeon 305-806, Korea and Department of Urology, Chungbuk National University College of Medicine, Cheongju 360-100, Korea.|Medical Genomics Research Center, Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Department of Functional Genomics, University of Science and Technology, Daejeon 305-806, Korea and Department of Urology, Chungbuk National University College of Medicine, Cheongju 360-100, Korea.|Medical Genomics Research Center, Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Department of Functional Genomics, University of Science and Technology, Daejeon 305-806, Korea and Department of Urology, Chungbuk National University College of Medicine, Cheongju 360-100, Korea.|Medical Genomics Research Center, Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Department of Functional Genomics, University of Science and Technology, Daejeon 305-806, Korea and Department of Urology, Chungbuk National University College of Medicine, Cheongju 360-100, Korea Medical Genomics Research Center, Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Department of Functional Genomics, University of Science and Technology, Daejeon 305-806, Korea and Department of Urology, Chungbuk National University College of Medicine, Cheongju 360-100, Korea.', '-|-|-|-|-', 7, 'Disease Progression|Gene Expression Profiling|Genomics|Humans|Internet|Neoplasm Recurrence, Local|Neoplasms|Prognosis|Software|Survival Analysis|Urinary Bladder Neoplasms', 'Journal Article', '10.1093/bioinformatics/btu521', '25091586', 'Because cancer has heterogeneous clinical behaviors due to the progressive accumulation of multiple genetic and epigenetic alterations, the identification of robust molecular signatures for predicting cancer outcome is profoundly important. Here, we introduce the APPEX Web-based analysis platform as a versatile tool for identifying prognostic molecular signatures that predict cancer diversity. We incorporated most of statistical methods for survival analysis and implemented seven survival analysis workflows, including CoxSingle, CoxMulti, IntransSingle, IntransMulti, SuperPC, TimeRoc and multivariate. A total of 236 publicly available datasets were collected, processed and stored to support easy independent validation of prognostic signatures. Two case studies including disease recurrence and bladder cancer progression were described using different combinations of the seven workflows.'),
(78591, 2014, 'bio', 'Tracking global changes induced in the CD4 T-cell receptor repertoire by immunization with a complex antigen using short stretches of CDR3 protein sequence', 'Thomas, Niclas|Best, Katharine|Cinelli, Mattia|Reich-Zeliger, Shlomit|Gal, Hilah|Shifrut, Eric|Madi, Asaf|Friedman, Nir|Shawe-Taylor, John|Chain, Benny', 'UCL CoMPLEX, UCL Division of Infection and Immunity, London WC1 6BT, UK, Weizmann Institute of Science, Rehovot 76000, Israel and UCL Computer Science, London WC1E 6BT, UK.|UCL CoMPLEX, UCL Division of Infection and Immunity, London WC1 6BT, UK, Weizmann Institute of Science, Rehovot 76000, Israel and UCL Computer Science, London WC1E 6BT, UK.|UCL CoMPLEX, UCL Division of Infection and Immunity, London WC1 6BT, UK, Weizmann Institute of Science, Rehovot 76000, Israel and UCL Computer Science, London WC1E 6BT, UK.|UCL CoMPLEX, UCL Division of Infection and Immunity, London WC1 6BT, UK, Weizmann Institute of Science, Rehovot 76000, Israel and UCL Computer Science, London WC1E 6BT, UK.|UCL CoMPLEX, UCL Division of Infection and Immunity, London WC1 6BT, UK, Weizmann Institute of Science, Rehovot 76000, Israel and UCL Computer Science, London WC1E 6BT, UK.|UCL CoMPLEX, UCL Division of Infection and Immunity, London WC1 6BT, UK, Weizmann Institute of Science, Rehovot 76000, Israel and UCL Computer Science, London WC1E 6BT, UK.|UCL CoMPLEX, UCL Division of Infection and Immunity, London WC1 6BT, UK, Weizmann Institute of Science, Rehovot 76000, Israel and UCL Computer Science, London WC1E 6BT, UK.|UCL CoMPLEX, UCL Division of Infection and Immunity, London WC1 6BT, UK, Weizmann Institute of Science, Rehovot 76000, Israel and UCL Computer Science, London WC1E 6BT, UK.|UCL CoMPLEX, UCL Division of Infection and Immunity, London WC1 6BT, UK, Weizmann Institute of Science, Rehovot 76000, Israel and UCL Computer Science, London WC1E 6BT, UK.|UCL CoMPLEX, UCL Division of Infection and Immunity, London WC1 6BT, UK, Weizmann Institute of Science, Rehovot 76000, Israel and UCL Computer Science, London WC1E 6BT, UK.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel', 38, 'Amino Acid Sequence|Animals|CD4-Positive T-Lymphocytes|Cluster Analysis|Complementarity Determining Regions|Immunization|Mice|Mycobacterium tuberculosis|Receptors, Antigen, T-Cell|Receptors, Antigen, T-Cell, alpha-beta|Sequence Analysis, Protein|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btu523', '25095879', 'The clonal theory of adaptive immunity proposes that immunological responses are encoded by increases in the frequency of lymphocytes carrying antigen-specific receptors. In this study, we measure the frequency of different T-cell receptors (TcR) in CD4 + T cell populations of mice immunized with a complex antigen, killed Mycobacterium tuberculosis, using high throughput parallel sequencing of the TcRxcexb2 chain. Our initial hypothesis that immunization would induce repertoire convergence proved to be incorrect, and therefore an alternative approach was developed that allows accurate stratification of TcR repertoires and provides novel insights into the nature of CD4 + T-cell receptor recognition.'),
(78592, 2014, 'bio', 'AliView: a fast and lightweight alignment viewer and editor for large datasets', 'Larsson, Anders', 'Systematic Biology, Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Uppsala 75236, Sweden.', 'Sweden', 0, 'High-Throughput Nucleotide Sequencing|Phylogeny|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btu531', '25095880', 'AliView is an alignment viewer and editor designed to meet the requirements of next-generation sequencing era phylogenetic datasets. AliView handles alignments of unlimited size in the formats most commonly used, i.e. FASTA, Phylip, Nexus, Clustal and MSF. The intuitive graphical interface makes it easy to inspect, sort, delete, merge and realign sequences as part of the manual filtering process of large datasets. AliView also works as an easy-to-use alignment editor for small as well as large datasets.'),
(78593, 2014, 'bio', 'Thresher: an improved algorithm for peak height thresholding of microbial community profiles', 'Starke, Verena|Steele, Andrew', 'Carnegie Institution of Washington, Geophysical Laboratory, Washington DC 20015, USA.|Carnegie Institution of Washington, Geophysical Laboratory, Washington DC 20015, USA.', 'United States|United States', 0, 'Algorithms|DNA, Ribosomal Spacer|Environmental Microbiology|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu528', '25095881', 'This article presents Thresher, an improved technique for finding peak height thresholds for automated rRNA intergenic spacer analysis (ARISA) profiles. We argue that thresholds must be sample dependent, taking community richness into account. In most previous fragment analyses, a common threshold is applied to all samples simultaneously, ignoring richness variations among samples and thereby compromising cross-sample comparison. Our technique solves this problem, and at the same time provides a robust method for outlier rejection, selecting for removal any replicate pairs that are not valid replicates.'),
(78594, 2014, 'bio', 'DNAApp: a mobile application for sequencing data analysis', 'Nguyen, Phi-Vu|Verma, Chandra Shekhar|Gan, Samuel Ken-En', 'Bioinformatics Institute, Agency for Science, Technology, and Research (A*STAR), Singapore 138671, Department of Biological Sciences, National University of Singapore (NUS), Singapore 119077, School of Biological Sciences, Nanyang Technological University (NTU), Singapore 639798 and p53 Laboratory, Agency for Science, Technology, and Research (A*STAR), Singapore 138648, Republic of Singapore.|Bioinformatics Institute, Agency for Science, Technology, and Research (A*STAR), Singapore 138671, Department of Biological Sciences, National University of Singapore (NUS), Singapore 119077, School of Biological Sciences, Nanyang Technological University (NTU), Singapore 639798 and p53 Laboratory, Agency for Science, Technology, and Research (A*STAR), Singapore 138648, Republic of Singapore Bioinformatics Institute, Agency for Science, Technology, and Research (A*STAR), Singapore 138671, Department of Biological Sciences, National University of Singapore (NUS), Singapore 119077, School of Biological Sciences, Nanyang Technological University (NTU), Singapore 639798 and p53 Laboratory, Agency for Science, Technology, and Research (A*STAR), Singapore 138648, Republic of Singapore Bioinformatics Institute, Agency for Science, Technology, and Research (A*STAR), Singapore 138671, Department of Biological Sciences, National University of Singapore (NUS), Singapore 119077, School of Biological Sciences, Nanyang Technological University (NTU), Singapore 639798 and p53 Laboratory, Agency for Science, Technology, and Research (A*STAR), Singapore 138648, Republic of Singapore.|Bioinformatics Institute, Agency for Science, Technology, and Research (A*STAR), Singapore 138671, Department of Biological Sciences, National University of Singapore (NUS), Singapore 119077, School of Biological Sciences, Nanyang Technological University (NTU), Singapore 639798 and p53 Laboratory, Agency for Science, Technology, and Research (A*STAR), Singapore 138648, Republic of Singapore Bioinformatics Institute, Agency for Science, Technology, and Research (A*STAR), Singapore 138671, Department of Biological Sciences, National University of Singapore (NUS), Singapore 119077, School of Biological Sciences, Nanyang Technological University (NTU), Singapore 639798 and p53 Laboratory, Agency for Science, Technology, and Research (A*STAR), Singapore 138648, Republic of Singapore.', 'Singapore|Singapore|Singapore', 0, 'Humans|Internet|Mobile Applications|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu525', '25095882', 'There have been numerous applications developed for decoding and visualization of ab1 DNA sequencing files for Windows and MAC platforms, yet none exists for the increasingly popular smartphone operating systems. The ability to decode sequencing files cannot easily be carried out using browser accessed Web tools. To overcome this hurdle, we have developed a new native app called DNAApp that can decode and display ab1 sequencing file on Android and iOS. In addition to in-built analysis tools such as reverse complementation, protein translation and searching for specific sequences, we have incorporated convenient functions that would facilitate the harnessing of online Web tools for a full range of analysis. Given the high usage of Android/iOS tablets and smartphones, such bioinformatics apps would raise productivity and facilitate the high demand for analyzing sequencing data in biomedical research.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78595, 2014, 'bio', 'BioTextQuest(+): a knowledge integration platform for literature mining and concept discovery', 'Papanikolaou, Nikolas|Pavlopoulos, Georgios A|Pafilis, Evangelos|Theodosiou, Theodosios|Schneider, Reinhard|Satagopam, Venkata P|Ouzounis, Christos A|Eliopoulos, Aristides G|Promponas, Vasilis J|Iliopoulos, Ioannis', 'Division of Basic Sciences, University of Crete, Medical School, Heraklion 71110, Greece, Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Heraklion, Greece, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval, 7, avenue des Hauts-Fourneaux, L-4362 Esch sur Alzette, Luxembourg, Biological Computation & Process Laboratory (BCPL), Chemical Process & Energy Resources Institute (CPERI), Centre for Research & Technology Hellas (CERTH), PO Box 361, GR-57001 Thessalonica, Greece, Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, 70013 Heraklion, Crete, Greece and Department of Biological Sciences, Bioinformatics Research Laboratory, University of Cyprus, PO Box 20537, CY 1678, Nicosia, Cyprus.|Division of Basic Sciences, University of Crete, Medical School, Heraklion 71110, Greece, Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Heraklion, Greece, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval, 7, avenue des Hauts-Fourneaux, L-4362 Esch sur Alzette, Luxembourg, Biological Computation & Process Laboratory (BCPL), Chemical Process & Energy Resources Institute (CPERI), Centre for Research & Technology Hellas (CERTH), PO Box 361, GR-57001 Thessalonica, Greece, Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, 70013 Heraklion, Crete, Greece and Department of Biological Sciences, Bioinformatics Research Laboratory, University of Cyprus, PO Box 20537, CY 1678, Nicosia, Cyprus.|Division of Basic Sciences, University of Crete, Medical School, Heraklion 71110, Greece, Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Heraklion, Greece, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval, 7, avenue des Hauts-Fourneaux, L-4362 Esch sur Alzette, Luxembourg, Biological Computation & Process Laboratory (BCPL), Chemical Process & Energy Resources Institute (CPERI), Centre for Research & Technology Hellas (CERTH), PO Box 361, GR-57001 Thessalonica, Greece, Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, 70013 Heraklion, Crete, Greece and Department of Biological Sciences, Bioinformatics Research Laboratory, University of Cyprus, PO Box 20537, CY 1678, Nicosia, Cyprus.|Division of Basic Sciences, University of Crete, Medical School, Heraklion 71110, Greece, Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Heraklion, Greece, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval, 7, avenue des Hauts-Fourneaux, L-4362 Esch sur Alzette, Luxembourg, Biological Computation & Process Laboratory (BCPL), Chemical Process & Energy Resources Institute (CPERI), Centre for Research & Technology Hellas (CERTH), PO Box 361, GR-57001 Thessalonica, Greece, Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, 70013 Heraklion, Crete, Greece and Department of Biological Sciences, Bioinformatics Research Laboratory, University of Cyprus, PO Box 20537, CY 1678, Nicosia, Cyprus.|Division of Basic Sciences, University of Crete, Medical School, Heraklion 71110, Greece, Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Heraklion, Greece, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval, 7, avenue des Hauts-Fourneaux, L-4362 Esch sur Alzette, Luxembourg, Biological Computation & Process Laboratory (BCPL), Chemical Process & Energy Resources Institute (CPERI), Centre for Research & Technology Hellas (CERTH), PO Box 361, GR-57001 Thessalonica, Greece, Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, 70013 Heraklion, Crete, Greece and Department of Biological Sciences, Bioinformatics Research Laboratory, University of Cyprus, PO Box 20537, CY 1678, Nicosia, Cyprus.|Division of Basic Sciences, University of Crete, Medical School, Heraklion 71110, Greece, Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Heraklion, Greece, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval, 7, avenue des Hauts-Fourneaux, L-4362 Esch sur Alzette, Luxembourg, Biological Computation & Process Laboratory (BCPL), Chemical Process & Energy Resources Institute (CPERI), Centre for Research & Technology Hellas (CERTH), PO Box 361, GR-57001 Thessalonica, Greece, Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, 70013 Heraklion, Crete, Greece and Department of Biological Sciences, Bioinformatics Research Laboratory, University of Cyprus, PO Box 20537, CY 1678, Nicosia, Cyprus.|Division of Basic Sciences, University of Crete, Medical School, Heraklion 71110, Greece, Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Heraklion, Greece, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval, 7, avenue des Hauts-Fourneaux, L-4362 Esch sur Alzette, Luxembourg, Biological Computation & Process Laboratory (BCPL), Chemical Process & Energy Resources Institute (CPERI), Centre for Research & Technology Hellas (CERTH), PO Box 361, GR-57001 Thessalonica, Greece, Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, 70013 Heraklion, Crete, Greece and Department of Biological Sciences, Bioinformatics Research Laboratory, University of Cyprus, PO Box 20537, CY 1678, Nicosia, Cyprus Division of Basic Sciences, University of Crete, Medical School, Heraklion 71110, Greece, Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Heraklion, Greece, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval, 7, avenue des Hauts-Fourneaux, L-4362 Esch sur Alzette, Luxembourg, Biological Computation & Process Laboratory (BCPL), Chemical Process & Energy Resources Institute (CPERI), Centre for Research & Technology Hellas (CERTH), PO Box 361, GR-57001 Thessalonica, Greece, Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, 70013 Heraklion, Crete, Greece and Department of Biological Sciences, Bioinformatics Research Laboratory, University of Cyprus, PO Box 20537, CY 1678, Nicosia, Cyprus.|Division of Basic Sciences, University of Crete, Medical School, Heraklion 71110, Greece, Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Heraklion, Greece, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval, 7, avenue des Hauts-Fourneaux, L-4362 Esch sur Alzette, Luxembourg, Biological Computation & Process Laboratory (BCPL), Chemical Process & Energy Resources Institute (CPERI), Centre for Research & Technology Hellas (CERTH), PO Box 361, GR-57001 Thessalonica, Greece, Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, 70013 Heraklion, Crete, Greece and Department of Biological Sciences, Bioinformatics Research Laboratory, University of Cyprus, PO Box 20537, CY 1678, Nicosia, Cyprus Division of Basic Sciences, University of Crete, Medical School, Heraklion 71110, Greece, Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Heraklion, Greece, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval, 7, avenue des Hauts-Fourneaux, L-4362 Esch sur Alzette, Luxembourg, Biological Computation & Process Laboratory (BCPL), Chemical Process & Energy Resources Institute (CPERI), Centre for Research & Technology Hellas (CERTH), PO Box 361, GR-57001 Thessalonica, Greece, Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, 70013 Heraklion, Crete, Greece and Department of Biological Sciences, Bioinformatics Research Laboratory, University of Cyprus, PO Box 20537, CY 1678, Nicosia, Cyprus.|Division of Basic Sciences, University of Crete, Medical School, Heraklion 71110, Greece, Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Heraklion, Greece, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval, 7, avenue des Hauts-Fourneaux, L-4362 Esch sur Alzette, Luxembourg, Biological Computation & Process Laboratory (BCPL), Chemical Process & Energy Resources Institute (CPERI), Centre for Research & Technology Hellas (CERTH), PO Box 361, GR-57001 Thessalonica, Greece, Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, 70013 Heraklion, Crete, Greece and Department of Biological Sciences, Bioinformatics Research Laboratory, University of Cyprus, PO Box 20537, CY 1678, Nicosia, Cyprus.|Division of Basic Sciences, University of Crete, Medical School, Heraklion 71110, Greece, Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Heraklion, Greece, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval, 7, avenue des Hauts-Fourneaux, L-4362 Esch sur Alzette, Luxembourg, Biological Computation & Process Laboratory (BCPL), Chemical Process & Energy Resources Institute (CPERI), Centre for Research & Technology Hellas (CERTH), PO Box 361, GR-57001 Thessalonica, Greece, Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, 70013 Heraklion, Crete, Greece and Department of Biological Sciences, Bioinformatics Research Laboratory, University of Cyprus, PO Box 20537, CY 1678, Nicosia, Cyprus.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 12, 'Authorship|Cluster Analysis|Data Mining|Disease|Genes|Humans|Internet|Medical Subject Headings|Proteins|PubMed|Publications|Software', 'Journal Article', '10.1093/bioinformatics/btu524', '25100685', 'The iterative process of finding relevant information in biomedical literature and performing bioinformatics analyses might result in an endless loop for an inexperienced user, considering the exponential growth of scientific corpora and the plethora of tools designed to mine PubMed(®) and related biological databases. Herein, we describe BioTextQuest(+), a web-based interactive knowledge exploration platform with significant advances to its predecessor (BioTextQuest), aiming to bridge processes such as bioentity recognition, functional annotation, document clustering and data integration towards literature mining and concept discovery. BioTextQuest(+) enables PubMed and OMIM querying, retrieval of abstracts related to a targeted request and optimal detection of genes, proteins, molecular functions, pathways and biological processes within the retrieved documents. The front-end interface facilitates the browsing of document clustering per subject, the analysis of term co-occurrence, the generation of tag clouds containing highly represented terms per cluster and at-a-glance popup windows with information about relevant genes and proteins. Moreover, to support experimental research, BioTextQuest(+) addresses integration of its primary functionality with biological repositories and software tools able to deliver further bioinformatics services. The Google-like interface extends beyond simple use by offering a range of advanced parameterization for expert users. We demonstrate the functionality of BioTextQuest(+) through several exemplary research scenarios including author disambiguation, functional term enrichment, knowledge acquisition and concept discovery linking major human diseases, such as obesity and ageing.'),
(78596, 2014, 'bio', 'MEGADOCK 40: an ultra-high-performance protein-protein docking software for heterogeneous supercomputers', 'Ohue, Masahito|Shimoda, Takehiro|Suzuki, Shuji|Matsuzaki, Yuri|Ishida, Takashi|Akiyama, Yutaka', 'Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 W8-76, Ookayama, Meguro-ku, Tokyo 152-8550, Japan, Japan Society for the Promotion of Science (JSPS) and Education Academy of Computational Life Sciences (ACLS), Tokyo Institute of Technology, 2-12-1 W8-93, Ookayama, Meguro-ku, Tokyo 152-8550, Japan Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 W8-76, Ookayama, Meguro-ku, Tokyo 152-8550, Japan, Japan Society for the Promotion of Science (JSPS) and Education Academy of Computational Life Sciences (ACLS), Tokyo Institute of Technology, 2-12-1 W8-93, Ookayama, Meguro-ku, Tokyo 152-8550, Japan.|Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 W8-76, Ookayama, Meguro-ku, Tokyo 152-8550, Japan, Japan Society for the Promotion of Science (JSPS) and Education Academy of Computational Life Sciences (ACLS), Tokyo Institute of Technology, 2-12-1 W8-93, Ookayama, Meguro-ku, Tokyo 152-8550, Japan Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 W8-76, Ookayama, Meguro-ku, Tokyo 152-8550, Japan, Japan Society for the Promotion of Science (JSPS) and Education Academy of Computational Life Sciences (ACLS), Tokyo Institute of Technology, 2-12-1 W8-93, Ookayama, Meguro-ku, Tokyo 152-8550, Japan.|Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 W8-76, Ookayama, Meguro-ku, Tokyo 152-8550, Japan, Japan Society for the Promotion of Science (JSPS) and Education Academy of Computational Life Sciences (ACLS), Tokyo Institute of Technology, 2-12-1 W8-93, Ookayama, Meguro-ku, Tokyo 152-8550, Japan Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 W8-76, Ookayama, Meguro-ku, Tokyo 152-8550, Japan, Japan Society for the Promotion of Science (JSPS) and Education Academy of Computational Life Sciences (ACLS), Tokyo Institute of Technology, 2-12-1 W8-93, Ookayama, Meguro-ku, Tokyo 152-8550, Japan Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 W8-76, Ookayama, Meguro-ku, Tokyo 152-8550, Japan, Japan Society for the Promotion of Science (JSPS) and Education Academy of Computational Life Sciences (ACLS), Tokyo Institute of Technology, 2-12-1 W8-93, Ookayama, Meguro-ku, Tokyo 152-8550, Japan.|Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 W8-76, Ookayama, Meguro-ku, Tokyo 152-8550, Japan, Japan Society for the Promotion of Science (JSPS) and Education Academy of Computational Life Sciences (ACLS), Tokyo Institute of Technology, 2-12-1 W8-93, Ookayama, Meguro-ku, Tokyo 152-8550, Japan.|Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 W8-76, Ookayama, Meguro-ku, Tokyo 152-8550, Japan, Japan Society for the Promotion of Science (JSPS) and Education Academy of Computational Life Sciences (ACLS), Tokyo Institute of Technology, 2-12-1 W8-93, Ookayama, Meguro-ku, Tokyo 152-8550, Japan.|Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 W8-76, Ookayama, Meguro-ku, Tokyo 152-8550, Japan, Japan Society for the Promotion of Science (JSPS) and Education Academy of Computational Life Sciences (ACLS), Tokyo Institute of Technology, 2-12-1 W8-93, Ookayama, Meguro-ku, Tokyo 152-8550, Japan Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 W8-76, Ookayama, Meguro-ku, Tokyo 152-8550, Japan, Japan Society for the Promotion of Science (JSPS) and Education Academy of Computational Life Sciences (ACLS), Tokyo Institute of Technology, 2-12-1 W8-93, Ookayama, Meguro-ku, Tokyo 152-8550, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan', 32, 'Computers|Molecular Docking Simulation|Protein Interaction Mapping|Software', 'Journal Article', '10.1093/bioinformatics/btu532', '25100686', 'The application of protein-protein docking in large-scale interactome analysis is a major challenge in structural bioinformatics and requires huge computing resources. In this work, we present MEGADOCK 4.0, an FFT-based docking software that makes extensive use of recent heterogeneous supercomputers and shows powerful, scalable performance of >97% strong scaling.'),
(78597, 2014, 'bio', 'Estimating biological elementary flux modes that decompose a flux distribution by the minimal branching property', 'Chan, Siu Hung Joshua|Solem, Christian|Jensen, Peter Ruhdal|Ji, Ping', 'Systems Biotechnology and Biorefining, National Food Institute, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark and Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong.|Systems Biotechnology and Biorefining, National Food Institute, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark and Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong.|Systems Biotechnology and Biorefining, National Food Institute, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark and Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong.|Systems Biotechnology and Biorefining, National Food Institute, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark and Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong.', 'Denmark|Denmark|Denmark|Denmark', 3, 'Acetates|Animals|Escherichia coli|Glyoxylates|Lactococcus lactis|Metabolic Flux Analysis|Metabolic Networks and Pathways|Mice|Myocardium', 'Journal Article', '10.1093/bioinformatics/btu529', '25100687', 'Elementary flux mode (EFM) is a useful tool in constraint-based modeling of metabolic networks. The property that every flux distribution can be decomposed as a weighted sum of EFMs allows certain applications of EFMs to studying flux distributions. The existence of biologically infeasible EFMs and the non-uniqueness of the decomposition, however, undermine the applicability of such methods. Efforts have been made to find biologically feasible EFMs by incorporating information from transcriptional regulation and thermodynamics. Yet, no attempt has been made to distinguish biologically feasible EFMs by considering their graphical properties. A previous study on the transcriptional regulation of metabolic genes found that distinct branches at a branch point metabolite usually belong to distinct metabolic pathways. This suggests an intuitive property of biologically feasible EFMs, i.e. minimal branching.'),
(78598, 2014, 'bio', 'Drug/Cell-line Browser: interactive canvas visualization of cancer drug/cell-line viability assay datasets', 'Duan, Qiaonan|Wang, Zichen|Fernandez, Nicolas F|Rouillard, Andrew D|Tan, Christopher M|Benes, Cyril H|Maayan, Avi', 'Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York, Icahn School of Medicine at Mount Sinai, New York, NY 10029 and Center for Cancer Research, Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York, Icahn School of Medicine at Mount Sinai, New York, NY 10029 and Center for Cancer Research, Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York, Icahn School of Medicine at Mount Sinai, New York, NY 10029 and Center for Cancer Research, Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York, Icahn School of Medicine at Mount Sinai, New York, NY 10029 and Center for Cancer Research, Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York, Icahn School of Medicine at Mount Sinai, New York, NY 10029 and Center for Cancer Research, Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York, Icahn School of Medicine at Mount Sinai, New York, NY 10029 and Center for Cancer Research, Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York, Icahn School of Medicine at Mount Sinai, New York, NY 10029 and Center for Cancer Research, Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129, USA.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Antineoplastic Agents|Cell Line, Tumor|Cell Survival|Cluster Analysis|Computer Graphics|Drug Screening Assays, Antitumor|Humans|Internet|Software', 'Journal Article', '10.1093/bioinformatics/btu526', '25100688', 'Recently, several high profile studies collected cell viability data from panels of cancer cell lines treated with many drugs applied at different concentrations. Such drug sensitivity data for cancer cell lines provide suggestive treatments for different types and subtypes of cancer. Visualization of these datasets can reveal patterns that may not be obvious by examining the data without such efforts. Here we introduce Drug/Cell-line Browser (DCB), an online interactive HTML5 data visualization tool for interacting with three of the recently published datasets of cancer cell lines/drug-viability studies. DCB uses clustering and canvas visualization of the drugs and the cell lines, as well as a bar graph that summarizes drug effectiveness for the tissue of origin or the cancer subtypes for single or multiple drugs. DCB can help in understanding drug response patterns and prioritizing drug/cancer cell line interactions by tissue of origin or cancer subtype.'),
(78599, 2014, 'bio', 'A method for de novo nucleic acid diagnostic target discovery', 'Zhang, Yeting|Sun, Yazhou', 'Department of Biology, Pennsylvania State University, University Park, PA 16802, Department of Research, Synblex LLC, 200 Innovation Blvd. State College, PA 16801 and New Jersey Center for Science, Technology & Mathematics, Kean University, Union, NJ 07083, USA Department of Biology, Pennsylvania State University, University Park, PA 16802, Department of Research, Synblex LLC, 200 Innovation Blvd. State College, PA 16801 and New Jersey Center for Science, Technology & Mathematics, Kean University, Union, NJ 07083, USA.|Department of Biology, Pennsylvania State University, University Park, PA 16802, Department of Research, Synblex LLC, 200 Innovation Blvd. State College, PA 16801 and New Jersey Center for Science, Technology & Mathematics, Kean University, Union, NJ 07083, USA Department of Biology, Pennsylvania State University, University Park, PA 16802, Department of Research, Synblex LLC, 200 Innovation Blvd. State College, PA 16801 and New Jersey Center for Science, Technology & Mathematics, Kean University, Union, NJ 07083, USA.', 'Jersey|Jersey', 3, 'Algorithms|Base Sequence|Conserved Sequence|DNA Primers|DNA, Bacterial|Genome, Bacterial|Genomics|Molecular Diagnostic Techniques|Polymerase Chain Reaction|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu515', '25104813', 'A proper target or marker is essential in any diagnosis (e.g. an infection or cancer). An ideal diagnostic target should be both conserved in and unique to the pathogen. Currently, these targets can only be identified manually, which is time-consuming and usually error-prone. Because of the increasingly frequent occurrences of emerging epidemics and multidrug-resistant superbugs, a rapid diagnostic target identification process is needed.'),
(78600, 2014, 'bio', 'Quartet inference from SNP data under the coalescent model', 'Chifman, Julia|Kubatko, Laura', 'Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC 27157, Department of Statistics, The Ohio State University, Columbus, OH 43210 and Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH 43210, USA.|Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC 27157, Department of Statistics, The Ohio State University, Columbus, OH 43210 and Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH 43210, USA Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC 27157, Department of Statistics, The Ohio State University, Columbus, OH 43210 and Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH 43210, USA.', 'United States|United States', 336, 'Algorithms|Animals|Bayes Theorem|Crotalus|Markov Chains|Models, Statistical|Monte Carlo Method|Phylogeny|Polymorphism, Single Nucleotide|Software|Soybeans', 'Journal Article', '10.1093/bioinformatics/btu530', '25104814', 'Increasing attention has been devoted to estimation of species-level phylogenetic relationships under the coalescent model. However, existing methods either use summary statistics (gene trees) to carry out estimation, ignoring an important source of variability in the estimates, or involve computationally intensive Bayesian Markov chain Monte Carlo algorithms that do not scale well to whole-genome datasets.'),
(78601, 2014, 'bio', 'Fast construction of FM-index for long sequence reads', 'Li, Heng', 'Medical Population Genetics Program, Broad Institute, 75 Ames Street, Cambridge, MA 02142, USA.', 'United States', 27, 'Algorithms|Genomics|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu541', '25107872', 'We present a new method to incrementally construct the FM-index for both short and long sequence reads, up to the size of a genome. It is the first algorithm that can build the index while implicitly sorting the sequences in the reverse (complement) lexicographical order without a separate sorting step. The implementation is among the fastest for indexing short reads and the only one that practically works for reads of averaged kilobases in length.'),
(78602, 2014, 'bio', 'Modeling genome coverage in single-cell sequencing', 'Daley, Timothy|Smith, Andrew D', 'Department of Mathematics and Department of Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.|Department of Mathematics and Department of Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.', 'United States|United States', 17, 'Bayes Theorem|Gene Library|Genetic Variation|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Models, Genetic|Sequence Analysis, DNA|Single-Cell Analysis', 'Journal Article', '10.1093/bioinformatics/btu540', '25107873', 'Single-cell DNA sequencing is necessary for examining genetic variation at the cellular level, which remains hidden in bulk sequencing experiments. But because they begin with such small amounts of starting material, the amount of information that is obtained from single-cell sequencing experiment is highly sensitive to the choice of protocol employed and variability in library preparation. In particular, the fraction of the genome represented in single-cell sequencing libraries exhibits extreme variability due to quantitative biases in amplification and loss of genetic material.'),
