INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78703, 2015, 'bio', 'The GOBLET training portal: a global repository of bioinformatics training materials, courses and trainers', 'Corpas, Manuel|Jimenez, Rafael C|Bongcam-Rudloff, Erik|Budd, Aidan|Brazas, Michelle D|Fernandes, Pedro L|Gaeta, Bruno|van Gelder, Celia|Korpelainen, Eija|Lewitter, Fran|McGrath, Annette|MacLean, Daniel|Palagi, Patricia M|Rother, Kristian|Taylor, Jan|Via, Allegra|Watson, Mick|Schneider, Maria Victoria|Attwood, Teresa K', 'The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.|The Genome Analysis Centre, Norwich, ELIXIR, Wellcome Trust Genome Campus, Hinxton, UK, The Swedish University for Agricultural Sciences, Uppsala, Sweden, European Molecular Biology Laboratory, Heidelberg, Germany, Ontario Institute for Cancer Research, Toronto, Canada, Instituto Gulbenkian de Ciência, Oeiras, Portugal, The University of New South Wales, Sydney, Australia, Netherlands Bioinformatics Centre, Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands, CSC - IT Center for Science Ltd., Espoo, Finland, Whitehead Institute for Biomedical Research, MIT, Cambridge, MA, USA, CSIRO, Bioinformatics Core, Canberra, Australia, The Sainsbury Laboratory, Norwich Research Park, Norwich, UK, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, Genève, Switzerland, Academis, Illstrasse 12, 12161 Berlin, Germany, The Nowgen Centre, 29 Grafton Street, Manchester, UK, Department of Physics, Sapienza University, Rome, Italy, The Roslin Institute, Edinburgh, UK and The University of Manchester, Manchester, UK.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|', 21, 'Computational Biology|Curriculum|Database Management Systems|Humans|Programming Languages|Research Personnel|Software Design|Teaching', 'Journal Article', '10.1093/bioinformatics/btu601', '25189782', 'Rapid technological advances have led to an explosion of biomedical data in recent years. The pace of change has inspired new collaborative approaches for sharing materials and resources to help train life scientists both in the use of cutting-edge bioinformatics tools and databases and in how to analyse and interpret large datasets. A prototype platform for sharing such training resources was recently created by the Bioinformatics Training Network (BTN). Building on this work, we have created a centralized portal for sharing training materials and courses, including a catalogue of trainers and course organizers, and an announcement service for training events. For course organizers, the portal provides opportunities to promote their training events, for trainers, the portal offers an environment for sharing materials, for gaining visibility for their work and promoting their skills, for trainees, it offers a convenient one-stop shop for finding suitable training resources and identifying relevant training events and activities locally and worldwide.'),
(78704, 2015, 'bio', 'Insights into structural variations and genome rearrangements in prokaryotic genomes', 'Periwal, Vinita|Scaria, Vinod', 'GN Ramachandran Knowledge Center for Genome Informatics, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi 110007 and Academy of Scientific & Innovative Research (AcSIR), Anusandhan Bhawan, New Delhi 110001, India GN Ramachandran Knowledge Center for Genome Informatics, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi 110007 and Academy of Scientific & Innovative Research (AcSIR), Anusandhan Bhawan, New Delhi 110001, India.|GN Ramachandran Knowledge Center for Genome Informatics, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi 110007 and Academy of Scientific & Innovative Research (AcSIR), Anusandhan Bhawan, New Delhi 110001, India GN Ramachandran Knowledge Center for Genome Informatics, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi 110007 and Academy of Scientific & Innovative Research (AcSIR), Anusandhan Bhawan, New Delhi 110001, India.', 'India|India', 14, 'Bacteria|DNA Copy Number Variations|Gene Rearrangement|Genome, Bacterial|Prokaryotic Cells|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu600', '25189783', 'Structural variations (SVs) are genomic rearrangements that affect fairly large fragments of DNA. Most of the SVs such as inversions, deletions and translocations have been largely studied in context of genetic diseases in eukaryotes. However, recent studies demonstrate that genome rearrangements can also have profound impact on prokaryotic genomes, leading to altered cell phenotype. In contrast to single-nucleotide variations, SVs provide a much deeper insight into organization of bacterial genomes at a much better resolution. SVs can confer change in gene copy number, creation of new genes, altered gene expression and many other functional consequences. High-throughput technologies have now made it possible to explore SVs at a much refined resolution in bacterial genomes. Through this review, we aim to highlight the importance of the less explored field of SVs in prokaryotic genomes and their impact. We also discuss its potential applicability in the emerging fields of synthetic biology and genome engineering where targeted SVs could serve to create sophisticated and accurate genome editing.'),
(78705, 2015, 'bio', 'mod_bio: Apache modules for Next-Generation sequencing data', 'Lindenbaum, Pierre|Redon, Richard', 'Institut National de la Santé et de la Recherche Médicale (INSERM) Unité Mixte de Recherche (UMR) 1087, LInstitut du Thorax, Centre National de la Recherche Scientifique (CNRS) UMR 6291, Centre Hospitalier Universitaire (CHU) de Nantes, LInstitut du Thorax, Service de Cardiologie, 44000 Nantes and Université de Nantes, 44000 Nantes, France Institut National de la Santé et de la Recherche Médicale (INSERM) Unité Mixte de Recherche (UMR) 1087, LInstitut du Thorax, Centre National de la Recherche Scientifique (CNRS) UMR 6291, Centre Hospitalier Universitaire (CHU) de Nantes, LInstitut du Thorax, Service de Cardiologie, 44000 Nantes and Université de Nantes, 44000 Nantes, France Institut National de la Santé et de la Recherche Médicale (INSERM) Unité Mixte de Recherche (UMR) 1087, LInstitut du Thorax, Centre National de la Recherche Scientifique (CNRS) UMR 6291, Centre Hospitalier Universitaire (CHU) de Nantes, LInstitut du Thorax, Service de Cardiologie, 44000 Nantes and Université de Nantes, 44000 Nantes, France Institut National de la Santé et de la Recherche Médicale (INSERM) Unité Mixte de Recherche (UMR) 1087, LInstitut du Thorax, Centre National de la Recherche Scientifique (CNRS) UMR 6291, Centre Hospitalier Universitaire (CHU) de Nantes, LInstitut du Thorax, Service de Cardiologie, 44000 Nantes and Université de Nantes, 44000 Nantes, France.|Institut National de la Santé et de la Recherche Médicale (INSERM) Unité Mixte de Recherche (UMR) 1087, LInstitut du Thorax, Centre National de la Recherche Scientifique (CNRS) UMR 6291, Centre Hospitalier Universitaire (CHU) de Nantes, LInstitut du Thorax, Service de Cardiologie, 44000 Nantes and Université de Nantes, 44000 Nantes, France Institut National de la Santé et de la Recherche Médicale (INSERM) Unité Mixte de Recherche (UMR) 1087, LInstitut du Thorax, Centre National de la Recherche Scientifique (CNRS) UMR 6291, Centre Hospitalier Universitaire (CHU) de Nantes, LInstitut du Thorax, Service de Cardiologie, 44000 Nantes and Université de Nantes, 44000 Nantes, France Institut National de la Santé et de la Recherche Médicale (INSERM) Unité Mixte de Recherche (UMR) 1087, LInstitut du Thorax, Centre National de la Recherche Scientifique (CNRS) UMR 6291, Centre Hospitalier Universitaire (CHU) de Nantes, LInstitut du Thorax, Service de Cardiologie, 44000 Nantes and Université de Nantes, 44000 Nantes, France Institut National de la Santé et de la Recherche Médicale (INSERM) Unité Mixte de Recherche (UMR) 1087, LInstitut du Thorax, Centre National de la Recherche Scientifique (CNRS) UMR 6291, Centre Hospitalier Universitaire (CHU) de Nantes, LInstitut du Thorax, Service de Cardiologie, 44000 Nantes and Université de Nantes, 44000 Nantes, France.', 'France|France', 0, 'Databases, Factual|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA|Software|User-Computer Interface|Web Browser', 'Journal Article', '10.1093/bioinformatics/btu547', '25192739', 'We describe mod_bio, a set of modules for the Apache HTTP server that allows the users to access and query fastq, tabix, fasta and bam files through a Web browser. Those data are made available in plain text, HTML, XML, JSON and JSON-P. A javascript-based genome browser using the JSON-P communication technique is provided as an example of cross-domain Web service.'),
(78706, 2015, 'bio', 'Genomon ITDetector: a tool for somatic internal tandem duplication detection from cancer genome sequencing data', 'Chiba, Kenichi|Shiraishi, Yuichi|Nagata, Yasunobu|Yoshida, Kenichi|Imoto, Seiya|Ogawa, Seishi|Miyano, Satoru', 'Laboratory of DNA Information Analysis, Human Genome Center, the Institute of Medical Science, The University of Tokyo, Tokyo 108-8639 and Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan.|Laboratory of DNA Information Analysis, Human Genome Center, the Institute of Medical Science, The University of Tokyo, Tokyo 108-8639 and Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan.|Laboratory of DNA Information Analysis, Human Genome Center, the Institute of Medical Science, The University of Tokyo, Tokyo 108-8639 and Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan.|Laboratory of DNA Information Analysis, Human Genome Center, the Institute of Medical Science, The University of Tokyo, Tokyo 108-8639 and Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan.|Laboratory of DNA Information Analysis, Human Genome Center, the Institute of Medical Science, The University of Tokyo, Tokyo 108-8639 and Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan.|Laboratory of DNA Information Analysis, Human Genome Center, the Institute of Medical Science, The University of Tokyo, Tokyo 108-8639 and Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan.|Laboratory of DNA Information Analysis, Human Genome Center, the Institute of Medical Science, The University of Tokyo, Tokyo 108-8639 and Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 13, 'Computational Biology|DNA Mutational Analysis|Exome|High-Throughput Nucleotide Sequencing|Humans|Leukemia, Myeloid, Acute|Mutation|Tandem Repeat Sequences|fms-Like Tyrosine Kinase 3', 'Journal Article', '10.1093/bioinformatics/btu593', '25192740', 'Somatic internal tandem duplications (ITDs) are known to play important roles in cancer pathogenesis. Although recent advances in high-throughput sequencing technologies have enabled genome-wide detection of various types of genomic mutations, including single nucleotide variants, indels and structural variations, only a few studies have focused on ITDs. We have developed an analytical tool called Genomon ITDetector for genome-wide detection of somatic ITDs. After evaluating the sensitivity and precision of the proposed approach using synthetic data, we have demonstrated that it can successfully detect not only common ITDs involving FLT3, but also a number of ITDs affecting other putative driver genes in acute myeloid leukemia exome sequencing data. Availability and implementaion: Genomon ITDetector is freely available at https://github.com/ken0-1n/Genomon-ITDetector.'),
(78707, 2015, 'bio', 'BalestraWeb: efficient online evaluation of drug-target interactions', 'Cobanoglu, Murat Can|Oltvai, Zoltán N|Taylor, D Lansing|Bahar, Ivet', 'Department of Computational and Systems Biology, University of Pittsburgh, School of Medicine, Pittsburgh, PA, The University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA 15260 and Department of Pathology, University of Pittsburgh, School of Medicine, Pittsburgh, PA 15213, USA Department of Computational and Systems Biology, University of Pittsburgh, School of Medicine, Pittsburgh, PA, The University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA 15260 and Department of Pathology, University of Pittsburgh, School of Medicine, Pittsburgh, PA 15213, USA.|Department of Computational and Systems Biology, University of Pittsburgh, School of Medicine, Pittsburgh, PA, The University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA 15260 and Department of Pathology, University of Pittsburgh, School of Medicine, Pittsburgh, PA 15213, USA Department of Computational and Systems Biology, University of Pittsburgh, School of Medicine, Pittsburgh, PA, The University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA 15260 and Department of Pathology, University of Pittsburgh, School of Medicine, Pittsburgh, PA 15213, USA.|Department of Computational and Systems Biology, University of Pittsburgh, School of Medicine, Pittsburgh, PA, The University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA 15260 and Department of Pathology, University of Pittsburgh, School of Medicine, Pittsburgh, PA 15213, USA Department of Computational and Systems Biology, University of Pittsburgh, School of Medicine, Pittsburgh, PA, The University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA 15260 and Department of Pathology, University of Pittsburgh, School of Medicine, Pittsburgh, PA 15213, USA.|Department of Computational and Systems Biology, University of Pittsburgh, School of Medicine, Pittsburgh, PA, The University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA 15260 and Department of Pathology, University of Pittsburgh, School of Medicine, Pittsburgh, PA 15213, USA.', 'United States|United States|United States|United States', 0, 'Databases, Pharmaceutical|Databases, Protein|Drug Discovery|Drug Repositioning|Humans|Internet|Software', 'Evaluation Studies', '10.1093/bioinformatics/btu599', '25192741', 'BalestraWeb is an online server that allows users to instantly make predictions about the potential occurrence of interactions between any given drug-target pair, or predict the most likely interaction partners of any drug or target listed in the DrugBank. It also permits users to identify most similar drugs or most similar targets based on their interaction patterns. Outputs help to develop hypotheses about drug repurposing as well as potential side effects.'),
(78708, 2015, 'bio', 'SignalSpider: probabilistic pattern discovery on multiple normalized ChIP-Seq signal profiles', 'Wong, Ka-Chun|Li, Yue|Peng, Chengbin|Zhang, Zhaolei', 'Department of Computer Science and Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, CEMSE Division, King Abdullah University of Science and Technology, Thuwal, Jeddah, K.S.A., Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada Department of Computer Science and Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, CEMSE Division, King Abdullah University of Science and Technology, Thuwal, Jeddah, K.S.A., Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.|Department of Computer Science and Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, CEMSE Division, King Abdullah University of Science and Technology, Thuwal, Jeddah, K.S.A., Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada Department of Computer Science and Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, CEMSE Division, King Abdullah University of Science and Technology, Thuwal, Jeddah, K.S.A., Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.|Department of Computer Science and Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, CEMSE Division, King Abdullah University of Science and Technology, Thuwal, Jeddah, K.S.A., Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.|Department of Computer Science and Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, CEMSE Division, King Abdullah University of Science and Technology, Thuwal, Jeddah, K.S.A., Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada Department of Computer Science and Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, CEMSE Division, King Abdullah University of Science and Technology, Thuwal, Jeddah, K.S.A., Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada Department of Computer Science and Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, CEMSE Division, King Abdullah University of Science and Technology, Thuwal, Jeddah, K.S.A., Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada Department of Computer Science and Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, CEMSE Division, King Abdullah University of Science and Technology, Thuwal, Jeddah, K.S.A., Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.', 'Canada|Canada|Canada|Canada', 21, 'Chromatin Immunoprecipitation|Cluster Analysis|Computational Biology|DNA-Binding Proteins|High-Throughput Nucleotide Sequencing|Humans|Pattern Recognition, Automated|Regulatory Sequences, Nucleic Acid|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btu604', '25192742', 'Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-Seq) measures the genome-wide occupancy of transcription factors in vivo. Different combinations of DNA-binding protein occupancies may result in a gene being expressed in different tissues or at different developmental stages. To fully understand the functions of genes, it is essential to develop probabilistic models on multiple ChIP-Seq profiles to decipher the combinatorial regulatory mechanisms by multiple transcription factors.'),
(78709, 2015, 'bio', 'Snowball: resampling combined with distance-based regression to discover transcriptional consequences of a driver mutation', 'Xu, Yaomin|Guo, Xingyi|Sun, Jiayang|Zhao, Zhongming', 'Department of Biomedical Informatics, Department of Biostatistics and Center for Quantitative Sciences, Vanderbilt University, Nashville, TN 37232, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, Department of Psychiatry and Department of Cancer Biology, Vanderbilt University, Nashville, TN 37212, USA Department of Biomedical Informatics, Department of Biostatistics and Center for Quantitative Sciences, Vanderbilt University, Nashville, TN 37232, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, Department of Psychiatry and Department of Cancer Biology, Vanderbilt University, Nashville, TN 37212, USA Department of Biomedical Informatics, Department of Biostatistics and Center for Quantitative Sciences, Vanderbilt University, Nashville, TN 37232, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, Department of Psychiatry and Department of Cancer Biology, Vanderbilt University, Nashville, TN 37212, USA.|Department of Biomedical Informatics, Department of Biostatistics and Center for Quantitative Sciences, Vanderbilt University, Nashville, TN 37232, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, Department of Psychiatry and Department of Cancer Biology, Vanderbilt University, Nashville, TN 37212, USA.|Department of Biomedical Informatics, Department of Biostatistics and Center for Quantitative Sciences, Vanderbilt University, Nashville, TN 37232, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, Department of Psychiatry and Department of Cancer Biology, Vanderbilt University, Nashville, TN 37212, USA.|Department of Biomedical Informatics, Department of Biostatistics and Center for Quantitative Sciences, Vanderbilt University, Nashville, TN 37232, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, Department of Psychiatry and Department of Cancer Biology, Vanderbilt University, Nashville, TN 37212, USA Department of Biomedical Informatics, Department of Biostatistics and Center for Quantitative Sciences, Vanderbilt University, Nashville, TN 37232, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, Department of Psychiatry and Department of Cancer Biology, Vanderbilt University, Nashville, TN 37212, USA Department of Biomedical Informatics, Department of Biostatistics and Center for Quantitative Sciences, Vanderbilt University, Nashville, TN 37232, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, Department of Psychiatry and Department of Cancer Biology, Vanderbilt University, Nashville, TN 37212, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Computer Simulation|DNA Mutational Analysis|Gene Expression Profiling|Genomics|Humans|Melanoma|Models, Genetic|Mutation|Neoplasms|Proto-Oncogene Proteins B-raf|Regression Analysis', 'Journal Article', '10.1093/bioinformatics/btu603', '25192743', 'Large-scale cancer genomic studies, such as The Cancer Genome Atlas (TCGA), have profiled multidimensional genomic data, including mutation and expression profiles on a variety of cancer cell types, to uncover the molecular mechanism of cancerogenesis. More than a hundred driver mutations have been characterized that confer the advantage of cell growth. However, how driver mutations regulate the transcriptome to affect cellular functions remains largely unexplored. Differential analysis of gene expression relative to a driver mutation on patient samples could provide us with new insights in understanding driver mutation dysregulation in tumor genome and developing personalized treatment strategies.'),
(78710, 2015, 'bio', 'cddApp: a Cytoscape app for accessing the NCBI conserved domain database', 'Morris, John H|Wu, Allan|Yamashita, Roxanne A|Marchler-Bauer, Aron|Ferrin, Thomas E', 'Resource for Biocomputing, Visualization, and Informatics, University of California, San Francisco, CA 94143, USA and National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.|Resource for Biocomputing, Visualization, and Informatics, University of California, San Francisco, CA 94143, USA and National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.|Resource for Biocomputing, Visualization, and Informatics, University of California, San Francisco, CA 94143, USA and National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.|Resource for Biocomputing, Visualization, and Informatics, University of California, San Francisco, CA 94143, USA and National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.|Resource for Biocomputing, Visualization, and Informatics, University of California, San Francisco, CA 94143, USA and National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Bacillus|Bacterial Proteins|Computational Biology|Conserved Sequence|Databases, Protein|Humans|Metabolic Networks and Pathways|Molecular Sequence Annotation|Protein Conformation|Protein Interaction Mapping|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btu605', '25212755', 'cddApp is a Cytoscape extension that supports the annotation of protein networks with information about domains and specific functional sites from the National Center for Biotechnology Informations conserved domain database (CDD). CDD information is loaded for nodes annotated with NCBI numbers or UniProt identifiers and (optionally) Protein Data Bank structures. cddApp integrates with the Cytoscape apps structureViz2 and enhancedGraphics. Together, these three apps provide powerful tools to annotate nodes with CDD domain and site information and visualize that information in both network and structural contexts.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78711, 2015, 'bio', 'UNDO: a Bioconductor R package for unsupervised deconvolution of mixed gene expressions in tumor samples', 'Wang, Niya|Gong, Ting|Clarke, Robert|Chen, Lulu|Shih, Ie-Ming|Zhang, Zhen|Levine, Douglas A|Xuan, Jianhua|Wang, Yue', 'Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, Department of Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX 78957, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231 and Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA.|Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, Department of Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX 78957, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231 and Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA.|Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, Department of Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX 78957, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231 and Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA.|Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, Department of Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX 78957, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231 and Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA.|Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, Department of Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX 78957, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231 and Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA.|Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, Department of Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX 78957, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231 and Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA.|Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, Department of Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX 78957, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231 and Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA.|Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, Department of Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX 78957, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231 and Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA.|Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, Department of Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX 78957, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231 and Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Breast Neoplasms|Computer Simulation|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, RNA|Software|Tumor Cells, Cultured', 'Journal Article', '10.1093/bioinformatics/btu607', '25212756', 'We develop a novel unsupervised deconvolution method, within a well-grounded mathematical framework, to dissect mixed gene expressions in heterogeneous tumor samples. We implement an R package, UNsupervised DecOnvolution (UNDO), that can be used to automatically detect cell-specific marker genes (MGs) located on the scatter radii of mixed gene expressions, estimate cellular proportions in each sample and deconvolute mixed expressions into cell-specific expression profiles. We demonstrate the performance of UNDO over a wide range of tumor-stroma mixing proportions, validate UNDO on various biologically mixed benchmark gene expression datasets and further estimate tumor purity in TCGA/CPTAC datasets. The highly accurate deconvolution results obtained suggest not only the existence of cell-specific MGs but also UNDOs ability to detect them blindly and correctly. Although the principal application here involves microarray gene expressions, our methodology can be readily applied to other types of quantitative molecular profiling data.'),
(78712, 2015, 'bio', 'EUROCarbDB(CCRC): a EUROCarbDB node for storing glycomics standard data', 'Al Jadda, Khalifeh|Porterfield, Melody P|Bridger, Robert|Heiss, Christian|Tiemeyer, Michael|Wells, Lance|Miller, John A|York, William S|Ranzinger, Rene', 'Department of Computer Science and Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA.|Department of Computer Science and Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA.|Department of Computer Science and Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA.|Department of Computer Science and Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA.|Department of Computer Science and Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA.|Department of Computer Science and Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA.|Department of Computer Science and Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA.|Department of Computer Science and Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA.|Department of Computer Science and Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA.', 'Georgia|Georgia|Georgia|Georgia|Georgia|Georgia|Georgia|Georgia|Georgia', 3, 'Carbohydrates|Computational Biology|Databases as Topic|Glycomics|Humans|Software', 'Journal Article', '10.1093/bioinformatics/btu609', '25217575', 'In the field of glycomics research, several different techniques are used for structure elucidation. Although multiple techniques are often used to increase confidence in structure assignments, most glycomics databases allow storing of only a single type of experimental data. In addition, the methods used to prepare a sample for analysis is seldom recorded making it harder to reproduce the analytical data and results.'),
(78713, 2015, 'bio', 'Improved rat genome gene prediction by integration of ESTs with RNA-Seq information', 'Li, Liping|Chen, Enguo|Yang, Chun|Zhu, Jun|Jayaraman, Pushkala|De Pons, Jeffrey|Kaczorowski, Catherine C|Jacob, Howard J|Greene, Andrew S|Hodges, Matthew R|Cowley, Allen W|Liang, Mingyu|Xu, Haiming|Liu, Pengyuan|Lu, Yan', 'Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.|Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.|Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.|Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.|Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.|Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.|Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.|Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.|Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.|Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.|Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.|Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.|Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.|Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.|Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA Department of Gynecologic Oncology, The Affiliated Womens Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.', 'China|China|China|China|China|China|China|China|China|China|China|China|China|China|China', 3, 'Animals|Expressed Sequence Tags|Genetic Variation|Genome|High-Throughput Nucleotide Sequencing|Mice|Molecular Sequence Annotation|RNA|Rats|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btu608', '25217576', 'RNA-Seq (also called whole-transcriptome sequencing) is an emerging technology that uses the capabilities of next-generation sequencing to detect and quantify entire transcripts. One of its important applications is the improvement of existing genome annotations. RNA-Seq provides rapid, comprehensive and cost-effective tools for the discovery of novel genes and transcripts compared with expressed sequence tag (EST), which is instrumental in gene discovery and gene sequence determination. The rat is widely used as a laboratory disease model, but has a less well-annotated genome as compared with humans and mice. In this study, we incorporated deep RNA-Seq data from three rat tissues-bone marrow, brain and kidney-with EST data to improve the annotation of the rat genome.'),
(78714, 2015, 'bio', 'JAMM: a peak finder for joint analysis of NGS replicates', 'Ibrahim, Mahmoud M|Lacadie, Scott A|Ohler, Uwe', 'Department of Biology, Humboldt University, Invalidenstrasse 43, D-10115 Berlin, Germany and The Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine Berlin-Buch, Robert Rössle Str. 10, Berlin 13125, Germany Department of Biology, Humboldt University, Invalidenstrasse 43, D-10115 Berlin, Germany and The Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine Berlin-Buch, Robert Rössle Str. 10, Berlin 13125, Germany.|Department of Biology, Humboldt University, Invalidenstrasse 43, D-10115 Berlin, Germany and The Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine Berlin-Buch, Robert Rössle Str. 10, Berlin 13125, Germany.|Department of Biology, Humboldt University, Invalidenstrasse 43, D-10115 Berlin, Germany and The Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine Berlin-Buch, Robert Rössle Str. 10, Berlin 13125, Germany Department of Biology, Humboldt University, Invalidenstrasse 43, D-10115 Berlin, Germany and The Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine Berlin-Buch, Robert Rössle Str. 10, Berlin 13125, Germany.', 'Germany|Germany|Germany', 0, 'Algorithms|Genetic Variation|High-Throughput Nucleotide Sequencing|Humans|Models, Statistical|Reproducibility of Results|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu568', '25223640', 'Although peak finding in next-generation sequencing (NGS) datasets has been addressed extensively, there is no consensus on how to analyze and process biological replicates. Furthermore, most peak finders do not focus on accurate determination of enrichment site widths and are not widely applicable to different types of datasets.'),