(78603, 2014, 'bio', 'Modeling dynamic functional relationship networks and application to ex vivo human erythroid differentiation', 'Zhu, Fan|Shi, Lihong|Li, Hongdong|Eksi, Ridvan|Engel, James Douglas|Guan, Yuanfang', 'Department of Computational Medicine and Bioinformatics, Department of Cell and Developmental Biology, Department of Internal Medicine and Department of Computer Science and Engineering, University of Michigan, MI48109, USA.|Department of Computational Medicine and Bioinformatics, Department of Cell and Developmental Biology, Department of Internal Medicine and Department of Computer Science and Engineering, University of Michigan, MI48109, USA.|Department of Computational Medicine and Bioinformatics, Department of Cell and Developmental Biology, Department of Internal Medicine and Department of Computer Science and Engineering, University of Michigan, MI48109, USA.|Department of Computational Medicine and Bioinformatics, Department of Cell and Developmental Biology, Department of Internal Medicine and Department of Computer Science and Engineering, University of Michigan, MI48109, USA.|Department of Computational Medicine and Bioinformatics, Department of Cell and Developmental Biology, Department of Internal Medicine and Department of Computer Science and Engineering, University of Michigan, MI48109, USA.|Department of Computational Medicine and Bioinformatics, Department of Cell and Developmental Biology, Department of Internal Medicine and Department of Computer Science and Engineering, University of Michigan, MI48109, USA Department of Computational Medicine and Bioinformatics, Department of Cell and Developmental Biology, Department of Internal Medicine and Department of Computer Science and Engineering, University of Michigan, MI48109, USA Department of Computational Medicine and Bioinformatics, Department of Cell and Developmental Biology, Department of Internal Medicine and Department of Computer Science and Engineering, University of Michigan, MI48109, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Erythropoiesis|Gene Regulatory Networks|Humans|Models, Genetic|Sequence Analysis, RNA|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btu542', '25115705', 'Functional relationship networks, which summarize the probability of co-functionality between any two genes in the genome, could complement the reductionist focus of modern biology for understanding diverse biological processes in an organism. One major limitation of the current networks is that they are static, while one might expect functional relationships to consistently reprogram during the differentiation of a cell lineage. To address this potential limitation, we developed a novel algorithm that leverages both differentiation stage-specific expression data and large-scale heterogeneous functional genomic data to model such dynamic changes. We then applied this algorithm to the time-course RNA-Seq data we collected for ex vivo human erythroid cell differentiation.'),
(78604, 2014, 'bio', 'Figmop: a profile HMM to identify genes and bypass troublesome gene models in draft genomes', 'Curran, David M|Gilleard, John S|Wasmuth, James D', 'Department of Ecosystem and Public Health and Department of Comparative Biology and Experimental Medicine, Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, T2N 4Z6, Canada Department of Ecosystem and Public Health and Department of Comparative Biology and Experimental Medicine, Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, T2N 4Z6, Canada.|Department of Ecosystem and Public Health and Department of Comparative Biology and Experimental Medicine, Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, T2N 4Z6, Canada.|Department of Ecosystem and Public Health and Department of Comparative Biology and Experimental Medicine, Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, T2N 4Z6, Canada.', 'Canada|Canada|Canada', 4, 'Cytochrome P-450 Enzyme System|Genes|Genomics|Markov Chains|Models, Genetic|Multigene Family|Software', 'Journal Article', '10.1093/bioinformatics/btu544', '25115706', 'Gene models from draft genome assemblies of metazoan species are often incorrect, missing exons or entire genes, particularly for large gene families. Consequently, labour-intensive manual curation is often necessary. We present Figmop (Finding Genes using Motif Patterns) to help with the manual curation of gene families in draft genome assemblies. The program uses a pattern of short sequence motifs to identify putative genes directly from the genome sequence. Using a large gene family as a test case, Figmop was found to be more sensitive and specific than a BLAST-based approach. The visualization used allows the validation of potential genes to be carried out quickly and easily, saving hours if not days from an analysis.'),
(78605, 2014, 'bio', 'MindTheGap: integrated detection and assembly of short and long insertions', 'Rizk, Guillaume|Gouin, Anaïs|Chikhi, Rayan|Lemaitre, Claire', 'Inria/IRISA GenScale, Campus de Beaulieu, 35042 Rennes cedex, France, INRA, UMR 1349 Institut de Génétique, Environnement et Protection des Plantes, Domaine de la Motte - 35653 Le Rheu Cedex, France and Department of Computer Science and Engineering, Pennsylvania State University, PA, USA.|Inria/IRISA GenScale, Campus de Beaulieu, 35042 Rennes cedex, France, INRA, UMR 1349 Institut de Génétique, Environnement et Protection des Plantes, Domaine de la Motte - 35653 Le Rheu Cedex, France and Department of Computer Science and Engineering, Pennsylvania State University, PA, USA.|Inria/IRISA GenScale, Campus de Beaulieu, 35042 Rennes cedex, France, INRA, UMR 1349 Institut de Génétique, Environnement et Protection des Plantes, Domaine de la Motte - 35653 Le Rheu Cedex, France and Department of Computer Science and Engineering, Pennsylvania State University, PA, USA.|Inria/IRISA GenScale, Campus de Beaulieu, 35042 Rennes cedex, France, INRA, UMR 1349 Institut de Génétique, Environnement et Protection des Plantes, Domaine de la Motte - 35653 Le Rheu Cedex, France and Department of Computer Science and Engineering, Pennsylvania State University, PA, USA.', 'France|France|France|France', 0, 'Animals|Caenorhabditis elegans|Genome|Humans|Mutagenesis, Insertional|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu545', '25123898', 'Insertions play an important role in genome evolution. However, such variants are difficult to detect from short-read sequencing data, especially when they exceed the paired-end insert size. Many approaches have been proposed to call short insertion variants based on paired-end mapping. However, there remains a lack of practical methods to detect and assemble long variants.'),
(78606, 2014, 'bio', 'NetComm: a network analysis tool based on communicability', 'Campbell, Ian M|James, Regis A|Chen, Edward S|Shaw, Chad A', 'Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77054, USA.|Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77054, USA.|Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77054, USA.|Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77054, USA.', 'United States|United States|United States|United States', 0, 'Disease|Humans|Protein Interaction Mapping|Software', 'Journal Article', '10.1093/bioinformatics/btu536', '25123899', 'Set-based network similarity metrics are increasingly used to productively analyze genome-wide data. Conventional approaches, such as mean shortest path and clique-based metrics, have been useful but are not well suited to all applications. Computational scientists in other disciplines have developed communicability as a complementary metric. Network communicability considers all paths of all lengths between two network members. Given the success of previous network analyses of protein-protein interactions, we applied the concepts of network communicability to this problem. Here we show that our communicability implementation has advantages over traditional approaches. Overall, analyses suggest network communicability has considerable utility in analysis of large-scale biological networks.'),
(78607, 2014, 'bio', 'READemption-a tool for the computational analysis of deep-sequencing-based transcriptome data', 'Förstner, Konrad U|Vogel, Jörg|Sharma, Cynthia M', 'Institute for Molecular Infection Biology and Research Centre for Infectious Diseases (ZINF), University of Würzburg, D-97080 Würzburg, Germany Institute for Molecular Infection Biology and Research Centre for Infectious Diseases (ZINF), University of Würzburg, D-97080 Würzburg, Germany.|Institute for Molecular Infection Biology and Research Centre for Infectious Diseases (ZINF), University of Würzburg, D-97080 Würzburg, Germany.|Institute for Molecular Infection Biology and Research Centre for Infectious Diseases (ZINF), University of Würzburg, D-97080 Würzburg, Germany.', 'Germany|Germany|Germany', 66, 'Computational Biology|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu533', '25123900', 'RNA-Seq has become a potent and widely used method to qualitatively and quantitatively study transcriptomes. To draw biological conclusions based on RNA-Seq data, several steps, some of which are computationally intensive, have to be taken. Our READemption pipeline takes care of these individual tasks and integrates them into an easy-to-use tool with a command line interface. To leverage the full power of modern computers, most subcommands of READemption offer parallel data processing. While READemption was mainly developed for the analysis of bacterial primary transcriptomes, we have successfully applied it to analyze RNA-Seq reads from other sample types, including whole transcriptomes and RNA immunoprecipitated with proteins, not only from bacteria but also from eukaryotes and archaea.'),
(78608, 2014, 'bio', 'gCUP: rapid GPU-based HIV-1 co-receptor usage prediction for next-generation sequencing', 'Olejnik, Michael|Steuwer, Michel|Gorlatch, Sergei|Heider, Dominik', 'Institute of Computer Science, University of Muenster, 48149 Muenster and Department of Bioinformatics, University of Applied Sciences Weihenstephan-Triesdorf, 94315 Straubing, Germany.|Institute of Computer Science, University of Muenster, 48149 Muenster and Department of Bioinformatics, University of Applied Sciences Weihenstephan-Triesdorf, 94315 Straubing, Germany.|Institute of Computer Science, University of Muenster, 48149 Muenster and Department of Bioinformatics, University of Applied Sciences Weihenstephan-Triesdorf, 94315 Straubing, Germany.|Institute of Computer Science, University of Muenster, 48149 Muenster and Department of Bioinformatics, University of Applied Sciences Weihenstephan-Triesdorf, 94315 Straubing, Germany.', 'Germany|Germany|Germany|Germany', 0, 'HIV-1|High-Throughput Nucleotide Sequencing|Receptors, HIV|Software|Viral Tropism', 'Journal Article', '10.1093/bioinformatics/btu535', '25123901', 'Next-generation sequencing (NGS) has a large potential in HIV diagnostics, and genotypic prediction models have been developed and successfully tested in the recent years. However, albeit being highly accurate, these computational models lack computational efficiency to reach their full potential. In this study, we demonstrate the use of graphics processing units (GPUs) in combination with a computational prediction model for HIV tropism. Our new model named gCUP, parallelized and optimized for GPU, is highly accurate and can classify >175 000 sequences per second on an NVIDIA GeForce GTX 460. The computational efficiency of our new model is the next step to enable NGS technologies to reach clinical significance in HIV diagnostics. Moreover, our approach is not limited to HIV tropism prediction, but can also be easily adapted to other settings, e.g. drug resistance prediction.'),
(78609, 2014, 'bio', 'Cross-validation under separate sampling: strong bias and how to correct it', 'Braga-Neto, Ulisses M|Zollanvari, Amin|Dougherty, Edward R', 'Department of Electrical and Computer Engineering, Center for Bioinformatics and Genomic Systems Engineering and Department of Statistics, Texas A&M University, College Station, TX, 77843, USA Department of Electrical and Computer Engineering, Center for Bioinformatics and Genomic Systems Engineering and Department of Statistics, Texas A&M University, College Station, TX, 77843, USA.|Department of Electrical and Computer Engineering, Center for Bioinformatics and Genomic Systems Engineering and Department of Statistics, Texas A&M University, College Station, TX, 77843, USA Department of Electrical and Computer Engineering, Center for Bioinformatics and Genomic Systems Engineering and Department of Statistics, Texas A&M University, College Station, TX, 77843, USA.|Department of Electrical and Computer Engineering, Center for Bioinformatics and Genomic Systems Engineering and Department of Statistics, Texas A&M University, College Station, TX, 77843, USA Department of Electrical and Computer Engineering, Center for Bioinformatics and Genomic Systems Engineering and Department of Statistics, Texas A&M University, College Station, TX, 77843, USA.', 'United States|United States|United States', 19, 'Humans|Neoplasms|Oligonucleotide Array Sequence Analysis|Parkinson Disease|Probability|Selection Bias|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btu527', '25123902', 'It is commonly assumed in pattern recognition that cross-validation error estimation is almost unbiased as long as the number of folds is not too small. While this is true for random sampling, it is not true with separate sampling, where the populations are independently sampled, which is a common situation in bioinformatics.'),
(78610, 2014, 'bio', 'HapMuC: somatic mutation calling using heterozygous germ line variants near candidate mutations', 'Usuyama, Naoto|Shiraishi, Yuichi|Sato, Yusuke|Kume, Haruki|Homma, Yukio|Ogawa, Seishi|Miyano, Satoru|Imoto, Seiya', 'Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655 and Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan.|Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655 and Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan.|Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655 and Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655 and Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan.|Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655 and Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan.|Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655 and Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan.|Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655 and Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan.|Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655 and Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan.|Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655 and Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Algorithms|Bayes Theorem|Cell Line, Tumor|DNA Mutational Analysis|Gene Frequency|Haplotypes|Heterozygote|Humans|Mutation|Neoplasms|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btu537', '25123903', 'Identifying somatic changes from tumor and matched normal sequences has become a standard approach in cancer research. More specifically, this requires accurate detection of somatic point mutations with low allele frequencies in impure and heterogeneous cancer samples. Although haplotype phasing information derived by using heterozygous germ line variants near candidate mutations would improve accuracy, no somatic mutation caller that uses such information is currently available.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78611, 2014, 'bio', 'Cordova: web-based management of genetic variation data', 'Ephraim, Sean S|Anand, Nikhil|DeLuca, Adam P|Taylor, Kyle R|Kolbe, Diana L|Simpson, Allen C|Azaiez, Hela|Sloan, Christina M|Shearer, A Eliot|Hallier, Andrea R|Casavant, Thomas L|Scheetz, Todd E|Smith, Richard J H|Braun, Terry A', 'Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, USA.|Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, USA.|Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, USA.|Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, USA.|Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, USA.|Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, USA.|Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, USA.|Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, USA.|Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, USA Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, USA.|Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, USA.|Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, USA.|Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, USA.|Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, USA Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, USA Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, USA Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, USA.|Department of Biomedical Engineering, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, Department of Otolaryngology-Head & Neck Surgery, Carver College of Medicine, Department of Molecular Physiology & Biophysics, Carver College of Medicine, Interdisciplinary Graduate Program in Genetics and Iowa Institute for Human Genetics, Carver College of Medicine, The University of Iowa, Iowa City, IA 52242, 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', 0, 'Algorithms|Databases, Nucleic Acid|Genetic Variation|Humans|Internet|Software', 'Journal Article', '10.1093/bioinformatics/btu539', '25123904', 'Cordova is an out-of-the-box solution for building and maintaining an online database of genetic variations integrated with pathogenicity prediction results from popular algorithms. Our primary motivation for developing this system is to aid researchers and clinician-scientists in determining the clinical significance of genetic variations. To achieve this goal, Cordova provides an interface to review and manually or computationally curate genetic variation data as well as share it for clinical diagnostics and the advancement of research.'),
(78612, 2014, 'bio', 'SCDFinder, a web-based tool for the identification of putative novel ATM and ATR targets', 'Cara, Lukas|Baitemirova, Medina|Duong, Franklin|Larios-Sanz, Maia|Ribes-Zamora, Albert', 'Department of Mathematics, Computer Science and Cooperative Engineering, University of St. Thomas and Bioinformatics Program, Department of Biology, University of St. Thomas, 3800 Montrose Blvd, Houston, TX, 77006 USA.|Department of Mathematics, Computer Science and Cooperative Engineering, University of St. Thomas and Bioinformatics Program, Department of Biology, University of St. Thomas, 3800 Montrose Blvd, Houston, TX, 77006 USA.|Department of Mathematics, Computer Science and Cooperative Engineering, University of St. Thomas and Bioinformatics Program, Department of Biology, University of St. Thomas, 3800 Montrose Blvd, Houston, TX, 77006 USA.|Department of Mathematics, Computer Science and Cooperative Engineering, University of St. Thomas and Bioinformatics Program, Department of Biology, University of St. Thomas, 3800 Montrose Blvd, Houston, TX, 77006 USA.|Department of Mathematics, Computer Science and Cooperative Engineering, University of St. Thomas and Bioinformatics Program, Department of Biology, University of St. Thomas, 3800 Montrose Blvd, Houston, TX, 77006 USA.', 'United States|United States|United States|United States|United States', 1, 'Algorithms|Amino Acid Motifs|Ataxia Telangiectasia Mutated Proteins|Databases, Protein|Internet|Protein Structure, Tertiary|Proteome|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btu551', '25123905', 'The S/TQ cluster domain (SCD) constitutes a new type of protein domain that is not defined by sequence similarity but by the presence of multiple S/TQ motifs within a variable stretch of amino acids. SCDs are recognized targets for DNA damage response (DDR) kinases like ATM and ATR. Characterizing DDR targets is of significant interest. The aim of this work was to develop a web-based tool to allow for easy identification and visualization of SCDs within specific proteins or in whole proteome sets, a feature not supported by current domain and motif search tools.'),
(78613, 2014, 'bio', 'Comparative assembly hubs: web-accessible browsers for comparative genomics', 'Nguyen, Ngan|Hickey, Glenn|Raney, Brian J|Armstrong, Joel|Clawson, Hiram|Zweig, Ann|Karolchik, Donna|Kent, William James|Haussler, David|Paten, Benedict', 'Center for Biomolecular Sciences and Engineering, CBSE/ITI, UC Santa Cruz, 1156 High St, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, Center for Biomolecular Science and Engineering, UCSC, 1156 High Street, Santa Cruz, CA 95064, USA.|Center for Biomolecular Sciences and Engineering, CBSE/ITI, UC Santa Cruz, 1156 High St, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, Center for Biomolecular Science and Engineering, UCSC, 1156 High Street, Santa Cruz, CA 95064, USA.|Center for Biomolecular Sciences and Engineering, CBSE/ITI, UC Santa Cruz, 1156 High St, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, Center for Biomolecular Science and Engineering, UCSC, 1156 High Street, Santa Cruz, CA 95064, USA.|Center for Biomolecular Sciences and Engineering, CBSE/ITI, UC Santa Cruz, 1156 High St, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, Center for Biomolecular Science and Engineering, UCSC, 1156 High Street, Santa Cruz, CA 95064, USA.|Center for Biomolecular Sciences and Engineering, CBSE/ITI, UC Santa Cruz, 1156 High St, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, Center for Biomolecular Science and Engineering, UCSC, 1156 High Street, Santa Cruz, CA 95064, USA.|Center for Biomolecular Sciences and Engineering, CBSE/ITI, UC Santa Cruz, 1156 High St, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, Center for Biomolecular Science and Engineering, UCSC, 1156 High Street, Santa Cruz, CA 95064, USA.|Center for Biomolecular Sciences and Engineering, CBSE/ITI, UC Santa Cruz, 1156 High St, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, Center for Biomolecular Science and Engineering, UCSC, 1156 High Street, Santa Cruz, CA 95064, USA.|Center for Biomolecular Sciences and Engineering, CBSE/ITI, UC Santa Cruz, 1156 High St, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, Center for Biomolecular Science and Engineering, UCSC, 1156 High Street, Santa Cruz, CA 95064, USA.|Center for Biomolecular Sciences and Engineering, CBSE/ITI, UC Santa Cruz, 1156 High St, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, Center for Biomolecular Science and Engineering, UCSC, 1156 High Street, Santa Cruz, CA 95064, USA Center for Biomolecular Sciences and Engineering, CBSE/ITI, UC Santa Cruz, 1156 High St, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, Center for Biomolecular Science and Engineering, UCSC, 1156 High Street, Santa Cruz, CA 95064, USA.|Center for Biomolecular Sciences and Engineering, CBSE/ITI, UC Santa Cruz, 1156 High St, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, Center for Biomolecular Science and Engineering, UCSC, 1156 High Street, Santa Cruz, CA 95064, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 12, 'Algorithms|Escherichia coli|Genome, Bacterial|Genomics|Internet|Molecular Sequence Annotation|Sequence Alignment|Shigella|Web Browser', 'Journal Article', '10.1093/bioinformatics/btu534', '25138168', 'Researchers now have access to large volumes of genome sequences for comparative analysis, some generated by the plethora of public sequencing projects and, increasingly, from individual efforts. It is not possible, or necessarily desirable, that the public genome browsers attempt to curate all these data. Instead, a wealth of powerful tools is emerging to empower users to create their own visualizations and browsers.'),
(78614, 2014, 'bio', 'Pepper: cytoscape app for protein complex expansion using protein-protein interaction networks', 'Winterhalter, C|Nicolle, R|Louis, A|To, C|Radvanyi, F|Elati, M', 'iSSB, CNRS, University of Evry, Genopole, 5 rue H. Desbruères, 91030 Evry Cedex, France, School of Computing Science, Newcastle University, Newcastle NE1 7RU, UK and UMR 144 CNRS/Institut Curie, 26 rue dUlm, Paris, 75248 cedex 05, France iSSB, CNRS, University of Evry, Genopole, 5 rue H. Desbruères, 91030 Evry Cedex, France, School of Computing Science, Newcastle University, Newcastle NE1 7RU, UK and UMR 144 CNRS/Institut Curie, 26 rue dUlm, Paris, 75248 cedex 05, France.|iSSB, CNRS, University of Evry, Genopole, 5 rue H. Desbruères, 91030 Evry Cedex, France, School of Computing Science, Newcastle University, Newcastle NE1 7RU, UK and UMR 144 CNRS/Institut Curie, 26 rue dUlm, Paris, 75248 cedex 05, France iSSB, CNRS, University of Evry, Genopole, 5 rue H. Desbruères, 91030 Evry Cedex, France, School of Computing Science, Newcastle University, Newcastle NE1 7RU, UK and UMR 144 CNRS/Institut Curie, 26 rue dUlm, Paris, 75248 cedex 05, France.|iSSB, CNRS, University of Evry, Genopole, 5 rue H. Desbruères, 91030 Evry Cedex, France, School of Computing Science, Newcastle University, Newcastle NE1 7RU, UK and UMR 144 CNRS/Institut Curie, 26 rue dUlm, Paris, 75248 cedex 05, France.|iSSB, CNRS, University of Evry, Genopole, 5 rue H. Desbruères, 91030 Evry Cedex, France, School of Computing Science, Newcastle University, Newcastle NE1 7RU, UK and UMR 144 CNRS/Institut Curie, 26 rue dUlm, Paris, 75248 cedex 05, France.|iSSB, CNRS, University of Evry, Genopole, 5 rue H. Desbruères, 91030 Evry Cedex, France, School of Computing Science, Newcastle University, Newcastle NE1 7RU, UK and UMR 144 CNRS/Institut Curie, 26 rue dUlm, Paris, 75248 cedex 05, France.|iSSB, CNRS, University of Evry, Genopole, 5 rue H. Desbruères, 91030 Evry Cedex, France, School of Computing Science, Newcastle University, Newcastle NE1 7RU, UK and UMR 144 CNRS/Institut Curie, 26 rue dUlm, Paris, 75248 cedex 05, France.', 'France|France|France|France|France|France', 7, 'Algorithms|Humans|Protein Interaction Mapping|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/btu517', '25138169', 'We introduce Pepper (Protein complex Expansion using Protein-Protein intERactions), a Cytoscape app designed to identify protein complexes as densely connected subnetworks from seed lists of proteins derived from proteomic studies. Pepper identifies connected subgraph by using multi-objective optimization involving two functions: (i) the coverage, a solution must contain as many proteins from the seed as possible, (ii) the density, the proteins of a solution must be as connected as possible, using only interactions from a proteome-wide interaction network. Comparisons based on gold standard yeast and human datasets showed Peppers integrative approach as superior to standard protein complex discovery methods. The visualization and interpretation of the results are facilitated by an automated post-processing pipeline based on topological analysis and data integration about the predicted complex proteins. Pepper is a user-friendly tool that can be used to analyse any list of proteins.'),
(78615, 2014, 'bio', 'A novel feature-based approach to extract drug-drug interactions from biomedical text', 'Bui, Quoc-Chinh|Sloot, Peter M A|van Mulligen, Erik M|Kors, Jan A', 'Department of Medical Informatics, Erasmus University Medical Center Rotterdam, Informatics Institute, University of Amsterdam, The Netherlands, Complexity Institute, Nanyang Technological University, Singapore and ITMO University, St. Petersburg, Russian Federation.|Department of Medical Informatics, Erasmus University Medical Center Rotterdam, Informatics Institute, University of Amsterdam, The Netherlands, Complexity Institute, Nanyang Technological University, Singapore and ITMO University, St. Petersburg, Russian Federation Department of Medical Informatics, Erasmus University Medical Center Rotterdam, Informatics Institute, University of Amsterdam, The Netherlands, Complexity Institute, Nanyang Technological University, Singapore and ITMO University, St. Petersburg, Russian Federation Department of Medical Informatics, Erasmus University Medical Center Rotterdam, Informatics Institute, University of Amsterdam, The Netherlands, Complexity Institute, Nanyang Technological University, Singapore and ITMO University, St. Petersburg, Russian Federation.|Department of Medical Informatics, Erasmus University Medical Center Rotterdam, Informatics Institute, University of Amsterdam, The Netherlands, Complexity Institute, Nanyang Technological University, Singapore and ITMO University, St. Petersburg, Russian Federation.|Department of Medical Informatics, Erasmus University Medical Center Rotterdam, Informatics Institute, University of Amsterdam, The Netherlands, Complexity Institute, Nanyang Technological University, Singapore and ITMO University, St. Petersburg, Russian Federation.', 'Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Data Mining|Drug Interactions|Humans|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btu557', '25143286', 'Knowledge of drug-drug interactions (DDIs) is crucial for health-care professionals to avoid adverse effects when co-administering drugs to patients. As most newly discovered DDIs are made available through scientific publications, automatic DDI extraction is highly relevant.'),
(78616, 2014, 'bio', 'OptiType: precision HLA typing from next-generation sequencing data', 'Szolek, András|Schubert, Benjamin|Mohr, Christopher|Sturm, Marc|Feldhahn, Magdalena|Kohlbacher, Oliver', 'Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Institute of Medical Genetics and Applied Genomics, University of Tübingen, and CeGaT GmbH, 72076 Tübingen, Germany.|Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Institute of Medical Genetics and Applied Genomics, University of Tübingen, and CeGaT GmbH, 72076 Tübingen, Germany Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Institute of Medical Genetics and Applied Genomics, University of Tübingen, and CeGaT GmbH, 72076 Tübingen, Germany.|Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Institute of Medical Genetics and Applied Genomics, University of Tübingen, and CeGaT GmbH, 72076 Tübingen, Germany Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Institute of Medical Genetics and Applied Genomics, University of Tübingen, and CeGaT GmbH, 72076 Tübingen, Germany.|Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Institute of Medical Genetics and Applied Genomics, University of Tübingen, and CeGaT GmbH, 72076 Tübingen, Germany.|Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Institute of Medical Genetics and Applied Genomics, University of Tübingen, and CeGaT GmbH, 72076 Tübingen, Germany.|Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Institute of Medical Genetics and Applied Genomics, University of Tübingen, and CeGaT GmbH, 72076 Tübingen, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 201, 'Algorithms|Exome|Genotyping Techniques|HLA Antigens|High-Throughput Nucleotide Sequencing|Histocompatibility Testing|Humans|Introns|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu548', '25143287', 'The human leukocyte antigen (HLA) gene cluster plays a crucial role in adaptive immunity and is thus relevant in many biomedical applications. While next-generation sequencing data are often available for a patient, deducing the HLA genotype is difficult because of substantial sequence similarity within the cluster and exceptionally high variability of the loci. Established approaches, therefore, rely on specific HLA enrichment and sequencing techniques, coming at an additional cost and extra turnaround time.'),
(78617, 2014, 'bio', 'GlycoPattern: a web platform for glycan array mining', 'Agravat, Sanjay B|Saltz, Joel H|Cummings, Richard D|Smith, David F', 'National Center For Functional Glycomics, Emory University School of Medicine, Atlanta, GA 30322, USA, Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322 and Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11794, USA National Center For Functional Glycomics, Emory University School of Medicine, Atlanta, GA 30322, USA, Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322 and Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11794, USA.|National Center For Functional Glycomics, Emory University School of Medicine, Atlanta, GA 30322, USA, Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322 and Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11794, USA National Center For Functional Glycomics, Emory University School of Medicine, Atlanta, GA 30322, USA, Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322 and Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11794, USA.|National Center For Functional Glycomics, Emory University School of Medicine, Atlanta, GA 30322, USA, Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322 and Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11794, USA.|National Center For Functional Glycomics, Emory University School of Medicine, Atlanta, GA 30322, USA, Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322 and Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11794, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Carrier Proteins|Cluster Analysis|Data Mining|Glycomics|Internet|Microarray Analysis|Polysaccharides|Software', 'Journal Article', '10.1093/bioinformatics/btu559', '25143288', 'GlycoPattern is Web-based bioinformatics resource to support the analysis of glycan array data for the Consortium for Functional Glycomics. This resource includes algorithms and tools to discover structural motifs, a heatmap visualization to compare multiple experiments, hierarchical clustering of Glycan Binding Proteins with respect to their binding motifs and a structural search feature on the experimental data.'),
(78618, 2014, 'bio', 'Acceleration of short and long DNA read mapping without loss of accuracy using suffix array', 'Tárraga, Joaquín|Arnau, Vicente|Martínez, Héctor|Moreno, Raul|Cazorla, Diego|Salavert-Torres, José|Blanquer-Espert, Ignacio|Dopazo, Joaquín|Medina, Ignacio', 'Department of Computational Genomics, Centro de Investigación Príncipe Felipe (CIPF), Functional Genomics Node, (INB) at CIPF 46012, Departamento de Informática, Universidad de Valencia, 46100 Valencia, Departamento de Ingeniería y Ciencia de Computadores, Universitat Jaume I, 12071 Castellón de la Plana, Instituto de Investigación en Informática de Albacete, Universidad de Castilla-La Mancha, Campus Universitario, 02071 Albacete, Universitat Politècnica de València, Instituto de Instrumentación para Imagen Molecular, 46022 Valencia, Grupo de Investigación Biomédica de Imagen (GIBI 2^30), La Fe Polytechnic University Hospital, 46022 Valencia and Bioinformatics of Rare Diseases (BIER), CIBER de Enfermedades Raras (CIBERER), Valencia, Spain Department of Computational Genomics, Centro de Investigación Príncipe Felipe (CIPF), Functional Genomics Node, (INB) at CIPF 46012, Departamento de Informática, Universidad de Valencia, 46100 Valencia, Departamento de Ingeniería y Ciencia de Computadores, Universitat Jaume I, 12071 Castellón de la Plana, Instituto de Investigación en Informática de Albacete, Universidad de Castilla-La Mancha, Campus Universitario, 02071 Albacete, Universitat Politècnica de València, Instituto de Instrumentación para Imagen Molecular, 46022 Valencia, Grupo de Investigación Biomédica de Imagen (GIBI 2^30), La Fe Polytechnic University Hospital, 46022 Valencia and Bioinformatics of Rare Diseases (BIER), CIBER de Enfermedades Raras (CIBERER), Valencia, Spain.|Department of Computational Genomics, Centro de Investigación Príncipe Felipe (CIPF), Functional Genomics Node, (INB) at CIPF 46012, Departamento de Informática, Universidad de Valencia, 46100 Valencia, Departamento de Ingeniería y Ciencia de Computadores, Universitat Jaume I, 12071 Castellón de la Plana, Instituto de Investigación en Informática de Albacete, Universidad de Castilla-La Mancha, Campus Universitario, 02071 Albacete, Universitat Politècnica de València, Instituto de Instrumentación para Imagen Molecular, 46022 Valencia, Grupo de Investigación Biomédica de Imagen (GIBI 2^30), La Fe Polytechnic University Hospital, 46022 Valencia and Bioinformatics of Rare Diseases (BIER), CIBER de Enfermedades Raras (CIBERER), Valencia, Spain.|Department of Computational Genomics, Centro de Investigación Príncipe Felipe (CIPF), Functional Genomics Node, (INB) at CIPF 46012, Departamento de Informática, Universidad de Valencia, 46100 Valencia, Departamento de Ingeniería y Ciencia de Computadores, Universitat Jaume I, 12071 Castellón de la Plana, Instituto de Investigación en Informática de Albacete, Universidad de Castilla-La Mancha, Campus Universitario, 02071 Albacete, Universitat Politècnica de València, Instituto de Instrumentación para Imagen Molecular, 46022 Valencia, Grupo de Investigación Biomédica de Imagen (GIBI 2^30), La Fe Polytechnic University Hospital, 46022 Valencia and Bioinformatics of Rare Diseases (BIER), CIBER de Enfermedades Raras (CIBERER), Valencia, Spain.|Department of Computational Genomics, Centro de Investigación Príncipe Felipe (CIPF), Functional Genomics Node, (INB) at CIPF 46012, Departamento de Informática, Universidad de Valencia, 46100 Valencia, Departamento de Ingeniería y Ciencia de Computadores, Universitat Jaume I, 12071 Castellón de la Plana, Instituto de Investigación en Informática de Albacete, Universidad de Castilla-La Mancha, Campus Universitario, 02071 Albacete, Universitat Politècnica de València, Instituto de Instrumentación para Imagen Molecular, 46022 Valencia, Grupo de Investigación Biomédica de Imagen (GIBI 2^30), La Fe Polytechnic University Hospital, 46022 Valencia and Bioinformatics of Rare Diseases (BIER), CIBER de Enfermedades Raras (CIBERER), Valencia, Spain.|Department of Computational Genomics, Centro de Investigación Príncipe Felipe (CIPF), Functional Genomics Node, (INB) at CIPF 46012, Departamento de Informática, Universidad de Valencia, 46100 Valencia, Departamento de Ingeniería y Ciencia de Computadores, Universitat Jaume I, 12071 Castellón de la Plana, Instituto de Investigación en Informática de Albacete, Universidad de Castilla-La Mancha, Campus Universitario, 02071 Albacete, Universitat Politècnica de València, Instituto de Instrumentación para Imagen Molecular, 46022 Valencia, Grupo de Investigación Biomédica de Imagen (GIBI 2^30), La Fe Polytechnic University Hospital, 46022 Valencia and Bioinformatics of Rare Diseases (BIER), CIBER de Enfermedades Raras (CIBERER), Valencia, Spain.|Department of Computational Genomics, Centro de Investigación Príncipe Felipe (CIPF), Functional Genomics Node, (INB) at CIPF 46012, Departamento de Informática, Universidad de Valencia, 46100 Valencia, Departamento de Ingeniería y Ciencia de Computadores, Universitat Jaume I, 12071 Castellón de la Plana, Instituto de Investigación en Informática de Albacete, Universidad de Castilla-La Mancha, Campus Universitario, 02071 Albacete, Universitat Politècnica de València, Instituto de Instrumentación para Imagen Molecular, 46022 Valencia, Grupo de Investigación Biomédica de Imagen (GIBI 2^30), La Fe Polytechnic University Hospital, 46022 Valencia and Bioinformatics of Rare Diseases (BIER), CIBER de Enfermedades Raras (CIBERER), Valencia, Spain.|Department of Computational Genomics, Centro de Investigación Príncipe Felipe (CIPF), Functional Genomics Node, (INB) at CIPF 46012, Departamento de Informática, Universidad de Valencia, 46100 Valencia, Departamento de Ingeniería y Ciencia de Computadores, Universitat Jaume I, 12071 Castellón de la Plana, Instituto de Investigación en Informática de Albacete, Universidad de Castilla-La Mancha, Campus Universitario, 02071 Albacete, Universitat Politècnica de València, Instituto de Instrumentación para Imagen Molecular, 46022 Valencia, Grupo de Investigación Biomédica de Imagen (GIBI 2^30), La Fe Polytechnic University Hospital, 46022 Valencia and Bioinformatics of Rare Diseases (BIER), CIBER de Enfermedades Raras (CIBERER), Valencia, Spain Department of Computational Genomics, Centro de Investigación Príncipe Felipe (CIPF), Functional Genomics Node, (INB) at CIPF 46012, Departamento de Informática, Universidad de Valencia, 46100 Valencia, Departamento de Ingeniería y Ciencia de Computadores, Universitat Jaume I, 12071 Castellón de la Plana, Instituto de Investigación en Informática de Albacete, Universidad de Castilla-La Mancha, Campus Universitario, 02071 Albacete, Universitat Politècnica de València, Instituto de Instrumentación para Imagen Molecular, 46022 Valencia, Grupo de Investigación Biomédica de Imagen (GIBI 2^30), La Fe Polytechnic University Hospital, 46022 Valencia and Bioinformatics of Rare Diseases (BIER), CIBER de Enfermedades Raras (CIBERER), Valencia, Spain.|Department of Computational Genomics, Centro de Investigación Príncipe Felipe (CIPF), Functional Genomics Node, (INB) at CIPF 46012, Departamento de Informática, Universidad de Valencia, 46100 Valencia, Departamento de Ingeniería y Ciencia de Computadores, Universitat Jaume I, 12071 Castellón de la Plana, Instituto de Investigación en Informática de Albacete, Universidad de Castilla-La Mancha, Campus Universitario, 02071 Albacete, Universitat Politècnica de València, Instituto de Instrumentación para Imagen Molecular, 46022 Valencia, Grupo de Investigación Biomédica de Imagen (GIBI 2^30), La Fe Polytechnic University Hospital, 46022 Valencia and Bioinformatics of Rare Diseases (BIER), CIBER de Enfermedades Raras (CIBERER), Valencia, Spain Department of Computational Genomics, Centro de Investigación Príncipe Felipe (CIPF), Functional Genomics Node, (INB) at CIPF 46012, Departamento de Informática, Universidad de Valencia, 46100 Valencia, Departamento de Ingeniería y Ciencia de Computadores, Universitat Jaume I, 12071 Castellón de la Plana, Instituto de Investigación en Informática de Albacete, Universidad de Castilla-La Mancha, Campus Universitario, 02071 Albacete, Universitat Politècnica de València, Instituto de Instrumentación para Imagen Molecular, 46022 Valencia, Grupo de Investigación Biomédica de Imagen (GIBI 2^30), La Fe Polytechnic University Hospital, 46022 Valencia and Bioinformatics of Rare Diseases (BIER), CIBER de Enfermedades Raras (CIBERER), Valencia, Spain Department of Computational Genomics, Centro de Investigación Príncipe Felipe (CIPF), Functional Genomics Node, (INB) at CIPF 46012, Departamento de Informática, Universidad de Valencia, 46100 Valencia, Departamento de Ingeniería y Ciencia de Computadores, Universitat Jaume I, 12071 Castellón de la Plana, Instituto de Investigación en Informática de Albacete, Universidad de Castilla-La Mancha, Campus Universitario, 02071 Albacete, Universitat Politècnica de Valènci|Department of Computational Genomics, Centro de Investigación Príncipe Felipe (CIPF), Functional Genomics Node, (INB) at CIPF 46012, Departamento de Informática, Universidad de Valencia, 46100 Valencia, Departamento de Ingeniería y Ciencia de Computadores, Universitat Jaume I, 12071 Castellón de la Plana, Instituto de Investigación en Informática de Albacete, Universidad de Castilla-La Mancha, Campus Universitario, 02071 Albacete, Universitat Politècnica de València, Instituto de Instrumentación para Imagen Molecular, 46022 Valencia, Grupo de Investigación Biomédica de Imagen (GIBI 2^30), La Fe Polytechnic University Hospital, 46022 Valencia and Bioinformatics of Rare Diseases (BIER), CIBER de Enfermedades Raras (CIBERER), Valencia, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain', 11, 'Algorithms|Animals|Drosophila|High-Throughput Nucleotide Sequencing|Humans|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu553', '25143289', 'HPG Aligner applies suffix arrays for DNA read mapping. This implementation produces a highly sensitive and extremely fast mapping of DNA reads that scales up almost linearly with read length. The approach presented here is faster (over 20× for long reads) and more sensitive (over 98% in a wide range of read lengths) than the current state-of-the-art mappers. HPG Aligner is not only an optimal alternative for current sequencers but also the only solution available to cope with longer reads and growing throughputs produced by forthcoming sequencing technologies.'),
(78619, 2014, 'bio', 'BioBloom tools: fast, accurate and memory-efficient host species sequence screening using bloom filters', 'Chu, Justin|Sadeghi, Sara|Raymond, Anthony|Jackman, Shaun D|Nip, Ka Ming|Mar, Richard|Mohamadi, Hamid|Butterfield, Yaron S|Robertson, A Gordon|Birol, Inanç', 'Canadas Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada.|Canadas Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada.|Canadas Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada.|Canadas Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada.|Canadas Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada.|Canadas Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada.|Canadas Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada.|Canadas Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada.|Canadas Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada.|Canadas Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Animals|Humans|Mice|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu558', '25143290', 'Large datasets can be screened for sequences from a specific organism, quickly and with low memory requirements, by a data structure that supports time- and memory-efficient set membership queries. Bloom filters offer such queries but require that false positives be controlled. We present BioBloom Tools, a Bloom filter-based sequence-screening tool that is faster than BWA, Bowtie 2 (popular alignment algorithms) and FACS (a membership query algorithm). It delivers accuracies comparable with these tools, controls false positives and has low memory requirements. Availability and implementaion: www.bcgsc.ca/platform/bioinfo/software/biobloomtools.'),
(78620, 2014, 'bio', 'Poretools: a toolkit for analyzing nanopore sequence data', 'Loman, Nicholas J|Quinlan, Aaron R', 'Institute of Microbiology and Infection, University of Birmingham, Birmingham B15 2TT, UK and Department of Public Health Sciences, University of Virginia, Charlottesville 22932, VA, USA.|Institute of Microbiology and Infection, University of Birmingham, Birmingham B15 2TT, UK and Department of Public Health Sciences, University of Virginia, Charlottesville 22932, VA, USA.', 'United States|United States', 0, 'Nanopores|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu555', '25143291', 'Nanopore sequencing may be the next disruptive technology in genomics, owing to its ability to detect single DNA molecules without prior amplification, lack of reliance on expensive optical components, and the ability to sequence long fragments. The MinION™ from Oxford Nanopore Technologies (ONT) is the first nanopore sequencer to be commercialized and is now available to early-access users. The MinION™ is a USB-connected, portable nanopore sequencer that permits real-time analysis of streaming event data. Currently, the research community lacks a standardized toolkit for the analysis of nanopore datasets.'),
(78621, 2014, 'bio', 'FACTERA: a practical method for the discovery of genomic rearrangements at breakpoint resolution', 'Newman, Aaron M|Bratman, Scott V|Stehr, Henning|Lee, Luke J|Liu, Chih Long|Diehn, Maximilian|Alizadeh, Ash A', 'Institute for Stem Cell Biology and Regenerative Medicine, Division of Oncology, Department of Medicine, Department of Radiation Oncology and Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA Institute for Stem Cell Biology and Regenerative Medicine, Division of Oncology, Department of Medicine, Department of Radiation Oncology and Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA.|Institute for Stem Cell Biology and Regenerative Medicine, Division of Oncology, Department of Medicine, Department of Radiation Oncology and Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA Institute for Stem Cell Biology and Regenerative Medicine, Division of Oncology, Department of Medicine, Department of Radiation Oncology and Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA.|Institute for Stem Cell Biology and Regenerative Medicine, Division of Oncology, Department of Medicine, Department of Radiation Oncology and Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA.|Institute for Stem Cell Biology and Regenerative Medicine, Division of Oncology, Department of Medicine, Department of Radiation Oncology and Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA Institute for Stem Cell Biology and Regenerative Medicine, Division of Oncology, Department of Medicine, Department of Radiation Oncology and Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA.|Institute for Stem Cell Biology and Regenerative Medicine, Division of Oncology, Department of Medicine, Department of Radiation Oncology and Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA Institute for Stem Cell Biology and Regenerative Medicine, Division of Oncology, Department of Medicine, Department of Radiation Oncology and Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA.|Institute for Stem Cell Biology and Regenerative Medicine, Division of Oncology, Department of Medicine, Department of Radiation Oncology and Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA Institute for Stem Cell Biology and Regenerative Medicine, Division of Oncology, Department of Medicine, Department of Radiation Oncology and Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA Institute for Stem Cell Biology and Regenerative Medicine, Division of Oncology, Department of Medicine, Department of Radiation Oncology and Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA.|Institute for Stem Cell Biology and Regenerative Medicine, Division of Oncology, Department of Medicine, Department of Radiation Oncology and Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA Institute for Stem Cell Biology and Regenerative Medicine, Division of Oncology, Department of Medicine, Department of Radiation Oncology and Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA Institute for Stem Cell Biology and Regenerative Medicine, Division of Oncology, Department of Medicine, Department of Radiation Oncology and Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA.', 'United States|United States|United States|United States|United States|United States|United States', 72, 'Algorithms|Carcinoma, Non-Small-Cell Lung|Chromosome Aberrations|Chromosome Breakpoints|Chromosome Mapping|Gene Fusion|Genomics|Humans|Lung Neoplasms|Sequence Analysis, DNA|Software|Translocation, Genetic', 'Journal Article', '10.1093/bioinformatics/btu549', '25143292', 'For practical and robust de novo identification of genomic fusions and breakpoints from targeted paired-end DNA sequencing data, we developed Fusion And Chromosomal Translocation Enumeration and Recovery Algorithm (FACTERA). Our method has minimal external dependencies, works directly on a preexisting Binary Alignment/Map file and produces easily interpretable output. We demonstrate FACTERAs ability to rapidly identify breakpoint-resolution fusion events with high sensitivity and specificity in patients with non-small cell lung cancer, including novel rearrangements. We anticipate that FACTERA will be broadly applicable to the discovery and analysis of clinically relevant fusions from both targeted and genome-wide sequencing datasets.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78622, 2014, 'bio', 'SecureMA: protecting participant privacy in genetic association meta-analysis', 'Xie, Wei|Kantarcioglu, Murat|Bush, William S|Crawford, Dana|Denny, Joshua C|Heatherly, Raymond|Malin, Bradley A', 'Department of Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN 37232, USA, Department of Computer Science, University of Texas at Dallas, Richardson, TX 75080, USA, Department of Biomedical Informatics, Center for Human Genetics Research, Department of Molecular Physiology and Biophysics and Department of Medicine, Vanderbilt University, Nashville, TN 37232, USA.|Department of Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN 37232, USA, Department of Computer Science, University of Texas at Dallas, Richardson, TX 75080, USA, Department of Biomedical Informatics, Center for Human Genetics Research, Department of Molecular Physiology and Biophysics and Department of Medicine, Vanderbilt University, Nashville, TN 37232, USA.|Department of Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN 37232, USA, Department of Computer Science, University of Texas at Dallas, Richardson, TX 75080, USA, Department of Biomedical Informatics, Center for Human Genetics Research, Department of Molecular Physiology and Biophysics and Department of Medicine, Vanderbilt University, Nashville, TN 37232, USA Department of Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN 37232, USA, Department of Computer Science, University of Texas at Dallas, Richardson, TX 75080, USA, Department of Biomedical Informatics, Center for Human Genetics Research, Department of Molecular Physiology and Biophysics and Department of Medicine, Vanderbilt University, Nashville, TN 37232, USA.|Department of Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN 37232, USA, Department of Computer Science, University of Texas at Dallas, Richardson, TX 75080, USA, Department of Biomedical Informatics, Center for Human Genetics Research, Department of Molecular Physiology and Biophysics and Department of Medicine, Vanderbilt University, Nashville, TN 37232, USA Department of Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN 37232, USA, Department of Computer Science, University of Texas at Dallas, Richardson, TX 75080, USA, Department of Biomedical Informatics, Center for Human Genetics Research, Department of Molecular Physiology and Biophysics and Department of Medicine, Vanderbilt University, Nashville, TN 37232, USA.|Department of Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN 37232, USA, Department of Computer Science, University of Texas at Dallas, Richardson, TX 75080, USA, Department of Biomedical Informatics, Center for Human Genetics Research, Department of Molecular Physiology and Biophysics and Department of Medicine, Vanderbilt University, Nashville, TN 37232, USA Department of Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN 37232, USA, Department of Computer Science, University of Texas at Dallas, Richardson, TX 75080, USA, Department of Biomedical Informatics, Center for Human Genetics Research, Department of Molecular Physiology and Biophysics and Department of Medicine, Vanderbilt University, Nashville, TN 37232, USA.|Department of Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN 37232, USA, Department of Computer Science, University of Texas at Dallas, Richardson, TX 75080, USA, Department of Biomedical Informatics, Center for Human Genetics Research, Department of Molecular Physiology and Biophysics and Department of Medicine, Vanderbilt University, Nashville, TN 37232, USA.|Department of Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN 37232, USA, Department of Computer Science, University of Texas at Dallas, Richardson, TX 75080, USA, Department of Biomedical Informatics, Center for Human Genetics Research, Department of Molecular Physiology and Biophysics and Department of Medicine, Vanderbilt University, Nashville, TN 37232, USA Department of Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN 37232, USA, Department of Computer Science, University of Texas at Dallas, Richardson, TX 75080, USA, Department of Biomedical Informatics, Center for Human Genetics Research, Department of Molecular Physiology and Biophysics and Department of Medicine, Vanderbilt University, Nashville, TN 37232, USA.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Genetic Association Studies|Genetic Privacy|Genome-Wide Association Study|Genomics|Humans|Hypothyroidism|Meta-Analysis as Topic|Obesity|Software', 'Journal Article', '10.1093/bioinformatics/btu561', '25147357', 'Sharing genomic data is crucial to support scientific investigation such as genome-wide association studies. However, recent investigations suggest the privacy of the individual participants in these studies can be compromised, leading to serious concerns and consequences, such as overly restricted access to data.'),
(78623, 2014, 'bio', 'MethylAid: visual and interactive quality control of large Illumina 450k datasets', 'van Iterson, Maarten|Tobi, Elmar W|Slieker, Roderick C|den Hollander, Wouter|Luijk, René|Slagboom, P Eline|Heijmans, Bastiaan T', 'Department of Molecular Epidemiology, Leiden University Medical Center, 2333 ZC Leiden, the Netherlands.|Department of Molecular Epidemiology, Leiden University Medical Center, 2333 ZC Leiden, the Netherlands.|Department of Molecular Epidemiology, Leiden University Medical Center, 2333 ZC Leiden, the Netherlands.|Department of Molecular Epidemiology, Leiden University Medical Center, 2333 ZC Leiden, the Netherlands.|Department of Molecular Epidemiology, Leiden University Medical Center, 2333 ZC Leiden, the Netherlands.|Department of Molecular Epidemiology, Leiden University Medical Center, 2333 ZC Leiden, the Netherlands.|Department of Molecular Epidemiology, Leiden University Medical Center, 2333 ZC Leiden, the Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 61, 'DNA Methylation|Genomics|Humans|Internet|Oligonucleotide Array Sequence Analysis|Quality Control|Software', 'Journal Article', '10.1093/bioinformatics/btu566', '25147358', 'The Illumina 450k array is a frequently used platform for large-scale genome-wide DNA methylation studies, i.e. epigenome-wide association studies. Currently, quality control of 450k data can be performed with Illuminas GenomeStudio and is part of a limited number 450k analysis pipelines. However, GenomeStudio cannot handle large-scale studies, and existing pipelines provide limited options for quality control and neither support interactive exploration by the user. To aid the detection of bad-quality samples in large-scale genome-wide DNA methylation studies as flexible and transparent as possible, we have developed MethylAid, a visual and interactive Web application using RStudios shiny package. Bad-quality samples are detected using sample-dependent and sample-independent quality control probes present on the array and user-adjustable thresholds. In-depth exploration of bad-quality samples can be performed using several interactive diagnostic plots. Furthermore, plots can be annotated with user-provided metadata, for example, to identify outlying batches. Our new tool makes quality assessment of 450k array data interactive, flexible and efficient and is, therefore, expected to be useful for both data analysts and core facilities.'),
(78624, 2014, 'bio', 'PyBamView: a browser-based application for viewing short read alignments', 'Gymrek, Melissa', 'Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, Harvard-MIT Division of Health Sciences and Technology, MIT, Cambridge, MA 02139 and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, Harvard-MIT Division of Health Sciences and Technology, MIT, Cambridge, MA 02139 and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, Harvard-MIT Division of Health Sciences and Technology, MIT, Cambridge, MA 02139 and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.', 'United States', 3, 'High-Throughput Nucleotide Sequencing|Internet|Sequence Alignment|Sequence Analysis, DNA|Web Browser', 'Journal Article', '10.1093/bioinformatics/btu565', '25147359', 'Current sequence alignment browsers allow visualization of large and complex next-generation sequencing datasets. However, most of these tools provide inadequate display of insertions and can be cumbersome to use on large datasets. I implemented PyBamView, a lightweight Web application for visualizing short read alignments. It provides an easy-to-use Web interface for viewing alignments across multiple samples, with a focus on accurate visualization of insertions.'),
(78625, 2014, 'bio', 'Visualization of protein sequence features using JavaScript and SVG with pVizjs', 'Mukhyala, Kiran|Masselot, Alexandre', 'Department of Bioinformatics and Computational Biology, Genentech Inc., South San Francisco, CA 94080, USA.|Department of Bioinformatics and Computational Biology, Genentech Inc., South San Francisco, CA 94080, USA.', 'United States|United States', 0, 'Computer Graphics|Models, Molecular|Protein Conformation|Protein Processing, Post-Translational|Proteomics|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btu567', '25147360', 'pViz.js is a visualization library for displaying protein sequence features in a Web browser. By simply providing a sequence and the locations of its features, this lightweight, yet versatile, JavaScript library renders an interactive view of the protein features. Interactive exploration of protein sequence features over the Web is a common need in Bioinformatics. Although many Web sites have developed viewers to display these features, their implementations are usually focused on data from a specific source or use case. Some of these viewers can be adapted to fit other use cases but are not designed to be reusable. pViz makes it easy to display features as boxes aligned to a protein sequence with zooming functionality but also includes predefined renderings for secondary structure and post-translational modifications. The library is designed to further customize this view. We demonstrate such applications of pViz using two examples: a proteomic data visualization tool with an embedded viewer for displaying features on protein structure, and a tool to visualize the results of the variant_effect_predictor tool from Ensembl.'),
(78626, 2014, 'bio', 'diCal-IBD: demography-aware inference of identity-by-descent tracts in unrelated individuals', 'Tataru, Paula|Nirody, Jasmine A|Song, Yun S', 'Bioinformatics Research Centre, Department of Computer Science, Aarhus University, 8000 Aarhus C, Denmark, Biophysics Graduate Group, Computer Science Division, Department of Statistics and Department of Integrative Biology, University of California, Berkeley, CA 94720, USA.|Bioinformatics Research Centre, Department of Computer Science, Aarhus University, 8000 Aarhus C, Denmark, Biophysics Graduate Group, Computer Science Division, Department of Statistics and Department of Integrative Biology, University of California, Berkeley, CA 94720, USA.|Bioinformatics Research Centre, Department of Computer Science, Aarhus University, 8000 Aarhus C, Denmark, Biophysics Graduate Group, Computer Science Division, Department of Statistics and Department of Integrative Biology, University of California, Berkeley, CA 94720, USA Bioinformatics Research Centre, Department of Computer Science, Aarhus University, 8000 Aarhus C, Denmark, Biophysics Graduate Group, Computer Science Division, Department of Statistics and Department of Integrative Biology, University of California, Berkeley, CA 94720, USA Bioinformatics Research Centre, Department of Computer Science, Aarhus University, 8000 Aarhus C, Denmark, Biophysics Graduate Group, Computer Science Division, Department of Statistics and Department of Integrative Biology, University of California, Berkeley, CA 94720, USA.', 'Denmark|Denmark|Denmark', 0, 'Demography|Genetics, Population|Genomics|Humans|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btu563', '25147361', 'We present a tool, diCal-IBD, for detecting identity-by-descent (IBD) tracts between pairs of genomic sequences. Our method builds on a recent demographic inference method based on the coalescent with recombination, and is able to incorporate demographic information as a prior. Simulation study shows that diCal-IBD has significantly higher recall and precision than that of existing single-nucleotide polymorphism-based IBD detection methods, while retaining reasonable accuracy for IBD tracts as small as 0.1 cM.'),
(78627, 2014, 'bio', 'Cosi2: an efficient simulator of exact and approximate coalescent with selection', 'Shlyakhter, Ilya|Sabeti, Pardis C|Schaffner, Stephen F', 'Broad Institute of MIT and Harvard, MA 02142 and Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA Broad Institute of MIT and Harvard, MA 02142 and Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.|Broad Institute of MIT and Harvard, MA 02142 and Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA Broad Institute of MIT and Harvard, MA 02142 and Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.|Broad Institute of MIT and Harvard, MA 02142 and Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.', 'United States|United States|United States', 0, 'Algorithms|Chromosomes|Demography|Gene Conversion|Genetics, Population|Markov Chains|Models, Genetic|Population Density|Recombination, Genetic|Selection, Genetic', 'Journal Article', '10.1093/bioinformatics/btu562', '25150247', 'Efficient simulation of population genetic samples under a given demographic model is a prerequisite for many analyses. Coalescent theory provides an efficient framework for such simulations, but simulating longer regions and higher recombination rates remains challenging. Simulators based on a Markovian approximation to the coalescent scale well, but do not support simulation of selection. Gene conversion is not supported by any published coalescent simulators that support selection.'),
(78628, 2014, 'bio', 'SUBAcon: a consensus algorithm for unifying the subcellular localization data of the Arabidopsis proteome', 'Hooper, Cornelia M|Tanz, Sandra K|Castleden, Ian R|Vacher, Michael A|Small, Ian D|Millar, A Harvey', 'Centre of Excellence in Computational Systems Biology, The University of Western Australia, Perth, WA 6009, Australia and ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, Perth, WA 6009, Australia.|Centre of Excellence in Computational Systems Biology, The University of Western Australia, Perth, WA 6009, Australia and ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, Perth, WA 6009, Australia Centre of Excellence in Computational Systems Biology, The University of Western Australia, Perth, WA 6009, Australia and ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, Perth, WA 6009, Australia.|Centre of Excellence in Computational Systems Biology, The University of Western Australia, Perth, WA 6009, Australia and ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, Perth, WA 6009, Australia.|Centre of Excellence in Computational Systems Biology, The University of Western Australia, Perth, WA 6009, Australia and ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, Perth, WA 6009, Australia Centre of Excellence in Computational Systems Biology, The University of Western Australia, Perth, WA 6009, Australia and ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, Perth, WA 6009, Australia.|Centre of Excellence in Computational Systems Biology, The University of Western Australia, Perth, WA 6009, Australia and ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, Perth, WA 6009, Australia Centre of Excellence in Computational Systems Biology, The University of Western Australia, Perth, WA 6009, Australia and ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, Perth, WA 6009, Australia.|Centre of Excellence in Computational Systems Biology, The University of Western Australia, Perth, WA 6009, Australia and ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, Perth, WA 6009, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia', 0, 'Algorithms|Arabidopsis|Arabidopsis Proteins|Bayes Theorem|Databases, Protein|Green Fluorescent Proteins|Mass Spectrometry|Membrane Proteins|Protein Interaction Mapping|Proteome|Software', 'Journal Article', '10.1093/bioinformatics/btu550', '25150248', 'Knowing the subcellular location of proteins is critical for understanding their function and developing accurate networks representing eukaryotic biological processes. Many computational tools have been developed to predict proteome-wide subcellular location, and abundant experimental data from green fluorescent protein (GFP) tagging or mass spectrometry (MS) are available in the model plant, Arabidopsis. None of these approaches is error-free, and thus, results are often contradictory.'),
(78629, 2015, 'bio', 'Inter-species pathway perturbation prediction via data-driven detection of functional homology', 'Hafemeister, Christoph|Romero, Roberto|Bilal, Erhan|Meyer, Pablo|Norel, Raquel|Rhrissorrakrai, Kahn|Bonneau, Richard|Tarca, Adi L', 'Department of Biology, Center for Genomics & Systems Biology, New York University, New York, NY 10003, Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD and Detroit, MI 48201, USA, IBM Thomas J. Watson Research Center, Yorktown Heights, NY 10598, Computer Science Department, Courant institute of Mathematical Sciences, New York University, New York, NY 10012 and Department of Computer Science, Wayne State University, Detroit, MI 48202, USA.|Department of Biology, Center for Genomics & Systems Biology, New York University, New York, NY 10003, Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD and Detroit, MI 48201, USA, IBM Thomas J. Watson Research Center, Yorktown Heights, NY 10598, Computer Science Department, Courant institute of Mathematical Sciences, New York University, New York, NY 10012 and Department of Computer Science, Wayne State University, Detroit, MI 48202, USA.|Department of Biology, Center for Genomics & Systems Biology, New York University, New York, NY 10003, Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD and Detroit, MI 48201, USA, IBM Thomas J. Watson Research Center, Yorktown Heights, NY 10598, Computer Science Department, Courant institute of Mathematical Sciences, New York University, New York, NY 10012 and Department of Computer Science, Wayne State University, Detroit, MI 48202, USA.|Department of Biology, Center for Genomics & Systems Biology, New York University, New York, NY 10003, Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD and Detroit, MI 48201, USA, IBM Thomas J. Watson Research Center, Yorktown Heights, NY 10598, Computer Science Department, Courant institute of Mathematical Sciences, New York University, New York, NY 10012 and Department of Computer Science, Wayne State University, Detroit, MI 48202, USA.|Department of Biology, Center for Genomics & Systems Biology, New York University, New York, NY 10003, Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD and Detroit, MI 48201, USA, IBM Thomas J. Watson Research Center, Yorktown Heights, NY 10598, Computer Science Department, Courant institute of Mathematical Sciences, New York University, New York, NY 10012 and Department of Computer Science, Wayne State University, Detroit, MI 48202, USA.|Department of Biology, Center for Genomics & Systems Biology, New York University, New York, NY 10003, Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD and Detroit, MI 48201, USA, IBM Thomas J. Watson Research Center, Yorktown Heights, NY 10598, Computer Science Department, Courant institute of Mathematical Sciences, New York University, New York, NY 10012 and Department of Computer Science, Wayne State University, Detroit, MI 48202, USA.|Department of Biology, Center for Genomics & Systems Biology, New York University, New York, NY 10003, Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD and Detroit, MI 48201, USA, IBM Thomas J. Watson Research Center, Yorktown Heights, NY 10598, Computer Science Department, Courant institute of Mathematical Sciences, New York University, New York, NY 10012 and Department of Computer Science, Wayne State University, Detroit, MI 48202, USA Department of Biology, Center for Genomics & Systems Biology, New York University, New York, NY 10003, Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD and Detroit, MI 48201, USA, IBM Thomas J. Watson Research Center, Yorktown Heights, NY 10598, Computer Science Department, Courant institute of Mathematical Sciences, New York University, New York, NY 10012 and Department of Computer Science, Wayne State University, Detroit, MI 48202, USA.|Department of Biology, Center for Genomics & Systems Biology, New York University, New York, NY 10003, Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD and Detroit, MI 48201, USA, IBM Thomas J. Watson Research Center, Yorktown Heights, NY 10598, Computer Science Department, Courant institute of Mathematical Sciences, New York University, New York, NY 10012 and Department of Computer Science, Wayne State University, Detroit, MI 48202, USA Department of Biology, Center for Genomics & Systems Biology, New York University, New York, NY 10003, Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD and Detroit, MI 48201, USA, IBM Thomas J. Watson Research Center, Yorktown Heights, NY 10598, Computer Science Department, Courant institute of Mathematical Sciences, New York University, New York, NY 10012 and Department of Computer Science, Wayne State University, Detroit, MI 48202, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 6, 'Algorithms|Animals|Artificial Intelligence|Bronchi|Cells, Cultured|Cytokines|Databases, Factual|Epithelial Cells|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Animal|Oligonucleotide Array Sequence Analysis|Phosphoproteins|Phosphorylation|Rats|Signal Transduction|Software|Species Specificity|Systems Biology|Translational Medical Research', 'Comparative Study', '10.1093/bioinformatics/btu570', '25150249', 'Experiments in animal models are often conducted to infer how humans will respond to stimuli by assuming that the same biological pathways will be affected in both organisms. The limitations of this assumption were tested in the IMPROVER Species Translation Challenge, where 52 stimuli were applied to both human and rat cells and perturbed pathways were identified. In the Inter-species Pathway Perturbation Prediction sub-challenge, multiple teams proposed methods to use rat transcription data from 26 stimuli to predict human gene set and pathway activity under the same perturbations. Submissions were evaluated using three performance metrics on data from the remaining 26 stimuli.'),