(78715, 2015, 'bio', 'PseKNC-General: a cross-platform package for generating various modes of pseudo nucleotide compositions', 'Chen, Wei|Zhang, Xitong|Brooker, Jordan|Lin, Hao|Zhang, Liqing|Chou, Kuo-Chen', 'Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063009, China, Department of Computer Science, Virginia Tech, Blacksburg, VA 24060, School of Life Science and Technology, Bioinformatics and Computer-Aided Drug Discovery, Gordon Life Science Institute, Boston, MA 02478, Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA 22904, Department of Computer Science, Vassar College, Poughkeepsie, NY 12604, USA, Excellence in Genomic Medicine Research, Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China and Excellence in Genomic Medicine Research, Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah 21589, Saudi Arabia Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063009, China, Department of Computer Science, Virginia Tech, Blacksburg, VA 24060, School of Life Science and Technology, Bioinformatics and Computer-Aided Drug Discovery, Gordon Life Science Institute, Boston, MA 02478, Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA 22904, Department of Computer Science, Vassar College, Poughkeepsie, NY 12604, USA, Excellence in Genomic Medicine Research, Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China and Excellence in Genomic Medicine Research, Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah 21589, Saudi Arabia Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063009, Chin|Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063009, China, Department of Computer Science, Virginia Tech, Blacksburg, VA 24060, School of Life Science and Technology, Bioinformatics and Computer-Aided Drug Discovery, Gordon Life Science Institute, Boston, MA 02478, Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA 22904, Department of Computer Science, Vassar College, Poughkeepsie, NY 12604, USA, Excellence in Genomic Medicine Research, Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China and Excellence in Genomic Medicine Research, Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah 21589, Saudi Arabia.|Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063009, China, Department of Computer Science, Virginia Tech, Blacksburg, VA 24060, School of Life Science and Technology, Bioinformatics and Computer-Aided Drug Discovery, Gordon Life Science Institute, Boston, MA 02478, Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA 22904, Department of Computer Science, Vassar College, Poughkeepsie, NY 12604, USA, Excellence in Genomic Medicine Research, Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China and Excellence in Genomic Medicine Research, Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah 21589, Saudi Arabia.|Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063009, China, Department of Computer Science, Virginia Tech, Blacksburg, VA 24060, School of Life Science and Technology, Bioinformatics and Computer-Aided Drug Discovery, Gordon Life Science Institute, Boston, MA 02478, Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA 22904, Department of Computer Science, Vassar College, Poughkeepsie, NY 12604, USA, Excellence in Genomic Medicine Research, Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China and Excellence in Genomic Medicine Research, Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah 21589, Saudi Arabia Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063009, China, Department of Computer Science, Virginia Tech, Blacksburg, VA 24060, School of Life Science and Technology, Bioinformatics and Computer-Aided Drug Discovery, Gordon Life Science Institute, Boston, MA 02478, Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA 22904, Department of Computer Science, Vassar College, Poughkeepsie, NY 12604, USA, Excellence in Genomic Medicine Research, Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China and Excellence in Genomic Medicine Research, Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah 21589, Saudi Arabia.|Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063009, China, Department of Computer Science, Virginia Tech, Blacksburg, VA 24060, School of Life Science and Technology, Bioinformatics and Computer-Aided Drug Discovery, Gordon Life Science Institute, Boston, MA 02478, Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA 22904, Department of Computer Science, Vassar College, Poughkeepsie, NY 12604, USA, Excellence in Genomic Medicine Research, Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China and Excellence in Genomic Medicine Research, Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah 21589, Saudi Arabia.|Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063009, China, Department of Computer Science, Virginia Tech, Blacksburg, VA 24060, School of Life Science and Technology, Bioinformatics and Computer-Aided Drug Discovery, Gordon Life Science Institute, Boston, MA 02478, Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA 22904, Department of Computer Science, Vassar College, Poughkeepsie, NY 12604, USA, Excellence in Genomic Medicine Research, Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China and Excellence in Genomic Medicine Research, Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah 21589, Saudi Arabia Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063009, China, Department of Computer Science, Virginia Tech, Blacksburg, VA 24060, School of Life Science and Technology, Bioinformatics and Computer-Aided Drug Discovery, Gordon Life Science Institute, Boston, MA 02478, Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA 22904, Department of Computer Science, Vassar College, Poughkeepsie, NY 12604, USA, Excellence in Genomic Medicine Research, Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China and Excellence in Genomic Medicine Research, Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah 21589, Saudi Arabia Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063009, Chin', 'China|China|China|China|China|China', 160, 'Base Composition|Computational Biology|Humans|Oligonucleotides|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu602', '25231908', 'The avalanche of genomic sequences generated in the post-genomic age requires efficient computational methods for rapidly and accurately identifying biological features from sequence information. Towards this goal, we developed a freely available and open-source package, called PseKNC-General (the general form of pseudo k-tuple nucleotide composition), that allows for fast and accurate computation of all the widely used nucleotide structural and physicochemical properties of both DNA and RNA sequences. PseKNC-General can generate several modes of pseudo nucleotide compositions, including conventional k-tuple nucleotide compositions, Moreau-Broto autocorrelation coefficient, Moran autocorrelation coefficient, Geary autocorrelation coefficient, Type I PseKNC and Type II PseKNC. In every mode, >100 physicochemical properties are available for choosing. Moreover, it is flexible enough to allow the users to calculate PseKNC with user-defined properties. The package can be run on Linux, Mac and Windows systems and also provides a graphical user interface.'),
(78716, 2015, 'bio', 'Using population data for assessing next-generation sequencing performance', 'Houniet, Darren T|Rahman, Thahira J|Al Turki, Saeed|Hurles, Matthew E|Xu, Yaobo|Goodship, Judith|Keavney, Bernard|Santibanez Koref, Mauro', 'Oxford Gene Technology, Begbroke Science Park, Oxford, Oxfordshire, OX5 1PF, Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway NE1 3BZ, Newcastle upon Tyne and The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.|Oxford Gene Technology, Begbroke Science Park, Oxford, Oxfordshire, OX5 1PF, Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway NE1 3BZ, Newcastle upon Tyne and The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.|Oxford Gene Technology, Begbroke Science Park, Oxford, Oxfordshire, OX5 1PF, Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway NE1 3BZ, Newcastle upon Tyne and The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.|Oxford Gene Technology, Begbroke Science Park, Oxford, Oxfordshire, OX5 1PF, Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway NE1 3BZ, Newcastle upon Tyne and The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.|Oxford Gene Technology, Begbroke Science Park, Oxford, Oxfordshire, OX5 1PF, Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway NE1 3BZ, Newcastle upon Tyne and The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.|Oxford Gene Technology, Begbroke Science Park, Oxford, Oxfordshire, OX5 1PF, Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway NE1 3BZ, Newcastle upon Tyne and The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.|Oxford Gene Technology, Begbroke Science Park, Oxford, Oxfordshire, OX5 1PF, Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway NE1 3BZ, Newcastle upon Tyne and The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.|Oxford Gene Technology, Begbroke Science Park, Oxford, Oxfordshire, OX5 1PF, Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway NE1 3BZ, Newcastle upon Tyne and The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Computational Biology|Exome|Genetic Variation|Genetics, Population|Genome, Human|Genome-Wide Association Study|High-Throughput Nucleotide Sequencing|Humans|Sample Size', 'Journal Article', '10.1093/bioinformatics/btu606', '25236458', 'During the past 4 years, whole-exome sequencing has become a standard tool for finding rare variants causing Mendelian disorders. In that time, there has also been a proliferation of both sequencing platforms and approaches to analyse their output. This requires approaches to assess the performance of different methods. Traditionally, criteria such as comparison with microarray data or a number of known polymorphic sites have been used. Here we expand such approaches, developing a maximum likelihood framework and using it to estimate the sensitivity and specificity of whole-exome sequencing data.'),
(78717, 2015, 'bio', 'Understanding the limits of animal models as predictors of human biology: lessons learned from the sbv IMPROVER Species Translation Challenge', 'Rhrissorrakrai, Kahn|Belcastro, Vincenzo|Bilal, Erhan|Norel, Raquel|Poussin, Carine|Mathis, Carole|Dulize, Rémi H J|Ivanov, Nikolai V|Alexopoulos, Leonidas|Rice, J Jeremy|Peitsch, Manuel C|Stolovitzky, Gustavo|Meyer, Pablo|Hoeng, Julia', 'IBM T.J. Watson Research Center, Computational Biology Center, Yorktown Heights, NY 10003, USA, Philip Morris International R&D, Philip Morris Products S.A., 2000 Neuchâtel, Switzerland, Telethon Institute of Genetics and Medicine, Via Pietro Castellino, 111, 80131 Naples, Italy, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki and National Technical University of Athens, Heroon Polytechniou 9, Zografou 15780, Greece.|IBM T.J. Watson Research Center, Computational Biology Center, Yorktown Heights, NY 10003, USA, Philip Morris International R&D, Philip Morris Products S.A., 2000 Neuchâtel, Switzerland, Telethon Institute of Genetics and Medicine, Via Pietro Castellino, 111, 80131 Naples, Italy, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki and National Technical University of Athens, Heroon Polytechniou 9, Zografou 15780, Greece IBM T.J. Watson Research Center, Computational Biology Center, Yorktown Heights, NY 10003, USA, Philip Morris International R&D, Philip Morris Products S.A., 2000 Neuchâtel, Switzerland, Telethon Institute of Genetics and Medicine, Via Pietro Castellino, 111, 80131 Naples, Italy, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki and National Technical University of Athens, Heroon Polytechniou 9, Zografou 15780, Greece.|IBM T.J. Watson Research Center, Computational Biology Center, Yorktown Heights, NY 10003, USA, Philip Morris International R&D, Philip Morris Products S.A., 2000 Neuchâtel, Switzerland, Telethon Institute of Genetics and Medicine, Via Pietro Castellino, 111, 80131 Naples, Italy, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki and National Technical University of Athens, Heroon Polytechniou 9, Zografou 15780, Greece.|IBM T.J. Watson Research Center, Computational Biology Center, Yorktown Heights, NY 10003, USA, Philip Morris International R&D, Philip Morris Products S.A., 2000 Neuchâtel, Switzerland, Telethon Institute of Genetics and Medicine, Via Pietro Castellino, 111, 80131 Naples, Italy, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki and National Technical University of Athens, Heroon Polytechniou 9, Zografou 15780, Greece.|IBM T.J. Watson Research Center, Computational Biology Center, Yorktown Heights, NY 10003, USA, Philip Morris International R&D, Philip Morris Products S.A., 2000 Neuchâtel, Switzerland, Telethon Institute of Genetics and Medicine, Via Pietro Castellino, 111, 80131 Naples, Italy, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki and National Technical University of Athens, Heroon Polytechniou 9, Zografou 15780, Greece.|IBM T.J. Watson Research Center, Computational Biology Center, Yorktown Heights, NY 10003, USA, Philip Morris International R&D, Philip Morris Products S.A., 2000 Neuchâtel, Switzerland, Telethon Institute of Genetics and Medicine, Via Pietro Castellino, 111, 80131 Naples, Italy, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki and National Technical University of Athens, Heroon Polytechniou 9, Zografou 15780, Greece.|IBM T.J. Watson Research Center, Computational Biology Center, Yorktown Heights, NY 10003, USA, Philip Morris International R&D, Philip Morris Products S.A., 2000 Neuchâtel, Switzerland, Telethon Institute of Genetics and Medicine, Via Pietro Castellino, 111, 80131 Naples, Italy, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki and National Technical University of Athens, Heroon Polytechniou 9, Zografou 15780, Greece.|IBM T.J. Watson Research Center, Computational Biology Center, Yorktown Heights, NY 10003, USA, Philip Morris International R&D, Philip Morris Products S.A., 2000 Neuchâtel, Switzerland, Telethon Institute of Genetics and Medicine, Via Pietro Castellino, 111, 80131 Naples, Italy, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki and National Technical University of Athens, Heroon Polytechniou 9, Zografou 15780, Greece.|IBM T.J. Watson Research Center, Computational Biology Center, Yorktown Heights, NY 10003, USA, Philip Morris International R&D, Philip Morris Products S.A., 2000 Neuchâtel, Switzerland, Telethon Institute of Genetics and Medicine, Via Pietro Castellino, 111, 80131 Naples, Italy, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki and National Technical University of Athens, Heroon Polytechniou 9, Zografou 15780, Greece IBM T.J. Watson Research Center, Computational Biology Center, Yorktown Heights, NY 10003, USA, Philip Morris International R&D, Philip Morris Products S.A., 2000 Neuchâtel, Switzerland, Telethon Institute of Genetics and Medicine, Via Pietro Castellino, 111, 80131 Naples, Italy, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki and National Technical University of Athens, Heroon Polytechniou 9, Zografou 15780, Greece.|IBM T.J. Watson Research Center, Computational Biology Center, Yorktown Heights, NY 10003, USA, Philip Morris International R&D, Philip Morris Products S.A., 2000 Neuchâtel, Switzerland, Telethon Institute of Genetics and Medicine, Via Pietro Castellino, 111, 80131 Naples, Italy, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki and National Technical University of Athens, Heroon Polytechniou 9, Zografou 15780, Greece.|IBM T.J. Watson Research Center, Computational Biology Center, Yorktown Heights, NY 10003, USA, Philip Morris International R&D, Philip Morris Products S.A., 2000 Neuchâtel, Switzerland, Telethon Institute of Genetics and Medicine, Via Pietro Castellino, 111, 80131 Naples, Italy, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki and National Technical University of Athens, Heroon Polytechniou 9, Zografou 15780, Greece.|IBM T.J. Watson Research Center, Computational Biology Center, Yorktown Heights, NY 10003, USA, Philip Morris International R&D, Philip Morris Products S.A., 2000 Neuchâtel, Switzerland, Telethon Institute of Genetics and Medicine, Via Pietro Castellino, 111, 80131 Naples, Italy, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki and National Technical University of Athens, Heroon Polytechniou 9, Zografou 15780, Greece.|IBM T.J. Watson Research Center, Computational Biology Center, Yorktown Heights, NY 10003, USA, Philip Morris International R&D, Philip Morris Products S.A., 2000 Neuchâtel, Switzerland, Telethon Institute of Genetics and Medicine, Via Pietro Castellino, 111, 80131 Naples, Italy, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki and National Technical University of Athens, Heroon Polytechniou 9, Zografou 15780, Greece.|IBM T.J. Watson Research Center, Computational Biology Center, Yorktown Heights, NY 10003, USA, Philip Morris International R&D, Philip Morris Products S.A., 2000 Neuchâtel, Switzerland, Telethon Institute of Genetics and Medicine, Via Pietro Castellino, 111, 80131 Naples, Italy, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki and National Technical University of Athens, Heroon Polytechniou 9, Zografou 15780, Greece.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Swit', 0, 'Algorithms|Animals|Bronchi|Cells, Cultured|Cytokines|Databases, Factual|Epithelial Cells|Gene Expression Profiling|Gene Expression Regulation|Gene Regulatory Networks|Humans|Models, Animal|Oligonucleotide Array Sequence Analysis|Phosphoproteins|Phosphorylation|Rats|Software|Species Specificity|Systems Biology|Translational Medical Research', 'Comparative Study', '10.1093/bioinformatics/btu611', '25236459', 'Inferring how humans respond to external cues such as drugs, chemicals, viruses or hormones is an essential question in biomedicine. Very often, however, this question cannot be addressed because it is not possible to perform experiments in humans. A reasonable alternative consists of generating responses in animal models and translating those results to humans. The limitations of such translation, however, are far from clear, and systematic assessments of its actual potential are urgently needed. sbv IMPROVER (systems biology verification for Industrial Methodology for PROcess VErification in Research) was designed as a series of challenges to address translatability between humans and rodents. This collaborative crowd-sourcing initiative invited scientists from around the world to apply their own computational methodologies on a multilayer systems biology dataset composed of phosphoproteomics, transcriptomics and cytokine data derived from normal human and rat bronchial epithelial cells exposed in parallel to 52 different stimuli under identical conditions. Our aim was to understand the limits of species-to-species translatability at different levels of biological organization: signaling, transcriptional and release of secreted factors (such as cytokines). Participating teams submitted 49 different solutions across the sub-challenges, two-thirds of which were statistically significantly better than random. Additionally, similar computational methods were found to range widely in their performance within the same challenge, and no single method emerged as a clear winner across all sub-challenges. Finally, computational methods were able to effectively translate some specific stimuli and biological processes in the lung epithelial system, such as DNA synthesis, cytoskeleton and extracellular matrix, translation, immune/inflammation and growth factor/proliferation pathways, better than the expected response similarity between species.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78718, 2015, 'bio', 'Making novel proteins from pseudogenes', 'Shidhi, P R|Suravajhala, Prashanth|Nayeema, Aysha|Nair, Achuthsankar S|Singh, Shailja|Dhar, Pawan K', 'Department of Computational Biology and Bioinformatics, University of Kerala, Kariyavattom, Trivandrum- 695 581, India, Bioinformatics.Org, 28 Pope Street, Hudson, MA 01749, USA, Bioclues.org, India, Bioclues.org, Denmark, National College, University of Kerala, Trivandrum- 695 009, Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Dadri, Uttar Pradesh- 201 314, and Centre for Systems and Synthetic Biology, University of Kerala, Kariyavattom, Trivandrum- 695 581, India.|Department of Computational Biology and Bioinformatics, University of Kerala, Kariyavattom, Trivandrum- 695 581, India, Bioinformatics.Org, 28 Pope Street, Hudson, MA 01749, USA, Bioclues.org, India, Bioclues.org, Denmark, National College, University of Kerala, Trivandrum- 695 009, Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Dadri, Uttar Pradesh- 201 314, and Centre for Systems and Synthetic Biology, University of Kerala, Kariyavattom, Trivandrum- 695 581, India Department of Computational Biology and Bioinformatics, University of Kerala, Kariyavattom, Trivandrum- 695 581, India, Bioinformatics.Org, 28 Pope Street, Hudson, MA 01749, USA, Bioclues.org, India, Bioclues.org, Denmark, National College, University of Kerala, Trivandrum- 695 009, Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Dadri, Uttar Pradesh- 201 314, and Centre for Systems and Synthetic Biology, University of Kerala, Kariyavattom, Trivandrum- 695 581, India Department of Computational Biology and Bioinformatics, University of Kerala, Kariyavattom, Trivandrum- 695 581, India, Bioinformatics.Org, 28 Pope Street, Hudson, MA 01749, USA, Bioclues.org, India, Bioclues.org, Denmark, National College, University of Kerala, Trivandrum- 695 009, Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Dadri, Uttar Pradesh- 201 314, and Centre for Systems and Synthetic Biology, University of Kerala, Kariyavattom, Trivandrum- 695 581, India.|Department of Computational Biology and Bioinformatics, University of Kerala, Kariyavattom, Trivandrum- 695 581, India, Bioinformatics.Org, 28 Pope Street, Hudson, MA 01749, USA, Bioclues.org, India, Bioclues.org, Denmark, National College, University of Kerala, Trivandrum- 695 009, Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Dadri, Uttar Pradesh- 201 314, and Centre for Systems and Synthetic Biology, University of Kerala, Kariyavattom, Trivandrum- 695 581, India.|Department of Computational Biology and Bioinformatics, University of Kerala, Kariyavattom, Trivandrum- 695 581, India, Bioinformatics.Org, 28 Pope Street, Hudson, MA 01749, USA, Bioclues.org, India, Bioclues.org, Denmark, National College, University of Kerala, Trivandrum- 695 009, Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Dadri, Uttar Pradesh- 201 314, and Centre for Systems and Synthetic Biology, University of Kerala, Kariyavattom, Trivandrum- 695 581, India.|Department of Computational Biology and Bioinformatics, University of Kerala, Kariyavattom, Trivandrum- 695 581, India, Bioinformatics.Org, 28 Pope Street, Hudson, MA 01749, USA, Bioclues.org, India, Bioclues.org, Denmark, National College, University of Kerala, Trivandrum- 695 009, Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Dadri, Uttar Pradesh- 201 314, and Centre for Systems and Synthetic Biology, University of Kerala, Kariyavattom, Trivandrum- 695 581, India.|Department of Computational Biology and Bioinformatics, University of Kerala, Kariyavattom, Trivandrum- 695 581, India, Bioinformatics.Org, 28 Pope Street, Hudson, MA 01749, USA, Bioclues.org, India, Bioclues.org, Denmark, National College, University of Kerala, Trivandrum- 695 009, Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Dadri, Uttar Pradesh- 201 314, and Centre for Systems and Synthetic Biology, University of Kerala, Kariyavattom, Trivandrum- 695 581, India Department of Computational Biology and Bioinformatics, University of Kerala, Kariyavattom, Trivandrum- 695 581, India, Bioinformatics.Org, 28 Pope Street, Hudson, MA 01749, USA, Bioclues.org, India, Bioclues.org, Denmark, National College, University of Kerala, Trivandrum- 695 009, Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Dadri, Uttar Pradesh- 201 314, and Centre for Systems and Synthetic Biology, University of Kerala, Kariyavattom, Trivandrum- 695 581, India.', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 7, 'Gene Expression Regulation, Fungal|Genome, Fungal|Protein Conformation|Pseudogenes|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btu615', '25236460', 'Recently, we made synthetic proteins from non-coding DNA of Escherichia coli. Encouraged by this, we asked: can we artificially express pseudogenes into novel and functional proteins? What kind of structures would be generated? Would these proteins be stable? How would the organism respond to the artificial reactivation of pseudogenes?'),
(78719, 2015, 'bio', 'The Ensembl REST API: Ensembl Data for Any Language', 'Yates, Andrew|Beal, Kathryn|Keenan, Stephen|McLaren, William|Pignatelli, Miguel|Ritchie, Graham R S|Ruffier, Magali|Taylor, Kieron|Vullo, Alessandro|Flicek, Paul', 'European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD and Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD and Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD and Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD and Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD and Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD and Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD and Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD and Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD and Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD and Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD and Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD and Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 70, 'Computational Biology|Databases, Factual|Genetic Variation|Genomics|Humans|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/btu613', '25236461', 'We present a Web service to access Ensembl data using Representational State Transfer (REST). The Ensembl REST server enables the easy retrieval of a wide range of Ensembl data by most programming languages, using standard formats such as JSON and FASTA while minimizing client work. We also introduce bindings to the popular Ensembl Variant Effect Predictor tool permitting large-scale programmatic variant analysis independent of any specific programming language.'),
(78720, 2015, 'bio', 'Proteomic analysis and prediction of human phosphorylation sites in subcellular level reveal subcellular specificity', 'Chen, Xiang|Shi, Shao-Ping|Suo, Sheng-Bao|Xu, Hao-Dong|Qiu, Jian-Ding', 'Department of Chemistry, Nanchang University, Nanchang 330031, Department of Mathematics, Nanchang University, Nanchang 330031 and Department of Materials and Chemical Engineering, Pingxiang College, Pingxiang 337055, P.R. China.|Department of Chemistry, Nanchang University, Nanchang 330031, Department of Mathematics, Nanchang University, Nanchang 330031 and Department of Materials and Chemical Engineering, Pingxiang College, Pingxiang 337055, P.R. China Department of Chemistry, Nanchang University, Nanchang 330031, Department of Mathematics, Nanchang University, Nanchang 330031 and Department of Materials and Chemical Engineering, Pingxiang College, Pingxiang 337055, P.R. China.|Department of Chemistry, Nanchang University, Nanchang 330031, Department of Mathematics, Nanchang University, Nanchang 330031 and Department of Materials and Chemical Engineering, Pingxiang College, Pingxiang 337055, P.R. China.|Department of Chemistry, Nanchang University, Nanchang 330031, Department of Mathematics, Nanchang University, Nanchang 330031 and Department of Materials and Chemical Engineering, Pingxiang College, Pingxiang 337055, P.R. China.|Department of Chemistry, Nanchang University, Nanchang 330031, Department of Mathematics, Nanchang University, Nanchang 330031 and Department of Materials and Chemical Engineering, Pingxiang College, Pingxiang 337055, P.R. China Department of Chemistry, Nanchang University, Nanchang 330031, Department of Mathematics, Nanchang University, Nanchang 330031 and Department of Materials and Chemical Engineering, Pingxiang College, Pingxiang 337055, P.R. China.', 'China|China|China|China|China', 0, 'Algorithms|Humans|Mass Spectrometry|Phosphopeptides|Phosphorylation|Protein Processing, Post-Translational|Proteome|Proteomics|Software|Subcellular Fractions|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btu598', '25236462', 'Protein phosphorylation is the most common post-translational modification (PTM) regulating major cellular processes through highly dynamic and complex signaling pathways. Large-scale comparative phosphoproteomic studies have frequently been done on whole cells or organs by conventional bottom-up mass spectrometry approaches, i.e at the phosphopeptide level. Using this approach, there is no way to know from where the phosphopeptide signal originated. Also, as a consequence of the scale of these studies, important information on the localization of phosphorylation sites in subcellular compartments (SCs) is not surveyed.'),
(78721, 2015, 'bio', 'Translating bioinformatics in oncology: guilt-by-profiling analysis and identification of KIF18B and CDCA3 as novel driver genes in carcinogenesis', 'Itzel, Timo|Scholz, Peter|Maass, Thorsten|Krupp, Markus|Marquardt, Jens U|Strand, Susanne|Becker, Diana|Staib, Frank|Binder, Harald|Roessler, Stephanie|Wang, Xin Wei|Thorgeirsson, Snorri|Mxc3xbcller, Martina|Galle, Peter R|Teufel, Andreas', 'Department of Medicine I, University of Regensburg, 93053, Regensburg, Department of Medicine I, Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55131, Mainz, Department of Pathology, University of Heidelberg, 69120, Germany and Laboratory of Experimental Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, 20892 MD, USA.|Department of Medicine I, University of Regensburg, 93053, Regensburg, Department of Medicine I, Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55131, Mainz, Department of Pathology, University of Heidelberg, 69120, Germany and Laboratory of Experimental Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, 20892 MD, USA.|Department of Medicine I, University of Regensburg, 93053, Regensburg, Department of Medicine I, Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55131, Mainz, Department of Pathology, University of Heidelberg, 69120, Germany and Laboratory of Experimental Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, 20892 MD, USA.|Department of Medicine I, University of Regensburg, 93053, Regensburg, Department of Medicine I, Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55131, Mainz, Department of Pathology, University of Heidelberg, 69120, Germany and Laboratory of Experimental Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, 20892 MD, USA.|Department of Medicine I, University of Regensburg, 93053, Regensburg, Department of Medicine I, Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55131, Mainz, Department of Pathology, University of Heidelberg, 69120, Germany and Laboratory of Experimental Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, 20892 MD, USA.|Department of Medicine I, University of Regensburg, 93053, Regensburg, Department of Medicine I, Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55131, Mainz, Department of Pathology, University of Heidelberg, 69120, Germany and Laboratory of Experimental Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, 20892 MD, USA.|Department of Medicine I, University of Regensburg, 93053, Regensburg, Department of Medicine I, Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55131, Mainz, Department of Pathology, University of Heidelberg, 69120, Germany and Laboratory of Experimental Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, 20892 MD, USA.|Department of Medicine I, University of Regensburg, 93053, Regensburg, Department of Medicine I, Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55131, Mainz, Department of Pathology, University of Heidelberg, 69120, Germany and Laboratory of Experimental Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, 20892 MD, USA.|Department of Medicine I, University of Regensburg, 93053, Regensburg, Department of Medicine I, Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55131, Mainz, Department of Pathology, University of Heidelberg, 69120, Germany and Laboratory of Experimental Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, 20892 MD, USA.|Department of Medicine I, University of Regensburg, 93053, Regensburg, Department of Medicine I, Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55131, Mainz, Department of Pathology, University of Heidelberg, 69120, Germany and Laboratory of Experimental Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, 20892 MD, USA.|Department of Medicine I, University of Regensburg, 93053, Regensburg, Department of Medicine I, Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55131, Mainz, Department of Pathology, University of Heidelberg, 69120, Germany and Laboratory of Experimental Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, 20892 MD, USA.|Department of Medicine I, University of Regensburg, 93053, Regensburg, Department of Medicine I, Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55131, Mainz, Department of Pathology, University of Heidelberg, 69120, Germany and Laboratory of Experimental Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, 20892 MD, USA.|Department of Medicine I, University of Regensburg, 93053, Regensburg, Department of Medicine I, Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55131, Mainz, Department of Pathology, University of Heidelberg, 69120, Germany and Laboratory of Experimental Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, 20892 MD, USA.|Department of Medicine I, University of Regensburg, 93053, Regensburg, Department of Medicine I, Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55131, Mainz, Department of Pathology, University of Heidelberg, 69120, Germany and Laboratory of Experimental Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, 20892 MD, USA.|Department of Medicine I, University of Regensburg, 93053, Regensburg, Department of Medicine I, Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55131, Mainz, Department of Pathology, University of Heidelberg, 69120, Germany and Laboratory of Experimental Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, 20892 MD, USA.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germ', 34, 'Biomarkers, Tumor|Blotting, Western|Carcinogenesis|Carcinoma, Hepatocellular|Cell Cycle|Cell Cycle Proteins|Cell Proliferation|Computational Biology|Disease Progression|Flow Cytometry|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Kinesin|Liver Neoplasms|Neoplasms|Oligonucleotide Array Sequence Analysis|Prognosis|Survival Rate|Tumor Cells, Cultured|Tumor Stem Cell Assay', 'Journal Article', '10.1093/bioinformatics/btu586', '25236463', 'Co-regulated genes are not identified in traditional microarray analyses, but may theoretically be closely functionally linked [guilt-by-association (GBA), guilt-by-profiling]. Thus, bioinformatics procedures for guilt-by-profiling/association analysis have yet to be applied to large-scale cancer biology. We analyzed 2158 full cancer transcriptomes from 163 diverse cancer entities in regard of their similarity of gene expression, using Pearsons correlation coefficient (CC). Subsequently, 428 highly co-regulated genes (|CC| xe2x89xa5 0.8) were clustered unsupervised to obtain small co-regulated networks. A major subnetwork containing 61 closely co-regulated genes showed highly significant enrichment of cancer bio-functions. All genes except kinesin family member 18B (KIF18B) and cell division cycle associated 3 (CDCA3) were of confirmed relevance for tumor biology. Therefore, we independently analyzed their differential regulation in multiple tumors and found severe deregulation in liver, breast, lung, ovarian and kidney cancers, thus proving our GBA hypothesis. Overexpression of KIF18B and CDCA3 in hepatoma cells and subsequent microarray analysis revealed significant deregulation of central cell cycle regulatory genes. Consistently, RT-PCR and proliferation assay confirmed the role of both genes in cell cycle progression. Finally, the prognostic significance of the identified KIF18B- and CDCA3-dependent predictors (P = 0.01, P = 0.04) was demonstrated in three independent HCC cohorts and several other tumors. In summary, we proved the efficacy of large-scale guilt-by-profiling/association strategies in oncology. We identified two novel oncogenes and functionally characterized them. The strong prognostic importance of downstream predictors for HCC and many other tumors indicates the clinical relevance of our findings.'),
(78722, 2015, 'bio', 'RAMONA: a Web application for gene set analysis on multilevel omics data', 'Sass, Steffen|Buettner, Florian|Mueller, Nikola S|Theis, Fabian J', 'Institute of Computational Biology, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany and Department of Mathematics, Technische Universität München, Boltzmannstraße 3, 85747 Garching, Germany.|Institute of Computational Biology, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany and Department of Mathematics, Technische Universität München, Boltzmannstraße 3, 85747 Garching, Germany.|Institute of Computational Biology, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany and Department of Mathematics, Technische Universität München, Boltzmannstraße 3, 85747 Garching, Germany.|Institute of Computational Biology, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany and Department of Mathematics, Technische Universität München, Boltzmannstraße 3, 85747 Garching, Germany Institute of Computational Biology, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany and Department of Mathematics, Technische Universität München, Boltzmannstraße 3, 85747 Garching, Germany.', 'Germany|Germany|Germany|Germany', 6, 'Bayes Theorem|DNA Methylation|Gene Expression Profiling|Genes|Humans|MicroRNAs|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btu610', '25236464', 'Decreasing costs of modern high-throughput experiments allow for the simultaneous analysis of altered gene activity on various molecular levels. However, these multi-omics approaches lead to a large amount of data, which is hard to interpret for a non-bioinformatician. Here, we present the remotely accessible multilevel ontology analysis (RAMONA). It offers an easy-to-use interface for the simultaneous gene set analysis of combined omics datasets and is an extension of the previously introduced MONA approach. RAMONA is based on a Bayesian enrichment method for the inference of overrepresented biological processes among given gene sets. Overrepresentation is quantified by interpretable term probabilities. It is able to handle data from various molecular levels, while in parallel coping with redundancies arising from gene set overlaps and related multiple testing problems. The comprehensive output of RAMONA is easy to interpret and thus allows for functional insight into the affected biological processes. With RAMONA, we provide an efficient implementation of the Bayesian inference problem such that ontologies consisting of thousands of terms can be processed in the order of seconds.'),
(78723, 2015, 'bio', 'Rcpi: R/Bioconductor package to generate various descriptors of proteins, compounds and their interactions', 'Cao, Dong-Sheng|Xiao, Nan|Xu, Qing-Song|Chen, Alex F', 'School of Pharmaceutical Sciences and School of Mathematics and Statistics, Central South University, Changsha 410083, P. R. China.|School of Pharmaceutical Sciences and School of Mathematics and Statistics, Central South University, Changsha 410083, P. R. China.|School of Pharmaceutical Sciences and School of Mathematics and Statistics, Central South University, Changsha 410083, P. R. China.|School of Pharmaceutical Sciences and School of Mathematics and Statistics, Central South University, Changsha 410083, P. R. China.', 'China|China|China|China', 46, 'Computational Biology|Databases, Pharmaceutical|Drug Discovery|Drugs, Investigational|Humans|Protein Binding|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btu624', '25246429', 'In chemoinformatics and bioinformatics fields, one of the main computational challenges in various predictive modeling is to find a suitable way to effectively represent the molecules under investigation, such as small molecules, proteins and even complex interactions. To solve this problem, we developed a freely available R/Bioconductor package, called Compound-Protein Interaction with R (Rcpi), for complex molecular representation from drugs, proteins and more complex interactions, including protein-protein and compound-protein interactions. Rcpi could calculate a large number of structural and physicochemical features of proteins and peptides from amino acid sequences, molecular descriptors of small molecules from their topology and protein-protein interaction and compound-protein interaction descriptors. In addition to main functionalities, Rcpi could also provide a number of useful auxiliary utilities to facilitate the users need. With the descriptors calculated by this package, the users could conveniently apply various statistical machine learning methods in R to solve various biological and drug research questions in computational biology and drug discovery.'),
(78724, 2015, 'bio', 'PhaseTank: genome-wide computational identification of phasiRNAs and their regulatory cascades', 'Guo, Qingli|Qu, Xiongfei|Jin, Weibo', 'College of Life Sciences, Zhejiang Sci-Tech University, Hangzhou, Zhejiang, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China College of Life Sciences, Zhejiang Sci-Tech University, Hangzhou, Zhejiang, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.|College of Life Sciences, Zhejiang Sci-Tech University, Hangzhou, Zhejiang, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.|College of Life Sciences, Zhejiang Sci-Tech University, Hangzhou, Zhejiang, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China College of Life Sciences, Zhejiang Sci-Tech University, Hangzhou, Zhejiang, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.', 'China|China|China', 20, 'Computational Biology|Gene Expression Regulation, Plant|Gene Regulatory Networks|Genes, Plant|Genetic Variation|Genome, Plant|Plants|RNA, Small Interfering|Software', 'Journal Article', '10.1093/bioinformatics/btu628', '25246430', 'Emerging evidence has revealed phased siRNAs (phasiRNAs) as important endogenous regulators in plants. However, the integrated prediction tools for phasiRNAs are still limited. In this article, we introduce a stand-alone package PhaseTank for systematically characterizing phasiRNAs and their regulatory networks. (i) It can identify phasiRNAs/tasiRNAs functional cascades (miRNA/phasiRNA xe2x86x92 PHAS loci xe2x86x92 phasiRNA xe2x86x92 target) with high sensitivity and specificity. (ii) By one command analysis, it generates comprehensive annotation and quantification of the predicted PHAS genes from any given sequences. (iii) PhaseTank has no restriction with regards to prior information of sequence homology of unrestricted organism origins.'),
(78725, 2015, 'bio', 'NAIL, a software toolset for inferring, analyzing and visualizing regulatory networks', 'Hurley, Daniel G|Cursons, Joseph|Wang, Yi Kan|Budden, David M|Print, Cristin G|Crampin, Edmund J', 'Auckland Bioengineering Institute, University of Auckland, Auckland 1001, New Zealand, Department of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences,University of Auckland, Auckland 1001, New Zealand, Bioinformatics Institute, University of Auckland, Auckland 1001, New Zealand, Maurice Wilkins Centre, University of Auckland, Auckland 1001, New Zealand, Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Australia, Department of Mathematics and Statistics, University of Melbourne School of Medicine, University of Melbourne, Victoria 3010, Australia and Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, Canada Auckland Bioengineering Institute, University of Auckland, Auckland 1001, New Zealand, Department of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences,University of Auckland, Auckland 1001, New Zealand, Bioinformatics Institute, University of Auckland, Auckland 1001, New Zealand, Maurice Wilkins Centre, University of Auckland, Auckland 1001, New Zealand, Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Australia, Department of Mathematics and Statistics, University of Melbourne School of Medicine, University of Melbourne, Victoria 3010, Australia and Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, Canada Auckland Bioengineering Institute, University of Auckland, Auckland 1001, New Zealand, Department of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences,University of Auckland, Auckland 1001, New Zealand, Bioinformatics Institute, University of Auckland, Auckland 1001, New Zealand, Maurice Wilkins Centre, University of Auckland, Auckland 1001, New Zealand, Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Aus|Auckland Bioengineering Institute, University of Auckland, Auckland 1001, New Zealand, Department of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences,University of Auckland, Auckland 1001, New Zealand, Bioinformatics Institute, University of Auckland, Auckland 1001, New Zealand, Maurice Wilkins Centre, University of Auckland, Auckland 1001, New Zealand, Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Australia, Department of Mathematics and Statistics, University of Melbourne School of Medicine, University of Melbourne, Victoria 3010, Australia and Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, Canada Auckland Bioengineering Institute, University of Auckland, Auckland 1001, New Zealand, Department of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences,University of Auckland, Auckland 1001, New Zealand, Bioinformatics Institute, University of Auckland, Auckland 1001, New Zealand, Maurice Wilkins Centre, University of Auckland, Auckland 1001, New Zealand, Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Australia, Department of Mathematics and Statistics, University of Melbourne School of Medicine, University of Melbourne, Victoria 3010, Australia and Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, Canada.|Auckland Bioengineering Institute, University of Auckland, Auckland 1001, New Zealand, Department of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences,University of Auckland, Auckland 1001, New Zealand, Bioinformatics Institute, University of Auckland, Auckland 1001, New Zealand, Maurice Wilkins Centre, University of Auckland, Auckland 1001, New Zealand, Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Australia, Department of Mathematics and Statistics, University of Melbourne School of Medicine, University of Melbourne, Victoria 3010, Australia and Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, Canada Auckland Bioengineering Institute, University of Auckland, Auckland 1001, New Zealand, Department of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences,University of Auckland, Auckland 1001, New Zealand, Bioinformatics Institute, University of Auckland, Auckland 1001, New Zealand, Maurice Wilkins Centre, University of Auckland, Auckland 1001, New Zealand, Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Australia, Department of Mathematics and Statistics, University of Melbourne School of Medicine, University of Melbourne, Victoria 3010, Australia and Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, Canada.|Auckland Bioengineering Institute, University of Auckland, Auckland 1001, New Zealand, Department of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences,University of Auckland, Auckland 1001, New Zealand, Bioinformatics Institute, University of Auckland, Auckland 1001, New Zealand, Maurice Wilkins Centre, University of Auckland, Auckland 1001, New Zealand, Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Australia, Department of Mathematics and Statistics, University of Melbourne School of Medicine, University of Melbourne, Victoria 3010, Australia and Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, Canada.|Auckland Bioengineering Institute, University of Auckland, Auckland 1001, New Zealand, Department of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences,University of Auckland, Auckland 1001, New Zealand, Bioinformatics Institute, University of Auckland, Auckland 1001, New Zealand, Maurice Wilkins Centre, University of Auckland, Auckland 1001, New Zealand, Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Australia, Department of Mathematics and Statistics, University of Melbourne School of Medicine, University of Melbourne, Victoria 3010, Australia and Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, Canada Auckland Bioengineering Institute, University of Auckland, Auckland 1001, New Zealand, Department of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences,University of Auckland, Auckland 1001, New Zealand, Bioinformatics Institute, University of Auckland, Auckland 1001, New Zealand, Maurice Wilkins Centre, University of Auckland, Auckland 1001, New Zealand, Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Australia, Department of Mathematics and Statistics, University of Melbourne School of Medicine, University of Melbourne, Victoria 3010, Australia and Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, Canada Auckland Bioengineering Institute, University of Auckland, Auckland 1001, New Zealand, Department of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences,University of Auckland, Auckland 1001, New Zealand, Bioinformatics Institute, University of Auckland, Auckland 1001, New Zealand, Maurice Wilkins Centre, University of Auckland, Auckland 1001, New Zealand, Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Aus|Auckland Bioengineering Institute, University of Auckland, Auckland 1001, New Zealand, Department of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences,University of Auckland, Auckland 1001, New Zealand, Bioinformatics Institute, University of Auckland, Auckland 1001, New Zealand, Maurice Wilkins Centre, University of Auckland, Auckland 1001, New Zealand, Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Australia, Department of Mathematics and Statistics, University of Melbourne School of Medicine, University of Melbourne, Victoria 3010, Australia and Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, Canada Auckland Bioengineering Institute, University of Auckland, Auckland 1001, New Zealand, Department of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences,University of Auckland, Auckland 1001, New Zealand, Bioinformatics Institute, University of Auckland, Auckland 1001, New Zealand, Maurice Wilkins Centre, University of Auckland, Auckland 1001, New Zealand, Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Australia, Department of Mathematics and Statistics, University of Melbourne School of Medicine, University of Melbourne, Victoria 3010, Australia and Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, Canada Auckland Bioengineering Institute, University of Auckland, Auckland 1001, New Zealand, Department of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences,University of Auckland, Auckland 1001, New Zealand, Bioinformatics Institute, University of Auckland, Auckland 1001, New Zealand, Maurice Wilkins Centre, University of Auckland, Auckland 1001, New Zealand, Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Aus', 'Australia|Australia|Australia|Australia|Australia|Australia', 11, 'Algorithms|Computer Graphics|Gene Regulatory Networks|Humans|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btu612', '25246431', 'The wide variety of published approaches for the problem of regulatory network inference makes using multiple inference algorithms complex and time-consuming. Network Analysis and Inference Library (NAIL) is a set of software tools to simplify the range of computational activities involved in regulatory network inference. It uses a modular approach to connect different network inference algorithms to the same visualization and network-based analyses. NAIL is technology-independent and includes an interface layer to allow easy integration of components into other applications.'),
(78726, 2015, 'bio', 'Comprehensive large-scale assessment of intrinsic protein disorder', 'Walsh, Ian|Giollo, Manuel|Di Domenico, Tomás|Ferrari, Carlo|Zimmermann, Olav|Tosatto, Silvio C E', 'Department of Biomedical Sciences, Department of Information Engineering, University of Padua, Via Gradenigo 6, 35121 Padova, Italy and Institute for Advanced Simulation, Forschungszentrum Juelich, Wilhelm-Johnen-Str., 52425 Juelich, Germany.|Department of Biomedical Sciences, Department of Information Engineering, University of Padua, Via Gradenigo 6, 35121 Padova, Italy and Institute for Advanced Simulation, Forschungszentrum Juelich, Wilhelm-Johnen-Str., 52425 Juelich, Germany Department of Biomedical Sciences, Department of Information Engineering, University of Padua, Via Gradenigo 6, 35121 Padova, Italy and Institute for Advanced Simulation, Forschungszentrum Juelich, Wilhelm-Johnen-Str., 52425 Juelich, Germany.|Department of Biomedical Sciences, Department of Information Engineering, University of Padua, Via Gradenigo 6, 35121 Padova, Italy and Institute for Advanced Simulation, Forschungszentrum Juelich, Wilhelm-Johnen-Str., 52425 Juelich, Germany.|Department of Biomedical Sciences, Department of Information Engineering, University of Padua, Via Gradenigo 6, 35121 Padova, Italy and Institute for Advanced Simulation, Forschungszentrum Juelich, Wilhelm-Johnen-Str., 52425 Juelich, Germany.|Department of Biomedical Sciences, Department of Information Engineering, University of Padua, Via Gradenigo 6, 35121 Padova, Italy and Institute for Advanced Simulation, Forschungszentrum Juelich, Wilhelm-Johnen-Str., 52425 Juelich, Germany.|Department of Biomedical Sciences, Department of Information Engineering, University of Padua, Via Gradenigo 6, 35121 Padova, Italy and Institute for Advanced Simulation, Forschungszentrum Juelich, Wilhelm-Johnen-Str., 52425 Juelich, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 98, 'Crystallography, X-Ray|Databases, Protein|Humans|Molecular Sequence Annotation|Protein Structure, Tertiary|Proteins|Sequence Analysis, Protein|Tumor Suppressor Protein p53', 'Journal Article', '10.1093/bioinformatics/btu625', '25246432', 'Intrinsically disordered regions are key for the function of numerous proteins. Due to the difficulties in experimental disorder characterization, many computational predictors have been developed with various disorder flavors. Their performance is generally measured on small sets mainly from experimentally solved structures, e.g. Protein Data Bank (PDB) chains. MobiDB has only recently started to collect disorder annotations from multiple experimental structures.'),
(78727, 2015, 'bio', 'PIP-DB: the Protein Isoelectric Point database', 'Bunkute, Egle|Cummins, Christopher|Crofts, Fraser J|Bunce, Gareth|Nabney, Ian T|Flower, Darren R', 'School of Life and Health Sciences and School of Engineering and Applied Science, University of Aston, Aston Triangle, Birmingham B4 7ET, UK.|School of Life and Health Sciences and School of Engineering and Applied Science, University of Aston, Aston Triangle, Birmingham B4 7ET, UK.|School of Life and Health Sciences and School of Engineering and Applied Science, University of Aston, Aston Triangle, Birmingham B4 7ET, UK.|School of Life and Health Sciences and School of Engineering and Applied Science, University of Aston, Aston Triangle, Birmingham B4 7ET, UK.|School of Life and Health Sciences and School of Engineering and Applied Science, University of Aston, Aston Triangle, Birmingham B4 7ET, UK.|School of Life and Health Sciences and School of Engineering and Applied Science, University of Aston, Aston Triangle, Birmingham B4 7ET, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 9, 'Databases, Protein|Isoelectric Point|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btu637', '25252779', 'A proteins isoelectric point or pI corresponds to the solution pH at which its net surface charge is zero. Since the early days of solution biochemistry, the pI has been recorded and reported, and thus literature reports of pI abound. The Protein Isoelectric Point database (PIP-DB) has collected and collated these data to provide an increasingly comprehensive database for comparison and benchmarking purposes. A web application has been developed to warehouse this database and provide public access to this unique resource. PIP-DB is a web-enabled SQL database with an HTML GUI front-end. PIP-DB is fully searchable across a range of properties.'),
(78728, 2015, 'bio', 'PHI-DAC: protein homology database through dihedral angle conservation', 'Maatuk, Noa|Glantz-Gashai, Yitav|Rotman, Maya|Baydany, Meirav|Fonar, Gennadiy|Shechvitz, Amir|Shemer, Karin|Peleg, Aviva|Reuveni, Eli|Samson, Abraham O', 'Faculty of Medicine in the Galilee, Bar Ilan University, 13100 Safed, Israel.|Faculty of Medicine in the Galilee, Bar Ilan University, 13100 Safed, Israel.|Faculty of Medicine in the Galilee, Bar Ilan University, 13100 Safed, Israel.|Faculty of Medicine in the Galilee, Bar Ilan University, 13100 Safed, Israel.|Faculty of Medicine in the Galilee, Bar Ilan University, 13100 Safed, Israel.|Faculty of Medicine in the Galilee, Bar Ilan University, 13100 Safed, Israel.|Faculty of Medicine in the Galilee, Bar Ilan University, 13100 Safed, Israel.|Faculty of Medicine in the Galilee, Bar Ilan University, 13100 Safed, Israel.|Faculty of Medicine in the Galilee, Bar Ilan University, 13100 Safed, Israel.|Faculty of Medicine in the Galilee, Bar Ilan University, 13100 Safed, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel', 0, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Computer Graphics|Databases, Protein|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btu617', '25252780', 'Finding related conformations in the Protein Data Bank is essential in many areas of bioscience. To assist this task, we designed a dihedral angle database for searching protein segment homologs. The search engine relies on encoding of the protein coordinates into text characters representing amino acid sequence, xcfx86 and xcfx88 dihedral angles. The search engine is advantageous owing to its high speed and interactive nature and is expected to assist scientists in discovering conformation homologs and evolutionary kinship. The search engine is fast, with query times lasting a few seconds, and freely available at http://tarshish.md.biu.ac.il/xe2x88xbcsamsona.'),
(78729, 2015, 'bio', 'METAINTER: meta-analysis of multiple regression models in genome-wide association studies', 'Vaitsiakhovich, Tatsiana|Drichel, Dmitriy|Herold, Christine|Lacour, André|Becker, Tim', 'Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn and German Center for Neurodegenerative Diseases (DZNE), Sigmund-Freud-Str. 25, D-53105 Bonn, Germany Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn and German Center for Neurodegenerative Diseases (DZNE), Sigmund-Freud-Str. 25, D-53105 Bonn, Germany.|Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn and German Center for Neurodegenerative Diseases (DZNE), Sigmund-Freud-Str. 25, D-53105 Bonn, Germany.|Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn and German Center for Neurodegenerative Diseases (DZNE), Sigmund-Freud-Str. 25, D-53105 Bonn, Germany.|Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn and German Center for Neurodegenerative Diseases (DZNE), Sigmund-Freud-Str. 25, D-53105 Bonn, Germany.|Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn and German Center for Neurodegenerative Diseases (DZNE), Sigmund-Freud-Str. 25, D-53105 Bonn, Germany Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn and German Center for Neurodegenerative Diseases (DZNE), Sigmund-Freud-Str. 25, D-53105 Bonn, Germany.', 'Germany|Germany|Germany|Germany|Germany', 3, 'Data Interpretation, Statistical|Diabetes Mellitus, Type 2|Gene-Environment Interaction|Genome, Human|Genome-Wide Association Study|Haplotypes|Humans|Linear Models|Logistic Models|Models, Statistical|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btu629', '25252781', 'Meta-analysis of summary statistics is an essential approach to guarantee the success of genome-wide association studies (GWAS). Application of the fixed or random effects model to single-marker association tests is a standard practice. More complex methods of meta-analysis involving multiple parameters have not been used frequently, a gap that could be explained by the lack of a respective meta-analysis pipeline. Meta-analysis based on combining p-values can be applied to any association test. However, to be powerful, meta-analysis methods for high-dimensional models should incorporate additional information such as study-specific properties of parameter estimates, their effect directions, standard errors and covariance structure.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78730, 2015, 'bio', 'A two-stage statistical procedure for feature selection and comparison in functional analysis of metagenomes', 'Pookhao, Naruekamol|Sohn, Michael B|Li, Qike|Jenkins, Isaac|Du, Ruofei|Jiang, Hongmei|An, Lingling', 'Department of Agricultural & Biosystems Engineering, Interdisciplinary Program in Statistics, University of Arizona, Tucson, AZ, 85721 and Department of Statistics, Northwestern University, Evanston, IL 60208, USA.|Department of Agricultural & Biosystems Engineering, Interdisciplinary Program in Statistics, University of Arizona, Tucson, AZ, 85721 and Department of Statistics, Northwestern University, Evanston, IL 60208, USA.|Department of Agricultural & Biosystems Engineering, Interdisciplinary Program in Statistics, University of Arizona, Tucson, AZ, 85721 and Department of Statistics, Northwestern University, Evanston, IL 60208, USA.|Department of Agricultural & Biosystems Engineering, Interdisciplinary Program in Statistics, University of Arizona, Tucson, AZ, 85721 and Department of Statistics, Northwestern University, Evanston, IL 60208, USA.|Department of Agricultural & Biosystems Engineering, Interdisciplinary Program in Statistics, University of Arizona, Tucson, AZ, 85721 and Department of Statistics, Northwestern University, Evanston, IL 60208, USA.|Department of Agricultural & Biosystems Engineering, Interdisciplinary Program in Statistics, University of Arizona, Tucson, AZ, 85721 and Department of Statistics, Northwestern University, Evanston, IL 60208, USA.|Department of Agricultural & Biosystems Engineering, Interdisciplinary Program in Statistics, University of Arizona, Tucson, AZ, 85721 and Department of Statistics, Northwestern University, Evanston, IL 60208, USA Department of Agricultural & Biosystems Engineering, Interdisciplinary Program in Statistics, University of Arizona, Tucson, AZ, 85721 and Department of Statistics, Northwestern University, Evanston, IL 60208, USA.', 'United States|United States|United States|United States|United States|United States|United States', 10, 'Case-Control Studies|Data Interpretation, Statistical|Gastrointestinal Tract|Gene Expression Regulation, Bacterial|Genes, Bacterial|Humans|Inflammatory Bowel Diseases|Metagenomics|Mucus|Obesity|ROC Curve|Saliva', 'Comparative Study', '10.1093/bioinformatics/btu635', '25256572', 'With the advance of new sequencing technologies producing massive short reads data, metagenomics is rapidly growing, especially in the fields of environmental biology and medical science. The metagenomic data are not only high dimensional with large number of features and limited number of samples but also complex with a large number of zeros and skewed distribution. Efficient computational and statistical tools are needed to deal with these unique characteristics of metagenomic sequencing data. In metagenomic studies, one main objective is to assess whether and how multiple microbial communities differ under various environmental conditions.'),
(78731, 2015, 'bio', 'MTide: an integrated tool for the identification of miRNA-target interaction in plants', 'Zhang, Zhao|Jiang, Li|Wang, Jingjing|Gu, Peizhen|Chen, Ming', 'Department of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058, China and Department of Control Science and Engineering, Zhejiang University, Hangzhou 310058, China.|Department of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058, China and Department of Control Science and Engineering, Zhejiang University, Hangzhou 310058, China.|Department of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058, China and Department of Control Science and Engineering, Zhejiang University, Hangzhou 310058, China.|Department of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058, China and Department of Control Science and Engineering, Zhejiang University, Hangzhou 310058, China.|Department of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058, China and Department of Control Science and Engineering, Zhejiang University, Hangzhou 310058, China.', 'China|China|China|China|China', 36, 'Computational Biology|MicroRNAs|Plants|RNA, Messenger|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu633', '25256573', 'Small RNA sequencing and degradome sequencing (also known as parallel analysis of RNA ends) have provided rich information on the microRNA (miRNA) and its cleaved mRNA targets on a genome-wide scale in plants, but no computational tools have been developed to effectively and conveniently deconvolute the miRNA-target interaction (MTI).'),
(78732, 2015, 'bio', 'PINBPA: cytoscape app for network analysis of GWAS data', 'Wang, Lili|Matsushita, Takuya|Madireddy, Lohith|Mousavi, Parvin|Baranzini, Sergio E', 'School of Computing, Queens University, 25 Union Street, Goodwin Hall, Kingston, Ontario K7L 3N6, Canada and Department of Neurology, University of California San Francisco, 675 Nelson Rising Lane, Room 215, San Francisco, CA 94158, USA.|School of Computing, Queens University, 25 Union Street, Goodwin Hall, Kingston, Ontario K7L 3N6, Canada and Department of Neurology, University of California San Francisco, 675 Nelson Rising Lane, Room 215, San Francisco, CA 94158, USA.|School of Computing, Queens University, 25 Union Street, Goodwin Hall, Kingston, Ontario K7L 3N6, Canada and Department of Neurology, University of California San Francisco, 675 Nelson Rising Lane, Room 215, San Francisco, CA 94158, USA.|School of Computing, Queens University, 25 Union Street, Goodwin Hall, Kingston, Ontario K7L 3N6, Canada and Department of Neurology, University of California San Francisco, 675 Nelson Rising Lane, Room 215, San Francisco, CA 94158, USA.|School of Computing, Queens University, 25 Union Street, Goodwin Hall, Kingston, Ontario K7L 3N6, Canada and Department of Neurology, University of California San Francisco, 675 Nelson Rising Lane, Room 215, San Francisco, CA 94158, USA.', 'Canada|Canada|Canada|Canada|Canada', 21, 'Algorithms|Data Mining|Genome-Wide Association Study|Humans|Protein Interaction Maps|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/btu644', '25260698', 'Protein interaction network-based pathway analysis (PINBPA) for genome-wide association studies (GWAS) has been developed as a Cytoscape app, to enable analysis of GWAS data in a network fashion. Users can easily import GWAS summary-level data, draw Manhattan plots, define blocks, prioritize genes with random walk with restart, detect enriched subnetworks and test the significance of subnetworks via a user-friendly interface.'),
(78733, 2015, 'bio', 'EasyStrata: evaluation and visualization of stratified genome-wide association meta-analysis data', 'Winkler, Thomas W|Kutalik, Zoltan|Gorski, Mathias|Lottaz, Claudio|Kronenberg, Florian|Heid, Iris M', 'Department of Genetic Epidemiology, University of Regensburg, D-93053 Regensburg, Germany, Department of Medical Genetics, University of Lausanne, CH-1005 Lausanne, Switzerland, Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), CH-1010 Lausanne, Switzerland, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland, Department of Statistical Bioinformatics, Institute for Functional Genomics, University of Regensburg, D-93053 Regensburg, Germany and Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, A-6020 Innsbruck, Austria.|Department of Genetic Epidemiology, University of Regensburg, D-93053 Regensburg, Germany, Department of Medical Genetics, University of Lausanne, CH-1005 Lausanne, Switzerland, Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), CH-1010 Lausanne, Switzerland, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland, Department of Statistical Bioinformatics, Institute for Functional Genomics, University of Regensburg, D-93053 Regensburg, Germany and Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, A-6020 Innsbruck, Austria Department of Genetic Epidemiology, University of Regensburg, D-93053 Regensburg, Germany, Department of Medical Genetics, University of Lausanne, CH-1005 Lausanne, Switzerland, Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), CH-1010 Lausanne, Switzerland, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland, Department of Statistical Bioinformatics, Institute for Functional Genomics, University of Regensburg, D-93053 Regensburg, Germany and Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, A-6020 Innsbruck, Austria Department of Genetic Epidemiology, University of Regensburg, D-93053 Regensburg, Germany, Department of Medical Genetics, University of Lausanne, CH-1005 Lausanne, Switzerland, Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), CH-1010 Lausanne, Switzerland, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland, Department of Statistical Bioinformatics, Institute for Functional Genomics, University of Regensburg, D-93053 Regensburg, Germany and Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, A-6020 Innsbr|Department of Genetic Epidemiology, University of Regensburg, D-93053 Regensburg, Germany, Department of Medical Genetics, University of Lausanne, CH-1005 Lausanne, Switzerland, Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), CH-1010 Lausanne, Switzerland, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland, Department of Statistical Bioinformatics, Institute for Functional Genomics, University of Regensburg, D-93053 Regensburg, Germany and Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, A-6020 Innsbruck, Austria.|Department of Genetic Epidemiology, University of Regensburg, D-93053 Regensburg, Germany, Department of Medical Genetics, University of Lausanne, CH-1005 Lausanne, Switzerland, Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), CH-1010 Lausanne, Switzerland, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland, Department of Statistical Bioinformatics, Institute for Functional Genomics, University of Regensburg, D-93053 Regensburg, Germany and Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, A-6020 Innsbruck, Austria.|Department of Genetic Epidemiology, University of Regensburg, D-93053 Regensburg, Germany, Department of Medical Genetics, University of Lausanne, CH-1005 Lausanne, Switzerland, Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), CH-1010 Lausanne, Switzerland, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland, Department of Statistical Bioinformatics, Institute for Functional Genomics, University of Regensburg, D-93053 Regensburg, Germany and Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, A-6020 Innsbruck, Austria.|Department of Genetic Epidemiology, University of Regensburg, D-93053 Regensburg, Germany, Department of Medical Genetics, University of Lausanne, CH-1005 Lausanne, Switzerland, Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), CH-1010 Lausanne, Switzerland, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland, Department of Statistical Bioinformatics, Institute for Functional Genomics, University of Regensburg, D-93053 Regensburg, Germany and Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, A-6020 Innsbruck, Austria.', 'Austria|Austria|Austria|Austria|Austria|Austria', 0, 'Computational Biology|Computer Graphics|Datasets as Topic|Genome, Human|Genome-Wide Association Study|Humans|Meta-Analysis as Topic|Software', 'Journal Article', '10.1093/bioinformatics/btu621', '25260699', 'The R package EasyStrata facilitates the evaluation and visualization of stratified genome-wide association meta-analyses (GWAMAs) results. It provides (i) statistical methods to test and account for between-strata difference as a means to tackle gene-strata interaction effects and (ii) extended graphical features tailored for stratified GWAMA results. The software provides further features also suitable for general GWAMAs including functions to annotate, exclude or highlight specific loci in plots or to extract independent subsets of loci from genome-wide datasets. It is freely available and includes a user-friendly scripting interface that simplifies data handling and allows for combining statistical and graphical functions in a flexible fashion.'),