(78630, 2014, 'bio', 'ProtocolNavigator: emulation-based software for the design, documentation and reproduction biological experiments', 'Khan, Imtiaz A|Fraser, Adam|Bray, Mark-Anthony|Smith, Paul J|White, Nick S|Carpenter, Anne E|Errington, Rachel J', 'School of Medicine, Cardiff University, Cardiff, UK, Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA and School of Optometry and Vision Sciences, Cardiff University, Cardiff, UK School of Medicine, Cardiff University, Cardiff, UK, Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA and School of Optometry and Vision Sciences, Cardiff University, Cardiff, UK.|School of Medicine, Cardiff University, Cardiff, UK, Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA and School of Optometry and Vision Sciences, Cardiff University, Cardiff, UK.|School of Medicine, Cardiff University, Cardiff, UK, Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA and School of Optometry and Vision Sciences, Cardiff University, Cardiff, UK.|School of Medicine, Cardiff University, Cardiff, UK, Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA and School of Optometry and Vision Sciences, Cardiff University, Cardiff, UK.|School of Medicine, Cardiff University, Cardiff, UK, Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA and School of Optometry and Vision Sciences, Cardiff University, Cardiff, UK.|School of Medicine, Cardiff University, Cardiff, UK, Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA and School of Optometry and Vision Sciences, Cardiff University, Cardiff, UK.|School of Medicine, Cardiff University, Cardiff, UK, Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA and School of Optometry and Vision Sciences, Cardiff University, Cardiff, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 7, 'Documentation|Nanoparticles|Neoplasms|Reproducibility of Results|Research Design|Software', 'Journal Article', '10.1093/bioinformatics/btu554', '25150250', 'Experimental reproducibility is fundamental to the progress of science. Irreproducible research decreases the efficiency of basic biological research and drug discovery and impedes experimental data reuse. A major contributing factor to irreproducibility is difficulty in interpreting complex experimental methodologies and designs from written text and in assessing variations among different experiments. Current bioinformatics initiatives either are focused on computational research reproducibility (i.e. data analysis) or laboratory information management systems. Here, we present a software tool, ProtocolNavigator, which addresses the largely overlooked challenges of interpretation and assessment. It provides a biologist-friendly open-source emulation-based tool for designing, documenting and reproducing biological experiments.'),
(78631, 2015, 'bio', 'Inter-species inference of gene set enrichment in lung epithelial cells from proteomic and large transcriptomic datasets', 'Hormoz, Sahand|Bhanot, Gyan|Biehl, Michael|Bilal, Erhan|Meyer, Pablo|Norel, Raquel|Rhrissorrakrai, Kahn|Dayarian, Adel', 'Kavli Institute for Theoretical Physics, Kohn Hall, University of California, Santa Barbara, CA 93106, USA, Department of Physics, Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, USA, Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands and IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10003, USA.|Kavli Institute for Theoretical Physics, Kohn Hall, University of California, Santa Barbara, CA 93106, USA, Department of Physics, Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, USA, Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands and IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10003, USA Kavli Institute for Theoretical Physics, Kohn Hall, University of California, Santa Barbara, CA 93106, USA, Department of Physics, Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, USA, Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands and IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10003, USA.|Kavli Institute for Theoretical Physics, Kohn Hall, University of California, Santa Barbara, CA 93106, USA, Department of Physics, Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, USA, Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands and IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10003, USA.|Kavli Institute for Theoretical Physics, Kohn Hall, University of California, Santa Barbara, CA 93106, USA, Department of Physics, Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, USA, Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands and IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10003, USA.|Kavli Institute for Theoretical Physics, Kohn Hall, University of California, Santa Barbara, CA 93106, USA, Department of Physics, Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, USA, Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands and IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10003, USA.|Kavli Institute for Theoretical Physics, Kohn Hall, University of California, Santa Barbara, CA 93106, USA, Department of Physics, Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, USA, Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands and IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10003, USA.|Kavli Institute for Theoretical Physics, Kohn Hall, University of California, Santa Barbara, CA 93106, USA, Department of Physics, Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, USA, Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands and IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10003, USA.|Kavli Institute for Theoretical Physics, Kohn Hall, University of California, Santa Barbara, CA 93106, USA, Department of Physics, Department of Molecular Biology and Biochemistry, Busch Campus, Rutgers University, Piscataway, NJ 08854, USA, Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, 9700 AK Groningen, The Netherlands and IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10003, USA.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 1, 'Algorithms|Animals|Bronchi|Cells, Cultured|Cytokines|Data Interpretation, Statistical|Databases, Factual|Epithelial Cells|Gene Expression Profiling|Gene Expression Regulation|Gene Regulatory Networks|Humans|Mice|Phosphoproteins|Phosphorylation|Proteomics|Rats|Signal Transduction|Species Specificity|Systems Biology', 'Comparative Study', '10.1093/bioinformatics/btu569', '25152231', 'Translating findings in rodent models to human models has been a cornerstone of modern biology and drug development. However, in many cases, a naive extrapolation between the two species has not succeeded. As a result, clinical trials of new drugs sometimes fail even after considerable success in the mouse or rat stage of development. In addition to in vitro studies, inter-species translation requires analytical tools that can predict the enriched gene sets in human cells under various stimuli from corresponding measurements in animals. Such tools can improve our understanding of the underlying biology and optimize the allocation of resources for drug development.'),
(78632, 2014, 'bio', 'PHOXTRACK-a tool for interpreting comprehensive datasets of post-translational modifications of proteins', 'Weidner, Christopher|Fischer, Cornelius|Sauer, Sascha', 'Otto Warburg Laboratory, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, 14195 Berlin, Germany.|Otto Warburg Laboratory, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, 14195 Berlin, Germany.|Otto Warburg Laboratory, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, 14195 Berlin, Germany.', 'Germany|Germany|Germany', 13, 'Animals|Humans|Mass Spectrometry|Phosphorylation|Protein Processing, Post-Translational|Proteins|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/btu572', '25152232', 'We introduce PHOXTRACK (PHOsphosite-X-TRacing Analysis of Causal Kinases), a user-friendly freely available software tool for analyzing large datasets of post-translational modifications of proteins, such as phosphorylation, which are commonly gained by mass spectrometry detection. In contrast to other currently applied data analysis approaches, PHOXTRACK uses full sets of quantitative proteomics data and applies non-parametric statistics to calculate whether defined kinase-specific sets of phosphosite sequences indicate statistically significant concordant differences between various biological conditions. PHOXTRACK is an efficient tool for extracting post-translational information of comprehensive proteomics datasets to decipher key regulatory proteins and to infer biologically relevant molecular pathways.'),
(78633, 2014, 'bio', 'ExpTreeDB: web-based query and visualization of manually annotated gene expression profiling experiments of human and mouse from GEO', 'Ni, Ming|Ye, Fuqiang|Zhu, Juanjuan|Li, Zongwei|Yang, Shuai|Yang, Bite|Han, Lu|Wu, Yongge|Chen, Ying|Li, Fei|Wang, Shengqi|Bo, Xiaochen', 'Beijing Institute of Radiation Medicine, Beijing 100850, College of Life Sciences, Jilin University, Changchun 130012 and Henan University of Traditional Chinese Medicine, Zhengzhou 450008, China.|Beijing Institute of Radiation Medicine, Beijing 100850, College of Life Sciences, Jilin University, Changchun 130012 and Henan University of Traditional Chinese Medicine, Zhengzhou 450008, China.|Beijing Institute of Radiation Medicine, Beijing 100850, College of Life Sciences, Jilin University, Changchun 130012 and Henan University of Traditional Chinese Medicine, Zhengzhou 450008, China Beijing Institute of Radiation Medicine, Beijing 100850, College of Life Sciences, Jilin University, Changchun 130012 and Henan University of Traditional Chinese Medicine, Zhengzhou 450008, China.|Beijing Institute of Radiation Medicine, Beijing 100850, College of Life Sciences, Jilin University, Changchun 130012 and Henan University of Traditional Chinese Medicine, Zhengzhou 450008, China.|Beijing Institute of Radiation Medicine, Beijing 100850, College of Life Sciences, Jilin University, Changchun 130012 and Henan University of Traditional Chinese Medicine, Zhengzhou 450008, China.|Beijing Institute of Radiation Medicine, Beijing 100850, College of Life Sciences, Jilin University, Changchun 130012 and Henan University of Traditional Chinese Medicine, Zhengzhou 450008, China.|Beijing Institute of Radiation Medicine, Beijing 100850, College of Life Sciences, Jilin University, Changchun 130012 and Henan University of Traditional Chinese Medicine, Zhengzhou 450008, China.|Beijing Institute of Radiation Medicine, Beijing 100850, College of Life Sciences, Jilin University, Changchun 130012 and Henan University of Traditional Chinese Medicine, Zhengzhou 450008, China.|Beijing Institute of Radiation Medicine, Beijing 100850, College of Life Sciences, Jilin University, Changchun 130012 and Henan University of Traditional Chinese Medicine, Zhengzhou 450008, China.|Beijing Institute of Radiation Medicine, Beijing 100850, College of Life Sciences, Jilin University, Changchun 130012 and Henan University of Traditional Chinese Medicine, Zhengzhou 450008, China.|Beijing Institute of Radiation Medicine, Beijing 100850, College of Life Sciences, Jilin University, Changchun 130012 and Henan University of Traditional Chinese Medicine, Zhengzhou 450008, China Beijing Institute of Radiation Medicine, Beijing 100850, College of Life Sciences, Jilin University, Changchun 130012 and Henan University of Traditional Chinese Medicine, Zhengzhou 450008, China.|Beijing Institute of Radiation Medicine, Beijing 100850, College of Life Sciences, Jilin University, Changchun 130012 and Henan University of Traditional Chinese Medicine, Zhengzhou 450008, China.', 'China|China|China|China|China|China|China|China|China|China|China|China', 0, 'Animals|Cell Hypoxia|Cluster Analysis|Databases, Genetic|Gene Expression Profiling|Humans|Internet|Mice|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btu560', '25152233', 'Numerous public microarray datasets are valuable resources for the scientific communities. Several online tools have made great steps to use these data by querying related datasets with users own gene signatures or expression profiles. However, dataset annotation and result exhibition still need to be improved.'),
(78634, 2014, 'bio', 'ECCB 2014: The 13th European Conference on Computational Biology', 'Devignes, Marie-Dominique|Moreau, Yves', '(ECCB14 Conference Chair) CNRS-University of Lorraine, Nancy, France.|(ECCB14 Co-Chair) University of Leuven, Belgium.', 'France|Belgium', 2, 'Computational Biology|Congresses as Topic|Humans|Molecular Biology', 'Editorial', '10.1093/bioinformatics/btu512', '25161218', '-'),
(78635, 2014, 'bio', 'Lambda: the local aligner for massive biological data', 'Hauswedell, Hannes|Singer, Jochen|Reinert, Knut', 'Department of Mathematics and Computer Science, Freie Universität Berlin, Takustr. 9, 14195 Berlin, Germany.|Department of Mathematics and Computer Science, Freie Universität Berlin, Takustr. 9, 14195 Berlin, Germany.|Department of Mathematics and Computer Science, Freie Universität Berlin, Takustr. 9, 14195 Berlin, Germany.', 'Germany|Germany|Germany', 29, 'Algorithms|High-Throughput Nucleotide Sequencing|Metagenomics|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu439', '25161219', 'Next-generation sequencing technologies produce unprecedented amounts of data, leading to completely new research fields. One of these is metagenomics, the study of large-size DNA samples containing a multitude of diverse organisms. A key problem in metagenomics is to functionally and taxonomically classify the sequenced DNA, to which end the well-known BLAST program is usually used. But BLAST has dramatic resource requirements at metagenomic scales of data, imposing a high financial or technical burden on the researcher. Multiple attempts have been made to overcome these limitations and present a viable alternative to BLAST.'),
(78636, 2014, 'bio', 'Fiona: a parallel and automatic strategy for read error correction', 'Schulz, Marcel H|Weese, David|Holtgrewe, Manuel|Dimitrova, Viktoria|Niu, Sijia|Reinert, Knut|Richard, Hugues', 'Multimodal Computing and Interaction, Saarland University & Department for Computational Biology and Applied Computing, Max Planck Institute for Informatics, Saarbrücken, 66123 Saarland, Germany, Ray and Stephanie Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, 15206 PA, USA, Department of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany, Université Pierre et Marie Curie, UMR7238, CNRS-UPMC, Paris, France and CNRS, UMR7238, Laboratory of Computational and Quantitative Biology, Paris, France Multimodal Computing and Interaction, Saarland University & Department for Computational Biology and Applied Computing, Max Planck Institute for Informatics, Saarbrücken, 66123 Saarland, Germany, Ray and Stephanie Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, 15206 PA, USA, Department of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany, Université Pierre et Marie Curie, UMR7238, CNRS-UPMC, Paris, France and CNRS, UMR7238, Laboratory of Computational and Quantitative Biology, Paris, France.|Multimodal Computing and Interaction, Saarland University & Department for Computational Biology and Applied Computing, Max Planck Institute for Informatics, Saarbrücken, 66123 Saarland, Germany, Ray and Stephanie Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, 15206 PA, USA, Department of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany, Université Pierre et Marie Curie, UMR7238, CNRS-UPMC, Paris, France and CNRS, UMR7238, Laboratory of Computational and Quantitative Biology, Paris, France.|Multimodal Computing and Interaction, Saarland University & Department for Computational Biology and Applied Computing, Max Planck Institute for Informatics, Saarbrücken, 66123 Saarland, Germany, Ray and Stephanie Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, 15206 PA, USA, Department of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany, Université Pierre et Marie Curie, UMR7238, CNRS-UPMC, Paris, France and CNRS, UMR7238, Laboratory of Computational and Quantitative Biology, Paris, France.|Multimodal Computing and Interaction, Saarland University & Department for Computational Biology and Applied Computing, Max Planck Institute for Informatics, Saarbrücken, 66123 Saarland, Germany, Ray and Stephanie Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, 15206 PA, USA, Department of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany, Université Pierre et Marie Curie, UMR7238, CNRS-UPMC, Paris, France and CNRS, UMR7238, Laboratory of Computational and Quantitative Biology, Paris, France Multimodal Computing and Interaction, Saarland University & Department for Computational Biology and Applied Computing, Max Planck Institute for Informatics, Saarbrücken, 66123 Saarland, Germany, Ray and Stephanie Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, 15206 PA, USA, Department of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany, Université Pierre et Marie Curie, UMR7238, CNRS-UPMC, Paris, France and CNRS, UMR7238, Laboratory of Computational and Quantitative Biology, Paris, France.|Multimodal Computing and Interaction, Saarland University & Department for Computational Biology and Applied Computing, Max Planck Institute for Informatics, Saarbrücken, 66123 Saarland, Germany, Ray and Stephanie Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, 15206 PA, USA, Department of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany, Université Pierre et Marie Curie, UMR7238, CNRS-UPMC, Paris, France and CNRS, UMR7238, Laboratory of Computational and Quantitative Biology, Paris, France Multimodal Computing and Interaction, Saarland University & Department for Computational Biology and Applied Computing, Max Planck Institute for Informatics, Saarbrücken, 66123 Saarland, Germany, Ray and Stephanie Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, 15206 PA, USA, Department of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany, Université Pierre et Marie Curie, UMR7238, CNRS-UPMC, Paris, France and CNRS, UMR7238, Laboratory of Computational and Quantitative Biology, Paris, France.|Multimodal Computing and Interaction, Saarland University & Department for Computational Biology and Applied Computing, Max Planck Institute for Informatics, Saarbrücken, 66123 Saarland, Germany, Ray and Stephanie Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, 15206 PA, USA, Department of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany, Université Pierre et Marie Curie, UMR7238, CNRS-UPMC, Paris, France and CNRS, UMR7238, Laboratory of Computational and Quantitative Biology, Paris, France.|Multimodal Computing and Interaction, Saarland University & Department for Computational Biology and Applied Computing, Max Planck Institute for Informatics, Saarbrücken, 66123 Saarland, Germany, Ray and Stephanie Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, 15206 PA, USA, Department of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany, Université Pierre et Marie Curie, UMR7238, CNRS-UPMC, Paris, France and CNRS, UMR7238, Laboratory of Computational and Quantitative Biology, Paris, France Multimodal Computing and Interaction, Saarland University & Department for Computational Biology and Applied Computing, Max Planck Institute for Informatics, Saarbrücken, 66123 Saarland, Germany, Ray and Stephanie Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, 15206 PA, USA, Department of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany, Université Pierre et Marie Curie, UMR7238, CNRS-UPMC, Paris, France and CNRS, UMR7238, Laboratory of Computational and Quantitative Biology, Paris, France.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 37, 'Algorithms|High-Throughput Nucleotide Sequencing|INDEL Mutation|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu440', '25161220', 'Automatic error correction of high-throughput sequencing data can have a dramatic impact on the amount of usable base pairs and their quality. It has been shown that the performance of tasks such as de novo genome assembly and SNP calling can be dramatically improved after read error correction. While a large number of methods specialized for correcting substitution errors as found in Illumina data exist, few methods for the correction of indel errors, common to technologies like 454 or Ion Torrent, have been proposed.'),
(78637, 2014, 'bio', 'Towards a piRNA prediction using multiple kernel fusion and support vector machine', 'Brayet, Jocelyn|Zehraoui, Farida|Jeanson-Leh, Laurence|Israeli, David|Tahi, Fariza', 'IBISC EA 4526, UEVE/Genopole, IBGBI, 23 bv. de France, 91000 Evry, France and Genethon, 1, bis rue de lInternationale, 91002 Evry Cedex, France IBISC EA 4526, UEVE/Genopole, IBGBI, 23 bv. de France, 91000 Evry, France and Genethon, 1, bis rue de lInternationale, 91002 Evry Cedex, France.|IBISC EA 4526, UEVE/Genopole, IBGBI, 23 bv. de France, 91000 Evry, France and Genethon, 1, bis rue de lInternationale, 91002 Evry Cedex, France.|IBISC EA 4526, UEVE/Genopole, IBGBI, 23 bv. de France, 91000 Evry, France and Genethon, 1, bis rue de lInternationale, 91002 Evry Cedex, France.|IBISC EA 4526, UEVE/Genopole, IBGBI, 23 bv. de France, 91000 Evry, France and Genethon, 1, bis rue de lInternationale, 91002 Evry Cedex, France.|IBISC EA 4526, UEVE/Genopole, IBGBI, 23 bv. de France, 91000 Evry, France and Genethon, 1, bis rue de lInternationale, 91002 Evry Cedex, France.', 'France|France|France|France|France', 21, 'Algorithms|Animals|Artificial Intelligence|Drosophila|Humans|RNA, Small Interfering|Sequence Analysis, RNA|Software|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btu441', '25161221', 'Piwi-interacting RNA (piRNA) is the most recently discovered and the least investigated class of Argonaute/Piwi protein-interacting small non-coding RNAs. The piRNAs are mostly known to be involved in protecting the genome from invasive transposable elements. But recent discoveries suggest their involvement in the pathophysiology of diseases, such as cancer. Their identification is therefore an important task, and computational methods are needed. However, the lack of conserved piRNA sequences and structural elements makes this identification challenging and difficult.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78638, 2014, 'bio', 'FastHap: fast and accurate single individual haplotype reconstruction using fuzzy conflict graphs', 'Mazrouee, Sepideh|Wang, Wei', 'Computer Science Department, University of California Los Angeles (UCLA), 3551 Boelter Hall, Los Angeles, CA 90095-1596, USA.|Computer Science Department, University of California Los Angeles (UCLA), 3551 Boelter Hall, Los Angeles, CA 90095-1596, USA.', 'United States|United States', 10, 'Algorithms|Haplotypes|Humans|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu442', '25161222', 'Understanding exact structure of an individuals haplotype plays a significant role in various fields of human genetics. Despite tremendous research effort in recent years, fast and accurate haplotype reconstruction remains as an active research topic, mainly owing to the computational challenges involved. Existing haplotype assembly algorithms focus primarily on improving accuracy of the assembly, making them computationally challenging for applications on large high-throughput sequence data. Therefore, there is a need to develop haplotype reconstruction algorithms that are not only accurate but also highly scalable.'),
(78639, 2014, 'bio', 'Probabilistic single-individual haplotyping', 'Kuleshov, Volodymyr', 'Department of Computer Science, Stanford University, Stanford, CA 94305, USA.', 'United States', 29, 'Algorithms|Genome, Human|Genomics|Haplotypes|Humans|Likelihood Functions|Models, Statistical|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu484', '25161223', 'Accurate haplotyping-determining from which parent particular portions of the genome are inherited-is still mostly an unresolved problem in genomics. This problem has only recently started to become tractable, thanks to the development of new long read sequencing technologies. Here, we introduce ProbHap, a haplotyping algorithm targeted at such technologies. The main algorithmic idea of ProbHap is a new dynamic programming algorithm that exactly optimizes a likelihood function specified by a probabilistic graphical model and which generalizes a popular objective called the minimum error correction. In addition to being accurate, ProbHap also provides confidence scores at phased positions.'),
(78640, 2014, 'bio', 'Two-dimensional segmentation for analyzing Hi-C data', 'Lévy-Leduc, Celine|Delattre, M|Mary-Huard, T|Robin, S', 'AgroParisTech/INRA MIA 518, 75005 Paris and UMR de Génétique Végétale, INRA/Univ. Paris-Sud/CNRS, 91190 Gif-sur-Yvette, France.|AgroParisTech/INRA MIA 518, 75005 Paris and UMR de Génétique Végétale, INRA/Univ. Paris-Sud/CNRS, 91190 Gif-sur-Yvette, France.|AgroParisTech/INRA MIA 518, 75005 Paris and UMR de Génétique Végétale, INRA/Univ. Paris-Sud/CNRS, 91190 Gif-sur-Yvette, France AgroParisTech/INRA MIA 518, 75005 Paris and UMR de Génétique Végétale, INRA/Univ. Paris-Sud/CNRS, 91190 Gif-sur-Yvette, France.|AgroParisTech/INRA MIA 518, 75005 Paris and UMR de Génétique Végétale, INRA/Univ. Paris-Sud/CNRS, 91190 Gif-sur-Yvette, France.', 'France|France|France|France', 68, 'Animals|Chromatin|Chromosomes, Human|Chromosomes, Mammalian|High-Throughput Nucleotide Sequencing|Humans|Mice|Models, Statistical|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu443', '25161224', 'The spatial conformation of the chromosome has a deep influence on gene regulation and expression. Hi-C technology allows the evaluation of the spatial proximity between any pair of loci along the genome. It results in a data matrix where blocks corresponding to (self-)interacting regions appear. The delimitation of such blocks is critical to better understand the spatial organization of the chromatin. From a computational point of view, it results in a 2D segmentation problem.'),
(78641, 2014, 'bio', 'Broad-Enrich: functional interpretation of large sets of broad genomic regions', 'Cavalcante, Raymond G|Lee, Chee|Welch, Ryan P|Patil, Snehal|Weymouth, Terry|Scott, Laura J|Sartor, Maureen A', 'Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.', 'United States|United States|United States|United States|United States|United States|United States', 5, 'Cell Line|Chromatin Immunoprecipitation|Genetic Loci|Genomics|High-Throughput Nucleotide Sequencing|Histones|Humans|Logistic Models|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btu444', '25161225', 'Functional enrichment testing facilitates the interpretation of Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) data in terms of pathways and other biological contexts. Previous methods developed and used to test for key gene sets affected in ChIP-seq experiments treat peaks as points, and are based on the number of peaks associated with a gene or a binary score for each gene. These approaches work well for transcription factors, but histone modifications often occur over broad domains, and across multiple genes.'),
(78642, 2014, 'bio', 'Estimating the activity of transcription factors by the effect on their target genes', 'Schacht, Theresa|Oswald, Marcus|Eils, Roland|Eichmüller, Stefan B|König, Rainer', 'Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, D-07747 Jena, Erlanger Allee 101, Network Modeling, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute Jena, Beutenbergstrasse 11a, 07745 Jena, Theoretical Bioinformatics, German Cancer Research Center, INF 580, 69121 Heidelberg, Department of Bioinformatics and Functional Genomics, Institute of Pharmacy and Molecular Biotechnology, and Bioquant, University of Heidelberg, Im Neuenheimer Feld 267 and Division Translational Immunology, Group Tumor Antigens, German Cancer Research Center (DKFZ), INF 280, 69120 Heidelberg, Germany Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, D-07747 Jena, Erlanger Allee 101, Network Modeling, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute Jena, Beutenbergstrasse 11a, 07745 Jena, Theoretical Bioinformatics, German Cancer Research Center, INF 580, 69121 Heidelberg, Department of Bioinformatics and Functional Genomics, Institute of Pharmacy and Molecular Biotechnology, and Bioquant, University of Heidelberg, Im Neuenheimer Feld 267 and Division Translational Immunology, Group Tumor Antigens, German Cancer Research Center (DKFZ), INF 280, 69120 Heidelberg, Germany Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, D-07747 Jena, Erlanger Allee 101, Network Modeling, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute Jena, Beutenbergstrasse 11a, 07745 Jena, Theoretical Bioinformatics, German Cancer Research Center, INF 580, 69121 Heidelberg, Department of Bioinformatics and Functional Genomics, Institute of Pharmacy and Molecular Biotechnology, and Bioquant, University of Heidelberg, Im Neuenheimer Feld 267 and Division Translational Immunology, Group Tumor Antigens, German Cancer R|Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, D-07747 Jena, Erlanger Allee 101, Network Modeling, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute Jena, Beutenbergstrasse 11a, 07745 Jena, Theoretical Bioinformatics, German Cancer Research Center, INF 580, 69121 Heidelberg, Department of Bioinformatics and Functional Genomics, Institute of Pharmacy and Molecular Biotechnology, and Bioquant, University of Heidelberg, Im Neuenheimer Feld 267 and Division Translational Immunology, Group Tumor Antigens, German Cancer Research Center (DKFZ), INF 280, 69120 Heidelberg, Germany Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, D-07747 Jena, Erlanger Allee 101, Network Modeling, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute Jena, Beutenbergstrasse 11a, 07745 Jena, Theoretical Bioinformatics, German Cancer Research Center, INF 580, 69121 Heidelberg, Department of Bioinformatics and Functional Genomics, Institute of Pharmacy and Molecular Biotechnology, and Bioquant, University of Heidelberg, Im Neuenheimer Feld 267 and Division Translational Immunology, Group Tumor Antigens, German Cancer Research Center (DKFZ), INF 280, 69120 Heidelberg, Germany.|Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, D-07747 Jena, Erlanger Allee 101, Network Modeling, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute Jena, Beutenbergstrasse 11a, 07745 Jena, Theoretical Bioinformatics, German Cancer Research Center, INF 580, 69121 Heidelberg, Department of Bioinformatics and Functional Genomics, Institute of Pharmacy and Molecular Biotechnology, and Bioquant, University of Heidelberg, Im Neuenheimer Feld 267 and Division Translational Immunology, Group Tumor Antigens, German Cancer Research Center (DKFZ), INF 280, 69120 Heidelberg, Germany Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, D-07747 Jena, Erlanger Allee 101, Network Modeling, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute Jena, Beutenbergstrasse 11a, 07745 Jena, Theoretical Bioinformatics, German Cancer Research Center, INF 580, 69121 Heidelberg, Department of Bioinformatics and Functional Genomics, Institute of Pharmacy and Molecular Biotechnology, and Bioquant, University of Heidelberg, Im Neuenheimer Feld 267 and Division Translational Immunology, Group Tumor Antigens, German Cancer Research Center (DKFZ), INF 280, 69120 Heidelberg, Germany.|Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, D-07747 Jena, Erlanger Allee 101, Network Modeling, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute Jena, Beutenbergstrasse 11a, 07745 Jena, Theoretical Bioinformatics, German Cancer Research Center, INF 580, 69121 Heidelberg, Department of Bioinformatics and Functional Genomics, Institute of Pharmacy and Molecular Biotechnology, and Bioquant, University of Heidelberg, Im Neuenheimer Feld 267 and Division Translational Immunology, Group Tumor Antigens, German Cancer Research Center (DKFZ), INF 280, 69120 Heidelberg, Germany.|Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, D-07747 Jena, Erlanger Allee 101, Network Modeling, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute Jena, Beutenbergstrasse 11a, 07745 Jena, Theoretical Bioinformatics, German Cancer Research Center, INF 580, 69121 Heidelberg, Department of Bioinformatics and Functional Genomics, Institute of Pharmacy and Molecular Biotechnology, and Bioquant, University of Heidelberg, Im Neuenheimer Feld 267 and Division Translational Immunology, Group Tumor Antigens, German Cancer Research Center (DKFZ), INF 280, 69120 Heidelberg, Germany Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, D-07747 Jena, Erlanger Allee 101, Network Modeling, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute Jena, Beutenbergstrasse 11a, 07745 Jena, Theoretical Bioinformatics, German Cancer Research Center, INF 580, 69121 Heidelberg, Department of Bioinformatics and Functional Genomics, Institute of Pharmacy and Molecular Biotechnology, and Bioquant, University of Heidelberg, Im Neuenheimer Feld 267 and Division Translational Immunology, Group Tumor Antigens, German Cancer Research Center (DKFZ), INF 280, 69120 Heidelberg, Germany Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, D-07747 Jena, Erlanger Allee 101, Network Modeling, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute Jena, Beutenbergstrasse 11a, 07745 Jena, Theoretical Bioinformatics, German Cancer Research Center, INF 580, 69121 Heidelberg, Department of Bioinformatics and Functional Genomics, Institute of Pharmacy and Molecular Biotechnology, and Bioquant, University of Heidelberg, Im Neuenheimer Feld 267 and Division Translational Immunology, Group Tumor Antigens, German Cancer R', 'Germany|Germany|Germany|Germany|Germany', 24, 'Cell Line, Tumor|Gene Expression Regulation|Humans|Melanocytes|Promoter Regions, Genetic|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btu446', '25161226', 'Understanding regulation of transcription is central for elucidating cellular regulation. Several statistical and mechanistic models have come up the last couple of years explaining gene transcription levels using information of potential transcriptional regulators as transcription factors (TFs) and information from epigenetic modifications. The activity of TFs is often inferred by their transcription levels, promoter binding and epigenetic effects. However, in principle, these methods do not take hard-to-measure influences such as post-transcriptional modifications into account.'),
(78643, 2014, 'bio', 'Modeling DNA methylation dynamics with approaches from phylogenetics', 'Capra, John A|Kostka, Dennis', 'Center for Human Genetics Research, Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, Departments of Developmental Biology and Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA 15201, USA Center for Human Genetics Research, Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, Departments of Developmental Biology and Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA 15201, USA.|Center for Human Genetics Research, Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, Departments of Developmental Biology and Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA 15201, USA Center for Human Genetics Research, Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, Departments of Developmental Biology and Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA 15201, USA.', 'United States|United States', 13, 'Animals|Base Sequence|Cell Differentiation|CpG Islands|DNA|DNA Methylation|Genomics|Markov Chains|Mice|Models, Genetic|Phylogeny', 'Journal Article', '10.1093/bioinformatics/btu445', '25161227', 'Methylation of CpG dinucleotides is a prevalent epigenetic modification that is required for proper development in vertebrates. Genome-wide DNA methylation assays have become increasingly common, and this has enabled characterization of DNA methylation in distinct stages across differentiating cellular lineages. Changes in CpG methylation are essential to cellular differentiation, however, current methods for modeling methylation dynamics do not account for the dependency structure between precursor and dependent cell types.'),