(78734, 2015, 'bio', 'HTSeq--a Python framework to work with high-throughput sequencing data', 'Anders, Simon|Pyl, Paul Theodor|Huber, Wolfgang', 'Genome Biology Unit, European Molecular Biology Laboratory, 69111 Heidelberg, Germany.|Genome Biology Unit, European Molecular Biology Laboratory, 69111 Heidelberg, Germany.|Genome Biology Unit, European Molecular Biology Laboratory, 69111 Heidelberg, Germany.', 'Germany|Germany|Germany', 0, 'Gene Expression Regulation|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|Software', 'Journal Article', '10.1093/bioinformatics/btu638', '25260700', 'A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard workflows, custom scripts are needed.'),
(78735, 2015, 'bio', 'Enlight: web-based integration of GWAS results with biological annotations', 'Guo, Yunfei|Conti, David V|Wang, Kai', 'Zilkha Neurogenetic Institute, University of Southern California, Los Angeles, CA 90033, Department of Preventive Medicine, USC Keck School of Medicine, Los Angeles, CA 90032 and Department of Psychiatry & Behavioral Sciences, USC Keck School of Medicine, Los Angeles, CA 90033, USA Zilkha Neurogenetic Institute, University of Southern California, Los Angeles, CA 90033, Department of Preventive Medicine, USC Keck School of Medicine, Los Angeles, CA 90032 and Department of Psychiatry & Behavioral Sciences, USC Keck School of Medicine, Los Angeles, CA 90033, USA.|Zilkha Neurogenetic Institute, University of Southern California, Los Angeles, CA 90033, Department of Preventive Medicine, USC Keck School of Medicine, Los Angeles, CA 90032 and Department of Psychiatry & Behavioral Sciences, USC Keck School of Medicine, Los Angeles, CA 90033, USA Zilkha Neurogenetic Institute, University of Southern California, Los Angeles, CA 90033, Department of Preventive Medicine, USC Keck School of Medicine, Los Angeles, CA 90032 and Department of Psychiatry & Behavioral Sciences, USC Keck School of Medicine, Los Angeles, CA 90033, USA.|Zilkha Neurogenetic Institute, University of Southern California, Los Angeles, CA 90033, Department of Preventive Medicine, USC Keck School of Medicine, Los Angeles, CA 90032 and Department of Psychiatry & Behavioral Sciences, USC Keck School of Medicine, Los Angeles, CA 90033, USA Zilkha Neurogenetic Institute, University of Southern California, Los Angeles, CA 90033, Department of Preventive Medicine, USC Keck School of Medicine, Los Angeles, CA 90032 and Department of Psychiatry & Behavioral Sciences, USC Keck School of Medicine, Los Angeles, CA 90033, USA Zilkha Neurogenetic Institute, University of Southern California, Los Angeles, CA 90033, Department of Preventive Medicine, USC Keck School of Medicine, Los Angeles, CA 90032 and Department of Psychiatry & Behavioral Sciences, USC Keck School of Medicine, Los Angeles, CA 90033, USA.', 'United States|United States|United States', 0, 'Arthritis, Rheumatoid|Databases, Genetic|Genome, Human|Genome-Wide Association Study|Genomics|Humans|Internet|Molecular Sequence Annotation|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Software', 'Journal Article', '10.1093/bioinformatics/btu639', '25262152', 'Identifying causal variants remains a key challenge in post-GWAS (genome-wide association study) era, as many GWAS single-nucleotide polymorphisms (SNPs) (including imputed ones) fall into non-coding regions, making it difficult to associate statistical significance with predicted functionality. Therefore, we created a web-based tool, Enlight, which overlays functional annotation information, such as histone modification states, methylation patterns, transcription factor binding sites, eQTL and higher-order chromosomal structure, to GWAS results.'),
(78736, 2015, 'bio', 'switchBox: an R package for k-Top Scoring Pairs classifier development', 'Afsari, Bahman|Fertig, Elana J|Geman, Donald|Marchionni, Luigi', 'Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, MD 21205 and Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD 21218, USA.|Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, MD 21205 and Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD 21218, USA.|Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, MD 21205 and Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD 21218, USA.|Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, MD 21205 and Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD 21218, USA.', 'United States|United States|United States|United States', 17, 'Algorithms|Biomarkers, Tumor|Breast Neoplasms|Computational Biology|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Neoplasm Recurrence, Local|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btu622', '25262153', 'k-Top Scoring Pairs (kTSP) is a classification method for prediction from high-throughput data based on a set of the paired measurements. Each of the two possible orderings of a pair of measurements (e.g. a reversal in the expression of two genes) is associated with one of two classes. The kTSP prediction rule is the aggregation of voting among such individual two-feature decision rules based on order switching. kTSP, like its predecessor, Top Scoring Pair (TSP), is a parameter-free classifier relying only on ranking of a small subset of features, rendering it robust to noise and potentially easy to interpret in biological terms. In contrast to TSP, kTSP has comparable accuracy to standard genomics classification techniques, including Support Vector Machines and Prediction Analysis for Microarrays. Here, we describe switchBox, an R package for kTSP-based prediction.'),
(78737, 2015, 'bio', 'Shiny-phyloseq: Web application for interactive microbiome analysis with provenance tracking', 'McMurdie, Paul J|Holmes, Susan', 'Department of Statistics, Stanford University, Stanford, CA 94305, USA.|Department of Statistics, Stanford University, Stanford, CA 94305, USA.', 'United States|United States', 0, 'Computer Graphics|Data Interpretation, Statistical|Humans|Microbiota|Phylogeny|Software|Web Browser', 'Journal Article', '10.1093/bioinformatics/btu616', '25262154', 'We have created a Shiny-based Web application, called Shiny-phyloseq, for dynamic interaction with microbiome data that runs on any modern Web browser and requires no programming, increasing the accessibility and decreasing the entrance requirement to using phyloseq and related R tools. Along with a data- and context-aware dynamic interface for exploring the effects of parameter and method choices, Shiny-phyloseq also records the complete user input and subsequent graphical results of a users session, allowing the user to archive, share and reproduce the sequence of steps that created their result-without writing any new code themselves.'),
(78738, 2015, 'bio', 'LongTarget: a tool to predict lncRNA DNA-binding motifs and binding sites via Hoogsteen base-pairing analysis', 'He, Sha|Zhang, Hai|Liu, Haihua|Zhu, Hao', 'Bioinformatics Section, School of Basic Medical Sciences and Network Center, Southern Medical University, Guangzhou 510515, China.|Bioinformatics Section, School of Basic Medical Sciences and Network Center, Southern Medical University, Guangzhou 510515, China.|Bioinformatics Section, School of Basic Medical Sciences and Network Center, Southern Medical University, Guangzhou 510515, China.|Bioinformatics Section, School of Basic Medical Sciences and Network Center, Southern Medical University, Guangzhou 510515, China.', 'China|China|China|China', 39, 'Base Pairing|Binding Sites|Computational Biology|DNA Methylation|DNA-Binding Proteins|Gene Expression Regulation|Genome, Human|Genomic Imprinting|Humans|Promoter Regions, Genetic|RNA, Long Noncoding|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu643', '25262155', 'In mammalian cells, many genes are silenced by genome methylation. DNA methyltransferases and polycomb repressive complexes, which both lack sequence-specific DNA-binding motifs, are recruited by long non-coding RNA (lncRNA) to specific genomic sites to methylate DNA and chromatin. Increasing evidence indicates that many lncRNAs contain DNA-binding motifs that can bind to DNA by forming RNA:DNA triplexes. The identification of lncRNA DNA-binding motifs and binding sites is essential for deciphering lncRNA functions and correct and erroneous genome methylation, however, such identification is challenging because lncRNAs may contain thousands of nucleotides. No computational analysis of typical lncRNAs has been reported. Here, we report a computational method and program (LongTarget) to predict lncRNA DNA-binding motifs and binding sites. We used this program to analyse multiple antisense lncRNAs, including those that control well-known imprinting clusters, and obtained results agreeing with experimental observations and epigenetic marks. These results suggest that it is feasible to predict many lncRNA DNA-binding motifs and binding sites genome-wide.'),
(78739, 2015, 'bio', 'Sigma: strain-level inference of genomes from metagenomic analysis for biosurveillance', 'Ahn, Tae-Hyuk|Chai, Juanjuan|Pan, Chongle', 'Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA.|Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA.|Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA.', 'United States|United States|United States', 0, 'Algorithms|Biosurveillance|Computational Biology|DNA, Bacterial|Genome, Bacterial|Humans|Metagenomics|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu641', '25266224', 'Metagenomic sequencing of clinical samples provides a promising technique for direct pathogen detection and characterization in biosurveillance. Taxonomic analysis at the strain level can be used to resolve serotypes of a pathogen in biosurveillance. Sigma was developed for strain-level identification and quantification of pathogens using their reference genomes based on metagenomic analysis.'),
(78740, 2015, 'bio', 'GLAD: a mixed-membership model for heterogeneous tumor subtype classification', 'Saddiki, Hachem|McAuliffe, Jon|Flaherty, Patrick', 'Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA 01609, USA, School of Science and Engineering, Al Akhawayn University, Ifrane, 53000, Morocco, Department of Statistics, University of California, Berkeley, CA 94720, USA, and Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA 01609, USA, School of Science and Engineering, Al Akhawayn University, Ifrane, 53000, Morocco, Department of Statistics, University of California, Berkeley, CA 94720, USA, and Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA.|Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA 01609, USA, School of Science and Engineering, Al Akhawayn University, Ifrane, 53000, Morocco, Department of Statistics, University of California, Berkeley, CA 94720, USA, and Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA.|Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA 01609, USA, School of Science and Engineering, Al Akhawayn University, Ifrane, 53000, Morocco, Department of Statistics, University of California, Berkeley, CA 94720, USA, and Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA 01609, USA, School of Science and Engineering, Al Akhawayn University, Ifrane, 53000, Morocco, Department of Statistics, University of California, Berkeley, CA 94720, USA, and Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA.', 'Morocco|Morocco|Morocco', 6, 'Algorithms|Biomarkers, Tumor|Computational Biology|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Gene Regulatory Networks|Humans|Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/btu618', '25266225', 'Genomic analyses of many solid cancers have demonstrated extensive genetic heterogeneity between as well as within individual tumors. However, statistical methods for classifying tumors by subtype based on genomic biomarkers generally entail an all-or-none decision, which may be misleading for clinical samples containing a mixture of subtypes and/or normal cell contamination.'),
(78741, 2015, 'bio', 'Hybrid Bayesian-rank integration approach improves the predictive power of genomic dataset aggregation', 'Badgeley, Marcus A|Sealfon, Stuart C|Chikina, Maria D', 'Department of Neurology, Mount Sinai School of Medicine, New York, NY 10029 and Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA.|Department of Neurology, Mount Sinai School of Medicine, New York, NY 10029 and Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA.|Department of Neurology, Mount Sinai School of Medicine, New York, NY 10029 and Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA.', 'United States|United States|United States', 9, 'Algorithms|Bayes Theorem|Biomarkers|Computational Biology|Gene Expression Profiling|Gene Regulatory Networks|Humans|Meta-Analysis as Topic|Parkinson Disease', 'Journal Article', '10.1093/bioinformatics/btu518', '25266226', 'Modern molecular technologies allow the collection of large amounts of high-throughput data on the functional attributes of genes. Often multiple technologies and study designs are used to address the same biological question such as which genes are overexpressed in a specific disease state. Consequently, there is considerable interest in methods that can integrate across datasets to present a unified set of predictions.'),
(78742, 2015, 'bio', 'Consensus Genotyper for Exome Sequencing (CGES): improving the quality of exome variant genotypes', 'Trubetskoy, Vassily|Rodriguez, Alex|Dave, Uptal|Campbell, Nicholas|Crawford, Emily L|Cook, Edwin H|Sutcliffe, James S|Foster, Ian|Madduri, Ravi|Cox, Nancy J|Davis, Lea K', 'Department of Medicine, Section of Genetic Medicine, Computation Institute, University of Chicago, Chicago, IL 60637, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee 37232, USA, Vanderbilt Brain Institute, Vanderbilt University School of Medicine, Nashville, TN 37232 and Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60608, USA.|Department of Medicine, Section of Genetic Medicine, Computation Institute, University of Chicago, Chicago, IL 60637, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee 37232, USA, Vanderbilt Brain Institute, Vanderbilt University School of Medicine, Nashville, TN 37232 and Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60608, USA.|Department of Medicine, Section of Genetic Medicine, Computation Institute, University of Chicago, Chicago, IL 60637, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee 37232, USA, Vanderbilt Brain Institute, Vanderbilt University School of Medicine, Nashville, TN 37232 and Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60608, USA.|Department of Medicine, Section of Genetic Medicine, Computation Institute, University of Chicago, Chicago, IL 60637, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee 37232, USA, Vanderbilt Brain Institute, Vanderbilt University School of Medicine, Nashville, TN 37232 and Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60608, USA Department of Medicine, Section of Genetic Medicine, Computation Institute, University of Chicago, Chicago, IL 60637, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee 37232, USA, Vanderbilt Brain Institute, Vanderbilt University School of Medicine, Nashville, TN 37232 and Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60608, USA.|Department of Medicine, Section of Genetic Medicine, Computation Institute, University of Chicago, Chicago, IL 60637, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee 37232, USA, Vanderbilt Brain Institute, Vanderbilt University School of Medicine, Nashville, TN 37232 and Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60608, USA Department of Medicine, Section of Genetic Medicine, Computation Institute, University of Chicago, Chicago, IL 60637, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee 37232, USA, Vanderbilt Brain Institute, Vanderbilt University School of Medicine, Nashville, TN 37232 and Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60608, USA.|Department of Medicine, Section of Genetic Medicine, Computation Institute, University of Chicago, Chicago, IL 60637, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee 37232, USA, Vanderbilt Brain Institute, Vanderbilt University School of Medicine, Nashville, TN 37232 and Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60608, USA.|Department of Medicine, Section of Genetic Medicine, Computation Institute, University of Chicago, Chicago, IL 60637, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee 37232, USA, Vanderbilt Brain Institute, Vanderbilt University School of Medicine, Nashville, TN 37232 and Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60608, USA Department of Medicine, Section of Genetic Medicine, Computation Institute, University of Chicago, Chicago, IL 60637, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee 37232, USA, Vanderbilt Brain Institute, Vanderbilt University School of Medicine, Nashville, TN 37232 and Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60608, USA.|Department of Medicine, Section of Genetic Medicine, Computation Institute, University of Chicago, Chicago, IL 60637, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee 37232, USA, Vanderbilt Brain Institute, Vanderbilt University School of Medicine, Nashville, TN 37232 and Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60608, USA.|Department of Medicine, Section of Genetic Medicine, Computation Institute, University of Chicago, Chicago, IL 60637, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee 37232, USA, Vanderbilt Brain Institute, Vanderbilt University School of Medicine, Nashville, TN 37232 and Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60608, USA.|Department of Medicine, Section of Genetic Medicine, Computation Institute, University of Chicago, Chicago, IL 60637, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee 37232, USA, Vanderbilt Brain Institute, Vanderbilt University School of Medicine, Nashville, TN 37232 and Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60608, USA.|Department of Medicine, Section of Genetic Medicine, Computation Institute, University of Chicago, Chicago, IL 60637, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee 37232, USA, Vanderbilt Brain Institute, Vanderbilt University School of Medicine, Nashville, TN 37232 and Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60608, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Autistic Disorder|Consensus Sequence|Data Interpretation, Statistical|Exome|Genetic Testing|Genotype|High-Throughput Nucleotide Sequencing|Humans|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btu591', '25270638', 'The development of cost-effective next-generation sequencing methods has spurred the development of high-throughput bioinformatics tools for detection of sequence variation. With many disparate variant-calling algorithms available, investigators must ask, Which method is best for my data? Machine learning research has shown that so-called ensemble methods that combine the output of multiple models can dramatically improve classifier performance. Here we describe a novel variant-calling approach based on an ensemble of variant-calling algorithms, which we term the Consensus Genotyper for Exome Sequencing (CGES). CGES uses a two-stage voting scheme among four algorithm implementations. While our ensemble method can accept variants generated by any variant-calling algorithm, we used GATK2.8, SAMtools, FreeBayes and Atlas-SNP2 in building CGES because of their performance, widespread adoption and diverse but complementary algorithms.'),
(78743, 2015, 'bio', 'BioVLAB-MMIA-NGS: microRNA-mRNA integrated analysis using high-throughput sequencing data', 'Chae, Heejoon|Rhee, Sungmin|Nephew, Kenneth P|Kim, Sun', 'Department of Computer Science, School of Informatics and Computing, Indiana University Bloomington, IN 47404, USA, School of Computer Science and Engineering, Seoul National University, Seoul, Korea and Indiana University School of Medicine, Indianapolis, IN 46202, USA.|Department of Computer Science, School of Informatics and Computing, Indiana University Bloomington, IN 47404, USA, School of Computer Science and Engineering, Seoul National University, Seoul, Korea and Indiana University School of Medicine, Indianapolis, IN 46202, USA.|Department of Computer Science, School of Informatics and Computing, Indiana University Bloomington, IN 47404, USA, School of Computer Science and Engineering, Seoul National University, Seoul, Korea and Indiana University School of Medicine, Indianapolis, IN 46202, USA.|Department of Computer Science, School of Informatics and Computing, Indiana University Bloomington, IN 47404, USA, School of Computer Science and Engineering, Seoul National University, Seoul, Korea and Indiana University School of Medicine, Indianapolis, IN 46202, USA.', 'India|India|India|India', 20, 'Computational Biology|Database Management Systems|Databases, Genetic|Gene Expression Regulation|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|MicroRNAs|RNA|RNA, Messenger|Sequence Analysis, RNA|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu614', '25270639', 'It is now well established that microRNAs (miRNAs) play a critical role in regulating gene expression in a sequence-specific manner, and genome-wide efforts are underway to predict known and novel miRNA targets. However, the integrated miRNA-mRNA analysis remains a major computational challenge, requiring powerful informatics systems and bioinformatics expertise.'),
(78744, 2015, 'bio', 'A Python package for parsing, validating, mapping and formatting sequence variants using HGVS nomenclature', 'Hart, Reece K|Rico, Rudolph|Hare, Emily|Garcia, John|Westbrook, Jody|Fusaro, Vincent A', 'Invitae Inc., San Francisco, CA 94107 and 23andMe Inc., Mountain View, CA 94043, USA Invitae Inc., San Francisco, CA 94107 and 23andMe Inc., Mountain View, CA 94043, USA.|Invitae Inc., San Francisco, CA 94107 and 23andMe Inc., Mountain View, CA 94043, USA.|Invitae Inc., San Francisco, CA 94107 and 23andMe Inc., Mountain View, CA 94043, USA.|Invitae Inc., San Francisco, CA 94107 and 23andMe Inc., Mountain View, CA 94043, USA.|Invitae Inc., San Francisco, CA 94107 and 23andMe Inc., Mountain View, CA 94043, USA.|Invitae Inc., San Francisco, CA 94107 and 23andMe Inc., Mountain View, CA 94043, USA.', 'United States|United States|United States|United States|United States|United States', 22, 'Computational Biology|Databases, Factual|Genetic Variation|Genome, Human|Humans|Molecular Sequence Annotation|Software|Terminology as Topic', 'Journal Article', '10.1093/bioinformatics/btu630', '25273102', 'Biological sequence variants are commonly represented in scientific literature, clinical reports and databases of variation using the mutation nomenclature guidelines endorsed by the Human Genome Variation Society (HGVS). Despite the widespread use of the standard, no freely available and comprehensive programming libraries are available. Here we report an open-source and easy-to-use Python library that facilitates the parsing, manipulation, formatting and validation of variants according to the HGVS specification. The current implementation focuses on the subset of the HGVS recommendations that precisely describe sequence-level variation relevant to the application of high-throughput sequencing to clinical diagnostics.'),
(78745, 2015, 'bio', 'The RNA shapes studio', 'Janssen, Stefan|Giegerich, Robert', 'Practical Computer Science, Faculty of Technology, Bielefeld University, D-33615 Bielefeld, Germany.|Practical Computer Science, Faculty of Technology, Bielefeld University, D-33615 Bielefeld, Germany.', 'Germany|Germany', 42, 'Computational Biology|Coronavirus|Nucleic Acid Conformation|RNA|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btu649', '25273103', 'Abstract shape analysis, first proposed in 2004, allows one to extract several relevant structures from the folding space of an RNA sequence, preferable to focusing in a single structure of minimal free energy. We report recent extensions to this approach.'),
(78746, 2015, 'bio', 'WhopGenome: high-speed access to whole-genome variation and sequence data in R', 'Wittelsbürger, Ulrich|Pfeifer, Bastian|Lercher, Martin J', 'Institute for Computer Science, Heinrich Heine University, D-40255 Düsseldorf, Germany and Cluster of Excellence on Plant Sciences CEPLAS, D-40255 Düsseldorf, Germany.|Institute for Computer Science, Heinrich Heine University, D-40255 Düsseldorf, Germany and Cluster of Excellence on Plant Sciences CEPLAS, D-40255 Düsseldorf, Germany.|Institute for Computer Science, Heinrich Heine University, D-40255 Düsseldorf, Germany and Cluster of Excellence on Plant Sciences CEPLAS, D-40255 Düsseldorf, Germany Institute for Computer Science, Heinrich Heine University, D-40255 Düsseldorf, Germany and Cluster of Excellence on Plant Sciences CEPLAS, D-40255 Düsseldorf, Germany.', 'Germany|Germany|Germany', 1, 'Algorithms|Genetic Variation|Genome, Human|Genomics|Humans|Molecular Sequence Annotation|Software', 'Journal Article', '10.1093/bioinformatics/btu636', '25273104', 'The statistical programming language R has become a de facto standard for the analysis of many types of biological data, and is well suited for the rapid development of new algorithms. However, variant call data from population-scale resequencing projects are typically too large to be read and processed efficiently with Rs built-in I/O capabilities. WhopGenome can efficiently read whole-genome variation data stored in the widely used variant call format (VCF) file format into several R data types. VCF files can be accessed either on local hard drives or on remote servers. WhopGenome can associate variants with annotations such as those available from the UCSC genome browser, and can accelerate the reading process by filtering loci according to user-defined criteria. WhopGenome can also read other Tabix-indexed files and create indices to allow fast selective access to FASTA-formatted sequence files.'),
(78747, 2015, 'bio', 'OrthoInspector 20: Software and database updates', 'Linard, Benjamin|Allot, Alexis|Schneider, Raphaël|Morel, Can|Ripp, Raymond|Bigler, Marc|Thompson, Julie D|Poch, Olivier|Lecompte, Odile', 'LBGI, Computer Science Department, ICube, UMR 7357, University of Strasbourg, CNRS, Fédération de médecine translationnelle, 4 rue Kirschleger 67085 Strasbourg, France and Department of Life Sciences, Natural History Museum, Cromwell Road, London SW7 5BD LBGI, Computer Science Department, ICube, UMR 7357, University of Strasbourg, CNRS, Fédération de médecine translationnelle, 4 rue Kirschleger 67085 Strasbourg, France and Department of Life Sciences, Natural History Museum, Cromwell Road, London SW7 5BD.|LBGI, Computer Science Department, ICube, UMR 7357, University of Strasbourg, CNRS, Fédération de médecine translationnelle, 4 rue Kirschleger 67085 Strasbourg, France and Department of Life Sciences, Natural History Museum, Cromwell Road, London SW7 5BD.|LBGI, Computer Science Department, ICube, UMR 7357, University of Strasbourg, CNRS, Fédération de médecine translationnelle, 4 rue Kirschleger 67085 Strasbourg, France and Department of Life Sciences, Natural History Museum, Cromwell Road, London SW7 5BD.|LBGI, Computer Science Department, ICube, UMR 7357, University of Strasbourg, CNRS, Fédération de médecine translationnelle, 4 rue Kirschleger 67085 Strasbourg, France and Department of Life Sciences, Natural History Museum, Cromwell Road, London SW7 5BD.|LBGI, Computer Science Department, ICube, UMR 7357, University of Strasbourg, CNRS, Fédération de médecine translationnelle, 4 rue Kirschleger 67085 Strasbourg, France and Department of Life Sciences, Natural History Museum, Cromwell Road, London SW7 5BD.|LBGI, Computer Science Department, ICube, UMR 7357, University of Strasbourg, CNRS, Fédération de médecine translationnelle, 4 rue Kirschleger 67085 Strasbourg, France and Department of Life Sciences, Natural History Museum, Cromwell Road, London SW7 5BD.|LBGI, Computer Science Department, ICube, UMR 7357, University of Strasbourg, CNRS, Fédération de médecine translationnelle, 4 rue Kirschleger 67085 Strasbourg, France and Department of Life Sciences, Natural History Museum, Cromwell Road, London SW7 5BD.|LBGI, Computer Science Department, ICube, UMR 7357, University of Strasbourg, CNRS, Fédération de médecine translationnelle, 4 rue Kirschleger 67085 Strasbourg, France and Department of Life Sciences, Natural History Museum, Cromwell Road, London SW7 5BD.|LBGI, Computer Science Department, ICube, UMR 7357, University of Strasbourg, CNRS, Fédération de médecine translationnelle, 4 rue Kirschleger 67085 Strasbourg, France and Department of Life Sciences, Natural History Museum, Cromwell Road, London SW7 5BD.', 'France|France|France|France|France|France|France|France|France', 13, 'Algorithms|Computer Graphics|Databases, Factual|Humans|Molecular Sequence Annotation|Phylogeny|Proteomics|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btu642', '25273105', 'We previously developed OrthoInspector, a package incorporating an original algorithm for the detection of orthology and inparalogy relations between different species. We have added new functionalities to the package. While its original algorithm was not modified, performing similar orthology predictions, we facilitated the prediction of very large databases (thousands of proteomes), refurbished its graphical interface, added new visualization tools for comparative genomics/protein family analysis and facilitated its deployment in a network environment. Finally, we have released three online databases of precomputed orthology relationships.'),
(78748, 2015, 'bio', 'Curation, integration and visualization of bacterial virulence factors in PATRIC', 'Mao, Chunhong|Abraham, David|Wattam, Alice R|Wilson, Meredith J C|Shukla, Maulik|Yoo, Hyun Seung|Sobral, Bruno W', 'Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.', 'United States|United States|United States|United States|United States|United States|United States', 21, 'Bacteria|Bacterial Infections|Bacterial Proteins|Computer Graphics|Databases, Factual|Gene Expression Profiling|Genome, Bacterial|Genomics|Humans|Protein Interaction Mapping|Systems Integration|Virulence|Virulence Factors', 'Journal Article', '10.1093/bioinformatics/btu631', '25273106', 'Weve developed a highly curated bacterial virulence factor (VF) library in PATRIC (Pathosystems Resource Integration Center, www.patricbrc.org) to support infectious disease research. Although several VF databases are available, there is still a need to incorporate new knowledge found in published experimental evidence and integrate these data with other information known for these specific VF genes, including genomic and other omics data. This integration supports the identification of VFs, comparative studies and hypothesis generation, which facilitates the understanding of virulence and pathogenicity.'),
(78749, 2015, 'bio', 'ExportAid: database of RNA elements regulating nuclear RNA export in mammals', 'Giulietti, Matteo|Milantoni, Sara Armida|Armeni, Tatiana|Principato, Giovanni|Piva, Francesco', 'Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, Ancona 60131, Italy.|Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, Ancona 60131, Italy.|Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, Ancona 60131, Italy.|Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, Ancona 60131, Italy.|Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, Ancona 60131, Italy.', 'Italy|Italy|Italy|Italy|Italy', 10, 'Active Transport, Cell Nucleus|Animals|Binding Sites|Cell Nucleus|Databases, Nucleic Acid|Humans|Mammals|RNA|RNA, Nuclear|RNA-Binding Proteins|Regulatory Sequences, Nucleic Acid|Trans-Activators', 'Journal Article', '10.1093/bioinformatics/btu620', '25273107', 'Regulation of nuclear mRNA export or retention is carried out by RNA elements but the mechanism is not yet well understood. To understand the mRNA export process, it is important to collect all the involved RNA elements and their trans-acting factors.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78750, 2015, 'bio', 'Inference of protein kinetics by stochastic modeling and simulation of fluorescence recovery after photobleaching experiments', 'Rapsomaniki, Maria Anna|Cinquemani, Eugenio|Giakoumakis, Nickolaos Nikiforos|Kotsantis, Panagiotis|Lygeros, John|Lygerou, Zoi', 'Department of Biology, School of Medicine, University of Patras, 26505, Rio, Patras, Greece, Institut für Automatik, ETH Zürich, 8092 Zürich, Switzerland and INRIA Grenoble-Rhône-Alpes, Montbonnot, 38334 Saint-Ismier Cedex, France Department of Biology, School of Medicine, University of Patras, 26505, Rio, Patras, Greece, Institut für Automatik, ETH Zürich, 8092 Zürich, Switzerland and INRIA Grenoble-Rhône-Alpes, Montbonnot, 38334 Saint-Ismier Cedex, France.|Department of Biology, School of Medicine, University of Patras, 26505, Rio, Patras, Greece, Institut für Automatik, ETH Zürich, 8092 Zürich, Switzerland and INRIA Grenoble-Rhône-Alpes, Montbonnot, 38334 Saint-Ismier Cedex, France.|Department of Biology, School of Medicine, University of Patras, 26505, Rio, Patras, Greece, Institut für Automatik, ETH Zürich, 8092 Zürich, Switzerland and INRIA Grenoble-Rhône-Alpes, Montbonnot, 38334 Saint-Ismier Cedex, France.|Department of Biology, School of Medicine, University of Patras, 26505, Rio, Patras, Greece, Institut für Automatik, ETH Zürich, 8092 Zürich, Switzerland and INRIA Grenoble-Rhône-Alpes, Montbonnot, 38334 Saint-Ismier Cedex, France.|Department of Biology, School of Medicine, University of Patras, 26505, Rio, Patras, Greece, Institut für Automatik, ETH Zürich, 8092 Zürich, Switzerland and INRIA Grenoble-Rhône-Alpes, Montbonnot, 38334 Saint-Ismier Cedex, France.|Department of Biology, School of Medicine, University of Patras, 26505, Rio, Patras, Greece, Institut für Automatik, ETH Zürich, 8092 Zürich, Switzerland and INRIA Grenoble-Rhône-Alpes, Montbonnot, 38334 Saint-Ismier Cedex, France.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 8, 'Computer Simulation|Fluorescence|Fluorescence Recovery After Photobleaching|Humans|Kinetics|Models, Biological|Monte Carlo Method|Nuclear Proteins|Photobleaching|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/btu619', '25273108', 'Fluorescence recovery after photobleaching (FRAP) is a functional live cell imaging technique that permits the exploration of protein dynamics in living cells. To extract kinetic parameters from FRAP data, a number of analytical models have been developed. Simplifications are inherent in these models, which may lead to inexhaustive or inaccurate exploitation of the experimental data. An appealing alternative is offered by the simulation of biological processes in realistic environments at a particle level. However, inference of kinetic parameters using simulation-based models is still limited.'),
(78751, 2015, 'bio', 'KDDN: an open-source Cytoscape app for constructing differential dependency networks with significant rewiring', 'Tian, Ye|Zhang, Bai|Hoffman, Eric P|Clarke, Robert|Zhang, Zhen|Shih, Ie-Ming|Xuan, Jianhua|Herrington, David M|Wang, Yue', 'Department of Electrical & Computer Engineering, Virginia Tech, Arlington, VA 22203, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231, Research Center for Genetic Medicine, Childrens National Medical Center, Washington, DC 20010, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057 and Department of Medicine, Wake Forest University, Winston-Salem, NC 27157, USA.|Department of Electrical & Computer Engineering, Virginia Tech, Arlington, VA 22203, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231, Research Center for Genetic Medicine, Childrens National Medical Center, Washington, DC 20010, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057 and Department of Medicine, Wake Forest University, Winston-Salem, NC 27157, USA.|Department of Electrical & Computer Engineering, Virginia Tech, Arlington, VA 22203, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231, Research Center for Genetic Medicine, Childrens National Medical Center, Washington, DC 20010, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057 and Department of Medicine, Wake Forest University, Winston-Salem, NC 27157, USA.|Department of Electrical & Computer Engineering, Virginia Tech, Arlington, VA 22203, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231, Research Center for Genetic Medicine, Childrens National Medical Center, Washington, DC 20010, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057 and Department of Medicine, Wake Forest University, Winston-Salem, NC 27157, USA.|Department of Electrical & Computer Engineering, Virginia Tech, Arlington, VA 22203, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231, Research Center for Genetic Medicine, Childrens National Medical Center, Washington, DC 20010, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057 and Department of Medicine, Wake Forest University, Winston-Salem, NC 27157, USA.|Department of Electrical & Computer Engineering, Virginia Tech, Arlington, VA 22203, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231, Research Center for Genetic Medicine, Childrens National Medical Center, Washington, DC 20010, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057 and Department of Medicine, Wake Forest University, Winston-Salem, NC 27157, USA.|Department of Electrical & Computer Engineering, Virginia Tech, Arlington, VA 22203, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231, Research Center for Genetic Medicine, Childrens National Medical Center, Washington, DC 20010, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057 and Department of Medicine, Wake Forest University, Winston-Salem, NC 27157, USA.|Department of Electrical & Computer Engineering, Virginia Tech, Arlington, VA 22203, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231, Research Center for Genetic Medicine, Childrens National Medical Center, Washington, DC 20010, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057 and Department of Medicine, Wake Forest University, Winston-Salem, NC 27157, USA.|Department of Electrical & Computer Engineering, Virginia Tech, Arlington, VA 22203, Departments of Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21231, Research Center for Genetic Medicine, Childrens National Medical Center, Washington, DC 20010, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057 and Department of Medicine, Wake Forest University, Winston-Salem, NC 27157, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 10, 'Algorithms|Cell Cycle|Gene Regulatory Networks|Genes, cdc|Models, Biological|Molecular Sequence Annotation|Oxidative Stress|Saccharomyces cerevisiae|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btu632', '25273109', 'We have developed an integrated molecular network learning method, within a well-grounded mathematical framework, to construct differential dependency networks with significant rewiring. This knowledge-fused differential dependency networks (KDDN) method, implemented as a Java Cytoscape app, can be used to optimally integrate prior biological knowledge with measured data to simultaneously construct both common and differential networks, to quantitatively assign model parameters and significant rewiring p-values and to provide user-friendly graphical results. The KDDN algorithm is computationally efficient and provides users with parallel computing capability using ubiquitous multi-core machines. We demonstrate the performance of KDDN on various simulations and real gene expression datasets, and further compare the results with those obtained by the most relevant peer methods. The acquired biologically plausible results provide new insights into network rewiring as a mechanistic principle and illustrate KDDNs ability to detect them efficiently and correctly. Although the principal application here involves microarray gene expressions, our methodology can be readily applied to other types of quantitative molecular profiling data.'),
(78752, 2015, 'bio', 'PROPER: comprehensive power evaluation for differential expression using RNA-seq', 'Wu, Hao|Wang, Chi|Wu, Zhijin', 'Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, Department of Biostatistics and Markey Cancer Center, University of Kentucky, Lexington, KY 40536 and Department of Biostatistics, Brown University, Providence, RI 02806, USA.|Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, Department of Biostatistics and Markey Cancer Center, University of Kentucky, Lexington, KY 40536 and Department of Biostatistics, Brown University, Providence, RI 02806, USA.|Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, Department of Biostatistics and Markey Cancer Center, University of Kentucky, Lexington, KY 40536 and Department of Biostatistics, Brown University, Providence, RI 02806, USA.', 'United States|United States|United States', 32, 'Animals|Computational Biology|Datasets as Topic|Gene Expression Regulation|High-Throughput Nucleotide Sequencing|Humans|Lymphocytes|Mice|Mice, Inbred C57BL|Mice, Inbred DBA|RNA|Sample Size|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu640', '25273110', 'RNA-seq has become a routine technique in differential expression (DE) identification. Scientists face a number of experimental design decisions, including the sample size. The power for detecting differential expression is affected by several factors, including the fraction of DE genes, distribution of the magnitude of DE, distribution of gene expression level, sequencing coverage and the choice of type I error control. The complexity and flexibility of RNA-seq experiments, the high-throughput nature of transcriptome-wide expression measurements and the unique characteristics of RNA-seq data make the power assessment particularly challenging.'),
(78753, 2015, 'bio', 'PFP/ESG: automated protein function prediction servers enhanced with Gene Ontology visualization tool', 'Khan, Ishita K|Wei, Qing|Chitale, Meghana|Kihara, Daisuke', 'Department of Computer Science and Department of Biological Science, Purdue University, West Lafayette, IN 47907, USA.|Department of Computer Science and Department of Biological Science, Purdue University, West Lafayette, IN 47907, USA.|Department of Computer Science and Department of Biological Science, Purdue University, West Lafayette, IN 47907, USA.|Department of Computer Science and Department of Biological Science, Purdue University, West Lafayette, IN 47907, USA Department of Computer Science and Department of Biological Science, Purdue University, West Lafayette, IN 47907, USA.', 'United States|United States|United States|United States', 13, 'Algorithms|Computational Biology|Computer Graphics|Databases, Protein|Gene Ontology|Humans|Molecular Sequence Annotation|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btu646', '25273111', 'Protein function prediction (PFP) is an automated function prediction method that predicts Gene Ontology (GO) annotations for a protein sequence using distantly related sequences and contextual associations of GO terms. Extended similarity group (ESG) is another GO prediction algorithm that makes predictions based on iterative sequence database searches. Here, we provide interactive web servers for the PFP and ESG algorithms that are equipped with an effective visualization of the GO predictions in a hierarchical topology.'),
(78754, 2015, 'bio', 'MulRF: a software package for phylogenetic analysis using multi-copy gene trees', 'Chaudhary, Ruchi|Fernández-Baca, David|Burleigh, John Gordon', 'Department of Biology, University of Florida, Gainesville, FL 32611 and Department of Computer Science, Iowa State University, Ames, IA 50011, USA.|Department of Biology, University of Florida, Gainesville, FL 32611 and Department of Computer Science, Iowa State University, Ames, IA 50011, USA.|Department of Biology, University of Florida, Gainesville, FL 32611 and Department of Computer Science, Iowa State University, Ames, IA 50011, USA.', 'United States|United States|United States', 17, 'Algorithms|Computer Simulation|Evolution, Molecular|Gene Dosage|Humans|Phylogeny|Programming Languages|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu648', '25273112', 'MulRF is a platform-independent software package for phylogenetic analysis using multi-copy gene trees. It seeks the species tree that minimizes the Robinson-Foulds (RF) distance to the input trees using a generalization of the RF distance to multi-labeled trees. The underlying generic tree distance measure and fast running time make MulRF useful for inferring phylogenies from large collections of gene trees, in which multiple evolutionary processes as well as phylogenetic error may contribute to gene tree discord. MulRF implements several features for customizing the species tree search and assessing the results, and it provides a user-friendly graphical user interface (GUI) with tree visualization. The species tree search is implemented in C++ and the GUI in Java Swing.'),
(78755, 2014, 'bio', 'Proceedings of the 22nd Annual Meeting of Intelligent Systems for Molecular Biology (ISMB), July 11-15, 2014, Boston, MA', '-', '-', '-', 17, 'Computational Biology', 'Congress', '10.1093/bioinformatics/btu648', '25275154', '-'),
(78756, 2015, 'bio', 'CompMap: a reference-based compression program to speed up read mapping to related reference sequences', 'Zhu, Zexuan|Li, Linsen|Zhang, Yongpeng|Yang, Yanli|Yang, Xiao', 'College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China and Infectious Disease Initiative, The Broad Institute, Cambridge, MA 02142, USA.|College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China and Infectious Disease Initiative, The Broad Institute, Cambridge, MA 02142, USA.|College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China and Infectious Disease Initiative, The Broad Institute, Cambridge, MA 02142, USA.|College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China and Infectious Disease Initiative, The Broad Institute, Cambridge, MA 02142, USA.|College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China and Infectious Disease Initiative, The Broad Institute, Cambridge, MA 02142, USA.', 'China|China|China|China|China', 9, 'Computational Biology|Data Compression|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Reference Values|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/btu656', '25282641', 'Exhaustive mapping of next-generation sequencing data to a set of relevant reference sequences becomes an important task in pathogen discovery and metagenomic classification. However, the runtime and memory usage increase as the number of reference sequences and the repeat content among these sequences increase. In many applications, read mapping time dominates the entire application. We developed CompMap, a reference-based compression program, to speed up this process. CompMap enables the generation of a non-redundant representative sequence for the input sequences. We have demonstrated that reads can be mapped to this representative sequence with a much reduced time and memory usage, and the mapping to the original reference sequences can be recovered with high accuracy.'),
(78757, 2015, 'bio', 'LocalAli: an evolutionary-based local alignment approach to identify functionally conserved modules in multiple networks', 'Hu, Jialu|Reinert, Knut', 'Department of Mathematics and Computer Science, Freie Universität Berlin, Takustrasse 9, 14195 Berlin, Germany.|Department of Mathematics and Computer Science, Freie Universität Berlin, Takustrasse 9, 14195 Berlin, Germany.', 'Germany|Germany', 0, 'Algorithms|Biological Evolution|Computational Biology|Databases, Protein|Gene Regulatory Networks|Humans|Phylogeny|Protein Interaction Mapping|Proteins|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btu652', '25282642', 'Sequences and protein interaction data are of significance to understand the underlying molecular mechanism of organisms. Local network alignment is one of key systematic ways for predicting protein functions, identifying functional modules and understanding the phylogeny from these data. Most of currently existing tools, however, encounter their limitations, which are mainly concerned with scoring scheme, speed and scalability. Therefore, there are growing demands for sophisticated network evolution models and efficient local alignment algorithms.'),
(78758, 2015, 'bio', 'Using the plurality of codon positions to identify deleterious variants in human exomes', 'Subramanian, Sankar', 'Environmental Futures Research Institute, Griffith University, 170 Kessels Road, Nathan Qld 4111, Australia.', 'Australia', 2, 'Alternative Splicing|Codon|Exome|Genetic Variation|Genome, Human|Humans|Introns|Proteins', 'Journal Article', '10.1093/bioinformatics/btu653', '25282643', 'A codon position could perform different or multiple roles in alternative transcripts of a gene. For instance, a non-synonymous position in one transcript could be a synonymous site in another. Alternatively, a position could remain as non-synonymous in multiple transcripts. Here we examined the impact of codon position plurality on the frequency of deleterious single-nucleotide variations (SNVs) using data from 6500 human exomes.'),
(78759, 2015, 'bio', 'SIST: stress-induced structural transitions in superhelical DNA', 'Zhabinskaya, Dina|Madden, Sally|Benham, Craig J', 'UC Davis Genome Center and Department of Mathematics, University of California, Davis, CA 95616, USA.|UC Davis Genome Center and Department of Mathematics, University of California, Davis, CA 95616, USA.|UC Davis Genome Center and Department of Mathematics, University of California, Davis, CA 95616, USA.', 'United States|United States|United States', 12, 'Algorithms|DNA, Superhelical|Humans|Models, Statistical|Nucleic Acid Conformation|Oxidative Stress|Software|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btu657', '25282644', 'Supercoiling imposes stress on a DNA molecule that can drive susceptible sequences into alternative non-B form structures. This phenomenon occurs frequently in vivo and has been implicated in biological processes, such as replication, transcription, recombination and translocation. SIST is a software package that analyzes sequence-dependent structural transitions in kilobase length superhelical DNA molecules. The numerical algorithms in SIST are based on a statistical mechanical model that calculates the equilibrium probability of transition for each base pair in the domain. They are extensions of the original stress-induced duplex destabilization (SIDD) method, which analyzes stress-driven DNA strand separation. SIST also includes algorithms to analyze B-Z transitions and cruciform extrusion. The SIST pipeline has an option to use the DZCBtrans algorithm, which analyzes the competition among these three transitions within a superhelical domain.'),
(78760, 2015, 'bio', 'An alternative approach to multiple testing for methylation QTL mapping reduces the proportion of falsely identified CpGs', 'Luijk, René|Goeman, Jelle J|Slagboom, Eline P|Heijmans, Bastiaan T|van Zwet, Erik W', 'Department of Molecular Epidemiology, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, 2333 ZC Leiden and Biostatistics, Department for Health Evidence, Radboud University Nijmegen Medical Center, 6500 HB Nijmegen, The Netherlands Department of Molecular Epidemiology, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, 2333 ZC Leiden and Biostatistics, Department for Health Evidence, Radboud University Nijmegen Medical Center, 6500 HB Nijmegen, The Netherlands.|Department of Molecular Epidemiology, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, 2333 ZC Leiden and Biostatistics, Department for Health Evidence, Radboud University Nijmegen Medical Center, 6500 HB Nijmegen, The Netherlands.|Department of Molecular Epidemiology, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, 2333 ZC Leiden and Biostatistics, Department for Health Evidence, Radboud University Nijmegen Medical Center, 6500 HB Nijmegen, The Netherlands.|Department of Molecular Epidemiology, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, 2333 ZC Leiden and Biostatistics, Department for Health Evidence, Radboud University Nijmegen Medical Center, 6500 HB Nijmegen, The Netherlands.|Department of Molecular Epidemiology, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, 2333 ZC Leiden and Biostatistics, Department for Health Evidence, Radboud University Nijmegen Medical Center, 6500 HB Nijmegen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'CpG Islands|DNA Methylation|False Positive Reactions|Genome, Human|Humans|Polymorphism, Single Nucleotide|Quantitative Trait Loci', 'Journal Article', '10.1093/bioinformatics/btu654', '25282645', 'An increasing number of studies investigates the influence of local genetic variation on DNA methylation levels, so-called in cis methylation quantitative trait loci (meQTLs). A common multiple testing approach in genome-wide cis meQTL studies limits the false discovery rate (FDR) among all CpG-SNP pairs to 0.05 and reports on CpGs from the significant CpG-SNP pairs. However, a statistical test for each CpG is not performed, potentially increasing the proportion of CpGs falsely reported on. Here, we presented an alternative approach that properly control for multiple testing at the CpG level.'),
(78761, 2015, 'bio', 'VCF2Networks: applying genotype networks to single-nucleotide variants data', 'DallOlio, Giovanni Marco|Vahdati, Ali R|Bertranpetit, Jaume|Wagner, Andreas|Laayouni, Hafid', 'Department of Experimental and Health Sciences, Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Catalonia, Spain, Institute of Evolutionary Biology and Environmental Studies/Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland, SIB, CIG Quartier Sorge, bâtiment Génopode 1015 Lausanne, Switzerland, The Santa Fe Institute, 1399 Hyde Parke Road, 87501 Santa Fe, New Mexico, USA and Departament de Genetica i de Microbiologia, Grup de Biologia Evolutiva (GBE), Universitat Autonoma de Barcelona, 08913 Bellaterra, Barcelona.|Department of Experimental and Health Sciences, Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Catalonia, Spain, Institute of Evolutionary Biology and Environmental Studies/Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland, SIB, CIG Quartier Sorge, bâtiment Génopode 1015 Lausanne, Switzerland, The Santa Fe Institute, 1399 Hyde Parke Road, 87501 Santa Fe, New Mexico, USA and Departament de Genetica i de Microbiologia, Grup de Biologia Evolutiva (GBE), Universitat Autonoma de Barcelona, 08913 Bellaterra, Barcelona.|Department of Experimental and Health Sciences, Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Catalonia, Spain, Institute of Evolutionary Biology and Environmental Studies/Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland, SIB, CIG Quartier Sorge, bâtiment Génopode 1015 Lausanne, Switzerland, The Santa Fe Institute, 1399 Hyde Parke Road, 87501 Santa Fe, New Mexico, USA and Departament de Genetica i de Microbiologia, Grup de Biologia Evolutiva (GBE), Universitat Autonoma de Barcelona, 08913 Bellaterra, Barcelona.|Department of Experimental and Health Sciences, Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Catalonia, Spain, Institute of Evolutionary Biology and Environmental Studies/Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland, SIB, CIG Quartier Sorge, bâtiment Génopode 1015 Lausanne, Switzerland, The Santa Fe Institute, 1399 Hyde Parke Road, 87501 Santa Fe, New Mexico, USA and Departament de Genetica i de Microbiologia, Grup de Biologia Evolutiva (GBE), Universitat Autonoma de Barcelona, 08913 Bellaterra, Barcelona Department of Experimental and Health Sciences, Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Catalonia, Spain, Institute of Evolutionary Biology and Environmental Studies/Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland, SIB, CIG Quartier Sorge, bâtiment Génopode 1015 Lausanne, Switzerland, The Santa Fe Institute, 1399 Hyde Parke Road, 87501 Santa Fe, New Mexico, USA and Departament de Genetica i de Microbiologia, Grup de Biologia Evolutiva (GBE), Universitat Autonoma de Barcelona, 08913 Bellaterra, Barcelona Department of Experimental and Health Sciences, Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Catalonia, Spain, Institute of Evolutionary Biology and Environmental Studies/Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland, SIB, CIG Quartier Sorge, bâtiment Génopode 1015 Lausanne, Switzerland, The Santa Fe Institute, 1399 Hyde Parke Road, 87501 Santa Fe, New Mexico, USA and Departament de Genetica i de Microbiologia, Grup de Biologia Evolutiva (GBE), Universitat Autonoma de Barcelona, 08913 Bellaterra, Barcelona.|Department of Experimental and Health Sciences, Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Catalonia, Spain, Institute of Evolutionary Biology and Environmental Studies/Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland, SIB, CIG Quartier Sorge, bâtiment Génopode 1015 Lausanne, Switzerland, The Santa Fe Institute, 1399 Hyde Parke Road, 87501 Santa Fe, New Mexico, USA and Departament de Genetica i de Microbiologia, Grup de Biologia Evolutiva (GBE), Universitat Autonoma de Barcelona, 08913 Bellaterra, Barcelona Department of Experimental and Health Sciences, Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Catalonia, Spain, Institute of Evolutionary Biology and Environmental Studies/Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland, SIB, CIG Quartier Sorge, bâtiment Génopode 1015 Lausanne, Switzerland, The Santa Fe Institute, 1399 Hyde Parke Road, 87501 Santa Fe, New Mexico, USA and Departament de Genetica i de Microbiologia, Grup de Biologia Evolutiva (GBE), Universitat Autonoma de Barcelona, 08913 Bellaterra, Barcelona.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Biological Evolution|Gene Regulatory Networks|Genetics, Population|Genome, Human|Genotype|Humans|Phenotype|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btu650', '25282646', 'A wealth of large-scale genome sequencing projects opens the doors to new approaches to study the relationship between genotype and phenotype. One such opportunity is the possibility to apply genotype networks analysis to population genetics data. Genotype networks are a representation of the set of genotypes associated with a single phenotype, and they allow one to estimate properties such as the robustness of the phenotype to mutations, and the ability of its associated genotypes to evolve new adaptations. So far, though, genotype networks analysis has rarely been applied to population genetics data. To help fill this gap, here we present VCF2Networks, a tool to determine and study genotype network structure from single-nucleotide variant data.'),
(78762, 2015, 'bio', 'Computing autocatalytic sets to unravel inconsistencies in metabolic network reconstructions', 'Schmidt, Ralf|Waschina, Silvio|Boettger-Schmidt, Daniela|Kost, Christian|Kaleta, Christoph', 'Research Group Theoretical Systems Biology, Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, 07743 Jena, Department of Bioorganic Chemistry, Experimental Ecology and Evolution Research Group, Max Planck Institute for Chemical Ecology, 07745 Jena, Department of Biomolecular Chemistry, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knxc3xb6ll Institute, 07745 Jena and Department of Computational Biology, Institute for Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense M, Denmark.|Research Group Theoretical Systems Biology, Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, 07743 Jena, Department of Bioorganic Chemistry, Experimental Ecology and Evolution Research Group, Max Planck Institute for Chemical Ecology, 07745 Jena, Department of Biomolecular Chemistry, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knxc3xb6ll Institute, 07745 Jena and Department of Computational Biology, Institute for Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense M, Denmark Research Group Theoretical Systems Biology, Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, 07743 Jena, Department of Bioorganic Chemistry, Experimental Ecology and Evolution Research Group, Max Planck Institute for Chemical Ecology, 07745 Jena, Department of Biomolecular Chemistry, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knxc3xb6ll Institute, 07745 Jena and Department of Computational Biology, Institute for Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense M, Denmark.|Research Group Theoretical Systems Biology, Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, 07743 Jena, Department of Bioorganic Chemistry, Experimental Ecology and Evolution Research Group, Max Planck Institute for Chemical Ecology, 07745 Jena, Department of Biomolecular Chemistry, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knxc3xb6ll Institute, 07745 Jena and Department of Computational Biology, Institute for Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense M, Denmark.|Research Group Theoretical Systems Biology, Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, 07743 Jena, Department of Bioorganic Chemistry, Experimental Ecology and Evolution Research Group, Max Planck Institute for Chemical Ecology, 07745 Jena, Department of Biomolecular Chemistry, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knxc3xb6ll Institute, 07745 Jena and Department of Computational Biology, Institute for Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense M, Denmark.|Research Group Theoretical Systems Biology, Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, 07743 Jena, Department of Bioorganic Chemistry, Experimental Ecology and Evolution Research Group, Max Planck Institute for Chemical Ecology, 07745 Jena, Department of Biomolecular Chemistry, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knxc3xb6ll Institute, 07745 Jena and Department of Computational Biology, Institute for Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense M, Denmark Research Group Theoretical Systems Biology, Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, 07743 Jena, Department of Bioorganic Chemistry, Experimental Ecology and Evolution Research Group, Max Planck Institute for Chemical Ecology, 07745 Jena, Department of Biomolecular Chemistry, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knxc3xb6ll Institute, 07745 Jena and Department of Computational Biology, Institute for Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense M, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark', 0, 'Bacterial Proteins|Catalytic Domain|Computational Biology|Genome, Bacterial|Metabolic Networks and Pathways|Models, Biological|Phenotype|Software', 'Journal Article', '10.1093/bioinformatics/btu658', '25286919', 'Genome-scale metabolic network reconstructions have been established as a powerful tool for the prediction of cellular phenotypes and metabolic capabilities of organisms. In recent years, the number of network reconstructions has been constantly increasing, mostly because of the availability of novel (semi-)automated procedures, which enabled the reconstruction of metabolic models based on individual genomes and their annotation. The resulting models are widely used in numerous applications. However, the accuracy and predictive power of network reconstructions are commonly limited by inherent inconsistencies and gaps.'),
(78763, 2015, 'bio', 'Deviance residuals-based sparse PLS and sparse kernel PLS regression for censored data', 'Bastien, Philippe|Bertrand, Frédéric|Meyer, Nicolas|Maumy-Bertrand, Myriam', 'LOréal Recherche & Innovation, 93601 Aulnay-sous-Bois, IRMA, CNRS UMR 7501, Labex IRMIA, Université de Strasbourg, 67084 Strasbourg Cedex, INSERM EA3430, Laboratoire de Biostatistique, Faculté de Médecine de Strasbourg, Labex IRMIA, Université de Strasbourg, 67085 Strasbourg Cedex, France.|LOréal Recherche & Innovation, 93601 Aulnay-sous-Bois, IRMA, CNRS UMR 7501, Labex IRMIA, Université de Strasbourg, 67084 Strasbourg Cedex, INSERM EA3430, Laboratoire de Biostatistique, Faculté de Médecine de Strasbourg, Labex IRMIA, Université de Strasbourg, 67085 Strasbourg Cedex, France.|LOréal Recherche & Innovation, 93601 Aulnay-sous-Bois, IRMA, CNRS UMR 7501, Labex IRMIA, Université de Strasbourg, 67084 Strasbourg Cedex, INSERM EA3430, Laboratoire de Biostatistique, Faculté de Médecine de Strasbourg, Labex IRMIA, Université de Strasbourg, 67085 Strasbourg Cedex, France.|LOréal Recherche & Innovation, 93601 Aulnay-sous-Bois, IRMA, CNRS UMR 7501, Labex IRMIA, Université de Strasbourg, 67084 Strasbourg Cedex, INSERM EA3430, Laboratoire de Biostatistique, Faculté de Médecine de Strasbourg, Labex IRMIA, Université de Strasbourg, 67085 Strasbourg Cedex, France.', 'France|France|France|France', 0, 'Algorithms|Datasets as Topic|Gene Expression Profiling|Humans|Least-Squares Analysis|Proportional Hazards Models|Regression Analysis|Sample Size|Software|Survival Rate', 'Journal Article', '10.1093/bioinformatics/btu660', '25286920', 'A vast literature from the past decade is devoted to relating gene profiles and subject survival or time to cancer recurrence. Biomarker discovery from high-dimensional data, such as transcriptomic or single nucleotide polymorphism profiles, is a major challenge in the search for more precise diagnoses. The proportional hazard regression model suggested by Cox (1972), to study the relationship between the time to event and a set of covariates in the presence of censoring is the most commonly used model for the analysis of survival data. However, like multivariate regression, it supposes that more observations than variables, complete data, and not strongly correlated variables are available. In practice, when dealing with high-dimensional data, these constraints are crippling. Collinearity gives rise to issues of over-fitting and model misidentification. Variable selection can improve the estimation accuracy by effectively identifying the subset of relevant predictors and enhance the model interpretability with parsimonious representation. To deal with both collinearity and variable selection issues, many methods based on least absolute shrinkage and selection operator penalized Cox proportional hazards have been proposed since the reference paper of Tibshirani. Regularization could also be performed using dimension reduction as is the case with partial least squares (PLS) regression. We propose two original algorithms named sPLSDR and its non-linear kernel counterpart DKsPLSDR, by using sparse PLS regression (sPLS) based on deviance residuals. We compared their predicting performance with state-of-the-art algorithms on both simulated and real reference benchmark datasets.'),