(78644, 2014, 'bio', 'Identifying transcription factor complexes and their roles', 'Will, Thorsten|Helms, Volkhard', 'Center for Bioinformatics, Campus Building E2.1, Saarland University, D-66123 Saarbrücken, Germany.|Center for Bioinformatics, Campus Building E2.1, Saarland University, D-66123 Saarbrücken, Germany.', 'Germany|Germany', 10, 'Algorithms|Protein Interaction Domains and Motifs|Protein Interaction Mapping|Saccharomyces cerevisiae Proteins|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btu448', '25161228', 'Eukaryotic gene expression is controlled through molecular logic circuits that combine regulatory signals of many different factors. In particular, complexation of transcription factors (TFs) and other regulatory proteins is a prevailing and highly conserved mechanism of signal integration within critical regulatory pathways and enables us to infer controlled genes as well as the exerted regulatory mechanism. Common approaches for protein complex prediction that only use protein interaction networks, however, are designed to detect self-contained functional complexes and have difficulties to reveal dynamic combinatorial assemblies of physically interacting proteins.'),
(78645, 2014, 'bio', 'Personalized identification of altered pathways in cancer using accumulated normal tissue data', 'Ahn, TaeJin|Lee, Eunjin|Huh, Nam|Park, Taesung', 'Samsung Advanced Institute of Technology, 130, Suwon-si, Gyeonggi-do, 443-803, Korea, Samsung Genome Institute, Seoul, 135-710, Korea, Interdisciplinary Program in Bioinformatics and Department of Statistics, Seoul National University, Seoul, South Korea Samsung Advanced Institute of Technology, 130, Suwon-si, Gyeonggi-do, 443-803, Korea, Samsung Genome Institute, Seoul, 135-710, Korea, Interdisciplinary Program in Bioinformatics and Department of Statistics, Seoul National University, Seoul, South Korea Samsung Advanced Institute of Technology, 130, Suwon-si, Gyeonggi-do, 443-803, Korea, Samsung Genome Institute, Seoul, 135-710, Korea, Interdisciplinary Program in Bioinformatics and Department of Statistics, Seoul National University, Seoul, South Korea.|Samsung Advanced Institute of Technology, 130, Suwon-si, Gyeonggi-do, 443-803, Korea, Samsung Genome Institute, Seoul, 135-710, Korea, Interdisciplinary Program in Bioinformatics and Department of Statistics, Seoul National University, Seoul, South Korea Samsung Advanced Institute of Technology, 130, Suwon-si, Gyeonggi-do, 443-803, Korea, Samsung Genome Institute, Seoul, 135-710, Korea, Interdisciplinary Program in Bioinformatics and Department of Statistics, Seoul National University, Seoul, South Korea.|Samsung Advanced Institute of Technology, 130, Suwon-si, Gyeonggi-do, 443-803, Korea, Samsung Genome Institute, Seoul, 135-710, Korea, Interdisciplinary Program in Bioinformatics and Department of Statistics, Seoul National University, Seoul, South Korea.|Samsung Advanced Institute of Technology, 130, Suwon-si, Gyeonggi-do, 443-803, Korea, Samsung Genome Institute, Seoul, 135-710, Korea, Interdisciplinary Program in Bioinformatics and Department of Statistics, Seoul National University, Seoul, South Korea Samsung Advanced Institute of Technology, 130, Suwon-si, Gyeonggi-do, 443-803, Korea, Samsung Genome Institute, Seoul, 135-710, Korea, Interdisciplinary Program in Bioinformatics and Department of Statistics, Seoul National University, Seoul, South Korea.', '-|-|-|-', 61, 'Adenocarcinoma|Adenocarcinoma of Lung|Colon|Colonic Neoplasms|Gene Expression Profiling|Humans|Lung|Lung Neoplasms|Neoplasms|Survival Analysis', 'Journal Article', '10.1093/bioinformatics/btu449', '25161229', 'Identifying altered pathways in an individual is important for understanding disease mechanisms and for the future application of custom therapeutic decisions. Existing pathway analysis techniques are mainly focused on discovering altered pathways between normal and cancer groups and are not suitable for identifying the pathway aberrance that may occur in an individual sample. A simple way to identify individuals pathway aberrance is to compare normal and tumor data from the same individual. However, the matched normal data from the same individual are often unavailable in clinical situation. Therefore, we suggest a new approach for the personalized identification of altered pathways, making special use of accumulated normal data in cases when a patients matched normal data are unavailable. The philosophy behind our method is to quantify the aberrance of an individual samples pathway by comparing it with accumulated normal samples. We propose and examine personalized extensions of pathway statistics, overrepresentation analysis and functional class scoring, to generate individualized pathway aberrance score.'),
(78646, 2014, 'bio', 'Alignment-free protein interaction network comparison', 'Ali, Waqar|Rito, Tiago|Reinert, Gesine|Sun, Fengzhu|Deane, Charlotte M', 'Department of Statistics, University of Oxford, Oxford OX1 3TG, UK and Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, CA 90089-2910, USA.|Department of Statistics, University of Oxford, Oxford OX1 3TG, UK and Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, CA 90089-2910, USA.|Department of Statistics, University of Oxford, Oxford OX1 3TG, UK and Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, CA 90089-2910, USA.|Department of Statistics, University of Oxford, Oxford OX1 3TG, UK and Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, CA 90089-2910, USA.|Department of Statistics, University of Oxford, Oxford OX1 3TG, UK and Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, CA 90089-2910, USA.', 'United States|United States|United States|United States|United States', 24, 'Algorithms|Animals|Biological Evolution|Humans|Phylogeny|Protein Interaction Mapping', 'Journal Article', '10.1093/bioinformatics/btu447', '25161230', 'Biological network comparison software largely relies on the concept of alignment where close matches between the nodes of two or more networks are sought. These node matches are based on sequence similarity and/or interaction patterns. However, because of the incomplete and error-prone datasets currently available, such methods have had limited success. Moreover, the results of network alignment are in general not amenable for distance-based evolutionary analysis of sets of networks. In this article, we describe Netdis, a topology-based distance measure between networks, which offers the possibility of network phylogeny reconstruction.'),
(78647, 2014, 'bio', 'HubAlign: an accurate and efficient method for global alignment of protein-protein interaction networks', 'Hashemifar, Somaye|Xu, Jinbo', 'Toyota Technological Institute at Chicago, Chicago, IL 60637, USA.|Toyota Technological Institute at Chicago, Chicago, IL 60637, USA.', 'United States|United States', 54, 'Algorithms|Animals|Bacterial Proteins|Caenorhabditis elegans Proteins|Drosophila Proteins|Humans|Mice|Protein Interaction Mapping|Saccharomyces cerevisiae Proteins|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/bioinformatics/btu450', '25161231', 'High-throughput experimental techniques have produced a large amount of protein-protein interaction (PPI) data. The study of PPI networks, such as comparative analysis, shall benefit the understanding of life process and diseases at the molecular level. One way of comparative analysis is to align PPI networks to identify conserved or species-specific subnetwork motifs. A few methods have been developed for global PPI network alignment, but it still remains challenging in terms of both accuracy and efficiency.'),
(78648, 2014, 'bio', 'Experimental design schemes for learning Boolean network models', 'Atias, Nir|Gershenzon, Michal|Labazin, Katia|Sharan, Roded', 'Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel.|Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel.|Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel.|Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel.', 'Israel|Israel|Israel|Israel', 0, 'Algorithms|ErbB Receptors|Humans|Interleukin-1|Models, Biological|Research Design|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btu451', '25161232', 'A holy grail of biological research is a working model of the cell. Current modeling frameworks, especially in the protein-protein interaction domain, are mostly topological in nature, calling for stronger and more expressive network models. One promising alternative is logic-based or Boolean network modeling, which was successfully applied to model signaling regulatory circuits in human. Learning such models requires observing the system under a sufficient number of different conditions. To date, the amount of measured data is the main bottleneck in learning informative Boolean models, underscoring the need for efficient experimental design strategies.'),
(78649, 2014, 'bio', 'TEMPI: probabilistic modeling time-evolving differential PPI networks with multiPle information', 'Kim, Yongsoo|Jang, Jin-Hyeok|Choi, Seungjin|Hwang, Daehee', 'School of Interdisciplinary Bioscience and Bioengineering and Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang 790-784, Korea and Department of New Biology and Center for Plant Aging Research, Institute for Basic Science, Daegu Gyeongbuk Institute of Science and Technology, Daegu 711-873, Korea.|School of Interdisciplinary Bioscience and Bioengineering and Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang 790-784, Korea and Department of New Biology and Center for Plant Aging Research, Institute for Basic Science, Daegu Gyeongbuk Institute of Science and Technology, Daegu 711-873, Korea.|School of Interdisciplinary Bioscience and Bioengineering and Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang 790-784, Korea and Department of New Biology and Center for Plant Aging Research, Institute for Basic Science, Daegu Gyeongbuk Institute of Science and Technology, Daegu 711-873, Korea.|School of Interdisciplinary Bioscience and Bioengineering and Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang 790-784, Korea and Department of New Biology and Center for Plant Aging Research, Institute for Basic Science, Daegu Gyeongbuk Institute of Science and Technology, Daegu 711-873, Korea School of Interdisciplinary Bioscience and Bioengineering and Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang 790-784, Korea and Department of New Biology and Center for Plant Aging Research, Institute for Basic Science, Daegu Gyeongbuk Institute of Science and Technology, Daegu 711-873, Korea.', '-|-|-|-', 0, 'Cell Cycle|Gene Expression|Models, Statistical|Protein Interaction Mapping', 'Journal Article', '10.1093/bioinformatics/btu454', '25161233', 'Time-evolving differential protein-protein interaction (PPI) networks are essential to understand serial activation of differentially regulated (up- or downregulated) cellular processes (DRPs) and their interplays over time. Despite developments in the network inference, current methods are still limited in identifying temporal transition of structures of PPI networks, DRPs associated with the structural transition and the interplays among the DRPs over time.'),
(78650, 2014, 'bio', 'Stronger findings for metabolomics through Bayesian modeling of multiple peaks and compound correlations', 'Suvitaival, Tommi|Rogers, Simon|Kaski, Samuel', 'Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, FI-00076 Espoo, Finland, School of Computing Science, University of Glasgow, Glasgow G12 8QQ, UK and Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki, Finland.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, FI-00076 Espoo, Finland, School of Computing Science, University of Glasgow, Glasgow G12 8QQ, UK and Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki, Finland.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, FI-00076 Espoo, Finland, School of Computing Science, University of Glasgow, Glasgow G12 8QQ, UK and Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki, Finland Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, FI-00076 Espoo, Finland, School of Computing Science, University of Glasgow, Glasgow G12 8QQ, UK and Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki, Finland.', 'Finland|Finland|Finland', 5, 'Bayes Theorem|Mass Spectrometry|Metabolomics|Sample Size', 'Journal Article', '10.1093/bioinformatics/btu455', '25161234', 'Data analysis for metabolomics suffers from uncertainty because of the noisy measurement technology and the small sample size of experiments. Noise and the small sample size lead to a high probability of false findings. Further, individual compounds have natural variation between samples, which in many cases renders them unreliable as biomarkers. However, the levels of similar compounds are typically highly correlated, which is a phenomenon that we model in this work.'),
(78651, 2014, 'bio', 'Causal network inference using biochemical kinetics', 'Oates, Chris J|Dondelinger, Frank|Bayani, Nora|Korkola, James|Gray, Joe W|Mukherjee, Sach', 'Department of Statistics, University of Warwick, Coventry, CV4 7AL, MRC Biostatistics Unit, Cambridge, CB2 0SR, UK, Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94710, Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239-3098, USA and School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SP, UK.|Department of Statistics, University of Warwick, Coventry, CV4 7AL, MRC Biostatistics Unit, Cambridge, CB2 0SR, UK, Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94710, Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239-3098, USA and School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SP, UK.|Department of Statistics, University of Warwick, Coventry, CV4 7AL, MRC Biostatistics Unit, Cambridge, CB2 0SR, UK, Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94710, Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239-3098, USA and School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SP, UK.|Department of Statistics, University of Warwick, Coventry, CV4 7AL, MRC Biostatistics Unit, Cambridge, CB2 0SR, UK, Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94710, Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239-3098, USA and School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SP, UK.|Department of Statistics, University of Warwick, Coventry, CV4 7AL, MRC Biostatistics Unit, Cambridge, CB2 0SR, UK, Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94710, Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239-3098, USA and School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SP, UK.|Department of Statistics, University of Warwick, Coventry, CV4 7AL, MRC Biostatistics Unit, Cambridge, CB2 0SR, UK, Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94710, Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239-3098, USA and School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SP, UK Department of Statistics, University of Warwick, Coventry, CV4 7AL, MRC Biostatistics Unit, Cambridge, CB2 0SR, UK, Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94710, Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239-3098, USA and School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SP, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Bayes Theorem|Cell Line, Tumor|Humans|Kinetics|MAP Kinase Signaling System|Models, Chemical|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btu452', '25161235', 'Networks are widely used as structural summaries of biochemical systems. Statistical estimation of networks is usually based on linear or discrete models. However, the dynamics of biochemical systems are generally non-linear, suggesting that suitable non-linear formulations may offer gains with respect to causal network inference and aid in associated prediction problems.'),
(78652, 2014, 'bio', 'Effects of small particle numbers on long-term behaviour in discrete biochemical systems', 'Kreyssig, Peter|Wozar, Christian|Peter, Stephan|Veloz, Tomás|Ibrahim, Bashar|Dittrich, Peter', 'Bio Systems Analysis Group, Department of Mathematics and Computer Science and Jena Centre for Bioinformatics, Friedrich Schiller University Jena, 07743 Jena, Germany, Mathematics Department, University of British Columbia, Kelowna, BC V1V 1V7, Canada, Instituto de Filosofía y Ciencias de la Complejidad - IFICC, Los Alerces 3024 Ñuñoa, Santiago, Chile, Center Leo Apostel, Vrije Universiteit Brussel, B-1160 Brussels, Belgium, Umm Al-Qura University, 1109 Makkah Al-Mukarramah and Al-Qunfudah Center for Scientific Research (QCSR), 21912 Al-Qunfudah, Kingdom of Saudi Arabia.|Bio Systems Analysis Group, Department of Mathematics and Computer Science and Jena Centre for Bioinformatics, Friedrich Schiller University Jena, 07743 Jena, Germany, Mathematics Department, University of British Columbia, Kelowna, BC V1V 1V7, Canada, Instituto de Filosofía y Ciencias de la Complejidad - IFICC, Los Alerces 3024 Ñuñoa, Santiago, Chile, Center Leo Apostel, Vrije Universiteit Brussel, B-1160 Brussels, Belgium, Umm Al-Qura University, 1109 Makkah Al-Mukarramah and Al-Qunfudah Center for Scientific Research (QCSR), 21912 Al-Qunfudah, Kingdom of Saudi Arabia.|Bio Systems Analysis Group, Department of Mathematics and Computer Science and Jena Centre for Bioinformatics, Friedrich Schiller University Jena, 07743 Jena, Germany, Mathematics Department, University of British Columbia, Kelowna, BC V1V 1V7, Canada, Instituto de Filosofía y Ciencias de la Complejidad - IFICC, Los Alerces 3024 Ñuñoa, Santiago, Chile, Center Leo Apostel, Vrije Universiteit Brussel, B-1160 Brussels, Belgium, Umm Al-Qura University, 1109 Makkah Al-Mukarramah and Al-Qunfudah Center for Scientific Research (QCSR), 21912 Al-Qunfudah, Kingdom of Saudi Arabia.|Bio Systems Analysis Group, Department of Mathematics and Computer Science and Jena Centre for Bioinformatics, Friedrich Schiller University Jena, 07743 Jena, Germany, Mathematics Department, University of British Columbia, Kelowna, BC V1V 1V7, Canada, Instituto de Filosofía y Ciencias de la Complejidad - IFICC, Los Alerces 3024 Ñuñoa, Santiago, Chile, Center Leo Apostel, Vrije Universiteit Brussel, B-1160 Brussels, Belgium, Umm Al-Qura University, 1109 Makkah Al-Mukarramah and Al-Qunfudah Center for Scientific Research (QCSR), 21912 Al-Qunfudah, Kingdom of Saudi Arabia Bio Systems Analysis Group, Department of Mathematics and Computer Science and Jena Centre for Bioinformatics, Friedrich Schiller University Jena, 07743 Jena, Germany, Mathematics Department, University of British Columbia, Kelowna, BC V1V 1V7, Canada, Instituto de Filosofía y Ciencias de la Complejidad - IFICC, Los Alerces 3024 Ñuñoa, Santiago, Chile, Center Leo Apostel, Vrije Universiteit Brussel, B-1160 Brussels, Belgium, Umm Al-Qura University, 1109 Makkah Al-Mukarramah and Al-Qunfudah Center for Scientific Research (QCSR), 21912 Al-Qunfudah, Kingdom of Saudi Arabia Bio Systems Analysis Group, Department of Mathematics and Computer Science and Jena Centre for Bioinformatics, Friedrich Schiller University Jena, 07743 Jena, Germany, Mathematics Department, University of British Columbia, Kelowna, BC V1V 1V7, Canada, Instituto de Filosofía y Ciencias de la Complejidad - IFICC, Los Alerces 3024 Ñuñoa, Santiago, Chile, Center Leo Apostel, Vrije Universiteit Brussel, B-1160 Brussels, Belgium, Umm Al-Qura University, 1109 Makkah Al-Mukarramah and Al-Qunfudah Center for Scientific Research (QCSR), 21912 Al-Qunfudah, Kingdom of Saudi Arabia.|Bio Systems Analysis Group, Department of Mathematics and Computer Science and Jena Centre for Bioinformatics, Friedrich Schiller University Jena, 07743 Jena, Germany, Mathematics Department, University of British Columbia, Kelowna, BC V1V 1V7, Canada, Instituto de Filosofía y Ciencias de la Complejidad - IFICC, Los Alerces 3024 Ñuñoa, Santiago, Chile, Center Leo Apostel, Vrije Universiteit Brussel, B-1160 Brussels, Belgium, Umm Al-Qura University, 1109 Makkah Al-Mukarramah and Al-Qunfudah Center for Scientific Research (QCSR), 21912 Al-Qunfudah, Kingdom of Saudi Arabia Bio Systems Analysis Group, Department of Mathematics and Computer Science and Jena Centre for Bioinformatics, Friedrich Schiller University Jena, 07743 Jena, Germany, Mathematics Department, University of British Columbia, Kelowna, BC V1V 1V7, Canada, Instituto de Filosofía y Ciencias de la Complejidad - IFICC, Los Alerces 3024 Ñuñoa, Santiago, Chile, Center Leo Apostel, Vrije Universiteit Brussel, B-1160 Brussels, Belgium, Umm Al-Qura University, 1109 Makkah Al-Mukarramah and Al-Qunfudah Center for Scientific Research (QCSR), 21912 Al-Qunfudah, Kingdom of Saudi Arabia Bio Systems Analysis Group, Department of Mathematics and Computer Science and Jena Centre for Bioinformatics, Friedrich Schiller University Jena, 07743 Jena, Germany, Mathematics Department, University of British Columbia, Kelowna, BC V1V 1V7, Canada, Instituto de Filosofía y Ciencias de la Complejidad - IFICC, Los Alerces 3024 Ñuñoa, Santiago, Chile, Center Leo Apostel, Vrije Universiteit Brussel, B-1160 Brussels, Belgium, Umm Al-Qura University, 1109 Makkah Al-Mukarramah and Al-Qunfudah Center for Scientific Research (QCSR), 21912 Al-Qunfudah, Kingdom of Saudi Arabia.|Bio Systems Analysis Group, Department of Mathematics and Computer Science and Jena Centre for Bioinformatics, Friedrich Schiller University Jena, 07743 Jena, Germany, Mathematics Department, University of British Columbia, Kelowna, BC V1V 1V7, Canada, Instituto de Filosofía y Ciencias de la Complejidad - IFICC, Los Alerces 3024 Ñuñoa, Santiago, Chile, Center Leo Apostel, Vrije Universiteit Brussel, B-1160 Brussels, Belgium, Umm Al-Qura University, 1109 Makkah Al-Mukarramah and Al-Qunfudah Center for Scientific Research (QCSR), 21912 Al-Qunfudah, Kingdom of Saudi Arabia.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 19, 'Databases, Factual|Models, Biological|Spindle Apparatus|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btu453', '25161236', 'The functioning of many biological processes depends on the appearance of only a small number of a single molecular species. Additionally, the observation of molecular crowding leads to the insight that even a high number of copies of species do not guarantee their interaction. How single particles contribute to stabilizing biological systems is not well understood yet. Hence, we aim at determining the influence of single molecules on the long-term behaviour of biological systems, i.e. whether they can reach a steady state.'),
(78653, 2014, 'bio', 'PconsFold: improved contact predictions improve protein models', 'Michel, Mirco|Hayat, Sikander|Skwark, Marcin J|Sander, Chris|Marks, Debora S|Elofsson, Arne', 'Department of Biochemistry and Biophysics, Stockholm University, 10691 Stockholm, Sweden, Science for Life Laboratory, Stockholm University, Box 1031, 17121 Solna, Sweden, Department of Systems Biology, Harvard Medical School, Boston, MA, USA, Department of Information and Computer Science, Aalto University, PO Box 15400, FI-00076 Aalto, Finland and Computational Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA Department of Biochemistry and Biophysics, Stockholm University, 10691 Stockholm, Sweden, Science for Life Laboratory, Stockholm University, Box 1031, 17121 Solna, Sweden, Department of Systems Biology, Harvard Medical School, Boston, MA, USA, Department of Information and Computer Science, Aalto University, PO Box 15400, FI-00076 Aalto, Finland and Computational Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA.|Department of Biochemistry and Biophysics, Stockholm University, 10691 Stockholm, Sweden, Science for Life Laboratory, Stockholm University, Box 1031, 17121 Solna, Sweden, Department of Systems Biology, Harvard Medical School, Boston, MA, USA, Department of Information and Computer Science, Aalto University, PO Box 15400, FI-00076 Aalto, Finland and Computational Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA.|Department of Biochemistry and Biophysics, Stockholm University, 10691 Stockholm, Sweden, Science for Life Laboratory, Stockholm University, Box 1031, 17121 Solna, Sweden, Department of Systems Biology, Harvard Medical School, Boston, MA, USA, Department of Information and Computer Science, Aalto University, PO Box 15400, FI-00076 Aalto, Finland and Computational Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA.|Department of Biochemistry and Biophysics, Stockholm University, 10691 Stockholm, Sweden, Science for Life Laboratory, Stockholm University, Box 1031, 17121 Solna, Sweden, Department of Systems Biology, Harvard Medical School, Boston, MA, USA, Department of Information and Computer Science, Aalto University, PO Box 15400, FI-00076 Aalto, Finland and Computational Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA.|Department of Biochemistry and Biophysics, Stockholm University, 10691 Stockholm, Sweden, Science for Life Laboratory, Stockholm University, Box 1031, 17121 Solna, Sweden, Department of Systems Biology, Harvard Medical School, Boston, MA, USA, Department of Information and Computer Science, Aalto University, PO Box 15400, FI-00076 Aalto, Finland and Computational Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA.|Department of Biochemistry and Biophysics, Stockholm University, 10691 Stockholm, Sweden, Science for Life Laboratory, Stockholm University, Box 1031, 17121 Solna, Sweden, Department of Systems Biology, Harvard Medical School, Boston, MA, USA, Department of Information and Computer Science, Aalto University, PO Box 15400, FI-00076 Aalto, Finland and Computational Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA Department of Biochemistry and Biophysics, Stockholm University, 10691 Stockholm, Sweden, Science for Life Laboratory, Stockholm University, Box 1031, 17121 Solna, Sweden, Department of Systems Biology, Harvard Medical School, Boston, MA, USA, Department of Information and Computer Science, Aalto University, PO Box 15400, FI-00076 Aalto, Finland and Computational Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA.', 'Finland|Finland|Finland|Finland|Finland|Finland', 0, 'Algorithms|Amino Acids|Models, Molecular|Protein Conformation|Protein Folding|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btu458', '25161237', 'Recently it has been shown that the quality of protein contact prediction from evolutionary information can be improved significantly if direct and indirect information is separated. Given sufficiently large protein families, the contact predictions contain sufficient information to predict the structure of many protein families. However, since the first studies contact prediction methods have improved. Here, we ask how much the final models are improved if improved contact predictions are used.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78654, 2014, 'bio', 'CRISPRstrand: predicting repeat orientations to determine the crRNA-encoding strand at CRISPR loci', 'Alkhnbashi, Omer S|Costa, Fabrizio|Shah, Shiraz A|Garrett, Roger A|Saunders, Sita J|Backofen, Rolf', 'Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany, Department of Biology, University of Copenhagen, Archaea Centre, Ole Maaloes Vej 5, DK2200 Copenhagen, Denmark and BIOSS Centre for Biological Signalling Studies, Cluster of Excellence, University of Freiburg, Germany.|Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany, Department of Biology, University of Copenhagen, Archaea Centre, Ole Maaloes Vej 5, DK2200 Copenhagen, Denmark and BIOSS Centre for Biological Signalling Studies, Cluster of Excellence, University of Freiburg, Germany.|Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany, Department of Biology, University of Copenhagen, Archaea Centre, Ole Maaloes Vej 5, DK2200 Copenhagen, Denmark and BIOSS Centre for Biological Signalling Studies, Cluster of Excellence, University of Freiburg, Germany.|Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany, Department of Biology, University of Copenhagen, Archaea Centre, Ole Maaloes Vej 5, DK2200 Copenhagen, Denmark and BIOSS Centre for Biological Signalling Studies, Cluster of Excellence, University of Freiburg, Germany.|Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany, Department of Biology, University of Copenhagen, Archaea Centre, Ole Maaloes Vej 5, DK2200 Copenhagen, Denmark and BIOSS Centre for Biological Signalling Studies, Cluster of Excellence, University of Freiburg, Germany.|Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany, Department of Biology, University of Copenhagen, Archaea Centre, Ole Maaloes Vej 5, DK2200 Copenhagen, Denmark and BIOSS Centre for Biological Signalling Studies, Cluster of Excellence, University of Freiburg, Germany Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany, Department of Biology, University of Copenhagen, Archaea Centre, Ole Maaloes Vej 5, DK2200 Copenhagen, Denmark and BIOSS Centre for Biological Signalling Studies, Cluster of Excellence, University of Freiburg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 26, 'Archaea|Base Sequence|CRISPR-Cas Systems|Clustered Regularly Interspaced Short Palindromic Repeats|Conserved Sequence|Genetic Loci|Molecular Sequence Annotation|RNA|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu459', '25161238', 'The discovery of CRISPR-Cas systems almost 20 years ago rapidly changed our perception of the bacterial and archaeal immune systems. CRISPR loci consist of several repetitive DNA sequences called repeats, inter-spaced by stretches of variable length sequences called spacers. This CRISPR array is transcribed and processed into multiple mature RNA species (crRNAs). A single crRNA is integrated into an interference complex, together with CRISPR-associated (Cas) proteins, to bind and degrade invading nucleic acids. Although existing bioinformatics tools can recognize CRISPR loci by their characteristic repeat-spacer architecture, they generally output CRISPR arrays of ambiguous orientation and thus do not determine the strand from which crRNAs are processed. Knowledge of the correct orientation is crucial for many tasks, including the classification of CRISPR conservation, the detection of leader regions, the identification of target sites (protospacers) on invading genetic elements and the characterization of protospacer-adjacent motifs.'),
(78655, 2014, 'bio', 'Identification of structural features in chemicals associated with cancer drug response: a systematic data-driven analysis', 'Khan, Suleiman A|Virtanen, Seppo|Kallioniemi, Olli P|Wennerberg, Krister|Poso, Antti|Kaski, Samuel', 'Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, 00076 Espoo, Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University Of Helsinki, 00014 Helsinki, Finland.|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, 00076 Espoo, Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University Of Helsinki, 00014 Helsinki, Finland.|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, 00076 Espoo, Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University Of Helsinki, 00014 Helsinki, Finland.|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, 00076 Espoo, Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University Of Helsinki, 00014 Helsinki, Finland.|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, 00076 Espoo, Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University Of Helsinki, 00014 Helsinki, Finland Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, 00076 Espoo, Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University Of Helsinki, 00014 Helsinki, Finland.|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, 00076 Espoo, Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University Of Helsinki, 00014 Helsinki, Finland Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, 00076 Espoo, Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University Of Helsinki, 00014 Helsinki, Finland.', 'Finland|Finland|Finland|Finland|Finland|Finland', 20, 'Antineoplastic Agents|Bayes Theorem|Cell Line, Tumor|Gene Expression|Humans|Neoplasms|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btu456', '25161239', 'Analysis of relationships of drug structure to biological response is key to understanding off-target and unexpected drug effects, and for developing hypotheses on how to tailor drug therapies. New methods are required for integrated analyses of a large number of chemical features of drugs against the corresponding genome-wide responses of multiple cell models.'),
(78656, 2014, 'bio', 'Assessing the local structural quality of transmembrane protein models using statistical potentials (QMEANBrane)', 'Studer, Gabriel|Biasini, Marco|Schwede, Torsten', 'Biozentrum, University of Basel, Basel, 4056, Switzerland and SIB Swiss Institute of Bioinformatics, Basel, 4056, Switzerland Biozentrum, University of Basel, Basel, 4056, Switzerland and SIB Swiss Institute of Bioinformatics, Basel, 4056, Switzerland.|Biozentrum, University of Basel, Basel, 4056, Switzerland and SIB Swiss Institute of Bioinformatics, Basel, 4056, Switzerland Biozentrum, University of Basel, Basel, 4056, Switzerland and SIB Swiss Institute of Bioinformatics, Basel, 4056, Switzerland.|Biozentrum, University of Basel, Basel, 4056, Switzerland and SIB Swiss Institute of Bioinformatics, Basel, 4056, Switzerland Biozentrum, University of Basel, Basel, 4056, Switzerland and SIB Swiss Institute of Bioinformatics, Basel, 4056, Switzerland.', 'Switzerland|Switzerland|Switzerland', 0, 'Algorithms|Data Interpretation, Statistical|Humans|Membrane Proteins|Models, Molecular', 'Journal Article', '10.1093/bioinformatics/btu457', '25161240', 'Membrane proteins are an important class of biological macromolecules involved in many cellular key processes including signalling and transport. They account for one third of genes in the human genome and >50% of current drug targets. Despite their importance, experimental structural data are sparse, resulting in high expectations for computational modelling tools to help fill this gap. However, as many empirical methods have been trained on experimental structural data, which is biased towards soluble globular proteins, their accuracy for transmembrane proteins is often limited.'),
(78657, 2014, 'bio', 'A new statistical framework to assess structural alignment quality using information compression', 'Collier, James H|Allison, Lloyd|Lesk, Arthur M|Garcia de la Banda, Maria|Konagurthu, Arun S', 'Clayton School of Information Technology, Monash University, Clayton, VIC 3800, Australia and Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA.|Clayton School of Information Technology, Monash University, Clayton, VIC 3800, Australia and Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA.|Clayton School of Information Technology, Monash University, Clayton, VIC 3800, Australia and Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA.|Clayton School of Information Technology, Monash University, Clayton, VIC 3800, Australia and Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA.|Clayton School of Information Technology, Monash University, Clayton, VIC 3800, Australia and Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA.', 'Australia|Australia|Australia|Australia|Australia', 6, 'Algorithms|Data Compression|Data Interpretation, Statistical|Structural Homology, Protein', 'Journal Article', '10.1093/bioinformatics/btu460', '25161241', 'Progress in protein biology depends on the reliability of results from a handful of computational techniques, structural alignments being one. Recent reviews have highlighted substantial inconsistencies and differences between alignment results generated by the ever-growing stock of structural alignment programs. The lack of consensus on how the quality of structural alignments must be assessed has been identified as the main cause for the observed differences. Current methods assess structural alignment quality by constructing a scoring function that attempts to balance conflicting criteria, mainly alignment coverage and fidelity of structures under superposition. This traditional approach to measuring alignment quality, the subject of considerable literature, has failed to solve the problem. Further development along the same lines is unlikely to rectify the current deficiencies in the field.'),