(78764, 2014, 'bio', 'Chimera: a Bioconductor package for secondary analysis of fusion products', 'Beccuti, Marco|Carrara, Matteo|Cordero, Francesca|Lazzarato, Fulvio|Donatelli, Susanna|Nadalin, Francesca|Policriti, Alberto|Calogero, Raffaele A', 'Department of Computer Sciences, University of Torino, C.so Svizzera 185, 10149 Torino, Department of Molecular Biotechnology and Health Sciences, University of Torino, Via Nizza 52, 10126 Torino, Department of Translational Medicine, University of Piemonte Orientale Avogadro, Novara, Unit of Cancer Epidemiology, Department of Medical Sciences, University of Turin, Turin, Department of Computational and Quantitative Biology, UMR 7238 CNRS - Université Pierre et Marie Curie, Paris, France and Department of Mathematics and Computer Science, University of Udine, Italy.|Department of Computer Sciences, University of Torino, C.so Svizzera 185, 10149 Torino, Department of Molecular Biotechnology and Health Sciences, University of Torino, Via Nizza 52, 10126 Torino, Department of Translational Medicine, University of Piemonte Orientale Avogadro, Novara, Unit of Cancer Epidemiology, Department of Medical Sciences, University of Turin, Turin, Department of Computational and Quantitative Biology, UMR 7238 CNRS - Université Pierre et Marie Curie, Paris, France and Department of Mathematics and Computer Science, University of Udine, Italy.|Department of Computer Sciences, University of Torino, C.so Svizzera 185, 10149 Torino, Department of Molecular Biotechnology and Health Sciences, University of Torino, Via Nizza 52, 10126 Torino, Department of Translational Medicine, University of Piemonte Orientale Avogadro, Novara, Unit of Cancer Epidemiology, Department of Medical Sciences, University of Turin, Turin, Department of Computational and Quantitative Biology, UMR 7238 CNRS - Université Pierre et Marie Curie, Paris, France and Department of Mathematics and Computer Science, University of Udine, Italy.|Department of Computer Sciences, University of Torino, C.so Svizzera 185, 10149 Torino, Department of Molecular Biotechnology and Health Sciences, University of Torino, Via Nizza 52, 10126 Torino, Department of Translational Medicine, University of Piemonte Orientale Avogadro, Novara, Unit of Cancer Epidemiology, Department of Medical Sciences, University of Turin, Turin, Department of Computational and Quantitative Biology, UMR 7238 CNRS - Université Pierre et Marie Curie, Paris, France and Department of Mathematics and Computer Science, University of Udine, Italy Department of Computer Sciences, University of Torino, C.so Svizzera 185, 10149 Torino, Department of Molecular Biotechnology and Health Sciences, University of Torino, Via Nizza 52, 10126 Torino, Department of Translational Medicine, University of Piemonte Orientale Avogadro, Novara, Unit of Cancer Epidemiology, Department of Medical Sciences, University of Turin, Turin, Department of Computational and Quantitative Biology, UMR 7238 CNRS - Université Pierre et Marie Curie, Paris, France and Department of Mathematics and Computer Science, University of Udine, Italy.|Department of Computer Sciences, University of Torino, C.so Svizzera 185, 10149 Torino, Department of Molecular Biotechnology and Health Sciences, University of Torino, Via Nizza 52, 10126 Torino, Department of Translational Medicine, University of Piemonte Orientale Avogadro, Novara, Unit of Cancer Epidemiology, Department of Medical Sciences, University of Turin, Turin, Department of Computational and Quantitative Biology, UMR 7238 CNRS - Université Pierre et Marie Curie, Paris, France and Department of Mathematics and Computer Science, University of Udine, Italy.|Department of Computer Sciences, University of Torino, C.so Svizzera 185, 10149 Torino, Department of Molecular Biotechnology and Health Sciences, University of Torino, Via Nizza 52, 10126 Torino, Department of Translational Medicine, University of Piemonte Orientale Avogadro, Novara, Unit of Cancer Epidemiology, Department of Medical Sciences, University of Turin, Turin, Department of Computational and Quantitative Biology, UMR 7238 CNRS - Université Pierre et Marie Curie, Paris, France and Department of Mathematics and Computer Science, University of Udine, Italy.|Department of Computer Sciences, University of Torino, C.so Svizzera 185, 10149 Torino, Department of Molecular Biotechnology and Health Sciences, University of Torino, Via Nizza 52, 10126 Torino, Department of Translational Medicine, University of Piemonte Orientale Avogadro, Novara, Unit of Cancer Epidemiology, Department of Medical Sciences, University of Turin, Turin, Department of Computational and Quantitative Biology, UMR 7238 CNRS - Université Pierre et Marie Curie, Paris, France and Department of Mathematics and Computer Science, University of Udine, Italy.|Department of Computer Sciences, University of Torino, C.so Svizzera 185, 10149 Torino, Department of Molecular Biotechnology and Health Sciences, University of Torino, Via Nizza 52, 10126 Torino, Department of Translational Medicine, University of Piemonte Orientale Avogadro, Novara, Unit of Cancer Epidemiology, Department of Medical Sciences, University of Turin, Turin, Department of Computational and Quantitative Biology, UMR 7238 CNRS - Université Pierre et Marie Curie, Paris, France and Department of Mathematics and Computer Science, University of Udine, Italy.', 'France|France|France|France|France|France|France|France', 0, 'Animals|Gene Fusion|Molecular Sequence Annotation|Software', 'Journal Article', '10.1093/bioinformatics/btu662', '25286921', 'Chimera is a Bioconductor package that organizes, annotates, analyses and validates fusions reported by different fusion detection tools, current implementation can deal with output from bellerophontes, chimeraScan, deFuse, fusionCatcher, FusionFinder, FusionHunter, FusionMap, mapSplice, Rsubread, tophat-fusion and STAR. The core of Chimera is a fusion data structure that can store fusion events detected with any of the aforementioned tools. Fusions are then easily manipulated with standard R functions or through the set of functionalities specifically developed in Chimera with the aim of supporting the user in managing fusions and discriminating false-positive results.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78765, 2015, 'bio', 'A crowd-sourcing approach for the construction of species-specific cell signaling networks', 'Bilal, Erhan|Sakellaropoulos, Theodore|Melas, Ioannis N|Messinis, Dimitris E|Belcastro, Vincenzo|Rhrissorrakrai, Kahn|Meyer, Pablo|Norel, Raquel|Iskandar, Anita|Blaese, Elise|Rice, John J|Peitsch, Manuel C|Hoeng, Julia|Stolovitzky, Gustavo|Alexopoulos, Leonidas G|Poussin, Carine|Challenge Participants', 'IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.|IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.|IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.|IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.|IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.|IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.|IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.|IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.|IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.|IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.|IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.|IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.|IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.|IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.|IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.|IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.|IBM Research, Computational Biology Center, Yorktown Heights, NY 10598, USA, ProtATonce Ltd, Scientific Park Lefkippos, Patriarchou Grigoriou & Neapoleos 15343 Ag. Paraskevi, Attiki, Greece, National Technical University of Athens, Heroon Polytechniou 9, Zografou, 15780, Greece and Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Swit', 0, 'Algorithms|Animals|Bronchi|Cell Communication|Cells, Cultured|Crowdsourcing|Cytokines|Databases, Factual|Epithelial Cells|Gene Expression Profiling|Gene Expression Regulation|Gene Regulatory Networks|Humans|Models, Animal|Oligonucleotide Array Sequence Analysis|Phosphoproteins|Phosphorylation|Rats|Signal Transduction|Software|Species Specificity|Systems Biology', 'Comparative Study', '10.1093/bioinformatics/btu659', '25294919', 'Animal models are important tools in drug discovery and for understanding human biology in general. However, many drugs that initially show promising results in rodents fail in later stages of clinical trials. Understanding the commonalities and differences between human and rat cell signaling networks can lead to better experimental designs, improved allocation of resources and ultimately better drugs.'),
(78766, 2015, 'bio', 'DupliPHY-Web: a web server for DupliPHY and DupliPHY-ML', 'Ames, Ryan M|Lovell, Simon C', 'Faculty of Life Sciences, University of Manchester, Oxford Road, Manchester M13 9PL, UK.|Faculty of Life Sciences, University of Manchester, Oxford Road, Manchester M13 9PL, UK.', 'United Kingdom|United Kingdom', 0, 'Computational Biology|Evolution, Molecular|Gene Duplication|Humans|Internet|Likelihood Functions|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btu645', '25294920', 'Gene duplication and loss are important processes in the evolution of gene families. Moreover, growth of families by duplication and retention is an important mechanism by which organisms gain new functions. Therefore the ability to infer the evolutionary histories of families is an important step in understanding the evolution of function. We have recently developed DupliPHY, a software tool to infer gene family histories using parsimony and maximum likelihood. Here, we present DupliPHY-Web a web server for DupliPHY that implements additional maximum likelihood functionality and provides users an intuitive interface to run DupliPHY.'),
(78767, 2015, 'bio', 'FungiFun2: a comprehensive online resource for systematic analysis of gene lists from fungal species', 'Priebe, Steffen|Kreisel, Christian|Horn, Fabian|Guthke, Reinhard|Linde, Jörg', 'Research Group Systems Biology/Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology - Hans-Knöll-Institute, Beutenbergstraße 11a, 07745 Jena, Germany.|Research Group Systems Biology/Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology - Hans-Knöll-Institute, Beutenbergstraße 11a, 07745 Jena, Germany.|Research Group Systems Biology/Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology - Hans-Knöll-Institute, Beutenbergstraße 11a, 07745 Jena, Germany.|Research Group Systems Biology/Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology - Hans-Knöll-Institute, Beutenbergstraße 11a, 07745 Jena, Germany.|Research Group Systems Biology/Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology - Hans-Knöll-Institute, Beutenbergstraße 11a, 07745 Jena, Germany.', 'Germany|Germany|Germany|Germany|Germany', 88, 'Databases, Factual|Genes, Fungal|Internet|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btu627', '25294921', 'Systematically extracting biological meaning from omics data is a major challenge in systems biology. Enrichment analysis is often used to identify characteristic patterns in candidate lists. FungiFun is a user-friendly Web tool for functional enrichment analysis of fungal genes and proteins. The novel tool FungiFun2 uses a completely revised data management system and thus allows enrichment analysis for 298 currently available fungal strains published in standard databases. FungiFun2 offers a modern Web interface and creates interactive tables, charts and figures, which users can directly manipulate to their needs.'),
(78768, 2015, 'bio', 'Log-odds sequence logos', 'Yu, Yi-Kuo|Capra, John A|Stojmirovixc4x87, Aleksandar|Landsman, David|Altschul, Stephen F', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, Center for Human Genetics Research and Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, Center for Human Genetics Research and Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, Center for Human Genetics Research and Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, Center for Human Genetics Research and Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, Center for Human Genetics Research and Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, Center for Human Genetics Research and Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA.', 'United States|United States|United States|United States|United States', 6, 'Amino Acid Sequence|Bayes Theorem|Humans|Molecular Sequence Annotation|Molecular Sequence Data|Position-Specific Scoring Matrices|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1093/bioinformatics/btu634', '25294922', 'DNA and protein patterns are usefully represented by sequence logos. However, the methods for logo generation in common use lack a proper statistical basis, and are non-optimal for recognizing functionally relevant alignment columns.'),
(78769, 2015, 'bio', 'Visual workflows for 13C-metabolic flux analysis', 'Nöh, Katharina|Droste, Peter|Wiechert, Wolfgang', 'Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany.|Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany.|Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany.', 'Germany|Germany|Germany', 0, 'Carbon Isotopes|Computer Graphics|Corynebacterium glutamicum|Humans|Metabolic Flux Analysis|Software|Workflow', 'Journal Article', '10.1093/bioinformatics/btu585', '25297067', 'The precise quantification of intracellular metabolic flow rates is of fundamental importance in bio(techno)logy and medical research. The gold standard in the field is metabolic flux analysis (MFA) with 13C-labeling experiments. 13C-MFA workflows orchestrate several, mainly human-in-the-loop, software applications, integrating them with plenty of heterogeneous information. In practice, this had posed a major practical barrier for evaluating, interpreting and understanding isotopic data from carbon labeling experiments.'),
(78770, 2015, 'bio', 'Genome measures used for quality control are dependent on gene function and ancestry', 'Wang, Jing|Raskin, Leon|Samuels, David C|Shyr, Yu|Guo, Yan', 'Center for Quantitative Sciences and Department of Medicine and Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37212, USA.|Center for Quantitative Sciences and Department of Medicine and Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37212, USA.|Center for Quantitative Sciences and Department of Medicine and Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37212, USA.|Center for Quantitative Sciences and Department of Medicine and Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37212, USA.|Center for Quantitative Sciences and Department of Medicine and Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37212, USA.', 'United States|United States|United States|United States|United States', 43, 'Evolution, Molecular|Genome, Human|Genome-Wide Association Study|Genotype|High-Throughput Nucleotide Sequencing|Humans|Phenotype|Polymorphism, Single Nucleotide|Quality Control', 'Journal Article', '10.1093/bioinformatics/btu668', '25297068', 'The transition/transversion (Ti/Tv) ratio and heterozygous/nonreference-homozygous (het/nonref-hom) ratio have been commonly computed in genetic studies as a quality control (QC) measurement. Additionally, these two ratios are helpful in our understanding of the patterns of DNA sequence evolution.'),
(78771, 2015, 'bio', 'ExomeAI: detection of recurrent allelic imbalance in tumors using whole-exome sequencing data', 'Nadaf, Javad|Majewski, Jacek|Fahiminiya, Somayyeh', 'Department of Human Genetics, Faculty of Medicine, McGill University and Genome Quebec Innovation Center, Montreal, Quebec, Canada.|Department of Human Genetics, Faculty of Medicine, McGill University and Genome Quebec Innovation Center, Montreal, Quebec, Canada.|Department of Human Genetics, Faculty of Medicine, McGill University and Genome Quebec Innovation Center, Montreal, Quebec, Canada.', 'Canada|Canada|Canada', 0, 'Allelic Imbalance|Computer Simulation|Exome|Genome, Human|Heterozygote|Humans|Loss of Heterozygosity|Neoplasms|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu665', '25297069', 'Whole-exome sequencing (WES) has extensively been used in cancer genome studies, however, the use of WES data in the study of loss of heterozygosity or more generally allelic imbalance (AI) has so far been very limited, which highlights the need for user-friendly and flexible software that can handle low-quality datasets. We have developed a statistical approach, ExomeAI, for the detection of recurrent AI events using WES datasets, specifically where matched normal samples are not available.'),
(78772, 2014, 'bio', 'Quantifying tumor heterogeneity in whole-genome and whole-exome sequencing data', 'Oesper, Layla|Satas, Gryte|Raphael, Benjamin J', 'Department of Computer Science and Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA.|Department of Computer Science and Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA.|Department of Computer Science and Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA Department of Computer Science and Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA.', 'United States|United States|United States', 0, 'Algorithms|Breast Neoplasms|Exome|Female|Gene Frequency|Genomics|High-Throughput Nucleotide Sequencing|Humans|Lung Neoplasms|Models, Statistical|Neoplasms|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu651', '25297070', 'Most tumor samples are a heterogeneous mixture of cells, including admixture by normal (non-cancerous) cells and subpopulations of cancerous cells with different complements of somatic aberrations. This intra-tumor heterogeneity complicates the analysis of somatic aberrations in DNA sequencing data from tumor samples.'),
(78773, 2015, 'bio', 'NOVA: a software to analyze complexome profiling data', 'Giese, Heiko|Ackermann, Jörg|Heide, Heinrich|Bleier, Lea|Dröse, Stefan|Wittig, Ilka|Brandt, Ulrich|Koch, Ina', 'Molecular Bioinformatics Group, Institute of Computer Science, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Robert-Mayer-Str. 11-15, 60325 Frankfurt am Main, Germany, Molecular Bioenergetics Group, Medical School, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany, Functional Proteomics, SFB815 core unit, Medical School, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany and Nijmegen Centre for Mitochondrial Disorders, Radboud University Medical Centre, 6525 GA, Nijmegen, The Netherlands.|Molecular Bioinformatics Group, Institute of Computer Science, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Robert-Mayer-Str. 11-15, 60325 Frankfurt am Main, Germany, Molecular Bioenergetics Group, Medical School, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany, Functional Proteomics, SFB815 core unit, Medical School, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany and Nijmegen Centre for Mitochondrial Disorders, Radboud University Medical Centre, 6525 GA, Nijmegen, The Netherlands.|Molecular Bioinformatics Group, Institute of Computer Science, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Robert-Mayer-Str. 11-15, 60325 Frankfurt am Main, Germany, Molecular Bioenergetics Group, Medical School, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany, Functional Proteomics, SFB815 core unit, Medical School, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany and Nijmegen Centre for Mitochondrial Disorders, Radboud University Medical Centre, 6525 GA, Nijmegen, The Netherlands Molecular Bioinformatics Group, Institute of Computer Science, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Robert-Mayer-Str. 11-15, 60325 Frankfurt am Main, Germany, Molecular Bioenergetics Group, Medical School, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany, Functional Proteomics, SFB815 core unit, Medical School, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany and Nijmegen Centre for Mitochondrial Disorders, Radboud University Medical Centre, 6525 GA, Nijmegen, The Netherlands.|Molecular Bioinformatics Group, Institute of Computer Science, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Robert-Mayer-Str. 11-15, 60325 Frankfurt am Main, Germany, Molecular Bioenergetics Group, Medical School, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany, Functional Proteomics, SFB815 core unit, Medical School, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany and Nijmegen Centre for Mitochondrial Disorders, Radboud University Medical Centre, 6525 GA, Nijmegen, The Netherlands.|Molecular Bioinformatics Group, Institute of Computer Science, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Robert-Mayer-Str. 11-15, 60325 Frankfurt am Main, Germany, Molecular Bioenergetics Group, Medical School, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany, Functional Proteomics, SFB815 core unit, Medical School, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany and Nijmegen Centre for Mitochondrial Disorders, Radboud University Medical Centre, 6525 GA, Nijmegen, The Netherlands.|Molecular Bioinformatics Group, Institute of Computer Science, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Robert-Mayer-Str. 11-15, 60325 Frankfurt am Main, Germany, Molecular Bioenergetics Group, Medical School, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany, Functional Proteomics, SFB815 core unit, Medical School, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany and Nijmegen Centre for Mitochondrial Disorders, Radboud University Medical Centre, 6525 GA, Nijmegen, The Netherlands Molecular Bioinformatics Group, Institute of Computer Science, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Robert-Mayer-Str. 11-15, 60325 Frankfurt am Main, Germany, Molecular Bioenergetics Group, Medical School, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany, Functional Proteomics, SFB815 core unit, Medical School, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany and Nijmegen Centre for Mitochondrial Disorders, Radboud University Medical Centre, 6525 GA, Nijmegen, The Netherlands.|Molecular Bioinformatics Group, Institute of Computer Science, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Robert-Mayer-Str. 11-15, 60325 Frankfurt am Main, Germany, Molecular Bioenergetics Group, Medical School, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany, Functional Proteomics, SFB815 core unit, Medical School, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany and Nijmegen Centre for Mitochondrial Disorders, Radboud University Medical Centre, 6525 GA, Nijmegen, The Netherlands Molecular Bioinformatics Group, Institute of Computer Science, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Robert-Mayer-Str. 11-15, 60325 Frankfurt am Main, Germany, Molecular Bioenergetics Group, Medical School, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany, Functional Proteomics, SFB815 core unit, Medical School, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany and Nijmegen Centre for Mitochondrial Disorders, Radboud University Medical Centre, 6525 GA, Nijmegen, The Netherlands.|Molecular Bioinformatics Group, Institute of Computer Science, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Robert-Mayer-Str. 11-15, 60325 Frankfurt am Main, Germany, Molecular Bioenergetics Group, Medical School, Cluster of Excellence Frankfurt Macromolecular Complexes, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany, Functional Proteomics, SFB815 core unit, Medical School, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany and Nijmegen Centre for Mitochondrial Disorders, Radboud University Medical Centre, 6525 GA, Nijmegen, The Netherlands.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 27, 'Cluster Analysis|Gene Expression Profiling|Humans|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu623', '25301849', 'We introduce nova, a software for the analysis of complexome profiling data. nova supports the investigation of the composition of complexes, cluster analysis of the experimental data, visual inspection and comparison of experiments and many other features.'),
(78774, 2015, 'bio', 'PDB-wide collection of binding data: current status of the PDBbind database', 'Liu, Zhihai|Li, Yan|Han, Li|Li, Jie|Liu, Jie|Zhao, Zhixiong|Nie, Wei|Liu, Yuchen|Wang, Renxiao', 'State Key Laboratory of Bioorganic and Natural Products Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032 and State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau, Peoples Republic of China.|State Key Laboratory of Bioorganic and Natural Products Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032 and State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau, Peoples Republic of China.|State Key Laboratory of Bioorganic and Natural Products Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032 and State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau, Peoples Republic of China.|State Key Laboratory of Bioorganic and Natural Products Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032 and State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau, Peoples Republic of China.|State Key Laboratory of Bioorganic and Natural Products Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032 and State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau, Peoples Republic of China.|State Key Laboratory of Bioorganic and Natural Products Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032 and State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau, Peoples Republic of China.|State Key Laboratory of Bioorganic and Natural Products Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032 and State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau, Peoples Republic of China.|State Key Laboratory of Bioorganic and Natural Products Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032 and State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau, Peoples Republic of China.|State Key Laboratory of Bioorganic and Natural Products Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032 and State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau, Peoples Republic of China State Key Laboratory of Bioorganic and Natural Products Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032 and State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau, Peoples Republic of China.', 'China|China|China|China|China|China|China|China|China', 119, 'Databases, Protein|Humans|Information Storage and Retrieval|Ligands|Protein Binding|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu626', '25301850', 'Molecular recognition between biological macromolecules and organic small molecules plays an important role in various life processes. Both structural information and binding data of biomolecular complexes are indispensable for depicting the underlying mechanism in such an event. The PDBbind database was created to collect experimentally measured binding data for the biomolecular complexes throughout the Protein Data Bank (PDB). It thus provides the linkage between structural information and energetic properties of biomolecular complexes, which is especially desirable for computational studies or statistical analyses.'),
(78775, 2015, 'bio', 'Tabhu: tools for antibody humanization', 'Olimpieri, Pier Paolo|Marcatili, Paolo|Tramontano, Anna', 'Department of Physics, Sapienza University, Rome 00185, Italy, Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Anker Engelunds Vej 1, 2800 Lyngby, Denmark and Istituto Pasteur-Fondazione Cenci Bolognetti, Rome 00185, Italy.|Department of Physics, Sapienza University, Rome 00185, Italy, Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Anker Engelunds Vej 1, 2800 Lyngby, Denmark and Istituto Pasteur-Fondazione Cenci Bolognetti, Rome 00185, Italy.|Department of Physics, Sapienza University, Rome 00185, Italy, Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Anker Engelunds Vej 1, 2800 Lyngby, Denmark and Istituto Pasteur-Fondazione Cenci Bolognetti, Rome 00185, Italy Department of Physics, Sapienza University, Rome 00185, Italy, Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Anker Engelunds Vej 1, 2800 Lyngby, Denmark and Istituto Pasteur-Fondazione Cenci Bolognetti, Rome 00185, Italy.', 'Denmark|Denmark|Denmark', 0, 'Animals|Antibodies, Monoclonal|Antibody Specificity|Antigen-Antibody Complex|Antigens|Humans|Mice|Protein Engineering|Software', 'Journal Article', '10.1093/bioinformatics/btu667', '25304777', 'Antibodies are rapidly becoming essential tools in the clinical practice, given their ability to recognize their cognate antigens with high specificity and affinity, and a high yield at reasonable costs in model animals. Unfortunately, when administered to human patients, xenogeneic antibodies can elicit unwanted and dangerous immunogenic responses. Antibody humanization methods are designed to produce molecules with a better safety profile still maintaining their ability to bind the antigen. This can be accomplished by grafting the non-human regions determining the antigen specificity into a suitable human template. Unfortunately, this procedure may results in a partial or complete loss of affinity of the grafted molecule that can be restored by back-mutating some of the residues of human origin to the corresponding murine ones. This trial-and-error procedure is hard and involves expensive and time-consuming experiments. Here we present tools for antibody humanization (Tabhu) a web server for antibody humanization. Tabhu includes tools for human template selection, grafting, back-mutation evaluation, antibody modelling and structural analysis, helping the user in all the critical steps of the humanization experiment protocol.'),
(78776, 2015, 'bio', 'Integrative data analysis indicates an intrinsic disordered domain character of Argonaute-binding motifs', 'Zielezinski, Andrzej|Karlowski, Wojciech M', 'Laboratory of Computational Genomics-Bioinformatics Laboratory, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznan, Poland.|Laboratory of Computational Genomics-Bioinformatics Laboratory, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznan, Poland.', 'Poland|Poland', 0, 'Algorithms|Amino Acid Motifs|Argonaute Proteins|Glycine|Protein Binding|Protein Structure, Tertiary|Repetitive Sequences, Amino Acid|Software|Tryptophan', 'Journal Article', '10.1093/bioinformatics/btu666', '25304778', 'Argonaute-interacting WG/GW proteins are characterized by the presence of repeated sequence motifs containing glycine (G) and tryptophan (W). The motifs seem to be remarkably adaptive to amino acid substitutions and their sequences show non-contiguity. Our previous approach to the detection of GW domains, based on scoring their gross amino acid composition, allowed annotation of several novel proteins involved in gene silencing. The accumulation of new experimental data and more advanced applications revealed some deficiency of the algorithm in prediction selectivity. Additionally, W-motifs, though critical in gene regulation, have not yet been annotated in any available online resources.'),
(78777, 2015, 'bio', 'A stochastic automaton model for simulating kinesin processivity', 'Khataee, Hamidreza|Liew, Alan Wee-Chung', 'School of Information and Communication Technology, Gold Coast Campus, Griffith University, QLD 4222, Australia.|School of Information and Communication Technology, Gold Coast Campus, Griffith University, QLD 4222, Australia.', 'Australia|Australia', 0, 'Adenosine Triphosphate|Algorithms|Computer Simulation|Humans|Hydrolysis|Kinesin|Kinetics|Microtubules|Models, Biological|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/btu664', '25304779', 'Cellular interactions of kinesin-1, an adenosine triphosphate (ATP)-driven motor protein capable of undergoing multiple steps on a microtubule (MT), affect its mechanical processivity, the number of steps taken per encounter with MT. Even though the processivity of kinesin has been widely studied, a detailed study of the factors that affect the stepping of the motor along MT is still lacking.'),
(78778, 2015, 'bio', 'Accurate estimation of haplotype frequency from pooled sequencing data and cost-effective identification of rare haplotype carriers by overlapping pool sequencing', 'Cao, Chang-Chang|Sun, Xiao', 'State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.|State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.', 'China|China', 5, 'Algorithms|Computational Biology|Databases, Factual|Genome, Human|Genome-Wide Association Study|Haplotypes|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu670', '25304780', 'A variety of hypotheses have been proposed for finding the missing heritability of complex diseases in genome-wide association studies. Studies have focused on the value of haplotype to improve the power of detecting associations with disease. To facilitate haplotype-based association analysis, it is necessary to accurately estimate haplotype frequencies of pooled samples.'),