(78658, 2014, 'bio', 'Polytomy refinement for the correction of dubious duplications in gene trees', 'Lafond, Manuel|Chauve, Cedric|Dondi, Riccardo|El-Mabrouk, Nadia', 'Department of Computer Science, Université de Montréal, Montréal, Quebec H3C 3J7, Canada, LaBRI, Université Bordeaux 1, Bordeaux, France, Department of Mathematics, Simon Fraser University, Burnaby (BC) V5A 1S6, Canada and Universitá degli Studi di Bergamo, Bergamo 24129 IT, Italy.|Department of Computer Science, Université de Montréal, Montréal, Quebec H3C 3J7, Canada, LaBRI, Université Bordeaux 1, Bordeaux, France, Department of Mathematics, Simon Fraser University, Burnaby (BC) V5A 1S6, Canada and Universitá degli Studi di Bergamo, Bergamo 24129 IT, Italy Department of Computer Science, Université de Montréal, Montréal, Quebec H3C 3J7, Canada, LaBRI, Université Bordeaux 1, Bordeaux, France, Department of Mathematics, Simon Fraser University, Burnaby (BC) V5A 1S6, Canada and Universitá degli Studi di Bergamo, Bergamo 24129 IT, Italy.|Department of Computer Science, Université de Montréal, Montréal, Quebec H3C 3J7, Canada, LaBRI, Université Bordeaux 1, Bordeaux, France, Department of Mathematics, Simon Fraser University, Burnaby (BC) V5A 1S6, Canada and Universitá degli Studi di Bergamo, Bergamo 24129 IT, Italy.|Department of Computer Science, Université de Montréal, Montréal, Quebec H3C 3J7, Canada, LaBRI, Université Bordeaux 1, Bordeaux, France, Department of Mathematics, Simon Fraser University, Burnaby (BC) V5A 1S6, Canada and Universitá degli Studi di Bergamo, Bergamo 24129 IT, Italy.', 'Canada|Canada|Canada|Canada', 0, 'Algorithms|Animals|Fishes|Genes|Phylogeny', 'Journal Article', '10.1093/bioinformatics/btu463', '25161242', 'Large-scale methods for inferring gene trees are error-prone. Correcting gene trees for weakly supported features often results in non-binary trees, i.e. trees with polytomies, thus raising the natural question of refining such polytomies into binary trees. A feature pointing toward potential errors in gene trees are duplications that are not supported by the presence of multiple gene copies.'),
(78659, 2014, 'bio', 'RidgeRace: ridge regression for continuous ancestral character estimation on phylogenetic trees', 'Kratsch, Christina|McHardy, Alice C', 'Department for Algorithmic Bioinformatics, Heinrich Heine University, Universitätsstr. 1, 40225 Düsseldorf, Germany.|Department for Algorithmic Bioinformatics, Heinrich Heine University, Universitätsstr. 1, 40225 Düsseldorf, Germany.', 'Germany|Germany', 12, 'Algorithms|Female|Humans|Least-Squares Analysis|Mutation|Ovarian Neoplasms|Phenotype|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btu477', '25161243', 'Ancestral character state reconstruction describes a set of techniques for estimating phenotypic or genetic features of species or related individuals that are the predecessors of those present today. Such reconstructions can reach into the distant past and can provide insights into the history of a population or a set of species when fossil data are not available, or they can be used to test evolutionary hypotheses, e.g. on the co-evolution of traits. Typical methods for ancestral character state reconstruction of continuous characters consider the phylogeny of the underlying data and estimate the ancestral process along the branches of the tree. They usually assume a Brownian motion model of character evolution or extensions thereof, requiring specific assumptions on the rate of phenotypic evolution.'),
(78660, 2014, 'bio', 'Point estimates in phylogenetic reconstructions', 'Benner, Philipp|Baxc4x8dxc3xa1k, Miroslav|Bourguignon, Pierre-Yves', 'Max-Planck Institute for Mathematics in the Sciences, 04103 Leipzig, Germany and Isthmus SARL, 75002 Paris, France.|Max-Planck Institute for Mathematics in the Sciences, 04103 Leipzig, Germany and Isthmus SARL, 75002 Paris, France.|Max-Planck Institute for Mathematics in the Sciences, 04103 Leipzig, Germany and Isthmus SARL, 75002 Paris, France Max-Planck Institute for Mathematics in the Sciences, 04103 Leipzig, Germany and Isthmus SARL, 75002 Paris, France.', 'Germany|Germany|Germany', 10, 'Algorithms|Bayes Theorem|Models, Statistical|Phylogeny', 'Journal Article', '10.1093/bioinformatics/btu461', '25161244', 'The construction of statistics for summarizing posterior samples returned by a Bayesian phylogenetic study has so far been hindered by the poor geometric insights available into the space of phylogenetic trees, and ad hoc methods such as the derivation of a consensus tree makeup for the ill-definition of the usual concepts of posterior mean, while bootstrap methods mitigate the absence of a sound concept of variance. Yielding satisfactory results with sufficiently concentrated posterior distributions, such methods fall short of providing a faithful summary of posterior distributions if the data do not offer compelling evidence for a single topology.'),
(78661, 2014, 'bio', 'ASTRAL: genome-scale coalescent-based species tree estimation', 'Mirarab, S|Reaz, R|Bayzid, Md S|Zimmermann, T|Swenson, M S|Warnow, T', 'Department of Computer Science, The University of Texas at Austin, Austin, TX 78712, USA, Departement dinformatique, Ecole Normale Superieure, 45 Rue dUlm, F-75230 Paris Cedex 05, France and Department of Electrical Engineering, The University of Southern California, Los Angeles, CA 90089, USA.|Department of Computer Science, The University of Texas at Austin, Austin, TX 78712, USA, Departement dinformatique, Ecole Normale Superieure, 45 Rue dUlm, F-75230 Paris Cedex 05, France and Department of Electrical Engineering, The University of Southern California, Los Angeles, CA 90089, USA.|Department of Computer Science, The University of Texas at Austin, Austin, TX 78712, USA, Departement dinformatique, Ecole Normale Superieure, 45 Rue dUlm, F-75230 Paris Cedex 05, France and Department of Electrical Engineering, The University of Southern California, Los Angeles, CA 90089, USA.|Department of Computer Science, The University of Texas at Austin, Austin, TX 78712, USA, Departement dinformatique, Ecole Normale Superieure, 45 Rue dUlm, F-75230 Paris Cedex 05, France and Department of Electrical Engineering, The University of Southern California, Los Angeles, CA 90089, USA Department of Computer Science, The University of Texas at Austin, Austin, TX 78712, USA, Departement dinformatique, Ecole Normale Superieure, 45 Rue dUlm, F-75230 Paris Cedex 05, France and Department of Electrical Engineering, The University of Southern California, Los Angeles, CA 90089, USA.|Department of Computer Science, The University of Texas at Austin, Austin, TX 78712, USA, Departement dinformatique, Ecole Normale Superieure, 45 Rue dUlm, F-75230 Paris Cedex 05, France and Department of Electrical Engineering, The University of Southern California, Los Angeles, CA 90089, USA.|Department of Computer Science, The University of Texas at Austin, Austin, TX 78712, USA, Departement dinformatique, Ecole Normale Superieure, 45 Rue dUlm, F-75230 Paris Cedex 05, France and Department of Electrical Engineering, The University of Southern California, Los Angeles, CA 90089, USA.', 'France|France|France|France|France|France', 449, 'Algorithms|Animals|Data Interpretation, Statistical|Genes|Genetic Speciation|Genomics|Mammals|Phylogeny', 'Journal Article', '10.1093/bioinformatics/btu462', '25161245', 'Species trees provide insight into basic biology, including the mechanisms of evolution and how it modifies biomolecular function and structure, biodiversity and co-evolution between genes and species. Yet, gene trees often differ from species trees, creating challenges to species tree estimation. One of the most frequent causes for conflicting topologies between gene trees and species trees is incomplete lineage sorting (ILS), which is modelled by the multi-species coalescent. While many methods have been developed to estimate species trees from multiple genes, some which have statistical guarantees under the multi-species coalescent model, existing methods are too computationally intensive for use with genome-scale analyses or have been shown to have poor accuracy under some realistic conditions.'),
(78662, 2014, 'bio', 'OncodriveROLE classifies cancer driver genes in loss of function and activating mode of action', 'Schroeder, Michael P|Rubio-Perez, Carlota|Tamborero, David|Gonzalez-Perez, Abel|Lopez-Bigas, Nuria', 'Research Unit on Biomedical Informatics, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, E08003 Barcelona and Institució Catalana de Recerca i Estudis Avançats (ICREA), E08010 Barcelona, Spain.|Research Unit on Biomedical Informatics, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, E08003 Barcelona and Institució Catalana de Recerca i Estudis Avançats (ICREA), E08010 Barcelona, Spain.|Research Unit on Biomedical Informatics, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, E08003 Barcelona and Institució Catalana de Recerca i Estudis Avançats (ICREA), E08010 Barcelona, Spain.|Research Unit on Biomedical Informatics, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, E08003 Barcelona and Institució Catalana de Recerca i Estudis Avançats (ICREA), E08010 Barcelona, Spain.|Research Unit on Biomedical Informatics, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, E08003 Barcelona and Institució Catalana de Recerca i Estudis Avançats (ICREA), E08010 Barcelona, Spain Research Unit on Biomedical Informatics, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, E08003 Barcelona and Institució Catalana de Recerca i Estudis Avançats (ICREA), E08010 Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain', 0, 'Algorithms|Artificial Intelligence|Genes, Tumor Suppressor|Genomics|Humans|Mutation|Neoplasms|Oncogenes|Software', 'Journal Article', '10.1093/bioinformatics/btu467', '25161246', 'Several computational methods have been developed to identify cancer drivers genes-genes responsible for cancer development upon specific alterations. These alterations can cause the loss of function (LoF) of the gene product, for instance, in tumor suppressors, or increase or change its activity or function, if it is an oncogene. Distinguishing between these two classes is important to understand tumorigenesis in patients and has implications for therapy decision making. Here, we assess the capacity of multiple gene features related to the pattern of genomic alterations across tumors to distinguish between activating and LoF cancer genes, and we present an automated approach to aid the classification of novel cancer drivers according to their role.'),
(78663, 2014, 'bio', 'Drug susceptibility prediction against a panel of drugs using kernelized Bayesian multitask learning', 'Gönen, Mehmet|Margolin, Adam A', 'Sage Bionetworks, Seattle, WA 98109, USA.|Sage Bionetworks, Seattle, WA 98109, USA.', 'United States|United States', 0, 'Algorithms|Anti-HIV Agents|Antineoplastic Agents|Bayes Theorem|Drug Resistance, Neoplasm|Drug Resistance, Viral|HIV-1|Humans|Software', 'Journal Article', '10.1093/bioinformatics/btu464', '25161247', 'Human immunodeficiency virus (HIV) and cancer require personalized therapies owing to their inherent heterogeneous nature. For both diseases, large-scale pharmacogenomic screens of molecularly characterized samples have been generated with the hope of identifying genetic predictors of drug susceptibility. Thus, computational algorithms capable of inferring robust predictors of drug responses from genomic information are of great practical importance. Most of the existing computational studies that consider drug susceptibility prediction against a panel of drugs formulate a separate learning problem for each drug, which cannot make use of commonalities between subsets of drugs.'),
(78664, 2014, 'bio', 'Transcriptome-guided amyloid imaging genetic analysis via a novel structured sparse learning algorithm', 'Yan, Jingwen|Du, Lei|Kim, Sungeun|Risacher, Shannon L|Huang, Heng|Moore, Jason H|Saykin, Andrew J|Shen, Li|Alzheimer’s Disease Neuroimaging Initiative', 'BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA.|BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA.|BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA.|BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA.|BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA.|BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA.|BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA.|BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA.|BioHealth, Indiana University School of Informatics & Computing, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA, Computer Science & Engineering, The University of Texas at Arlington, TX 76019, USA and Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH 03756, USA.', 'India|India|India|India|India|India|India|India|India', 30, 'Algorithms|Alzheimer Disease|Amyloid|Apolipoproteins E|Brain|Brain Chemistry|Gene Expression Profiling|Gene Regulatory Networks|Humans|Linkage Disequilibrium|Neuroimaging|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btu465', '25161248', 'Imaging genetics is an emerging field that studies the influence of genetic variation on brain structure and function. The major task is to examine the association between genetic markers such as single-nucleotide polymorphisms (SNPs) and quantitative traits (QTs) extracted from neuroimaging data. The complexity of these datasets has presented critical bioinformatics challenges that require new enabling tools. Sparse canonical correlation analysis (SCCA) is a bi-multivariate technique used in imaging genetics to identify complex multi-SNP-multi-QT associations. However, most of the existing SCCA algorithms are designed using the soft thresholding method, which assumes that the input features are independent from one another. This assumption clearly does not hold for the imaging genetic data. In this article, we propose a new knowledge-guided SCCA algorithm (KG-SCCA) to overcome this limitation as well as improve learning results by incorporating valuable prior knowledge.'),
(78665, 2014, 'bio', 'ContrastRank: a new method for ranking putative cancer driver genes and classification of tumor samples', 'Tian, Rui|Basu, Malay K|Capriotti, Emidio', 'Division of Informatics, Department of Pathology, Department of Clinical and Diagnostic Sciences and Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL 35249, USA.|Division of Informatics, Department of Pathology, Department of Clinical and Diagnostic Sciences and Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL 35249, USA Division of Informatics, Department of Pathology, Department of Clinical and Diagnostic Sciences and Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL 35249, USA.|Division of Informatics, Department of Pathology, Department of Clinical and Diagnostic Sciences and Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL 35249, USA Division of Informatics, Department of Pathology, Department of Clinical and Diagnostic Sciences and Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL 35249, USA Division of Informatics, Department of Pathology, Department of Clinical and Diagnostic Sciences and Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL 35249, USA.', 'United States|United States|United States', 0, 'Adenocarcinoma|Data Interpretation, Statistical|Genes, Neoplasm|Genetic Variation|Genomics|Genotype|Humans|Neoplasms', 'Journal Article', '10.1093/bioinformatics/btu466', '25161249', 'The recent advance in high-throughput sequencing technologies is generating a huge amount of data that are becoming an important resource for deciphering the genotype underlying a given phenotype. Genome sequencing has been extensively applied to the study of the cancer genomes. Although a few methods have been already proposed for the detection of cancer-related genes, their automatic identification is still a challenging task. Using the genomic data made available by The Cancer Genome Atlas Consortium (TCGA), we propose a new prioritization approach based on the analysis of the distribution of putative deleterious variants in a large cohort of cancer samples.'),
(78666, 2014, 'bio', 'Unveiling new biological relationships using shared hits of chemical screening assay pairs', 'Liu, Xueping|Campillos, Monica', 'Institute of Bioinformatics and Systems Biology and German Center for Diabetes Research, Helmholtz Center Munich, 85764 Neuherberg, Germany Institute of Bioinformatics and Systems Biology and German Center for Diabetes Research, Helmholtz Center Munich, 85764 Neuherberg, Germany.|Institute of Bioinformatics and Systems Biology and German Center for Diabetes Research, Helmholtz Center Munich, 85764 Neuherberg, Germany Institute of Bioinformatics and Systems Biology and German Center for Diabetes Research, Helmholtz Center Munich, 85764 Neuherberg, Germany.', 'Germany|Germany', 4, 'Databases, Chemical|High-Throughput Screening Assays|Phenotype|Proteins', 'Journal Article', '10.1093/bioinformatics/btu468', '25161250', 'Although the integration and analysis of the activity of small molecules across multiple chemical screens is a common approach to determine the specificity and toxicity of hits, the suitability of these approaches to reveal novel biological information is less explored. Here, we test the hypothesis that assays sharing selective hits are biologically related.'),
(78667, 2014, 'bio', 'Large-scale automated identification of mouse brain cells in confocal light sheet microscopy images', 'Frasconi, Paolo|Silvestri, Ludovico|Soda, Paolo|Cortini, Roberto|Pavone, Francesco S|Iannello, Giulio', 'Department of Information Engineering (DINFO), Università di Firenze, 50139 Firenze, Italy, European Laboratory for Nonlinear Spectroscopy (LENS), Università di Firenze, 50019 Sesto Fiorentino, Italy and Integrated Research Centre, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.|Department of Information Engineering (DINFO), Università di Firenze, 50139 Firenze, Italy, European Laboratory for Nonlinear Spectroscopy (LENS), Università di Firenze, 50019 Sesto Fiorentino, Italy and Integrated Research Centre, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.|Department of Information Engineering (DINFO), Università di Firenze, 50139 Firenze, Italy, European Laboratory for Nonlinear Spectroscopy (LENS), Università di Firenze, 50019 Sesto Fiorentino, Italy and Integrated Research Centre, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.|Department of Information Engineering (DINFO), Università di Firenze, 50139 Firenze, Italy, European Laboratory for Nonlinear Spectroscopy (LENS), Università di Firenze, 50019 Sesto Fiorentino, Italy and Integrated Research Centre, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.|Department of Information Engineering (DINFO), Università di Firenze, 50139 Firenze, Italy, European Laboratory for Nonlinear Spectroscopy (LENS), Università di Firenze, 50019 Sesto Fiorentino, Italy and Integrated Research Centre, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.|Department of Information Engineering (DINFO), Università di Firenze, 50139 Firenze, Italy, European Laboratory for Nonlinear Spectroscopy (LENS), Università di Firenze, 50019 Sesto Fiorentino, Italy and Integrated Research Centre, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Animals|Brain|Imaging, Three-Dimensional|Mice|Microscopy, Confocal|Neurons', 'Journal Article', '10.1093/bioinformatics/btu469', '25161251', 'Recently, confocal light sheet microscopy has enabled high-throughput acquisition of whole mouse brain 3D images at the micron scale resolution. This poses the unprecedented challenge of creating accurate digital maps of the whole set of cells in a brain.'),
(78668, 2014, 'bio', 'Integration of molecular network data reconstructs Gene Ontology', 'Gligorijevixc4x87, Vladimir|Janjixc4x87, Vuk|Prxc5xbeulj, Nataxc5xa1a', 'Department of Computing, Imperial College London SW7 2AZ, UK.|Department of Computing, Imperial College London SW7 2AZ, UK.|Department of Computing, Imperial College London SW7 2AZ, UK.', 'United Kingdom|United Kingdom|United Kingdom', 23, 'Algorithms|Cluster Analysis|Computational Biology|Gene Expression|Gene Ontology|Gene Regulatory Networks|Molecular Sequence Annotation|Protein Interaction Mapping|Saccharomyces cerevisiae', 'Journal Article', '10.1093/bioinformatics/btu470', '25161252', 'Recently, a shift was made from using Gene Ontology (GO) to evaluate molecular network data to using these data to construct and evaluate GO. Dutkowski et al. provide the first evidence that a large part of GO can be reconstructed solely from topologies of molecular networks. Motivated by this work, we develop a novel data integration framework that integrates multiple types of molecular network data to reconstruct and update GO. We ask how much of GO can be recovered by integrating various molecular interaction data.'),
(78669, 2014, 'bio', 'Extracting patterns of database and software usage from the bioinformatics literature', 'Duck, Geraint|Nenadic, Goran|Brass, Andy|Robertson, David L|Stevens, Robert', 'School of Computer Science, Manchester Institute of Biotechnology and Computational and Evolutionary Biology, Faculty of Life Sciences, The University of Manchester, Manchester M13 9PL, UK.|School of Computer Science, Manchester Institute of Biotechnology and Computational and Evolutionary Biology, Faculty of Life Sciences, The University of Manchester, Manchester M13 9PL, UK School of Computer Science, Manchester Institute of Biotechnology and Computational and Evolutionary Biology, Faculty of Life Sciences, The University of Manchester, Manchester M13 9PL, UK.|School of Computer Science, Manchester Institute of Biotechnology and Computational and Evolutionary Biology, Faculty of Life Sciences, The University of Manchester, Manchester M13 9PL, UK School of Computer Science, Manchester Institute of Biotechnology and Computational and Evolutionary Biology, Faculty of Life Sciences, The University of Manchester, Manchester M13 9PL, UK.|School of Computer Science, Manchester Institute of Biotechnology and Computational and Evolutionary Biology, Faculty of Life Sciences, The University of Manchester, Manchester M13 9PL, UK.|School of Computer Science, Manchester Institute of Biotechnology and Computational and Evolutionary Biology, Faculty of Life Sciences, The University of Manchester, Manchester M13 9PL, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Computational Biology|Data Mining|Databases, Factual|Periodicals as Topic|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btu471', '25161253', 'As a natural consequence of being a computer-based discipline, bioinformatics has a strong focus on database and software development, but the volume and variety of resources are growing at unprecedented rates. An audit of database and software usage patterns could help provide an overview of developments in bioinformatics and community common practice, and comparing the links between resources through time could demonstrate both the persistence of existing software and the emergence of new tools.'),
(78670, 2014, 'bio', 'The impact of incomplete knowledge on the evaluation of protein function prediction: a structured-output learning perspective', 'Jiang, Yuxiang|Clark, Wyatt T|Friedberg, Iddo|Radivojac, Predrag', 'Department of Computer Science and Informatics, Indiana University, Bloomington, IN, USA, Department of Microbiology and Department of Computer Science and Software Engineering, Miami University, Oxford, OH, USA.|Department of Computer Science and Informatics, Indiana University, Bloomington, IN, USA, Department of Microbiology and Department of Computer Science and Software Engineering, Miami University, Oxford, OH, USA.|Department of Computer Science and Informatics, Indiana University, Bloomington, IN, USA, Department of Microbiology and Department of Computer Science and Software Engineering, Miami University, Oxford, OH, USA Department of Computer Science and Informatics, Indiana University, Bloomington, IN, USA, Department of Microbiology and Department of Computer Science and Software Engineering, Miami University, Oxford, OH, USA.|Department of Computer Science and Informatics, Indiana University, Bloomington, IN, USA, Department of Microbiology and Department of Computer Science and Software Engineering, Miami University, Oxford, OH, USA.', 'India|India|India|India', 27, 'Algorithms|Computational Biology|Gene Ontology|Molecular Sequence Annotation|Proteins|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btu472', '25161254', 'The automated functional annotation of biological macromolecules is a problem of computational assignment of biological concepts or ontological terms to genes and gene products. A number of methods have been developed to computationally annotate genes using standardized nomenclature such as Gene Ontology (GO). However, questions remain about the possibility for development of accurate methods that can integrate disparate molecular data as well as about an unbiased evaluation of these methods. One important concern is that experimental annotations of proteins are incomplete. This raises questions as to whether and to what degree currently available data can be reliably used to train computational models and estimate their performance accuracy.'),
(78671, 2014, 'bio', 'Fast randomization of large genomic datasets while preserving alteration counts', 'Gobbi, Andrea|Iorio, Francesco|Dawson, Kevin J|Wedge, David C|Tamborero, David|Alexandrov, Ludmil B|Lopez-Bigas, Nuria|Garnett, Mathew J|Jurman, Giuseppe|Saez-Rodriguez, Julio', 'Fondazione Bruno Kessler, I-38100 Povo (Trento), Italy, European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge CB10 1SD, UK, Wellcome Trust Sanger Institute, Cambridge CB10 1SD, UK and Universitat Pompeu Fabra, Barcelona 08003, Spain.|Fondazione Bruno Kessler, I-38100 Povo (Trento), Italy, European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge CB10 1SD, UK, Wellcome Trust Sanger Institute, Cambridge CB10 1SD, UK and Universitat Pompeu Fabra, Barcelona 08003, Spain Fondazione Bruno Kessler, I-38100 Povo (Trento), Italy, European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge CB10 1SD, UK, Wellcome Trust Sanger Institute, Cambridge CB10 1SD, UK and Universitat Pompeu Fabra, Barcelona 08003, Spain.|Fondazione Bruno Kessler, I-38100 Povo (Trento), Italy, European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge CB10 1SD, UK, Wellcome Trust Sanger Institute, Cambridge CB10 1SD, UK and Universitat Pompeu Fabra, Barcelona 08003, Spain.|Fondazione Bruno Kessler, I-38100 Povo (Trento), Italy, European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge CB10 1SD, UK, Wellcome Trust Sanger Institute, Cambridge CB10 1SD, UK and Universitat Pompeu Fabra, Barcelona 08003, Spain.|Fondazione Bruno Kessler, I-38100 Povo (Trento), Italy, European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge CB10 1SD, UK, Wellcome Trust Sanger Institute, Cambridge CB10 1SD, UK and Universitat Pompeu Fabra, Barcelona 08003, Spain.|Fondazione Bruno Kessler, I-38100 Povo (Trento), Italy, European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge CB10 1SD, UK, Wellcome Trust Sanger Institute, Cambridge CB10 1SD, UK and Universitat Pompeu Fabra, Barcelona 08003, Spain.|Fondazione Bruno Kessler, I-38100 Povo (Trento), Italy, European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge CB10 1SD, UK, Wellcome Trust Sanger Institute, Cambridge CB10 1SD, UK and Universitat Pompeu Fabra, Barcelona 08003, Spain.|Fondazione Bruno Kessler, I-38100 Povo (Trento), Italy, European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge CB10 1SD, UK, Wellcome Trust Sanger Institute, Cambridge CB10 1SD, UK and Universitat Pompeu Fabra, Barcelona 08003, Spain.|Fondazione Bruno Kessler, I-38100 Povo (Trento), Italy, European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge CB10 1SD, UK, Wellcome Trust Sanger Institute, Cambridge CB10 1SD, UK and Universitat Pompeu Fabra, Barcelona 08003, Spain.|Fondazione Bruno Kessler, I-38100 Povo (Trento), Italy, European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge CB10 1SD, UK, Wellcome Trust Sanger Institute, Cambridge CB10 1SD, UK and Universitat Pompeu Fabra, Barcelona 08003, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain', 0, 'Algorithms|Genomics|Humans|Markov Chains|Monte Carlo Method|Neoplasms|Random Allocation|Software', 'Journal Article', '10.1093/bioinformatics/btu474', '25161255', 'Studying combinatorial patterns in cancer genomic datasets has recently emerged as a tool for identifying novel cancer driver networks. Approaches have been devised to quantify, for example, the tendency of a set of genes to be mutated in a mutually exclusive manner. The significance of the proposed metrics is usually evaluated by computing P-values under appropriate null models. To this end, a Monte Carlo method (the switching-algorithm) is used to sample simulated datasets under a null model that preserves patient- and gene-wise mutation rates. In this method, a genomic dataset is represented as a bipartite network, to which Markov chain updates (switching-steps) are applied. These steps modify the network topology, and a minimal number of them must be executed to draw simulated datasets independently under the null model. This number has previously been deducted empirically to be a linear function of the total number of variants, making this process computationally expensive.'),
(78672, 2014, 'bio', 'Entropy-driven partitioning of the hierarchical protein space', 'Rappoport, Nadav|Stern, Amos|Linial, Nathan|Linial, Michal', 'School of Computer Science and Engineering and Department of Biological Chemistry, Institute of Life Sciences, The Hebrew University of Jerusalem, 91904, Israel.|School of Computer Science and Engineering and Department of Biological Chemistry, Institute of Life Sciences, The Hebrew University of Jerusalem, 91904, Israel.|School of Computer Science and Engineering and Department of Biological Chemistry, Institute of Life Sciences, The Hebrew University of Jerusalem, 91904, Israel.|School of Computer Science and Engineering and Department of Biological Chemistry, Institute of Life Sciences, The Hebrew University of Jerusalem, 91904, Israel.', 'Israel|Israel|Israel|Israel', 2, 'Algorithms|Cluster Analysis|Molecular Sequence Annotation|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btu478', '25161256', 'Modern protein sequencing techniques have led to the determination of >50 million protein sequences. ProtoNet is a clustering system that provides a continuous hierarchical agglomerative clustering tree for all proteins. While ProtoNet performs unsupervised classification of all included proteins, finding an optimal level of granularity for the purpose of focusing on protein functional groups remain elusive. Here, we ask whether knowledge-based annotations on protein families can support the automatic unsupervised methods for identifying high-quality protein families. We present a method that yields within the ProtoNet hierarchy an optimal partition of clusters, relative to manual annotation schemes. The methods principle is to minimize the entropy-derived distance between annotation-based partitions and all available hierarchical partitions. We describe the best front (BF) partition of 2 478 328 proteins from UniRef50. Of 4,929,553 ProtoNet tree clusters, BF based on Pfam annotations contain 26,891 clusters. The high quality of the partition is validated by the close correspondence with the set of clusters that best describe thousands of keywords of Pfam. The BF is shown to be superior to naïve cut in the ProtoNet tree that yields a similar number of clusters. Finally, we used parameters intrinsic to the clustering process to enrich a priori the BFs clusters. We present the entropy-based methods benefit in overcoming the unavoidable limitations of nested clusters in ProtoNet. We suggest that this automatic information-based cluster selection can be useful for other large-scale annotation schemes, as well as for systematically testing and comparing putative families derived from alternative clustering methods.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78673, 2014, 'bio', 'Microarray R-based analysis of complex lysate experiments with MIRACLE', 'List, Markus|Block, Ines|Pedersen, Marlene Lemvig|Christiansen, Helle|Schmidt, Steffen|Thomassen, Mads|Tan, Qihua|Baumbach, Jan|Mollenhauer, Jan', 'Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark.|Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark.|Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark.|Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark.|Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark.|Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark.|Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark.|Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark.|Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 0, 'Cell Extracts|Internet|Protein Array Analysis|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btu473', '25161257', 'Reverse-phase protein arrays (RPPAs) allow sensitive quantification of relative protein abundance in thousands of samples in parallel. Typical challenges involved in this technology are antibody selection, sample preparation and optimization of staining conditions. The issue of combining effective sample management and data analysis, however, has been widely neglected.'),
(78674, 2014, 'bio', 'cnvOffSeq: detecting intergenic copy number variation using off-target exome sequencing data', 'Bellos, Evangelos|Coin, Lachlan J M', 'Department of Genomics of Common Disease, Imperial College London, London W12 0NN, UK and Institute for Molecular Bioscience, University of Queensland, St Lucia, QLD 4072, Australia.|Department of Genomics of Common Disease, Imperial College London, London W12 0NN, UK and Institute for Molecular Bioscience, University of Queensland, St Lucia, QLD 4072, Australia Department of Genomics of Common Disease, Imperial College London, London W12 0NN, UK and Institute for Molecular Bioscience, University of Queensland, St Lucia, QLD 4072, Australia.', 'Australia|Australia', 8, 'Algorithms|DNA Copy Number Variations|DNA, Intergenic|Exome|Genomics|Genotyping Techniques|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu475', '25161258', 'Exome sequencing technologies have transformed the field of Mendelian genetics and allowed for efficient detection of genomic variants in protein-coding regions. The target enrichment process that is intrinsic to exome sequencing is inherently imperfect, generating large amounts of unintended off-target sequence. Off-target data are characterized by very low and highly heterogeneous coverage and are usually discarded by exome analysis pipelines. We posit that off-target read depth is a rich, but overlooked, source of information that could be mined to detect intergenic copy number variation (CNV). We propose cnvOffseq, a novel normalization framework for off-target read depth that is based on local adaptive singular value decomposition (SVD). This method is designed to address the heterogeneity of the underlying data and allows for accurate and precise CNV detection and genotyping in off-target regions.'),