(78779, 2015, 'bio', 'PhosphoPICK: modelling cellular context to map kinase-substrate phosphorylation events', 'Patrick, Ralph|Lê Cao, Kim-Anh|Kobe, Bostjan|Bodén, Mikael', 'School of Chemistry and Molecular Biosciences and Queensland Facility for Advanced Bioinformatics, The University of Queensland, St Lucia 4072, Translational Research Institute, The University of Queensland Diamantina Institute, Brisbane, St Lucia 4102, Institute for Molecular Bioscience and Australian Infectious Diseases Research Centre, The University of Queensland, St Lucia, 4072, Australia.|School of Chemistry and Molecular Biosciences and Queensland Facility for Advanced Bioinformatics, The University of Queensland, St Lucia 4072, Translational Research Institute, The University of Queensland Diamantina Institute, Brisbane, St Lucia 4102, Institute for Molecular Bioscience and Australian Infectious Diseases Research Centre, The University of Queensland, St Lucia, 4072, Australia School of Chemistry and Molecular Biosciences and Queensland Facility for Advanced Bioinformatics, The University of Queensland, St Lucia 4072, Translational Research Institute, The University of Queensland Diamantina Institute, Brisbane, St Lucia 4102, Institute for Molecular Bioscience and Australian Infectious Diseases Research Centre, The University of Queensland, St Lucia, 4072, Australia School of Chemistry and Molecular Biosciences and Queensland Facility for Advanced Bioinformatics, The University of Queensland, St Lucia 4072, Translational Research Institute, The University of Queensland Diamantina Institute, Brisbane, St Lucia 4102, Institute for Molecular Bioscience and Australian Infectious Diseases Research Centre, The University of Queensland, St Lucia, 4072, Australia.|School of Chemistry and Molecular Biosciences and Queensland Facility for Advanced Bioinformatics, The University of Queensland, St Lucia 4072, Translational Research Institute, The University of Queensland Diamantina Institute, Brisbane, St Lucia 4102, Institute for Molecular Bioscience and Australian Infectious Diseases Research Centre, The University of Queensland, St Lucia, 4072, Australia School of Chemistry and Molecular Biosciences and Queensland Facility for Advanced Bioinformatics, The University of Queensland, St Lucia 4072, Translational Research Institute, The University of Queensland Diamantina Institute, Brisbane, St Lucia 4102, Institute for Molecular Bioscience and Australian Infectious Diseases Research Centre, The University of Queensland, St Lucia, 4072, Australia School of Chemistry and Molecular Biosciences and Queensland Facility for Advanced Bioinformatics, The University of Queensland, St Lucia 4072, Translational Research Institute, The University of Queensland Diamantina Institute, Brisbane, St Lucia 4102, Institute for Molecular Bioscience and Australian Infectious Diseases Research Centre, The University of Queensland, St Lucia, 4072, Australia.|School of Chemistry and Molecular Biosciences and Queensland Facility for Advanced Bioinformatics, The University of Queensland, St Lucia 4072, Translational Research Institute, The University of Queensland Diamantina Institute, Brisbane, St Lucia 4102, Institute for Molecular Bioscience and Australian Infectious Diseases Research Centre, The University of Queensland, St Lucia, 4072, Australia School of Chemistry and Molecular Biosciences and Queensland Facility for Advanced Bioinformatics, The University of Queensland, St Lucia 4072, Translational Research Institute, The University of Queensland Diamantina Institute, Brisbane, St Lucia 4102, Institute for Molecular Bioscience and Australian Infectious Diseases Research Centre, The University of Queensland, St Lucia, 4072, Australia.', 'Australia|Australia|Australia|Australia', 0, 'Bayes Theorem|Binding Sites|Cell Cycle|Cyclin-Dependent Kinases|Databases, Protein|Humans|Phosphoproteins|Phosphorylation|Protein Binding|Protein Interaction Mapping|Protein Kinases|Substrate Specificity|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu663', '25304781', 'The determinants of kinase-substrate phosphorylation can be found both in the substrate sequence and the surrounding cellular context. Cell cycle progression, interactions with mediating proteins and even prior phosphorylation events are necessary for kinases to maintain substrate specificity. While much work has focussed on the use of sequence-based methods to predict phosphorylation sites, there has been very little work invested into the application of systems biology to understand phosphorylation. Lack of specificity in many kinase substrate binding motifs means that sequence methods for predicting kinase binding sites are susceptible to high false-positive rates.'),
(78780, 2015, 'bio', 'Pooled assembly of marine metagenomic datasets: enriching annotation through chimerism', 'Magasin, Jonathan D|Gerloff, Dietlind L', 'Department of Biomolecular Engineering, University of California, Santa Cruz, CA 95064 and Foundation for Applied Molecular Evolution (FfAME), Gainesville, FL 32604, USA.|Department of Biomolecular Engineering, University of California, Santa Cruz, CA 95064 and Foundation for Applied Molecular Evolution (FfAME), Gainesville, FL 32604, USA.', 'United States|United States', 0, 'Archaeal Proteins|Bacterial Proteins|Chimerism|Datasets as Topic|Genome, Archaeal|Genome, Bacterial|Metagenomics|Molecular Sequence Annotation|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu546', '25306399', 'Despite advances in high-throughput sequencing, marine metagenomic samples remain largely opaque. A typical sample contains billions of microbial organisms from thousands of genomes and quadrillions of DNA base pairs. Its derived metagenomic dataset underrepresents this complexity by orders of magnitude because of the sparseness and shortness of sequencing reads. Read shortness and sequencing errors pose a major challenge to accurate species and functional annotation. This includes distinguishing known from novel species. Often the majority of reads cannot be annotated and thus cannot help our interpretation of the sample.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78781, 2015, 'bio', 'Novel function discovery with GeneMANIA: a new integrated resource for gene function prediction in Escherichia coli', 'Vlasblom, James|Zuberi, Khalid|Rodriguez, Harold|Arnold, Roland|Gagarinova, Alla|Deineko, Viktor|Kumar, Ashwani|Leung, Elisa|Rizzolo, Kamran|Samanfar, Bahram|Chang, Luke|Phanse, Sadhna|Golshani, Ashkan|Greenblatt, Jack F|Houry, Walid A|Emili, Andrew|Morris, Quaid|Bader, Gary|Babu, Mohan', 'Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, Univ|Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Computer Science, University of Regina, Regina, Saskatchewan S4S0A2, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada, Department of Biology, Carleton University, Ottawa, Ontario K1S 5B6, Canada and Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Ca', 24, 'Algorithms|Escherichia coli|Escherichia coli Proteins|Gene Regulatory Networks|Phenotype|Software', 'Journal Article', '10.1093/bioinformatics/btu671', '25316676', 'The model bacterium Escherichia coli is among the best studied prokaryotes, yet nearly half of its proteins are still of unknown biological function. This is despite a wealth of available large-scale physical and genetic interaction data. To address this, we extended the GeneMANIA function prediction web application developed for model eukaryotes to support E.coli.'),
(78782, 2015, 'bio', 'SNPsnap: a Web-based tool for identification and annotation of matched SNPs', 'Pers, Tune H|Timshel, Pascal|Hirschhorn, Joel N', 'Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Childrens Hospital, Boston, MA 02115, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 2142, USA, Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark and Department of Genetics, Harvard Medical School, Boston, MA 02115, USA Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Childrens Hospital, Boston, MA 02115, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 2142, USA, Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark and Department of Genetics, Harvard Medical School, Boston, MA 02115, USA Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Childrens Hospital, Boston, MA 02115, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 2142, USA, Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark and Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.|Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Childrens Hospital, Boston, MA 02115, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 2142, USA, Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark and Department of Genetics, Harvard Medical School, Boston, MA 02115, USA Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Childrens Hospital, Boston, MA 02115, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 2142, USA, Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark and Department of Genetics, Harvard Medical School, Boston, MA 02115, USA Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Childrens Hospital, Boston, MA 02115, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 2142, USA, Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark and Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.|Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Childrens Hospital, Boston, MA 02115, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 2142, USA, Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark and Department of Genetics, Harvard Medical School, Boston, MA 02115, USA Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Childrens Hospital, Boston, MA 02115, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 2142, USA, Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark and Department of Genetics, Harvard Medical School, Boston, MA 02115, USA Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Childrens Hospital, Boston, MA 02115, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 2142, USA, Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark and Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.', 'Denmark|Denmark|Denmark', 0, 'Genome-Wide Association Study|Humans|Internet|Linkage Disequilibrium|Molecular Sequence Annotation|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btu655', '25316677', 'An important computational step following genome-wide association studies (GWAS) is to assess whether disease or trait-associated single-nucleotide polymorphisms (SNPs) enrich for particular biological annotations. SNP-based enrichment analysis needs to account for biases such as co-localization of GWAS signals to gene-dense and high linkage disequilibrium (LD) regions, and correlations of gene size, location and function. The SNPsnap Web server enables SNP-based enrichment analysis by providing matched sets of SNPs that can be used to calibrate background expectations. Specifically, SNPsnap efficiently identifies sets of randomly drawn SNPs that are matched to a set of query SNPs based on allele frequency, number of SNPs in LD, distance to nearest gene and gene density.'),
(78783, 2015, 'bio', 'GeneNet Toolbox for MATLAB: a flexible platform for the analysis of gene connectivity in biological networks', 'Taylor, Avigail|Steinberg, Julia|Andrews, Tallulah S|Webber, Caleb', 'MRC Functional Genomics Unit, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK and The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK.|MRC Functional Genomics Unit, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK and The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK MRC Functional Genomics Unit, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK and The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK.|MRC Functional Genomics Unit, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK and The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK.|MRC Functional Genomics Unit, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK and The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 9, 'Algorithms|Computational Biology|Computer Graphics|Databases, Genetic|Gene Expression Regulation|Gene Regulatory Networks|Humans|Information Storage and Retrieval|Metabolic Networks and Pathways|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu669', '25319962', 'We present GeneNet Toolbox for MATLAB (also available as a set of standalone applications for Linux). The toolbox, available as command-line or with a graphical user interface, enables biologists to assess connectivity among a set of genes of interest (seed-genes) within a biological network of their choosing. Two methods are implemented for calculating the significance of connectivity among seed-genes: seed randomization and network permutation. Options include restricting analyses to a specified subnetwork of the primary biological network, and calculating connectivity from the seed-genes to a second set of interesting genes. Pre-analysis tools help the user choose the best connectivity-analysis algorithm for their network. The toolbox also enables visualization of the connections among seed-genes. GeneNet Toolbox functions execute in reasonable time for very large networks (xe2x88xbc10 million edges) on a desktop computer.'),
(78784, 2015, 'bio', 'miRseqViewer: multi-panel visualization of sequence, structure and expression for analysis of microRNA sequencing data', 'Jang, Insu|Chang, Hyeshik|Jun, Yukyung|Park, Seongjin|Yang, Jin Ok|Lee, Byungwook|Kim, Wankyu|Kim, V Narry|Lee, Sanghyuk', 'Korean Bioinformation Center (KOBIC), KRIBB, Daejeon 305-806, Korea, School of Biological Sciences, Seoul National University, Seoul 151-742, Korea and Department of Life Science and Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Korea.|Korean Bioinformation Center (KOBIC), KRIBB, Daejeon 305-806, Korea, School of Biological Sciences, Seoul National University, Seoul 151-742, Korea and Department of Life Science and Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Korea.|Korean Bioinformation Center (KOBIC), KRIBB, Daejeon 305-806, Korea, School of Biological Sciences, Seoul National University, Seoul 151-742, Korea and Department of Life Science and Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Korea.|Korean Bioinformation Center (KOBIC), KRIBB, Daejeon 305-806, Korea, School of Biological Sciences, Seoul National University, Seoul 151-742, Korea and Department of Life Science and Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Korea.|Korean Bioinformation Center (KOBIC), KRIBB, Daejeon 305-806, Korea, School of Biological Sciences, Seoul National University, Seoul 151-742, Korea and Department of Life Science and Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Korea.|Korean Bioinformation Center (KOBIC), KRIBB, Daejeon 305-806, Korea, School of Biological Sciences, Seoul National University, Seoul 151-742, Korea and Department of Life Science and Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Korea.|Korean Bioinformation Center (KOBIC), KRIBB, Daejeon 305-806, Korea, School of Biological Sciences, Seoul National University, Seoul 151-742, Korea and Department of Life Science and Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Korea.|Korean Bioinformation Center (KOBIC), KRIBB, Daejeon 305-806, Korea, School of Biological Sciences, Seoul National University, Seoul 151-742, Korea and Department of Life Science and Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Korea.|Korean Bioinformation Center (KOBIC), KRIBB, Daejeon 305-806, Korea, School of Biological Sciences, Seoul National University, Seoul 151-742, Korea and Department of Life Science and Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Korea.', '-|-|-|-|-|-|-|-|-', 0, 'Computational Biology|Computer Graphics|Databases, Nucleic Acid|High-Throughput Nucleotide Sequencing|Humans|MicroRNAs|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu676', '25322835', 'Deep sequencing of small RNAs has become a routine process in recent years, but no dedicated viewer is as yet available to explore the sequence features simultaneously along with secondary structure and gene expression of microRNA (miRNA). We present a highly interactive application that visualizes the sequence alignment, secondary structure and normalized read counts in synchronous multipanel windows. This helps users to easily examine the relationships between the structure of precursor and the sequences and abundance of final products and thereby will facilitate the studies on miRNA biogenesis and regulation. The project manager handles multiple samples of multiple groups. The read alignment is imported in BAM file format. Implemented features comprise sorting, zooming, highlighting, editing, filtering, saving, exporting, etc. Currently, miRseqViewer supports 84 organisms whose annotation is available at miRBase.'),
(78785, 2015, 'bio', 'Rcount: simple and flexible RNA-Seq read counting', 'Schmid, Marc W|Grossniklaus, Ueli', 'Institute of Plant Biology and Zürich-Basel Plant Science Center, University of Zurich, 8008 Zürich, Switzerland.|Institute of Plant Biology and Zürich-Basel Plant Science Center, University of Zurich, 8008 Zürich, Switzerland.', 'Switzerland|Switzerland', 17, 'Algorithms|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu680', '25322836', 'Analysis of differential gene expression by RNA sequencing (RNA-Seq) is frequently done using feature counts, i.e. the number of reads mapping to a gene. However, commonly used count algorithms (e.g. HTSeq) do not address the problem of reads aligning with multiple locations in the genome (multireads) or reads aligning with positions where two or more genes overlap (ambiguous reads). Rcount specifically addresses these issues. Furthermore, Rcount allows the user to assign priorities to certain feature types (e.g. higher priority for protein-coding genes compared to rRNA-coding genes) or to add flanking regions.'),
(78786, 2015, 'bio', 'An efficient algorithm for the blocked pattern matching problem', 'Deng, Fei|Wang, Lusheng|Liu, Xiaowen', 'Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis and Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA.|Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis and Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA.|Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis and Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis and Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA.', 'Hong Kong|Hong Kong|Hong Kong', 0, 'Algorithms|Computational Biology|Databases, Protein|Humans|Models, Biological|Peptide Fragments|Peptide Mapping|Proteins|Sequence Analysis, Protein|Tandem Mass Spectrometry', 'Journal Article', '10.1093/bioinformatics/btu678', '25322837', 'Tandem mass spectrometry (MS) has become the method of choice for protein identification and quantification. In the era of big data biology, tandem mass spectra are often searched against huge protein databases generated from genomes or RNA-Seq data for peptide identification. However, most existing tools for MS-based peptide identification compare a tandem mass spectrum against all peptides in a database whose molecular masses are similar to the precursor mass of the spectrum, making mass spectral data analysis slow for huge databases. Tag-based methods extract peptide sequence tags from a tandem mass spectrum and use them as a filter to reduce the number of candidate peptides, thus speeding up the database search. Recently, gapped tags have been introduced into mass spectral data analysis because they improve the sensitivity of peptide identification compared with sequence tags. However, the blocked pattern matching (BPM) problem, which is an essential step in gapped tag-based peptide identification, has not been fully solved.'),
(78787, 2015, 'bio', 'Differential regulation enrichment analysis via the integration of transcriptional regulatory network and gene expression data', 'Ma, Shining|Jiang, Tao|Jiang, Rui', 'MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST, Department of Automation, Tsinghua University, Beijing 100084, China, Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA, Department of Statistics, Stanford University, Stanford, CA 94305, USA.|MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST, Department of Automation, Tsinghua University, Beijing 100084, China, Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA, Department of Statistics, Stanford University, Stanford, CA 94305, USA MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST, Department of Automation, Tsinghua University, Beijing 100084, China, Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA, Department of Statistics, Stanford University, Stanford, CA 94305, USA.|MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST, Department of Automation, Tsinghua University, Beijing 100084, China, Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA, Department of Statistics, Stanford University, Stanford, CA 94305, USA MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST, Department of Automation, Tsinghua University, Beijing 100084, China, Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA, Department of Statistics, Stanford University, Stanford, CA 94305, USA.', 'China|China|China', 14, 'Algorithms|Breast Neoplasms|Computational Biology|Data Interpretation, Statistical|Databases, Factual|Escherichia coli|Escherichia coli Proteins|Female|Gene Expression Profiling|Gene Expression Regulation|Gene Regulatory Networks|HeLa Cells|Humans|MCF-7 Cells|Male|Oligonucleotide Array Sequence Analysis|Phenotype|Prostatic Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/btu672', '25322838', 'Although many gene set analysis methods have been proposed to explore associations between a phenotype and a group of genes sharing common biological functions or involved in the same biological process, the underlying biological mechanisms of identified gene sets are typically unexplained.'),
(78788, 2015, 'bio', 'FuncPatch: a web server for the fast Bayesian inference of conserved functional patches in protein 3D structures', 'Huang, Yi-Fei|Golding, G Brian', 'Department of Biology, McMaster University, Hamilton, ON L8S4K1, Canada.|Department of Biology, McMaster University, Hamilton, ON L8S4K1, Canada.', 'Canada|Canada', 0, 'Amino Acid Sequence|Bayes Theorem|Conserved Sequence|Humans|Internet|Protein Structure, Tertiary|Proteins|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu673', '25322839', 'A number of statistical phylogenetic methods have been developed to infer conserved functional sites or regions in proteins. Many methods, e.g. Rate4Site, apply the standard phylogenetic models to infer site-specific substitution rates and totally ignore the spatial correlation of substitution rates in protein tertiary structures, which may reduce their power to identify conserved functional patches in protein tertiary structures when the sequences used in the analysis are highly similar. The 3D sliding window method has been proposed to infer conserved functional patches in protein tertiary structures, but the window size, which reflects the strength of the spatial correlation, must be predefined and is not inferred from data. We recently developed GP4Rate to solve these problems under the Bayesian framework. Unfortunately, GP4Rate is computationally slow. Here, we present an intuitive web server, FuncPatch, to perform a fast approximate Bayesian inference of conserved functional patches in protein tertiary structures.'),
(78789, 2015, 'bio', 'Introducing dAUTObase: a first step towards the global scale geoepidemiology of autoimmune syndromes and diseases', 'Gkantouna, Vassiliki A|Kambouris, Manousos E|Viennas, Emmanouil S|Ioannou, Zafeiria-Marina|Paraskevas, Michael|Lagoumintzis, George|Zagoriti, Zoi|Patrinos, George P|Tzimas, Giannis E|Poulas, Konstantinos', 'Department of Computer Engineering and Informatics, University of Patras, Rio Patras, 26500, Greece, Department of Pharmacy, University of Patras, Rio Patras 26500, Greece, Department of Computer and Informatics Engineering, Technological Educational Institute of Western Greece, M. Alexandrou 1, Koukouli Patras 26334, Greece.|Department of Computer Engineering and Informatics, University of Patras, Rio Patras, 26500, Greece, Department of Pharmacy, University of Patras, Rio Patras 26500, Greece, Department of Computer and Informatics Engineering, Technological Educational Institute of Western Greece, M. Alexandrou 1, Koukouli Patras 26334, Greece.|Department of Computer Engineering and Informatics, University of Patras, Rio Patras, 26500, Greece, Department of Pharmacy, University of Patras, Rio Patras 26500, Greece, Department of Computer and Informatics Engineering, Technological Educational Institute of Western Greece, M. Alexandrou 1, Koukouli Patras 26334, Greece.|Department of Computer Engineering and Informatics, University of Patras, Rio Patras, 26500, Greece, Department of Pharmacy, University of Patras, Rio Patras 26500, Greece, Department of Computer and Informatics Engineering, Technological Educational Institute of Western Greece, M. Alexandrou 1, Koukouli Patras 26334, Greece.|Department of Computer Engineering and Informatics, University of Patras, Rio Patras, 26500, Greece, Department of Pharmacy, University of Patras, Rio Patras 26500, Greece, Department of Computer and Informatics Engineering, Technological Educational Institute of Western Greece, M. Alexandrou 1, Koukouli Patras 26334, Greece.|Department of Computer Engineering and Informatics, University of Patras, Rio Patras, 26500, Greece, Department of Pharmacy, University of Patras, Rio Patras 26500, Greece, Department of Computer and Informatics Engineering, Technological Educational Institute of Western Greece, M. Alexandrou 1, Koukouli Patras 26334, Greece.|Department of Computer Engineering and Informatics, University of Patras, Rio Patras, 26500, Greece, Department of Pharmacy, University of Patras, Rio Patras 26500, Greece, Department of Computer and Informatics Engineering, Technological Educational Institute of Western Greece, M. Alexandrou 1, Koukouli Patras 26334, Greece.|Department of Computer Engineering and Informatics, University of Patras, Rio Patras, 26500, Greece, Department of Pharmacy, University of Patras, Rio Patras 26500, Greece, Department of Computer and Informatics Engineering, Technological Educational Institute of Western Greece, M. Alexandrou 1, Koukouli Patras 26334, Greece.|Department of Computer Engineering and Informatics, University of Patras, Rio Patras, 26500, Greece, Department of Pharmacy, University of Patras, Rio Patras 26500, Greece, Department of Computer and Informatics Engineering, Technological Educational Institute of Western Greece, M. Alexandrou 1, Koukouli Patras 26334, Greece.|Department of Computer Engineering and Informatics, University of Patras, Rio Patras, 26500, Greece, Department of Pharmacy, University of Patras, Rio Patras 26500, Greece, Department of Computer and Informatics Engineering, Technological Educational Institute of Western Greece, M. Alexandrou 1, Koukouli Patras 26334, Greece.', 'Greece|Greece|Greece|Greece|Greece|Greece|Greece|Greece|Greece|Greece', 0, 'Autoimmune Diseases|Computational Biology|Databases, Genetic|Diabetes Mellitus, Type 1|Ethnic Groups|Female|Genetics, Population|Genome, Human|Global Health|Humans|Male|Software|Syndrome', 'Journal Article', '10.1093/bioinformatics/btu690', '25332376', 'An autoimmune disorder occurs when the immune system mistakenly attacks and destroys its own healthy body tissues. The initiation of a geoepidemiological database, for recording autoimmune incidents with a focus to clinical manifestations, demographic parameters and geographic background is crucial to detect correlations.'),
(78790, 2015, 'bio', 'Seed: a user-friendly tool for exploring and visualizing microbial community data', 'Beck, Daniel|Dennis, Christopher|Foster, James A', 'Department of Biological Sciences, University of Idaho, Moscow, ID 83844, USA.|Department of Biological Sciences, University of Idaho, Moscow, ID 83844, USA.|Department of Biological Sciences, University of Idaho, Moscow, ID 83844, USA.', 'United States|United States|United States', 0, 'Bacteria|Computational Biology|Computer Graphics|Ecology|Software', 'Journal Article', '10.1093/bioinformatics/btu693', '25332377', 'In this article we present Simple Exploration of Ecological Data (Seed), a data exploration tool for microbial communities. Seed is written in R using the Shiny library. This provides access to powerful R-based functions and libraries through a simple user interface. Seed allows users to explore ecological datasets using principal coordinate analyses, scatter plots, bar plots, hierarchal clustering and heatmaps.'),
(78791, 2015, 'bio', 'Statistical significance of variables driving systematic variation in high-dimensional data', 'Chung, Neo Christopher|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', 63, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Genes, cdc|Genetic Variation|Genomics|Humans|Inflammation|Microarray Analysis|Models, Statistical|Phenotype|Principal Component Analysis|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Software|Stress Disorders, Post-Traumatic', 'Journal Article', '10.1093/bioinformatics/btu674', '25336500', 'There are a number of well-established methods such as principal component analysis (PCA) for automatically capturing systematic variation due to latent variables in large-scale genomic data. PCA and related methods may directly provide a quantitative characterization of a complex biological variable that is otherwise difficult to precisely define or model. An unsolved problem in this context is how to systematically identify the genomic variables that are drivers of systematic variation captured by PCA. Principal components (PCs) (and other estimates of systematic variation) are directly constructed from the genomic variables themselves, making measures of statistical significance artificially inflated when using conventional methods due to over-fitting.'),
(78792, 2015, 'bio', 'LIGSIFT: an open-source tool for ligand structural alignment and virtual screening', 'Roy, Ambrish|Skolnick, Jeffrey', 'Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, GA 30076, USA.|Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, GA 30076, USA.', 'Georgia|Georgia', 27, 'Algorithms|Binding Sites|Databases, Chemical|Drug Discovery|Drug Evaluation, Preclinical|Humans|Ligands|Models, Molecular|Molecular Docking Simulation|Protein Conformation|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu692', '25336501', 'Shape-based alignment of small molecules is a widely used approach in computer-aided drug discovery. Most shape-based ligand structure alignment applications, both commercial and freely available ones, use the Tanimoto coefficient or similar functions for evaluating molecular similarity. Major drawbacks of using such functions are the size dependence of the score and the fact that the statistical significance of the molecular match using such metrics is not reported.'),
(78793, 2015, 'bio', 'Simple, rapid and accurate genotyping-by-sequencing from aligned whole genomes with ArrayMaker', 'Willet, Cali E|Haase, Bianca|Charleston, Michael A|Wade, Claire M', 'Faculty of Veterinary Science and School of Information Technologies, University of Sydney, Sydney, New South Wales 2006, Australia.|Faculty of Veterinary Science and School of Information Technologies, University of Sydney, Sydney, New South Wales 2006, Australia.|Faculty of Veterinary Science and School of Information Technologies, University of Sydney, Sydney, New South Wales 2006, Australia.|Faculty of Veterinary Science and School of Information Technologies, University of Sydney, Sydney, New South Wales 2006, Australia.', 'Australia|Australia|Australia|Australia', 0, 'Genome, Human|Genome-Wide Association Study|Genotype|Genotyping Techniques|Humans|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu691', '25336502', 'Whole-genome sequencing has revolutionized the study of genetics. Genotyping-by-sequencing is now a viable method of genotyping, yet the bioinformatics involved can be daunting if not prohibitive for some laboratories. Here we present ArrayMaker, a user-friendly tool that extracts accurate single nucleotide polymorphism genotypes at pre-defined loci from whole-genome alignments and presents them in a standard genotyping format compatible with association analysis software and datasets genotyped on commercial array platforms. Using this tool, geneticists with only basic computing ability can genotype samples at any desired list of markers, facilitating genome-wide association analysis, fine mapping, candidate variant assessment, data sharing and compatibility of data sourced from multiple technologies.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78794, 2015, 'bio', 'Context similarity scoring improves protein sequence alignments in the midnight zone', 'Meier, Armin|Söding, Johannes', 'Gene Center, LMU Munich, 81377 Munich and Max Planck Institute for Biophysical Chemistry, 37077 Göttingen, Germany.|Gene Center, LMU Munich, 81377 Munich and Max Planck Institute for Biophysical Chemistry, 37077 Göttingen, Germany Gene Center, LMU Munich, 81377 Munich and Max Planck Institute for Biophysical Chemistry, 37077 Göttingen, Germany.', 'Germany|Germany', 7, 'Algorithms|Amino Acids|Humans|Hydrophobic and Hydrophilic Interactions|Likelihood Functions|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btu697', '25338715', 'High-quality protein sequence alignments are essential for a number of downstream applications such as template-based protein structure prediction. In addition to the similarity score between sequence profile columns, many current profile-profile alignment tools use extra terms that compare 1D-structural properties such as secondary structure and solvent accessibility, which are predicted from short profile windows around each sequence position. Such scores add non-redundant information by evaluating the conservation of local patterns of hydrophobicity and other amino acid properties and thus exploiting correlations between profile columns.'),
(78795, 2015, 'bio', 'DANN: a deep learning approach for annotating the pathogenicity of genetic variants', 'Quang, Daniel|Chen, Yifei|Xie, Xiaohui', 'Department of Computer Science and Center for Complex Biological Systems, University of California, Irvine, CA 92697, USA Department of Computer Science and Center for Complex Biological Systems, University of California, Irvine, CA 92697, USA.|Department of Computer Science and Center for Complex Biological Systems, University of California, Irvine, CA 92697, USA.|Department of Computer Science and Center for Complex Biological Systems, University of California, Irvine, CA 92697, USA Department of Computer Science and Center for Complex Biological Systems, University of California, Irvine, CA 92697, USA.', 'United States|United States|United States', 295, 'Algorithms|Area Under Curve|Computer Graphics|Genetic Variation|Genome, Human|Humans|Molecular Sequence Annotation|Neural Networks (Computer)|Selection, Genetic|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btu703', '25338716', 'Annotating genetic variants, especially non-coding variants, for the purpose of identifying pathogenic variants remains a challenge. Combined annotation-dependent depletion (CADD) is an algorithm designed to annotate both coding and non-coding variants, and has been shown to outperform other annotation algorithms. CADD trains a linear kernel support vector machine (SVM) to differentiate evolutionarily derived, likely benign, alleles from simulated, likely deleterious, variants. However, SVMs cannot capture non-linear relationships among the features, which can limit performance. To address this issue, we have developed DANN. DANN uses the same feature set and training data as CADD to train a deep neural network (DNN). DNNs can capture non-linear relationships among features and are better suited than SVMs for problems with a large number of samples and features. We exploit Compute Unified Device Architecture-compatible graphics processing units and deep learning techniques such as dropout and momentum training to accelerate the DNN training. DANN achieves about a 19% relative reduction in the error rate and about a 14% relative increase in the area under the curve (AUC) metric over CADDs SVM methodology.'),
(78796, 2015, 'bio', 'FlaiMapper: computational annotation of small ncRNA-derived fragments using RNA-seq high-throughput data', 'Hoogstrate, Youri|Jenster, Guido|Martens-Uzunova, Elena S', 'Department of Urology, Erasmus University Medical Center, Be 362a, PO Box 2040, 3000 CA Rotterdam, The Netherlands.|Department of Urology, Erasmus University Medical Center, Be 362a, PO Box 2040, 3000 CA Rotterdam, The Netherlands.|Department of Urology, Erasmus University Medical Center, Be 362a, PO Box 2040, 3000 CA Rotterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 0, 'High-Throughput Nucleotide Sequencing|Humans|MicroRNAs|Molecular Sequence Annotation|RNA, Small Untranslated|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu696', '25338717', 'Recent discoveries show that most types of small non-coding RNAs (sncRNAs) such as miRNAs, snoRNAs and tRNAs get further processed into putatively active smaller RNA species. Their roles, genetic profiles and underlying processing mechanisms are only partially understood. To find their quantities and characteristics, a proper annotation is essential. Here, we present FlaiMapper, a method that extracts and annotates the locations of sncRNA-derived RNAs (sncdRNAs). These sncdRNAs are often detected in sequencing data and observed as fragments of their precursor sncRNA. Using small RNA-seq read alignments, FlaiMapper is able to annotate fragments primarily by peak detection on the start and end position densities followed by filtering and a reconstruction process.'),
(78797, 2015, 'bio', 'A5-miseq: an updated pipeline to assemble microbial genomes from Illumina MiSeq data', 'Coil, David|Jospin, Guillaume|Darling, Aaron E', 'Genome Center, University of California Davis, Davis, CA 95616, USA and ithree institute, University of Technology Sydney, New South Wales, Australia.|Genome Center, University of California Davis, Davis, CA 95616, USA and ithree institute, University of Technology Sydney, New South Wales, Australia.|Genome Center, University of California Davis, Davis, CA 95616, USA and ithree institute, University of Technology Sydney, New South Wales, Australia.', 'Australia|Australia|Australia', 495, 'Algorithms|Genome, Bacterial|Genomics|Programming Languages|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu661', '25338718', 'Open-source bacterial genome assembly remains inaccessible to many biologists because of its complexity. Few software solutions exist that are capable of automating all steps in the process of de novo genome assembly from Illumina data.'),
(78798, 2015, 'bio', 'MACOED: a multi-objective ant colony optimization algorithm for SNP epistasis detection in genome-wide association studies', 'Jing, Peng-Jie|Shen, Hong-Bin', 'Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China.|Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China.', 'China|China', 0, 'Algorithms|Animals|Ants|Bayes Theorem|Epistasis, Genetic|Genome|Genome-Wide Association Study|Logistic Models|Models, Biological|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btu702', '25338719', 'The existing methods for genetic-interaction detection in genome-wide association studies are designed from different paradigms, and their performances vary considerably for different disease models. One important reason for this variability is that their construction is based on a single-correlation model between SNPs and disease. Due to potential model preference and disease complexity, a single-objective method will therefore not work well in general, resulting in low power and a high false-positive rate.'),
(78799, 2015, 'bio', 'minimac2: faster genotype imputation', 'Fuchsberger, Christian|Abecasis, Gonçalo R|Hinds, David A', 'Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA and 23andMe, Inc., Mountain View, CA, USA.|Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA and 23andMe, Inc., Mountain View, CA, USA.|Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA and 23andMe, Inc., Mountain View, CA, USA.', 'United States|United States|United States', 174, 'Computational Biology|Genome-Wide Association Study|Genotype|Haplotypes|Humans|Polymorphism, Single Nucleotide|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/btu704', '25338720', 'Genotype imputation is a key step in the analysis of genome-wide association studies. Upcoming very large reference panels, such as those from The 1000 Genomes Project and the Haplotype Consortium, will improve imputation quality of rare and less common variants, but will also increase the computational burden. Here, we demonstrate how the application of software engineering techniques can help to keep imputation broadly accessible. Overall, these improvements speed up imputation by an order of magnitude compared with our previous implementation.'),
(78800, 2015, 'bio', 'A model for the expression of gap genes based on the Jeffreys-type equation', 'Gula, Igor A|Samsonov, Alexander M', 'The Ioffe Physical Technical Institute, St. Petersburg, 194021 Russia and State Polytechnical University, St. Petersburg, 195251 Russia.|The Ioffe Physical Technical Institute, St. Petersburg, 194021 Russia and State Polytechnical University, St. Petersburg, 195251 Russia The Ioffe Physical Technical Institute, St. Petersburg, 194021 Russia and State Polytechnical University, St. Petersburg, 195251 Russia.', '-|-', 0, 'Algorithms|Animals|Diffusion|Drosophila melanogaster|GTPase-Activating Proteins|Models, Theoretical|Protein Transport|Software', 'Journal Article', '10.1093/bioinformatics/btu695', '25338721', 'We propose the third-order model equation of the Jeffreys type for concentrations of gap gene proteins in order to take into account particle inertia. Gap genes are responsible for formation of body segments in Drosophila melanogaster embryo during its early development. Usually the expression of the genes is described by the model of protein transport based on conventional diffusion equation. However, the model is known to govern the Brownian (non-inertial) motion of particles, hence, it is hardly applicable to the description of protein transport.'),
(78801, 2015, 'bio', 'Waggawagga: comparative visualization of coiled-coil predictions and detection of stable single xcexb1-helices (SAH domains)', 'Simm, Dominic|Hatje, Klas|Kollmar, Martin', 'Department of NMR-based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Gxc3xb6ttingen, Germany.|Department of NMR-based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Gxc3xb6ttingen, Germany.|Department of NMR-based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Gxc3xb6ttingen, Germany.', 'Germany|Germany|Germany', 13, 'Amino Acid Sequence|Computer Graphics|Humans|Molecular Sequence Data|Myosins|Protein Structure, Secondary|Software', 'Journal Article', '10.1093/bioinformatics/btu700', '25338722', 'Waggawagga is a web-based tool for the comparative visualization of coiled-coil predictions and the detection of stable single xcexb1-helices (SAH domains). Overview schemes show the predicted coiled-coil regions found in the query sequence and provide sliders, which can be used to select segments for detailed helical wheel and helical net views. A window-based score has been developed to predict SAH domains. Export to several bitmap and vector graphics formats is supported.'),
(78802, 2015, 'bio', 'piPipes: a set of pipelines for piRNA and transposon analysis via small RNA-seq, RNA-seq, degradome- and CAGE-seq, ChIP-seq and genomic DNA sequencing', 'Han, Bo W|Wang, Wei|Zamore, Phillip D|Weng, Zhiping', 'RNA Therapeutics Institute, Howard Hughes Medical Institute, Department of Biochemistry & Molecular Pharmacology and Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA RNA Therapeutics Institute, Howard Hughes Medical Institute, Department of Biochemistry & Molecular Pharmacology and Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA RNA Therapeutics Institute, Howard Hughes Medical Institute, Department of Biochemistry & Molecular Pharmacology and Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA.|RNA Therapeutics Institute, Howard Hughes Medical Institute, Department of Biochemistry & Molecular Pharmacology and Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA RNA Therapeutics Institute, Howard Hughes Medical Institute, Department of Biochemistry & Molecular Pharmacology and Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA RNA Therapeutics Institute, Howard Hughes Medical Institute, Department of Biochemistry & Molecular Pharmacology and Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA RNA Therapeutics Institute, Howard Hughes Medical Institute, Department of Biochemistry & Molecular Pharmacology and Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA.|RNA Therapeutics Institute, Howard Hughes Medical Institute, Department of Biochemistry & Molecular Pharmacology and Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA RNA Therapeutics Institute, Howard Hughes Medical Institute, Department of Biochemistry & Molecular Pharmacology and Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA RNA Therapeutics Institute, Howard Hughes Medical Institute, Department of Biochemistry & Molecular Pharmacology and Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA.|RNA Therapeutics Institute, Howard Hughes Medical Institute, Department of Biochemistry & Molecular Pharmacology and Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA RNA Therapeutics Institute, Howard Hughes Medical Institute, Department of Biochemistry & Molecular Pharmacology and Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA.', 'United States|United States|United States|United States', 0, 'Animals|Chromatin Immunoprecipitation|Computational Biology|DNA Transposable Elements|Drosophila Proteins|Drosophila melanogaster|Female|Gene Expression Regulation|Genome|Genomics|High-Throughput Nucleotide Sequencing|Ovary|Proteolysis|RNA|RNA, Small Interfering|Sequence Analysis, DNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu647', '25342065', 'PIWI-interacting RNAs (piRNAs), 23-36 nt small silencing RNAs, repress transposon expression in the metazoan germ line, thereby protecting the genome. Although high-throughput sequencing has made it possible to examine the genome and transcriptome at unprecedented resolution, extracting useful information from gigabytes of sequencing data still requires substantial computational skills. Additionally, researchers may analyze and interpret the same data differently, generating results that are difficult to reconcile. To address these issues, we developed a coordinated set of pipelines, piPipes, to analyze piRNA and transposon-derived RNAs from a variety of high-throughput sequencing libraries, including small RNA, RNA, degradome or 7-methyl guanosine cap analysis of gene expression (CAGE), chromatin immunoprecipitation (ChIP) and genomic DNA-seq. piPipes can also produce figures and tables suitable for publication. By facilitating data analysis, piPipes provides an opportunity to standardize computational methods in the piRNA field.'),
(78803, 2015, 'bio', 'A novel representation of genomic sequences for taxonomic clustering and visualization by means of self-organizing maps', 'Delgado, Soledad|Morán, Federico|Mora, Antonio|Merelo, Juan Julián|Briones, Carlos', 'Department of Information Structure and Organization, Universidad Politécnica (UPM), Madrid 28031, Department of Biochemistry and Molecular Biology I, Universidad Complutense (UCM), Madrid 28040, Department of Computer Architecture and Computer Technology, Universidad de Granada (UGR), Granada 18071, Spain, CITIC, Campanillas, Malaga 29590, Spain, Department of Molecular Evolution, Centro de Astrobiología (CSIC-INTA), Torrejón de Ardoz, Madrid 28850 and Centro de Investigación Biomédica en Red de enfermedades hepáticas y digestivas (CIBERehd), Barcelona 08036, Spain.|Department of Information Structure and Organization, Universidad Politécnica (UPM), Madrid 28031, Department of Biochemistry and Molecular Biology I, Universidad Complutense (UCM), Madrid 28040, Department of Computer Architecture and Computer Technology, Universidad de Granada (UGR), Granada 18071, Spain, CITIC, Campanillas, Malaga 29590, Spain, Department of Molecular Evolution, Centro de Astrobiología (CSIC-INTA), Torrejón de Ardoz, Madrid 28850 and Centro de Investigación Biomédica en Red de enfermedades hepáticas y digestivas (CIBERehd), Barcelona 08036, Spain.|Department of Information Structure and Organization, Universidad Politécnica (UPM), Madrid 28031, Department of Biochemistry and Molecular Biology I, Universidad Complutense (UCM), Madrid 28040, Department of Computer Architecture and Computer Technology, Universidad de Granada (UGR), Granada 18071, Spain, CITIC, Campanillas, Malaga 29590, Spain, Department of Molecular Evolution, Centro de Astrobiología (CSIC-INTA), Torrejón de Ardoz, Madrid 28850 and Centro de Investigación Biomédica en Red de enfermedades hepáticas y digestivas (CIBERehd), Barcelona 08036, Spain Department of Information Structure and Organization, Universidad Politécnica (UPM), Madrid 28031, Department of Biochemistry and Molecular Biology I, Universidad Complutense (UCM), Madrid 28040, Department of Computer Architecture and Computer Technology, Universidad de Granada (UGR), Granada 18071, Spain, CITIC, Campanillas, Malaga 29590, Spain, Department of Molecular Evolution, Centro de Astrobiología (CSIC-INTA), Torrejón de Ardoz, Madrid 28850 and Centro de Investigación Biomédica en Red de enfermedades hepáticas y digestivas (CIBERehd), Barcelona 08036, Spain.|Department of Information Structure and Organization, Universidad Politécnica (UPM), Madrid 28031, Department of Biochemistry and Molecular Biology I, Universidad Complutense (UCM), Madrid 28040, Department of Computer Architecture and Computer Technology, Universidad de Granada (UGR), Granada 18071, Spain, CITIC, Campanillas, Malaga 29590, Spain, Department of Molecular Evolution, Centro de Astrobiología (CSIC-INTA), Torrejón de Ardoz, Madrid 28850 and Centro de Investigación Biomédica en Red de enfermedades hepáticas y digestivas (CIBERehd), Barcelona 08036, Spain Department of Information Structure and Organization, Universidad Politécnica (UPM), Madrid 28031, Department of Biochemistry and Molecular Biology I, Universidad Complutense (UCM), Madrid 28040, Department of Computer Architecture and Computer Technology, Universidad de Granada (UGR), Granada 18071, Spain, CITIC, Campanillas, Malaga 29590, Spain, Department of Molecular Evolution, Centro de Astrobiología (CSIC-INTA), Torrejón de Ardoz, Madrid 28850 and Centro de Investigación Biomédica en Red de enfermedades hepáticas y digestivas (CIBERehd), Barcelona 08036, Spain.|Department of Information Structure and Organization, Universidad Politécnica (UPM), Madrid 28031, Department of Biochemistry and Molecular Biology I, Universidad Complutense (UCM), Madrid 28040, Department of Computer Architecture and Computer Technology, Universidad de Granada (UGR), Granada 18071, Spain, CITIC, Campanillas, Malaga 29590, Spain, Department of Molecular Evolution, Centro de Astrobiología (CSIC-INTA), Torrejón de Ardoz, Madrid 28850 and Centro de Investigación Biomédica en Red de enfermedades hepáticas y digestivas (CIBERehd), Barcelona 08036, Spain Department of Information Structure and Organization, Universidad Politécnica (UPM), Madrid 28031, Department of Biochemistry and Molecular Biology I, Universidad Complutense (UCM), Madrid 28040, Department of Computer Architecture and Computer Technology, Universidad de Granada (UGR), Granada 18071, Spain, CITIC, Campanillas, Malaga 29590, Spain, Department of Molecular Evolution, Centro de Astrobiología (CSIC-INTA), Torrejón de Ardoz, Madrid 28850 and Centro de Investigación Biomédica en Red de enfermedades hepáticas y digestivas (CIBERehd), Barcelona 08036, Spain.', 'Spain|Spain|Spain|Spain|Spain', 10, 'Algorithms|Cluster Analysis|Computational Biology|Genome, Human|Genomics|Humans|Neural Networks (Computer)|Phylogeny|RNA, Ribosomal|Sequence Alignment|pol Gene Products, Human Immunodeficiency Virus', 'Journal Article', '10.1093/bioinformatics/btu708', '25344495', 'Self-organizing maps (SOMs) are readily available bioinformatics methods for clustering and visualizing high-dimensional data, provided that such biological information is previously transformed to fixed-size, metric-based vectors. To increase the usefulness of SOM-based approaches for the analysis of genomic sequence data, novel representation methods are required that automatically and objectively transform aligned nucleotide sequences into numeric vectors, dealing with both nucleotide ambiguity and gaps derived from sequence alignment.'),
(78804, 2015, 'bio', 'MP-GeneticSynth: inferring biological network regulations from time series', 'Castellini, Alberto|Paltrinieri, Daniele|Manca, Vincenzo', 'Center for BioMedical Computing, Verona University, 37134 Verona, Italy, Max Planck Institute for Molecular Plant Physiology-Syst Bio & Math Modelling Group, 14476, Germany, University of Potsdam, Institute for Biochemistry and Biology - Bioinformatics Group, 14476, Germany and Department of Computer Science, Verona University, 37134 Verona, Italy Center for BioMedical Computing, Verona University, 37134 Verona, Italy, Max Planck Institute for Molecular Plant Physiology-Syst Bio & Math Modelling Group, 14476, Germany, University of Potsdam, Institute for Biochemistry and Biology - Bioinformatics Group, 14476, Germany and Department of Computer Science, Verona University, 37134 Verona, Italy Center for BioMedical Computing, Verona University, 37134 Verona, Italy, Max Planck Institute for Molecular Plant Physiology-Syst Bio & Math Modelling Group, 14476, Germany, University of Potsdam, Institute for Biochemistry and Biology - Bioinformatics Group, 14476, Germany and Department of Computer Science, Verona University, 37134 Verona, Italy.|Center for BioMedical Computing, Verona University, 37134 Verona, Italy, Max Planck Institute for Molecular Plant Physiology-Syst Bio & Math Modelling Group, 14476, Germany, University of Potsdam, Institute for Biochemistry and Biology - Bioinformatics Group, 14476, Germany and Department of Computer Science, Verona University, 37134 Verona, Italy.|Center for BioMedical Computing, Verona University, 37134 Verona, Italy, Max Planck Institute for Molecular Plant Physiology-Syst Bio & Math Modelling Group, 14476, Germany, University of Potsdam, Institute for Biochemistry and Biology - Bioinformatics Group, 14476, Germany and Department of Computer Science, Verona University, 37134 Verona, Italy Center for BioMedical Computing, Verona University, 37134 Verona, Italy, Max Planck Institute for Molecular Plant Physiology-Syst Bio & Math Modelling Group, 14476, Germany, University of Potsdam, Institute for Biochemistry and Biology - Bioinformatics Group, 14476, Germany and Department of Computer Science, Verona University, 37134 Verona, Italy.', 'Germany|Germany|Germany', 0, 'Computational Biology|Databases, Factual|Gene Regulatory Networks|Humans|Metabolic Networks and Pathways|Models, Biological|Programming Languages|Software|Time Factors', 'Journal Article', '10.1093/bioinformatics/btu694', '25344496', 'MP-GeneticSynth is a Java tool for discovering the logic and regulation mechanisms responsible for observed biological dynamics in terms of finite difference recurrent equations. The software makes use of: (i) metabolic P systems as a modeling framework, (ii) an evolutionary approach to discover flux regulation functions as linear combinations of given primitive functions, (iii) a suitable reformulation of the least squares method to estimate function parameters considering simultaneously all the reactions involved in complex dynamics. The tool is available as a plugin for the virtual laboratory MetaPlab. It has graphical and interactive interfaces for data preparation, a priori knowledge integration, and flux regulator analysis. Availability and implementation: Source code, binaries, documentation (including quick start guide and videos) and case studies are freely available at http://mplab.sci.univr.it/plugins/mpgs/index.html.'),
(78805, 2015, 'bio', 'Semantic Body Browser: graphical exploration of an organism and spatially resolved expression data visualization', 'Lekschas, Fritz|Stachelscheid, Harald|Seltmann, Stefanie|Kurtz, Andreas', 'Berlin-Brandenburg Center for Regenerative Therapies, Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany and Seoul National University, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul 151-742, Republic of Korea.|Berlin-Brandenburg Center for Regenerative Therapies, Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany and Seoul National University, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul 151-742, Republic of Korea.|Berlin-Brandenburg Center for Regenerative Therapies, Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany and Seoul National University, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul 151-742, Republic of Korea.|Berlin-Brandenburg Center for Regenerative Therapies, Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany and Seoul National University, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul 151-742, Republic of Korea Berlin-Brandenburg Center for Regenerative Therapies, Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany and Seoul National University, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul 151-742, Republic of Korea.', 'Germany|Germany|Germany|Germany', 0, 'Computer Graphics|Gene Expression|Human Body|Humans|Information Storage and Retrieval|Internet|Male|Semantics|Software', 'Journal Article', '10.1093/bioinformatics/btu707', '25344497', 'Advancing technologies generate large amounts of molecular and phenotypic data on cells, tissues and organisms, leading to an ever-growing detail and complexity while information retrieval and analysis becomes increasingly time-consuming. The Semantic Body Browser is a web application for intuitively exploring the body of an organism from the organ to the subcellular level and visualising expression profiles by means of semantically annotated anatomical illustrations. It is used to comprehend biological and medical data related to the different body structures while relying on the strong pattern recognition capabilities of human users.'),
(78806, 2015, 'bio', 'Using 2kxe2x80x89+xe2x80x892 bubble searches to find single nucleotide polymorphisms in k-mer graphs', 'Younsi, Reda|MacLean, Dan', 'The Sainsbury Laboratory, Norwich Research Park, Norwich NR4 7UH, UK.|The Sainsbury Laboratory, Norwich Research Park, Norwich NR4 7UH, UK.', 'United Kingdom|United Kingdom', 5, 'Algorithms|Genome, Human|Genomics|Humans|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu706', '25344498', 'Single nucleotide polymorphism (SNP) discovery is an important preliminary for understanding genetic variation. With current sequencing methods, we can sample genomes comprehensively. SNPs are found by aligning sequence reads against longer assembled references. De Bruijn graphs are efficient data structures that can deal with the vast amount of data from modern technologies. Recent work has shown that the topology of these graphs captures enough information to allow the detection and characterization of genetic variants, offering an alternative to alignment-based methods. Such methods rely on depth-first walks of the graph to identify closing bifurcations. These methods are conservative or generate many false-positive results, particularly when traversing highly inter-connected (complex) regions of the graph or in regions of very high coverage.'),
(78807, 2015, 'bio', 'A coalescent-based method for population tree inference with haplotypes', 'Wu, Yufeng', 'Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269, USA.', 'United States', 0, 'Algorithms|Biological Evolution|Genetics, Population|Haplotypes|Humans|Likelihood Functions|Monte Carlo Method|Phylogeny|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btu710', '25344500', 'Population trees represent past population divergence histories. The inference of population trees can be useful for the study of population evolution. With the size of data increases in large-scale population genetic projects, such as the 1000 Genomes Project, there are new computational challenges for ancestral population inference, including population tree inference. Existing methods for population tree inference are mainly designed for unlinked genetic variants (e.g. single nucleotide polymorphisms or SNPs). There is a potential loss of information by not considering the haplotypes.'),
(78808, 2015, 'bio', 'iDoComp: a compression scheme for assembled genomes', 'Ochoa, Idoia|Hernaez, Mikel|Weissman, Tsachy', 'Department of Electrical Engineering, Stanford University, 350 Serra Mall, Stanford, CA.|Department of Electrical Engineering, Stanford University, 350 Serra Mall, Stanford, CA.|Department of Electrical Engineering, Stanford University, 350 Serra Mall, Stanford, CA.', '-|-|-', 0, 'Algorithms|Data Compression|Databases, Factual|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|Precision Medicine|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu698', '25344501', 'With the release of the latest next-generation sequencing (NGS) machine, the HiSeq X by Illumina, the cost of sequencing a Human has dropped to a mere $4000. Thus we are approaching a milestone in the sequencing history, known as the $1000 genome era, where the sequencing of individuals is affordable, opening the doors to effective personalized medicine. Massive generation of genomic data, including assembled genomes, is expected in the following years. There is crucial need for compression of genomes guaranteed of performing well simultaneously on different species, from simple bacteria to humans, which will ease their transmission, dissemination and analysis. Further, most of the new genomes to be compressed will correspond to individuals of a species from which a reference already exists on the database. Thus, it is natural to propose compression schemes that assume and exploit the availability of such references.'),
(78809, 2015, 'bio', 'SEABED: Small molEcule activity scanner weB servicE baseD', 'Fenollosa, Carlos|Otón, Marcel|Andrio, Pau|Cortés, Jorge|Orozco, Modesto|Goñi, J Ramon', 'Department of Life Sciences, Barcelona Supercomputing Center, Barcelona 08034, Spain, Joint BSC-CRG-IRB Program in Computational Biology, Barcelona, Spain, Computational Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08034, Spain, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain, Department of Biochemistry and Molecular Biology, Biology Faculty, University of Barcelona, Barcelona 08028, Spain and Structural Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08028, Spain Department of Life Sciences, Barcelona Supercomputing Center, Barcelona 08034, Spain, Joint BSC-CRG-IRB Program in Computational Biology, Barcelona, Spain, Computational Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08034, Spain, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain, Department of Biochemistry and Molecular Biology, Biology Faculty, University of Barcelona, Barcelona 08028, Spain and Structural Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08028, Spain.|Department of Life Sciences, Barcelona Supercomputing Center, Barcelona 08034, Spain, Joint BSC-CRG-IRB Program in Computational Biology, Barcelona, Spain, Computational Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08034, Spain, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain, Department of Biochemistry and Molecular Biology, Biology Faculty, University of Barcelona, Barcelona 08028, Spain and Structural Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08028, Spain Department of Life Sciences, Barcelona Supercomputing Center, Barcelona 08034, Spain, Joint BSC-CRG-IRB Program in Computational Biology, Barcelona, Spain, Computational Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08034, Spain, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain, Department of Biochemistry and Molecular Biology, Biology Faculty, University of Barcelona, Barcelona 08028, Spain and Structural Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08028, Spain.|Department of Life Sciences, Barcelona Supercomputing Center, Barcelona 08034, Spain, Joint BSC-CRG-IRB Program in Computational Biology, Barcelona, Spain, Computational Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08034, Spain, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain, Department of Biochemistry and Molecular Biology, Biology Faculty, University of Barcelona, Barcelona 08028, Spain and Structural Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08028, Spain Department of Life Sciences, Barcelona Supercomputing Center, Barcelona 08034, Spain, Joint BSC-CRG-IRB Program in Computational Biology, Barcelona, Spain, Computational Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08034, Spain, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain, Department of Biochemistry and Molecular Biology, Biology Faculty, University of Barcelona, Barcelona 08028, Spain and Structural Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08028, Spain Department of Life Sciences, Barcelona Supercomputing Center, Barcelona 08034, Spain, Joint BSC-CRG-IRB Program in Computational Biology, Barcelona, Spain, Computational Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08034, Spain, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain, Department of Biochemistry and Molecular Biology, Biology Faculty, University of Barcelona, Barcelona 08028, Spain and Structural Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08028, Spain.|Department of Life Sciences, Barcelona Supercomputing Center, Barcelona 08034, Spain, Joint BSC-CRG-IRB Program in Computational Biology, Barcelona, Spain, Computational Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08034, Spain, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain, Department of Biochemistry and Molecular Biology, Biology Faculty, University of Barcelona, Barcelona 08028, Spain and Structural Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08028, Spain Department of Life Sciences, Barcelona Supercomputing Center, Barcelona 08034, Spain, Joint BSC-CRG-IRB Program in Computational Biology, Barcelona, Spain, Computational Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08034, Spain, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain, Department of Biochemistry and Molecular Biology, Biology Faculty, University of Barcelona, Barcelona 08028, Spain and Structural Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08028, Spain.|Department of Life Sciences, Barcelona Supercomputing Center, Barcelona 08034, Spain, Joint BSC-CRG-IRB Program in Computational Biology, Barcelona, Spain, Computational Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08034, Spain, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain, Department of Biochemistry and Molecular Biology, Biology Faculty, University of Barcelona, Barcelona 08028, Spain and Structural Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08028, Spain Department of Life Sciences, Barcelona Supercomputing Center, Barcelona 08034, Spain, Joint BSC-CRG-IRB Program in Computational Biology, Barcelona, Spain, Computational Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08034, Spain, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain, Department of Biochemistry and Molecular Biology, Biology Faculty, University of Barcelona, Barcelona 08028, Spain and Structural Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08028, Spain Department of Life Sciences, Barcelona Supercomputing Center, Barcelona 08034, Spain, Joint BSC-CRG-IRB Program in Computational Biology, Barcelona, Spain, Computational Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08034, Spain, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain, Department of Biochemistry and Molecular Biology, Biology Faculty, University of Barcelona, Barcelona 08028, Spain and Structural Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08028, Spain Department of Life Sciences, Barcelona Supercomputing Center, Barcelona 08034, Spain, Joint BSC-CRG-IRB Program in Computational Biology, Barcelona, Spain, Computational Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08034, Spain, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain, Department of Biochemistry and Molec|Department of Life Sciences, Barcelona Supercomputing Center, Barcelona 08034, Spain, Joint BSC-CRG-IRB Program in Computational Biology, Barcelona, Spain, Computational Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08034, Spain, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain, Department of Biochemistry and Molecular Biology, Biology Faculty, University of Barcelona, Barcelona 08028, Spain and Structural Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08028, Spain Department of Life Sciences, Barcelona Supercomputing Center, Barcelona 08034, Spain, Joint BSC-CRG-IRB Program in Computational Biology, Barcelona, Spain, Computational Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08034, Spain, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain, Department of Biochemistry and Molecular Biology, Biology Faculty, University of Barcelona, Barcelona 08028, Spain and Structural Bioinformatics Node, National Institute of Bioinformatics, Barcelona 08028, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain', 3, 'Databases, Factual|Drug Design|Drug Discovery|Humans|Molecular Docking Simulation|Mutation|Peptide Library|Protein Structure, Tertiary|Proteins|Quantitative Structure-Activity Relationship|Small Molecule Libraries|Software|Workflow', 'Journal Article', '10.1093/bioinformatics/btu709', '25348211', 'The SEABED web server integrates a variety of docking and QSAR techniques in a user-friendly environment. SEABED goes beyond the basic docking and QSAR web tools and implements extended functionalities like receptor preparation, library editing, flexible ensemble docking, hybrid docking/QSAR experiments or virtual screening on protein mutants. SEABED is not a monolithic workflow tool but Software as a Service platform.'),
(78810, 2015, 'bio', 'Navigating protected genomics data with UCSC Genome Browser in a Box', 'Haeussler, Maximilian|Raney, Brian J|Hinrichs, Angie S|Clawson, Hiram|Zweig, Ann S|Karolchik, Donna|Casper, Jonathan|Speir, Matthew L|Haussler, David|Kent, W James', 'Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA.|Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA.|Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA.|Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA.|Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA.|Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA.|Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA.|