(78675, 2015, 'bio', 'Individual-level analysis of differential expression of genes and pathways for personalized medicine', 'Wang, Hongwei|Sun, Qiang|Zhao, Wenyuan|Qi, Lishuang|Gu, Yunyan|Li, Pengfei|Zhang, Mengmeng|Li, Yang|Liu, Shu-Lin|Guo, Zheng', 'College of Bioinformatics Science and Technology, Genomics Research Center, Harbin Medical University, Harbin 150086, China, Department of Microbiology and Infectious Diseases, University of Calgary, Calgary, AB, T2N 4N1, Canada and Bioinformatics Department, Basic Medical College, Fujian Medical University, Fuzhou 350004, China.|College of Bioinformatics Science and Technology, Genomics Research Center, Harbin Medical University, Harbin 150086, China, Department of Microbiology and Infectious Diseases, University of Calgary, Calgary, AB, T2N 4N1, Canada and Bioinformatics Department, Basic Medical College, Fujian Medical University, Fuzhou 350004, China.|College of Bioinformatics Science and Technology, Genomics Research Center, Harbin Medical University, Harbin 150086, China, Department of Microbiology and Infectious Diseases, University of Calgary, Calgary, AB, T2N 4N1, Canada and Bioinformatics Department, Basic Medical College, Fujian Medical University, Fuzhou 350004, China.|College of Bioinformatics Science and Technology, Genomics Research Center, Harbin Medical University, Harbin 150086, China, Department of Microbiology and Infectious Diseases, University of Calgary, Calgary, AB, T2N 4N1, Canada and Bioinformatics Department, Basic Medical College, Fujian Medical University, Fuzhou 350004, China.|College of Bioinformatics Science and Technology, Genomics Research Center, Harbin Medical University, Harbin 150086, China, Department of Microbiology and Infectious Diseases, University of Calgary, Calgary, AB, T2N 4N1, Canada and Bioinformatics Department, Basic Medical College, Fujian Medical University, Fuzhou 350004, China.|College of Bioinformatics Science and Technology, Genomics Research Center, Harbin Medical University, Harbin 150086, China, Department of Microbiology and Infectious Diseases, University of Calgary, Calgary, AB, T2N 4N1, Canada and Bioinformatics Department, Basic Medical College, Fujian Medical University, Fuzhou 350004, China.|College of Bioinformatics Science and Technology, Genomics Research Center, Harbin Medical University, Harbin 150086, China, Department of Microbiology and Infectious Diseases, University of Calgary, Calgary, AB, T2N 4N1, Canada and Bioinformatics Department, Basic Medical College, Fujian Medical University, Fuzhou 350004, China.|College of Bioinformatics Science and Technology, Genomics Research Center, Harbin Medical University, Harbin 150086, China, Department of Microbiology and Infectious Diseases, University of Calgary, Calgary, AB, T2N 4N1, Canada and Bioinformatics Department, Basic Medical College, Fujian Medical University, Fuzhou 350004, China.|College of Bioinformatics Science and Technology, Genomics Research Center, Harbin Medical University, Harbin 150086, China, Department of Microbiology and Infectious Diseases, University of Calgary, Calgary, AB, T2N 4N1, Canada and Bioinformatics Department, Basic Medical College, Fujian Medical University, Fuzhou 350004, China College of Bioinformatics Science and Technology, Genomics Research Center, Harbin Medical University, Harbin 150086, China, Department of Microbiology and Infectious Diseases, University of Calgary, Calgary, AB, T2N 4N1, Canada and Bioinformatics Department, Basic Medical College, Fujian Medical University, Fuzhou 350004, China.|College of Bioinformatics Science and Technology, Genomics Research Center, Harbin Medical University, Harbin 150086, China, Department of Microbiology and Infectious Diseases, University of Calgary, Calgary, AB, T2N 4N1, Canada and Bioinformatics Department, Basic Medical College, Fujian Medical University, Fuzhou 350004, China College of Bioinformatics Science and Technology, Genomics Research Center, Harbin Medical University, Harbin 150086, China, Department of Microbiology and Infectious Diseases, University of Calgary, Calgary, AB, T2N 4N1, Canada and Bioinformatics Department, Basic Medical College, Fujian Medical University, Fuzhou 350004, China.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Biomarkers, Tumor|Breast|Breast Neoplasms|Case-Control Studies|Computational Biology|Databases, Factual|Discriminant Analysis|Female|Gene Expression Profiling|Humans|Lung|Lung Neoplasms|Precision Medicine|Signal Transduction', 'Comparative Study', '10.1093/bioinformatics/btu522', '25165092', 'The differential expression analysis focusing on inter-group comparison can capture only differentially expressed genes (DE genes) at the population level, which may mask the heterogeneity of differential expression in individuals. Thus, to provide patient-specific information for personalized medicine, it is necessary to conduct differential expression analysis at the individual level.'),
(78676, 2014, 'bio', 'MR_predictor: a simulation engine for Mendelian Randomization studies', 'Voight, Benjamin F', 'Department of Pharmacology and Department of Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19143, USA Department of Pharmacology and Department of Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19143, USA.', 'United States', 0, 'Data Interpretation, Statistical|Genotype|Mendelian Randomization Analysis|Phenotype|Software', 'Journal Article', '10.1093/bioinformatics/btu564', '25165093', 'I present MR_predictor, a simulation engine designed to guide the development and interpretation of statistical tests of causality between phenotypes using genetic instruments. MR_predictor provides a framework to model either individual traits or complex scenarios where multiple phenotypes are correlated or dependent on each other. Crucially, MR_predictor can incorporate the effects of multiple biallelic loci (linked or unlinked) contributing genotypic variability to one or more simulated phenotypes. The software has a range of options for sample generation, and output files generated by MR_predictor port into commonly used analysis tools (e.g. PLINK, R), facilitating analyses germane for Mendelian Randomization studies. Benchmarks for speed and power calculations for summary statistic-based Mendelian Randomization analyses are presented and compared with analytical expectation.'),
(78677, 2014, 'bio', 'MIRPIPE: quantification of microRNAs in niche model organisms', 'Kuenne, Carsten|Preussner, Jens|Herzog, Mario|Braun, Thomas|Looso, Mario', 'Group of Bioinformatics and Cardiac Development and Remodelling, Max Planck Institute for Heart and Lung Research, Ludwigstrasse 43, D-61231 Bad Nauheim, Germany.|Group of Bioinformatics and Cardiac Development and Remodelling, Max Planck Institute for Heart and Lung Research, Ludwigstrasse 43, D-61231 Bad Nauheim, Germany.|Group of Bioinformatics and Cardiac Development and Remodelling, Max Planck Institute for Heart and Lung Research, Ludwigstrasse 43, D-61231 Bad Nauheim, Germany.|Group of Bioinformatics and Cardiac Development and Remodelling, Max Planck Institute for Heart and Lung Research, Ludwigstrasse 43, D-61231 Bad Nauheim, Germany.|Group of Bioinformatics and Cardiac Development and Remodelling, Max Planck Institute for Heart and Lung Research, Ludwigstrasse 43, D-61231 Bad Nauheim, Germany.', 'Germany|Germany|Germany|Germany|Germany', 12, 'Algorithms|Humans|MicroRNAs|Models, Biological|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu573', '25165094', 'MicroRNAs (miRNAs) represent an important class of small non-coding RNAs regulating gene expression in eukaryotes. Present algorithms typically rely on genomic data to identify miRNAs and require extensive installation procedures. Niche model organisms lacking genomic sequences cannot be analyzed by such tools. Here we introduce the MIRPIPE application enabling rapid and simple browser-based miRNA homology detection and quantification. MIRPIPE features automatic trimming of raw RNA-Seq reads originating from various sequencing instruments, processing of isomiRs and quantification of detected miRNAs versus public- or user-uploaded reference databases.'),
(78678, 2014, 'bio', 'LoRDEC: accurate and efficient long read error correction', 'Salmela, Leena|Rivals, Eric', 'Department of Computer Science and Helsinki Institute for Information Technology HIIT, FI-00014 University of Helsinki, Finland and LIRMM and Institut de Biologie Computationelle, CNRS and Université Montpellier, 34095 Montpellier Cedex 5, France.|Department of Computer Science and Helsinki Institute for Information Technology HIIT, FI-00014 University of Helsinki, Finland and LIRMM and Institut de Biologie Computationelle, CNRS and Université Montpellier, 34095 Montpellier Cedex 5, France.', 'Finland|Finland', 0, 'Algorithms|Animals|Escherichia coli|Genomics|High-Throughput Nucleotide Sequencing|Parrots|Software|Yeasts', 'Journal Article', '10.1093/bioinformatics/btu538', '25165095', 'PacBio single molecule real-time sequencing is a third-generation sequencing technique producing long reads, with comparatively lower throughput and higher error rate. Errors include numerous indels and complicate downstream analysis like mapping or de novo assembly. A hybrid strategy that takes advantage of the high accuracy of second-generation short reads has been proposed for correcting long reads. Mapping of short reads on long reads provides sufficient coverage to eliminate up to 99% of errors, however, at the expense of prohibitive running times and considerable amounts of disk and memory space.'),
(78679, 2014, 'bio', 'VSEAMS: a pipeline for variant set enrichment analysis using summary GWAS data identifies IKZF3, BATF and ESRRA as key transcription factors in type 1 diabetes', 'Burren, Oliver S|Guo, Hui|Wallace, Chris', 'Department of Medical Genetics, JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge, CB2 0XY, UK and MRC Biostatistics Unit, Cambridge Institute of Public Health, Forvie Site, Robinson Way, Cambridge Biomedical Campus, Cambridge, CB2 0SR, UK.|Department of Medical Genetics, JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge, CB2 0XY, UK and MRC Biostatistics Unit, Cambridge Institute of Public Health, Forvie Site, Robinson Way, Cambridge Biomedical Campus, Cambridge, CB2 0SR, UK.|Department of Medical Genetics, JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge, CB2 0XY, UK and MRC Biostatistics Unit, Cambridge Institute of Public Health, Forvie Site, Robinson Way, Cambridge Biomedical Campus, Cambridge, CB2 0SR, UK Department of Medical Genetics, JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge, CB2 0XY, UK and MRC Biostatistics Unit, Cambridge Institute of Public Health, Forvie Site, Robinson Way, Cambridge Biomedical Campus, Cambridge, CB2 0SR, UK.', 'United Kingdom|United Kingdom|United Kingdom', 5, 'Basic-Leucine Zipper Transcription Factors|Diabetes Mellitus, Type 1|Genome-Wide Association Study|Humans|Ikaros Transcription Factor|Polymorphism, Single Nucleotide|Receptors, Estrogen|Sample Size|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btu571', '25170024', 'Genome-wide association studies (GWAS) have identified many loci implicated in disease susceptibility. Integration of GWAS summary statistics (P-values) and functional genomic datasets should help to elucidate mechanisms.'),
(78680, 2014, 'bio', 'Cell population identification using fluorescence-minus-one controls with a one-class classifying algorithm', 'Feher, Kristen|Kirsch, Jenny|Radbruch, Andreas|Chang, Hyun-Dong|Kaiser, Toralf', 'Deutsches Rheuma-Forschungszentrum, Berlin 10117, Germany.|Deutsches Rheuma-Forschungszentrum, Berlin 10117, Germany.|Deutsches Rheuma-Forschungszentrum, Berlin 10117, Germany.|Deutsches Rheuma-Forschungszentrum, Berlin 10117, Germany.|Deutsches Rheuma-Forschungszentrum, Berlin 10117, Germany.', 'Germany|Germany|Germany|Germany|Germany', 2, 'Algorithms|Biomarkers|Cluster Analysis|Flow Cytometry|Fluorescence|Humans|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btu575', '25170025', 'The tried and true approach of flow cytometry data analysis is to manually gate on each biomarker separately, which is feasible for a small number of biomarkers, e.g. less than five. However, this rapidly becomes confusing as the number of biomarker increases. Furthermore, multivariate structure is not taken into account. Recently, automated gating algorithms have been implemented, all of which rely on unsupervised learning methodology. However, all unsupervised learning outputs suffer the same difficulties in validation in the absence of external knowledge, regardless of application domain.'),
(78681, 2014, 'bio', 'Limbform: a functional ontology-based database of limb regeneration experiments', 'Lobo, Daniel|Feldman, Erica B|Shah, Michelle|Malone, Taylor J|Levin, Michael', 'Center for Regenerative and Developmental Biology, Department of Biology, Tufts University, 200 Boston Avenue, Suite 4600, Medford, MA 02155, USA.|Center for Regenerative and Developmental Biology, Department of Biology, Tufts University, 200 Boston Avenue, Suite 4600, Medford, MA 02155, USA.|Center for Regenerative and Developmental Biology, Department of Biology, Tufts University, 200 Boston Avenue, Suite 4600, Medford, MA 02155, USA.|Center for Regenerative and Developmental Biology, Department of Biology, Tufts University, 200 Boston Avenue, Suite 4600, Medford, MA 02155, USA.|Center for Regenerative and Developmental Biology, Department of Biology, Tufts University, 200 Boston Avenue, Suite 4600, Medford, MA 02155, USA.', 'United States|United States|United States|United States|United States', 0, 'Biological Ontologies|Databases, Factual|Extremities|Phenotype|Regeneration', 'Journal Article', '10.1093/bioinformatics/btu582', '25170026', 'The ability of certain organisms to completely regenerate lost limbs is a fascinating process, far from solved. Despite the extraordinary published efforts during the past centuries of scientists performing amputations, transplantations and molecular experiments, no mechanistic model exists yet that can completely explain patterning during the limb regeneration process. The lack of a centralized repository to enable the efficient mining of this huge dataset is hindering the discovery of comprehensive models of limb regeneration. Here, we introduce Limbform (Limb formalization), a centralized database of published limb regeneration experiments. In contrast to natural language or text-based ontologies, Limbform is based on a functional ontology using mathematical graphs to represent unambiguously limb phenotypes and manipulation procedures. The centralized database currently contains >800 published limb regeneration experiments comprising many model organisms, including salamanders, frogs, insects, crustaceans and arachnids. The database represents an extraordinary resource for mining the existing knowledge of functional data in this field, furthermore, its mathematical nature based on a functional ontology will pave the way for artificial intelligence tools applied to the discovery of the sought-after comprehensive limb regeneration models.'),
(78682, 2014, 'bio', 'RVboost: RNA-seq variants prioritization using a boosting method', 'Wang, Chen|Davila, Jaime I|Baheti, Saurabh|Bhagwate, Aditya V|Wang, Xue|Kocher, Jean-Pierre A|Slager, Susan L|Feldman, Andrew L|Novak, Anne J|Cerhan, James R|Thompson, E Aubrey|Asmann, Yan W', 'Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester MN 55905, Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, Department of Laboratory Medicine and Pathology, Division of Hematology, Department of Internal Medicine, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester MN 55905 and Department of Cancer Biology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, USA.|Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester MN 55905, Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, Department of Laboratory Medicine and Pathology, Division of Hematology, Department of Internal Medicine, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester MN 55905 and Department of Cancer Biology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, USA.|Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester MN 55905, Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, Department of Laboratory Medicine and Pathology, Division of Hematology, Department of Internal Medicine, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester MN 55905 and Department of Cancer Biology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, USA.|Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester MN 55905, Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, Department of Laboratory Medicine and Pathology, Division of Hematology, Department of Internal Medicine, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester MN 55905 and Department of Cancer Biology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, USA.|Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester MN 55905, Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, Department of Laboratory Medicine and Pathology, Division of Hematology, Department of Internal Medicine, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester MN 55905 and Department of Cancer Biology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, USA.|Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester MN 55905, Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, Department of Laboratory Medicine and Pathology, Division of Hematology, Department of Internal Medicine, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester MN 55905 and Department of Cancer Biology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, USA.|Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester MN 55905, Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, Department of Laboratory Medicine and Pathology, Division of Hematology, Department of Internal Medicine, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester MN 55905 and Department of Cancer Biology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, USA.|Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester MN 55905, Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, Department of Laboratory Medicine and Pathology, Division of Hematology, Department of Internal Medicine, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester MN 55905 and Department of Cancer Biology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, USA.|Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester MN 55905, Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, Department of Laboratory Medicine and Pathology, Division of Hematology, Department of Internal Medicine, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester MN 55905 and Department of Cancer Biology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, USA.|Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester MN 55905, Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, Department of Laboratory Medicine and Pathology, Division of Hematology, Department of Internal Medicine, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester MN 55905 and Department of Cancer Biology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, USA.|Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester MN 55905, Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, Department of Laboratory Medicine and Pathology, Division of Hematology, Department of Internal Medicine, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester MN 55905 and Department of Cancer Biology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, USA.|Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester MN 55905, Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, Department of Laboratory Medicine and Pathology, Division of Hematology, Department of Internal Medicine, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester MN 55905 and Department of Cancer Biology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville FL 32224, 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', 15, 'Exome|Exons|Gene Expression Profiling|Genetic Variation|High-Throughput Nucleotide Sequencing|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu577', '25170027', 'RNA-seq has become the method of choice to quantify genes and exons, discover novel transcripts and detect fusion genes. However, reliable variant identification from RNA-seq data remains challenging because of the complexities of the transcriptome, the challenges of accurately mapping exon boundary spanning reads and the bias introduced during the sequencing library preparation.'),
(78683, 2014, 'bio', 'Merging of multi-string BWTs with applications', 'Holt, James|McMillan, Leonard', 'Department of Computer Science, 201 S. Columbia St. UNC-CH, Chapel Hill, NC 27599, USA.|Department of Computer Science, 201 S. Columbia St. UNC-CH, Chapel Hill, NC 27599, USA.', 'United States|United States', 0, 'Algorithms|Animals|Data Compression|Genomics|High-Throughput Nucleotide Sequencing|Mice|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btu584', '25172922', 'The throughput of genomic sequencing has increased to the point that is overrunning the rate of downstream analysis. This, along with the desire to revisit old data, has led to a situation where large quantities of raw, and nearly impenetrable, sequence data are rapidly filling the hard drives of modern biology labs. These datasets can be compressed via a multi-string variant of the Burrows-Wheeler Transform (BWT), which provides the side benefit of searches for arbitrary k-mers within the raw data as well as the ability to reconstitute arbitrary reads as needed. We propose a method for merging such datasets for both increased compression and downstream analysis.'),
(78684, 2014, 'bio', 'The Naked Mole Rat Genome Resource: facilitating analyses of cancer and longevity-related adaptations', 'Keane, Michael|Craig, Thomas|Alföldi, Jessica|Berlin, Aaron M|Johnson, Jeremy|Seluanov, Andrei|Gorbunova, Vera|Di Palma, Federica|Lindblad-Toh, Kerstin|Church, George M|de Magalhães, João Pedro', 'Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Department of Biology, University of Rochester, NY, USA, Vertebrate and Health Genomics, The Genome Analysis Center, Norwich, UK, Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden and Department of Genetics, Harvard Medical School, Boston, MA, USA.|Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Department of Biology, University of Rochester, NY, USA, Vertebrate and Health Genomics, The Genome Analysis Center, Norwich, UK, Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden and Department of Genetics, Harvard Medical School, Boston, MA, USA.|Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Department of Biology, University of Rochester, NY, USA, Vertebrate and Health Genomics, The Genome Analysis Center, Norwich, UK, Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden and Department of Genetics, Harvard Medical School, Boston, MA, USA.|Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Department of Biology, University of Rochester, NY, USA, Vertebrate and Health Genomics, The Genome Analysis Center, Norwich, UK, Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden and Department of Genetics, Harvard Medical School, Boston, MA, USA.|Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Department of Biology, University of Rochester, NY, USA, Vertebrate and Health Genomics, The Genome Analysis Center, Norwich, UK, Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden and Department of Genetics, Harvard Medical School, Boston, MA, USA.|Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Department of Biology, University of Rochester, NY, USA, Vertebrate and Health Genomics, The Genome Analysis Center, Norwich, UK, Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden and Department of Genetics, Harvard Medical School, Boston, MA, USA.|Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Department of Biology, University of Rochester, NY, USA, Vertebrate and Health Genomics, The Genome Analysis Center, Norwich, UK, Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden and Department of Genetics, Harvard Medical School, Boston, MA, USA.|Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Department of Biology, University of Rochester, NY, USA, Vertebrate and Health Genomics, The Genome Analysis Center, Norwich, UK, Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden and Department of Genetics, Harvard Medical School, Boston, MA, USA Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Department of Biology, University of Rochester, NY, USA, Vertebrate and Health Genomics, The Genome Analysis Center, Norwich, UK, Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden and Department of Genetics, Harvard Medical School, Boston, MA, USA.|Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Department of Biology, University of Rochester, NY, USA, Vertebrate and Health Genomics, The Genome Analysis Center, Norwich, UK, Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden and Department of Genetics, Harvard Medical School, Boston, MA, USA Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Department of Biology, University of Rochester, NY, USA, Vertebrate and Health Genomics, The Genome Analysis Center, Norwich, UK, Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden and Department of Genetics, Harvard Medical School, Boston, MA, USA.|Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Department of Biology, University of Rochester, NY, USA, Vertebrate and Health Genomics, The Genome Analysis Center, Norwich, UK, Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden and Department of Genetics, Harvard Medical School, Boston, MA, USA.|Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Department of Biology, University of Rochester, NY, USA, Vertebrate and Health Genomics, The Genome Analysis Center, Norwich, UK, Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden and Department of Genetics, Harvard Medical School, Boston, MA, USA.', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 0, 'Animals|Evolution, Molecular|Female|Genes|Genome|Genomics|Guinea Pigs|Humans|Longevity|Mice|Mole Rats|Neoplasms|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btu579', '25172923', 'The naked mole rat (Heterocephalus glaber) is an exceptionally long-lived and cancer-resistant rodent native to East Africa. Although its genome was previously sequenced, here we report a new assembly sequenced by us with substantially higher N50 values for scaffolds and contigs.'),
(78685, 2014, 'bio', 'Protein-protein binding affinity prediction from amino acid sequence', 'Yugandhar, K|Gromiha, M Michael', 'Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai-600036, Tamil Nadu, India.|Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai-600036, Tamil Nadu, India.', 'India|India', 0, 'Binding Sites|Multiprotein Complexes|Protein Binding|Protein Interaction Mapping|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btu580', '25172924', 'Protein-protein interactions play crucial roles in many biological processes and are responsible for smooth functioning of the machinery in living organisms. Predicting the binding affinity of protein-protein complexes provides deep insights to understand the recognition mechanism and identify the strong binding partners in protein-protein interaction networks.'),
(78686, 2014, 'bio', 'Frameshift alignment: statistics and post-genomic applications', 'Sheetlin, Sergey L|Park, Yonil|Frith, Martin C|Spouge, John L', 'National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA and Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo 135-0064, Japan.|National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA and Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo 135-0064, Japan.|National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA and Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo 135-0064, Japan.|National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA and Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo 135-0064, Japan.', 'Japan|Japan|Japan|Japan', 0, 'Algorithms|Data Interpretation, Statistical|Frameshift Mutation|Genome, Human|Genomics|Humans|Metagenomics|Pseudogenes|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu576', '25172925', 'The alignment of DNA sequences to proteins, allowing for frameshifts, is a classic method in sequence analysis. It can help identify pseudogenes (which accumulate mutations), analyze raw DNA and RNA sequence data (which may have frameshift sequencing errors), investigate ribosomal frameshifts, etc. Often, however, only ad hoc approximations or simulations are available to provide the statistical significance of a frameshift alignment score.'),
(78687, 2014, 'bio', 'Human structural proteome-wide characterization of Cyclosporine A targets', 'Hu, Gang|Wang, Kui|Groenendyk, Jody|Barakat, Khaled|Mizianty, Marcin J|Ruan, Jishou|Michalak, Marek|Kurgan, Lukasz', 'School of Mathematical Sciences and LPMC, Nankai University, Tianjin, 300071, PR China, Department of Biochemistry, Faculty of Pharmacy and Pharmaceutical Sciences, Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada and State Key Laboratory for Medicinal Chemical Biology, Nankai University, Tianjin, 300071, PR China.|School of Mathematical Sciences and LPMC, Nankai University, Tianjin, 300071, PR China, Department of Biochemistry, Faculty of Pharmacy and Pharmaceutical Sciences, Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada and State Key Laboratory for Medicinal Chemical Biology, Nankai University, Tianjin, 300071, PR China.|School of Mathematical Sciences and LPMC, Nankai University, Tianjin, 300071, PR China, Department of Biochemistry, Faculty of Pharmacy and Pharmaceutical Sciences, Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada and State Key Laboratory for Medicinal Chemical Biology, Nankai University, Tianjin, 300071, PR China.|School of Mathematical Sciences and LPMC, Nankai University, Tianjin, 300071, PR China, Department of Biochemistry, Faculty of Pharmacy and Pharmaceutical Sciences, Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada and State Key Laboratory for Medicinal Chemical Biology, Nankai University, Tianjin, 300071, PR China.|School of Mathematical Sciences and LPMC, Nankai University, Tianjin, 300071, PR China, Department of Biochemistry, Faculty of Pharmacy and Pharmaceutical Sciences, Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada and State Key Laboratory for Medicinal Chemical Biology, Nankai University, Tianjin, 300071, PR China.|School of Mathematical Sciences and LPMC, Nankai University, Tianjin, 300071, PR China, Department of Biochemistry, Faculty of Pharmacy and Pharmaceutical Sciences, Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada and State Key Laboratory for Medicinal Chemical Biology, Nankai University, Tianjin, 300071, PR China School of Mathematical Sciences and LPMC, Nankai University, Tianjin, 300071, PR China, Department of Biochemistry, Faculty of Pharmacy and Pharmaceutical Sciences, Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada and State Key Laboratory for Medicinal Chemical Biology, Nankai University, Tianjin, 300071, PR China.|School of Mathematical Sciences and LPMC, Nankai University, Tianjin, 300071, PR China, Department of Biochemistry, Faculty of Pharmacy and Pharmaceutical Sciences, Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada and State Key Laboratory for Medicinal Chemical Biology, Nankai University, Tianjin, 300071, PR China.|School of Mathematical Sciences and LPMC, Nankai University, Tianjin, 300071, PR China, Department of Biochemistry, Faculty of Pharmacy and Pharmaceutical Sciences, Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada and State Key Laboratory for Medicinal Chemical Biology, Nankai University, Tianjin, 300071, PR China.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 28, 'Algorithms|Calpain|Caspase 3|Cyclosporine|Humans|Immunosuppressive Agents|Mitogen-Activated Protein Kinase 14|Molecular Docking Simulation|Proteome|Proteomics|Signal Transduction|Surface Plasmon Resonance', 'Journal Article', '10.1093/bioinformatics/btu581', '25172926', 'Off-target interactions of a popular immunosuppressant Cyclosporine A (CSA) with several proteins besides its molecular target, cyclophilin A, are implicated in the activation of signaling pathways that lead to numerous side effects of this drug.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78688, 2015, 'bio', 'poRe: an R package for the visualization and analysis of nanopore sequencing data', 'Watson, Mick|Thomson, Marian|Risse, Judith|Talbot, Richard|Santoyo-Lopez, Javier|Gharbi, Karim|Blaxter, Mark', 'Edinburgh Genomics, The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Edinburgh EH25 9RG and Edinburgh Genomics, Institute of Evolutionary Biology, Ashworth Laboratories, University of Edinburgh, Edinburgh EH9 3JT, UK.|Edinburgh Genomics, The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Edinburgh EH25 9RG and Edinburgh Genomics, Institute of Evolutionary Biology, Ashworth Laboratories, University of Edinburgh, Edinburgh EH9 3JT, UK.|Edinburgh Genomics, The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Edinburgh EH25 9RG and Edinburgh Genomics, Institute of Evolutionary Biology, Ashworth Laboratories, University of Edinburgh, Edinburgh EH9 3JT, UK.|Edinburgh Genomics, The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Edinburgh EH25 9RG and Edinburgh Genomics, Institute of Evolutionary Biology, Ashworth Laboratories, University of Edinburgh, Edinburgh EH9 3JT, UK.|Edinburgh Genomics, The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Edinburgh EH25 9RG and Edinburgh Genomics, Institute of Evolutionary Biology, Ashworth Laboratories, University of Edinburgh, Edinburgh EH9 3JT, UK.|Edinburgh Genomics, The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Edinburgh EH25 9RG and Edinburgh Genomics, Institute of Evolutionary Biology, Ashworth Laboratories, University of Edinburgh, Edinburgh EH9 3JT, UK.|Edinburgh Genomics, The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Edinburgh EH25 9RG and Edinburgh Genomics, Institute of Evolutionary Biology, Ashworth Laboratories, University of Edinburgh, Edinburgh EH9 3JT, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 57, 'Computational Biology|Nanopores|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu590', '25173419', 'The Oxford Nanopore MinION device represents a unique sequencing technology. As a mobile sequencing device powered by the USB port of a laptop, the MinION has huge potential applications. To enable these applications, the bioinformatics community will need to design and build a suite of tools specifically for MinION data.'),
(78689, 2014, 'bio', 'Amplicon identification using SparsE representation of multiplex PYROsequencing signal (AdvISER-M-PYRO): application to bacterial resistance genotyping', 'Ambroise, Jxc3xa9rxc3xb4me|Deccache, Yann|Irenge, Leonid|Savov, Encho|Robert, Annie|Gala, Jean-Luc', 'Center for Applied Molecular Technologies (CTMA), Institut de Recherche Expxc3xa9rimentale et Clinique (IREC), Universitxc3xa9 catholique de Louvain, Clos Chapelle-aux-Champs 30, 1200 Bruxelles, Defence Laboratories Department, Belgian Armed Forces, 1800 Vilvoorde, Belgium, Department of Epidemiology and Hygiene, Military Medical Academy of Sofia, 1000 Sofia, Bulgaria and Epidemiology and Biostatistics Department (EPID), Institut de Recherche Expxc3xa9rimentale et Clinique (IREC), Universitxc3xa9 catholique de Louvain, Clos Chapelle-aux-Champs 30, 1200 Bruxelles, Belgium.|Center for Applied Molecular Technologies (CTMA), Institut de Recherche Expxc3xa9rimentale et Clinique (IREC), Universitxc3xa9 catholique de Louvain, Clos Chapelle-aux-Champs 30, 1200 Bruxelles, Defence Laboratories Department, Belgian Armed Forces, 1800 Vilvoorde, Belgium, Department of Epidemiology and Hygiene, Military Medical Academy of Sofia, 1000 Sofia, Bulgaria and Epidemiology and Biostatistics Department (EPID), Institut de Recherche Expxc3xa9rimentale et Clinique (IREC), Universitxc3xa9 catholique de Louvain, Clos Chapelle-aux-Champs 30, 1200 Bruxelles, Belgium.|Center for Applied Molecular Technologies (CTMA), Institut de Recherche Expxc3xa9rimentale et Clinique (IREC), Universitxc3xa9 catholique de Louvain, Clos Chapelle-aux-Champs 30, 1200 Bruxelles, Defence Laboratories Department, Belgian Armed Forces, 1800 Vilvoorde, Belgium, Department of Epidemiology and Hygiene, Military Medical Academy of Sofia, 1000 Sofia, Bulgaria and Epidemiology and Biostatistics Department (EPID), Institut de Recherche Expxc3xa9rimentale et Clinique (IREC), Universitxc3xa9 catholique de Louvain, Clos Chapelle-aux-Champs 30, 1200 Bruxelles, Belgium Center for Applied Molecular Technologies (CTMA), Institut de Recherche Expxc3xa9rimentale et Clinique (IREC), Universitxc3xa9 catholique de Louvain, Clos Chapelle-aux-Champs 30, 1200 Bruxelles, Defence Laboratories Department, Belgian Armed Forces, 1800 Vilvoorde, Belgium, Department of Epidemiology and Hygiene, Military Medical Academy of Sofia, 1000 Sofia, Bulgaria and Epidemiology and Biostatistics Department (EPID), Institut de Recherche Expxc3xa9rimentale et Clinique (IREC), Universitxc3xa9 catholique de Louvain, Clos Chapelle-aux-Champs 30, 1200 Bruxelles, Belgium.|Center for Applied Molecular Technologies (CTMA), Institut de Recherche Expxc3xa9rimentale et Clinique (IREC), Universitxc3xa9 catholique de Louvain, Clos Chapelle-aux-Champs 30, 1200 Bruxelles, Defence Laboratories Department, Belgian Armed Forces, 1800 Vilvoorde, Belgium, Department of Epidemiology and Hygiene, Military Medical Academy of Sofia, 1000 Sofia, Bulgaria and Epidemiology and Biostatistics Department (EPID), Institut de Recherche Expxc3xa9rimentale et Clinique (IREC), Universitxc3xa9 catholique de Louvain, Clos Chapelle-aux-Champs 30, 1200 Bruxelles, Belgium.|Center for Applied Molecular Technologies (CTMA), Institut de Recherche Expxc3xa9rimentale et Clinique (IREC), Universitxc3xa9 catholique de Louvain, Clos Chapelle-aux-Champs 30, 1200 Bruxelles, Defence Laboratories Department, Belgian Armed Forces, 1800 Vilvoorde, Belgium, Department of Epidemiology and Hygiene, Military Medical Academy of Sofia, 1000 Sofia, Bulgaria and Epidemiology and Biostatistics Department (EPID), Institut de Recherche Expxc3xa9rimentale et Clinique (IREC), Universitxc3xa9 catholique de Louvain, Clos Chapelle-aux-Champs 30, 1200 Bruxelles, Belgium.|Center for Applied Molecular Technologies (CTMA), Institut de Recherche Expxc3xa9rimentale et Clinique (IREC), Universitxc3xa9 catholique de Louvain, Clos Chapelle-aux-Champs 30, 1200 Bruxelles, Defence Laboratories Department, Belgian Armed Forces, 1800 Vilvoorde, Belgium, Department of Epidemiology and Hygiene, Military Medical Academy of Sofia, 1000 Sofia, Bulgaria and Epidemiology and Biostatistics Department (EPID), Institut de Recherche Expxc3xa9rimentale et Clinique (IREC), Universitxc3xa9 catholique de Louvain, Clos Chapelle-aux-Champs 30, 1200 Bruxelles, Belgium Center for Applied Molecular Technologies (CTMA), Institut de Recherche Expxc3xa9rimentale et Clinique (IREC), Universitxc3xa9 catholique de Louvain, Clos Chapelle-aux-Champs 30, 1200 Bruxelles, Defence Laboratories Department, Belgian Armed Forces, 1800 Vilvoorde, Belgium, Department of Epidemiology and Hygiene, Military Medical Academy of Sofia, 1000 Sofia, Bulgaria and Epidemiology and Biostatistics Department (EPID), Institut de Recherche Expxc3xa9rimentale et Clinique (IREC), Universitxc3xa9 catholique de Louvain, Clos Chapelle-aux-Champs 30, 1200 Bruxelles, Belgium.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 0, 'Algorithms|DNA Primers|DNA, Bacterial|Drug Resistance, Bacterial|Genome, Bacterial|Genotyping Techniques|Nucleotides|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu516', '25173420', 'Pyrosequencing is a cost-effective DNA sequencing technology that has many applications, including rapid genotyping of a broad spectrum of bacteria. When molecular typing requires to genotype multiple DNA stretches, several pyrosequencing primers could be used simultaneously but this would create overlapping primer-specific signals, which are visually uninterpretable. Accordingly, the objective was to develop a new method for signal processing (AdvISER-M-PYRO) to automatically analyze and interpret multiplex pyrosequencing signals. In parallel, the nucleotide dispensation order was improved by developing the SENATOR (SElecting the Nucleotide dispensATion Order) algorithm.'),
(78690, 2015, 'bio', 'VirVarSeq: a low-frequency virus variant detection pipeline for Illumina sequencing using adaptive base-calling accuracy filtering', 'Verbist, Bie M P|Thys, Kim|Reumers, Joke|Wetzels, Yves|Van der Borght, Koen|Talloen, Willem|Aerssens, Jeroen|Clement, Lieven|Thas, Olivier', 'Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Janssen R&D, Janssen Pharmaceutical Companies of Johnson & Johnson, Turnhoutseweg 30, 2340 Beerse, Applied Mathematics, Informatics and Statistics, Ghent University, Krijgslaan 281 S9, 9000 Gent, Belgium and University of Wollongong, National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, NSW 2522, Australia.|Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Janssen R&D, Janssen Pharmaceutical Companies of Johnson & Johnson, Turnhoutseweg 30, 2340 Beerse, Applied Mathematics, Informatics and Statistics, Ghent University, Krijgslaan 281 S9, 9000 Gent, Belgium and University of Wollongong, National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, NSW 2522, Australia.|Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Janssen R&D, Janssen Pharmaceutical Companies of Johnson & Johnson, Turnhoutseweg 30, 2340 Beerse, Applied Mathematics, Informatics and Statistics, Ghent University, Krijgslaan 281 S9, 9000 Gent, Belgium and University of Wollongong, National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, NSW 2522, Australia.|Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Janssen R&D, Janssen Pharmaceutical Companies of Johnson & Johnson, Turnhoutseweg 30, 2340 Beerse, Applied Mathematics, Informatics and Statistics, Ghent University, Krijgslaan 281 S9, 9000 Gent, Belgium and University of Wollongong, National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, NSW 2522, Australia.|Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Janssen R&D, Janssen Pharmaceutical Companies of Johnson & Johnson, Turnhoutseweg 30, 2340 Beerse, Applied Mathematics, Informatics and Statistics, Ghent University, Krijgslaan 281 S9, 9000 Gent, Belgium and University of Wollongong, National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, NSW 2522, Australia.|Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Janssen R&D, Janssen Pharmaceutical Companies of Johnson & Johnson, Turnhoutseweg 30, 2340 Beerse, Applied Mathematics, Informatics and Statistics, Ghent University, Krijgslaan 281 S9, 9000 Gent, Belgium and University of Wollongong, National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, NSW 2522, Australia.|Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Janssen R&D, Janssen Pharmaceutical Companies of Johnson & Johnson, Turnhoutseweg 30, 2340 Beerse, Applied Mathematics, Informatics and Statistics, Ghent University, Krijgslaan 281 S9, 9000 Gent, Belgium and University of Wollongong, National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, NSW 2522, Australia.|Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Janssen R&D, Janssen Pharmaceutical Companies of Johnson & Johnson, Turnhoutseweg 30, 2340 Beerse, Applied Mathematics, Informatics and Statistics, Ghent University, Krijgslaan 281 S9, 9000 Gent, Belgium and University of Wollongong, National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, NSW 2522, Australia.|Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Janssen R&D, Janssen Pharmaceutical Companies of Johnson & Johnson, Turnhoutseweg 30, 2340 Beerse, Applied Mathematics, Informatics and Statistics, Ghent University, Krijgslaan 281 S9, 9000 Gent, Belgium and University of Wollongong, National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, NSW 2522, Australia Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Janssen R&D, Janssen Pharmaceutical Companies of Johnson & Johnson, Turnhoutseweg 30, 2340 Beerse, Applied Mathematics, Informatics and Statistics, Ghent University, Krijgslaan 281 S9, 9000 Gent, Belgium and University of Wollongong, National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, NSW 2522, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia', 21, 'Algorithms|Genetic Variation|Genome, Viral|Genomics|Hepacivirus|Hepatitis C|High-Throughput Nucleotide Sequencing|Humans|Software', 'Journal Article', '10.1093/bioinformatics/btu587', '25178459', 'In virology, massively parallel sequencing (MPS) opens many opportunities for studying viral quasi-species, e.g. in HIV-1- and HCV-infected patients. This is essential for understanding pathways to resistance, which can substantially improve treatment. Although MPS platforms allow in-depth characterization of sequence variation, their measurements still involve substantial technical noise. For Illumina sequencing, single base substitutions are the main error source and impede powerful assessment of low-frequency mutations. Fortunately, base calls are complemented with quality scores (Qs) that are useful for differentiating errors from the real low-frequency mutations.'),
(78691, 2014, 'bio', 'PrEMeR-CG: inferring nucleotide level DNA methylation values from MethylCap-seq data', 'Frankhouser, David E|Murphy, Mark|Blachly, James S|Park, Jincheol|Zoller, Mike W|Ganbat, Javkhlan-Ochir|Curfman, John|Byrd, John C|Lin, Shili|Marcucci, Guido|Yan, Pearlly|Bundschuh, Ralf', 'College of Medicine, Biomedical Sciences Graduate Program, Department of Internal Medicine, Division of Hematology, Department of Statistics, Mathematical Biosciences Institute, Department of Physics, Department of Chemistry & Biochemistry and Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA.|College of Medicine, Biomedical Sciences Graduate Program, Department of Internal Medicine, Division of Hematology, Department of Statistics, Mathematical Biosciences Institute, Department of Physics, Department of Chemistry & Biochemistry and Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA.|College of Medicine, Biomedical Sciences Graduate Program, Department of Internal Medicine, Division of Hematology, Department of Statistics, Mathematical Biosciences Institute, Department of Physics, Department of Chemistry & Biochemistry and Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA.|College of Medicine, Biomedical Sciences Graduate Program, Department of Internal Medicine, Division of Hematology, Department of Statistics, Mathematical Biosciences Institute, Department of Physics, Department of Chemistry & Biochemistry and Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA College of Medicine, Biomedical Sciences Graduate Program, Department of Internal Medicine, Division of Hematology, Department of Statistics, Mathematical Biosciences Institute, Department of Physics, Department of Chemistry & Biochemistry and Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA.|College of Medicine, Biomedical Sciences Graduate Program, Department of Internal Medicine, Division of Hematology, Department of Statistics, Mathematical Biosciences Institute, Department of Physics, Department of Chemistry & Biochemistry and Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA.|College of Medicine, Biomedical Sciences Graduate Program, Department of Internal Medicine, Division of Hematology, Department of Statistics, Mathematical Biosciences Institute, Department of Physics, Department of Chemistry & Biochemistry and Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA.|College of Medicine, Biomedical Sciences Graduate Program, Department of Internal Medicine, Division of Hematology, Department of Statistics, Mathematical Biosciences Institute, Department of Physics, Department of Chemistry & Biochemistry and Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA.|College of Medicine, Biomedical Sciences Graduate Program, Department of Internal Medicine, Division of Hematology, Department of Statistics, Mathematical Biosciences Institute, Department of Physics, Department of Chemistry & Biochemistry and Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA.|College of Medicine, Biomedical Sciences Graduate Program, Department of Internal Medicine, Division of Hematology, Department of Statistics, Mathematical Biosciences Institute, Department of Physics, Department of Chemistry & Biochemistry and Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA.|College of Medicine, Biomedical Sciences Graduate Program, Department of Internal Medicine, Division of Hematology, Department of Statistics, Mathematical Biosciences Institute, Department of Physics, Department of Chemistry & Biochemistry and Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA.|College of Medicine, Biomedical Sciences Graduate Program, Department of Internal Medicine, Division of Hematology, Department of Statistics, Mathematical Biosciences Institute, Department of Physics, Department of Chemistry & Biochemistry and Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA.|College of Medicine, Biomedical Sciences Graduate Program, Department of Internal Medicine, Division of Hematology, Department of Statistics, Mathematical Biosciences Institute, Department of Physics, Department of Chemistry & Biochemistry and Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA College of Medicine, Biomedical Sciences Graduate Program, Department of Internal Medicine, Division of Hematology, Department of Statistics, Mathematical Biosciences Institute, Department of Physics, Department of Chemistry & Biochemistry and Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA College of Medicine, Biomedical Sciences Graduate Program, Department of Internal Medicine, Division of Hematology, Department of Statistics, Mathematical Biosciences Institute, Department of Physics, Department of Chemistry & Biochemistry and Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA College of Medicine, Biomedical Sciences Graduate Program, Department of Internal Medicine, Division of Hematology, Department of Statistics, Mathematical Biosciences Institute, Department of Physics, Department of Chemistry & Biochemistry and Center for RNA Biology, The Ohio State University, Columbus, OH 43210, 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', 0, 'Algorithms|CpG Islands|DNA Methylation|Genomics|High-Throughput Nucleotide Sequencing|Humans|Leukemia, Myeloid, Acute|Nucleotides|Sequence Analysis, DNA|Sulfites', 'Journal Article', '10.1093/bioinformatics/btu583', '25178460', 'DNA methylation is an epigenetic change occurring in genomic CpG sequences that contribute to the regulation of gene transcription both in normal and malignant cells. Next-generation sequencing has been used to characterize DNA methylation status at the genome scale, but suffers from high sequencing cost in the case of whole-genome bisulfite sequencing, or from reduced resolution (inability to precisely define which of the CpGs are methylated) with capture-based techniques.'),
(78692, 2015, 'bio', 'GenPlay Multi-Genome, a tool to compare and analyze multiple human genomes in a graphical interface', 'Lajugie, Julien|Fourel, Nicolas|Bouhassira, Eric E', 'Department of Cell Biology, Albert Einstein College of Medicine, New York, NY 10461, USA.|Department of Cell Biology, Albert Einstein College of Medicine, New York, NY 10461, USA.|Department of Cell Biology, Albert Einstein College of Medicine, New York, NY 10461, USA.', 'United States|United States|United States', 4, 'Computer Graphics|Databases, Genetic|Genome, Human|Humans|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu588', '25178461', 'Parallel visualization of multiple individual human genomes is a complex endeavor that is rapidly gaining importance with the increasing number of personal, phased and cancer genomes that are being generated. It requires the display of variants such as SNPs, indels and structural variants that are unique to specific genomes and the introduction of multiple overlapping gaps in the reference sequence. Here, we describe GenPlay Multi-Genome, an application specifically written to visualize and analyze multiple human genomes in parallel. GenPlay Multi-Genome is ideally suited for the comparison of allele-specific expression and functional genomic data obtained from multiple phased genomes in a graphical interface with access to multiple-track operation. It also allows the analysis of data that have been aligned to custom genomes rather than to a standard reference and can be used as a variant calling format file browser and as a tool to compare different genome assembly, such as hg19 and hg38.'),
(78693, 2015, 'bio', 'Prediction of Indel flanking regions in protein sequences using a variable-order Markov model', 'Al-Shatnawi, Mufleh|Ahmad, M Omair|Swamy, M N S', 'Department of Electrical and Computer Engineering, Concordia University, QC H3G 2W1, Canada.|Department of Electrical and Computer Engineering, Concordia University, QC H3G 2W1, Canada.|Department of Electrical and Computer Engineering, Concordia University, QC H3G 2W1, Canada.', 'Canada|Canada|Canada', 2, 'Algorithms|Amino Acid Substitution|Databases, Protein|Humans|INDEL Mutation|Markov Chains|Proteins', 'Journal Article', '10.1093/bioinformatics/btu556', '25178462', 'Insertion/deletion (indel) and amino acid substitution are two common events that lead to the evolution of and variations in protein sequences. Further, many of the human diseases and functional divergence between homologous proteins are more related to indel mutations, even though they occur less often than the substitution mutations do. A reliable identification of indels and their flanking regions is a major challenge in research related to protein evolution, structures and functions.'),
(78694, 2015, 'bio', 'Over-representation of correlation analysis (ORCA): a method for identifying associations between variable sets', 'Pomyen, Yotsawat|Segura, Marcelo|Ebbels, Timothy M D|Keun, Hector C', 'Department of Surgery and Cancer, Section of Computational and Systems Medicine, Imperial College London, Exhibition Road, London SW7 2AZ, UK and Translational Research Unit, Chulabhorn Research Institute, Bangkok 10210, Thailand Department of Surgery and Cancer, Section of Computational and Systems Medicine, Imperial College London, Exhibition Road, London SW7 2AZ, UK and Translational Research Unit, Chulabhorn Research Institute, Bangkok 10210, Thailand.|Department of Surgery and Cancer, Section of Computational and Systems Medicine, Imperial College London, Exhibition Road, London SW7 2AZ, UK and Translational Research Unit, Chulabhorn Research Institute, Bangkok 10210, Thailand.|Department of Surgery and Cancer, Section of Computational and Systems Medicine, Imperial College London, Exhibition Road, London SW7 2AZ, UK and Translational Research Unit, Chulabhorn Research Institute, Bangkok 10210, Thailand.|Department of Surgery and Cancer, Section of Computational and Systems Medicine, Imperial College London, Exhibition Road, London SW7 2AZ, UK and Translational Research Unit, Chulabhorn Research Institute, Bangkok 10210, Thailand.', 'Thailand|Thailand|Thailand|Thailand', 1, 'Alkylating Agents|Biomarkers, Tumor|Computational Biology|Data Interpretation, Statistical|Databases, Factual|Datasets as Topic|Enzyme Inhibitors|Gene Expression Profiling|Genomics|Humans|MicroRNAs|Molecular Sequence Annotation|Neoplasms|Tumor Cells, Cultured', 'Journal Article', '10.1093/bioinformatics/btu589', '25183485', 'Often during the analysis of biological data, it is of importance to interpret the correlation structure that exists between variables. Such correlations may reveal patterns of co-regulation that are indicative of biochemical pathways or common mechanisms of response to a related set of treatments. However, analyses of correlations are usually conducted by either subjective interpretation of the univariate covariance matrix or by applying multivariate modeling techniques, which do not take prior biological knowledge into account. Over-representation analysis (ORA) is a simple method for objectively deciding whether a set of variables of known or suspected biological relevance, such as a gene set or pathway, is more prevalent in a set of variables of interest than we expect by chance. However, ORA is usually applied to a set of variables differentiating a single experimental variable and does not take into account correlations.'),
(78695, 2014, 'bio', 'String graph construction using incremental hashing', 'Ben-Bassat, Ilan|Chor, Benny', 'School of Computer Science, Tel-Aviv University.|School of Computer Science, Tel-Aviv University.', '-|-', 9, 'Algorithms|Genomics|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu578', '25183486', 'New sequencing technologies generate larger amount of short reads data at decreasing cost. De novo sequence assembly is the problem of combining these reads back to the original genome sequence, without relying on a reference genome. This presents algorithmic and computational challenges, especially for long and repetitive genome sequences. Most existing approaches to the assembly problem operate in the framework of de Bruijn graphs. Yet, a number of recent works use the paradigm of string graph, using a variety of methods for storing and processing suffixes and prefixes, like suffix arrays, the Burrows-Wheeler transform or the FM index. Our work is motivated by a search for new approaches to constructing the string graph, using alternative yet simple data structures and algorithmic concepts.'),
(78696, 2015, 'bio', 'RCSB PDB Mobile: iOS and Android mobile apps to provide data access and visualization to the RCSB Protein Data Bank', 'Quinn, Gregory B|Bi, Chunxiao|Christie, Cole H|Pang, Kyle|Prlixc4x87, Andreas|Nakane, Takanori|Zardecki, Christine|Voigt, Maria|Berman, Helen M|Bourne, Philip E|Rose, Peter W', 'RCSB Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093-0743, USA, Graduate School of Medicine, Kyoto University, Yoshidakonoecho, Sakyo Ward, Kyoto, Kyoto Prefecture 606-8501, Japan, RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854-8087 and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093-0743.|RCSB Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093-0743, USA, Graduate School of Medicine, Kyoto University, Yoshidakonoecho, Sakyo Ward, Kyoto, Kyoto Prefecture 606-8501, Japan, RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854-8087 and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093-0743.|RCSB Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093-0743, USA, Graduate School of Medicine, Kyoto University, Yoshidakonoecho, Sakyo Ward, Kyoto, Kyoto Prefecture 606-8501, Japan, RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854-8087 and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093-0743.|RCSB Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093-0743, USA, Graduate School of Medicine, Kyoto University, Yoshidakonoecho, Sakyo Ward, Kyoto, Kyoto Prefecture 606-8501, Japan, RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854-8087 and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093-0743.|RCSB Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093-0743, USA, Graduate School of Medicine, Kyoto University, Yoshidakonoecho, Sakyo Ward, Kyoto, Kyoto Prefecture 606-8501, Japan, RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854-8087 and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093-0743.|RCSB Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093-0743, USA, Graduate School of Medicine, Kyoto University, Yoshidakonoecho, Sakyo Ward, Kyoto, Kyoto Prefecture 606-8501, Japan, RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854-8087 and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093-0743.|RCSB Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093-0743, USA, Graduate School of Medicine, Kyoto University, Yoshidakonoecho, Sakyo Ward, Kyoto, Kyoto Prefecture 606-8501, Japan, RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854-8087 and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093-0743.|RCSB Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093-0743, USA, Graduate School of Medicine, Kyoto University, Yoshidakonoecho, Sakyo Ward, Kyoto, Kyoto Prefecture 606-8501, Japan, RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854-8087 and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093-0743.|RCSB Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093-0743, USA, Graduate School of Medicine, Kyoto University, Yoshidakonoecho, Sakyo Ward, Kyoto, Kyoto Prefecture 606-8501, Japan, RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854-8087 and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093-0743.|RCSB Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093-0743, USA, Graduate School of Medicine, Kyoto University, Yoshidakonoecho, Sakyo Ward, Kyoto, Kyoto Prefecture 606-8501, Japan, RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854-8087 and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093-0743 RCSB Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093-0743, USA, Graduate School of Medicine, Kyoto University, Yoshidakonoecho, Sakyo Ward, Kyoto, Kyoto Prefecture 606-8501, Japan, RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854-8087 and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093-0743.|RCSB Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093-0743, USA, Graduate School of Medicine, Kyoto University, Yoshidakonoecho, Sakyo Ward, Kyoto, Kyoto Prefecture 606-8501, Japan, RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854-8087 and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093-0743.', 'Jersey|Jersey|Jersey|Jersey|Jersey|Jersey|Jersey|Jersey|Jersey|Jersey|Jersey', 0, 'Biomedical Research|Computational Biology|Computer Graphics|Databases, Protein|Humans|Mobile Applications|Software|User-Computer Interface|Workflow', 'Journal Article', '10.1093/bioinformatics/btu596', '25183487', 'The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) resource provides tools for query, analysis and visualization of the 3D structures in the PDB archive. As the mobile Web is starting to surpass desktop and laptop usage, scientists and educators are beginning to integrate mobile devices into their research and teaching. In response, we have developed the RCSB PDB Mobile app for the iOS and Android mobile platforms to enable fast and convenient access to RCSB PDB data and services. Using the app, users from the general public to expert researchers can quickly search and visualize biomolecules, and add personal annotations via the RCSB PDBs integrated MyPDB service.'),
(78697, 2015, 'bio', 'CCharPPI web server: computational characterization of protein-protein interactions from structure', 'Moal, Iain H|Jiménez-García, Brian|Fernández-Recio, Juan', 'Joint BSC-IRB Research Programme in Computational Biology, Department of Life Sciences, Barcelona Supercomputing Center, C/Jordi Girona 29, 08034 Barcelona, Spain.|Joint BSC-IRB Research Programme in Computational Biology, Department of Life Sciences, Barcelona Supercomputing Center, C/Jordi Girona 29, 08034 Barcelona, Spain.|Joint BSC-IRB Research Programme in Computational Biology, Department of Life Sciences, Barcelona Supercomputing Center, C/Jordi Girona 29, 08034 Barcelona, Spain.', 'Spain|Spain|Spain', 34, 'Humans|Hydrogen Bonding|Internet|Molecular Docking Simulation|Multiprotein Complexes|Protein Interaction Mapping|Software|Static Electricity', 'Journal Article', '10.1093/bioinformatics/btu594', '25183488', 'The atomic structures of protein-protein interactions are central to understanding their role in biological systems, and a wide variety of biophysical functions and potentials have been developed for their characterization and the construction of predictive models. These tools are scattered across a multitude of stand-alone programs, and are often available only as model parameters requiring reimplementation. This acts as a significant barrier to their widespread adoption. CCharPPI integrates many of these tools into a single web server. It calculates up to 108 parameters, including models of electrostatics, desolvation and hydrogen bonding, as well as interface packing and complementarity scores, empirical potentials at various resolutions, docking potentials and composite scoring functions.'),
(78698, 2015, 'bio', 'ballaxy: web services for structural bioinformatics', 'Hildebrandt, Anna Katharina|Stxc3xb6ckel, Daniel|Fischer, Nina M|de la Garza, Luis|Krxc3xbcger, Jens|Nickels, Stefan|Rxc3xb6ttig, Marc|Schxc3xa4rfe, Charlotta|Schumann, Marcel|Thiel, Philipp|Lenhof, Hans-Peter|Kohlbacher, Oliver|Hildebrandt, Andreas', 'Center for Bioinformatics, Saarland University, 66041 Saarbrxc3xbccken, Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, University of Txc3xbcbingen, 72607 Txc3xbcbingen and Chair for Software-Engineering and Bioinformatics, Institute for Informatics, Johannes-Gutenberg-University Mainz, 55128 Mainz, Germany.|Center for Bioinformatics, Saarland University, 66041 Saarbrxc3xbccken, Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, University of Txc3xbcbingen, 72607 Txc3xbcbingen and Chair for Software-Engineering and Bioinformatics, Institute for Informatics, Johannes-Gutenberg-University Mainz, 55128 Mainz, Germany.|Center for Bioinformatics, Saarland University, 66041 Saarbrxc3xbccken, Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, University of Txc3xbcbingen, 72607 Txc3xbcbingen and Chair for Software-Engineering and Bioinformatics, Institute for Informatics, Johannes-Gutenberg-University Mainz, 55128 Mainz, Germany.|Center for Bioinformatics, Saarland University, 66041 Saarbrxc3xbccken, Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, University of Txc3xbcbingen, 72607 Txc3xbcbingen and Chair for Software-Engineering and Bioinformatics, Institute for Informatics, Johannes-Gutenberg-University Mainz, 55128 Mainz, Germany.|Center for Bioinformatics, Saarland University, 66041 Saarbrxc3xbccken, Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, University of Txc3xbcbingen, 72607 Txc3xbcbingen and Chair for Software-Engineering and Bioinformatics, Institute for Informatics, Johannes-Gutenberg-University Mainz, 55128 Mainz, Germany.|Center for Bioinformatics, Saarland University, 66041 Saarbrxc3xbccken, Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, University of Txc3xbcbingen, 72607 Txc3xbcbingen and Chair for Software-Engineering and Bioinformatics, Institute for Informatics, Johannes-Gutenberg-University Mainz, 55128 Mainz, Germany.|Center for Bioinformatics, Saarland University, 66041 Saarbrxc3xbccken, Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, University of Txc3xbcbingen, 72607 Txc3xbcbingen and Chair for Software-Engineering and Bioinformatics, Institute for Informatics, Johannes-Gutenberg-University Mainz, 55128 Mainz, Germany.|Center for Bioinformatics, Saarland University, 66041 Saarbrxc3xbccken, Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, University of Txc3xbcbingen, 72607 Txc3xbcbingen and Chair for Software-Engineering and Bioinformatics, Institute for Informatics, Johannes-Gutenberg-University Mainz, 55128 Mainz, Germany.|Center for Bioinformatics, Saarland University, 66041 Saarbrxc3xbccken, Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, University of Txc3xbcbingen, 72607 Txc3xbcbingen and Chair for Software-Engineering and Bioinformatics, Institute for Informatics, Johannes-Gutenberg-University Mainz, 55128 Mainz, Germany.|Center for Bioinformatics, Saarland University, 66041 Saarbrxc3xbccken, Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, University of Txc3xbcbingen, 72607 Txc3xbcbingen and Chair for Software-Engineering and Bioinformatics, Institute for Informatics, Johannes-Gutenberg-University Mainz, 55128 Mainz, Germany.|Center for Bioinformatics, Saarland University, 66041 Saarbrxc3xbccken, Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, University of Txc3xbcbingen, 72607 Txc3xbcbingen and Chair for Software-Engineering and Bioinformatics, Institute for Informatics, Johannes-Gutenberg-University Mainz, 55128 Mainz, Germany.|Center for Bioinformatics, Saarland University, 66041 Saarbrxc3xbccken, Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, University of Txc3xbcbingen, 72607 Txc3xbcbingen and Chair for Software-Engineering and Bioinformatics, Institute for Informatics, Johannes-Gutenberg-University Mainz, 55128 Mainz, Germany.|Center for Bioinformatics, Saarland University, 66041 Saarbrxc3xbccken, Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, University of Txc3xbcbingen, 72607 Txc3xbcbingen and Chair for Software-Engineering and Bioinformatics, Institute for Informatics, Johannes-Gutenberg-University Mainz, 55128 Mainz, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germ', 0, 'Algorithms|Computational Biology|Humans|Models, Molecular|Sequence Analysis, DNA|Software|Systems Integration|User-Computer Interface|Workflow', 'Journal Article', '10.1093/bioinformatics/btu574', '25183489', 'Web-based workflow systems have gained considerable momentum in sequence-oriented bioinformatics. In structural bioinformatics, however, such systems are still relatively rare, while commercial stand-alone workflow applications are common in the pharmaceutical industry, academic researchers often still rely on command-line scripting to glue individual tools together.'),
(78699, 2015, 'bio', 'BigDataScript: a scripting language for data pipelines', 'Cingolani, Pablo|Sladek, Rob|Blanchette, Mathieu', 'McGill University School of Computer Science, 3480 University Street, Montreal, Québec H3A 0E9 and McGill University and Génome Québec Innovation Centre, 740 Dr. Penfield Avenue, Montréal, Québec H3A 0G1, Canada McGill University School of Computer Science, 3480 University Street, Montreal, Québec H3A 0E9 and McGill University and Génome Québec Innovation Centre, 740 Dr. Penfield Avenue, Montréal, Québec H3A 0G1, Canada.|McGill University School of Computer Science, 3480 University Street, Montreal, Québec H3A 0E9 and McGill University and Génome Québec Innovation Centre, 740 Dr. Penfield Avenue, Montréal, Québec H3A 0G1, Canada.|McGill University School of Computer Science, 3480 University Street, Montreal, Québec H3A 0E9 and McGill University and Génome Québec Innovation Centre, 740 Dr. Penfield Avenue, Montréal, Québec H3A 0G1, Canada.', 'Canada|Canada|Canada', 0, 'Computational Biology|High-Throughput Nucleotide Sequencing|Humans|Programming Languages|Software|Workflow', 'Journal Article', '10.1093/bioinformatics/btu595', '25189778', 'The analysis of large biological datasets often requires complex processing pipelines that run for a long time on large computational infrastructures. We designed and implemented a simple script-like programming language with a clean and minimalist syntax to develop and manage pipeline execution and provide robustness to various types of software and hardware failures as well as portability.'),
(78700, 2015, 'bio', 'Gene regulatory networks by transcription factors and microRNAs in breast cancer', 'Qin, Sheng|Ma, Fei|Chen, Liming', 'The Key Laboratory of Developmental Genes and Human Disease, Ministry of Education, Institute of Life Science, Southeast University Nanjing 210096, China and Laboratory for Comparative Genomics and Bioinformatics & Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Science, Nanjing Normal University, Nanjing 210046, China The Key Laboratory of Developmental Genes and Human Disease, Ministry of Education, Institute of Life Science, Southeast University Nanjing 210096, China and Laboratory for Comparative Genomics and Bioinformatics & Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Science, Nanjing Normal University, Nanjing 210046, China.|The Key Laboratory of Developmental Genes and Human Disease, Ministry of Education, Institute of Life Science, Southeast University Nanjing 210096, China and Laboratory for Comparative Genomics and Bioinformatics & Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Science, Nanjing Normal University, Nanjing 210046, China.|The Key Laboratory of Developmental Genes and Human Disease, Ministry of Education, Institute of Life Science, Southeast University Nanjing 210096, China and Laboratory for Comparative Genomics and Bioinformatics & Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Science, Nanjing Normal University, Nanjing 210046, China.', 'China|China|China', 18, 'Algorithms|Breast Neoplasms|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Humans|MicroRNAs|RNA, Messenger|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btu597', '25189779', 'Gene regulatory networks (GRNs) affect numerous cellular processes and every process of life, and abnormalities of GRN lead to breast cancer. Transcription factors (TFs) and microRNAs (miRNAs) are two of the best-studied gene regulatory mechanisms. However, the architecture and feature of GRNs by TFs and miRNAs in breast cancer and its subtypes were unknown. In this study, we investigated the GRNs by TFs and miRNAs with emphasis on breast cancer classifier genes at system level.'),
(78701, 2015, 'bio', 'Estimation of GFP-tagged RNA numbers from temporal fluorescence intensity data', 'Häkkinen, Antti|Ribeiro, Andre S', 'Laboratory of Biosystem Dynamics, Computational Systems Biology Research Group, Department of Signal Processing, Tampere University of Technology, P.O. box 553, 33101 Tampere, Finland.|Laboratory of Biosystem Dynamics, Computational Systems Biology Research Group, Department of Signal Processing, Tampere University of Technology, P.O. box 553, 33101 Tampere, Finland.', 'Finland|Finland', 13, 'Algorithms|Escherichia coli|Fluorescence|Fluorescent Dyes|Green Fluorescent Proteins|Image Processing, Computer-Assisted|Monte Carlo Method|RNA, Bacterial', 'Journal Article', '10.1093/bioinformatics/btu592', '25189780', 'MS2-GFP-tagging of RNA is currently the only method to measure intervals between consecutive transcription events in live cells. For this, new transcripts must be accurately detected from intensity time traces.'),
(78702, 2014, 'bio', 'subSeq: determining appropriate sequencing depth through efficient read subsampling', 'Robinson, David G|Storey, John D', 'Lewis-Sigler Institute for Integrative Genomics and Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA.|Lewis-Sigler Institute for Integrative Genomics and Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA Lewis-Sigler Institute for Integrative Genomics and Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA.', 'United States|United States', 0, 'Animals|High-Throughput Nucleotide Sequencing|Rats|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu552', '25189781', 'Next-generation sequencing experiments, such as RNA-Seq, play an increasingly important role in biological research. One complication is that the power and accuracy of such experiments depend substantially on the number of reads sequenced, so it is important and challenging to determine the optimal read depth for an experiment or to verify whether one has adequate depth in an existing experiment.');
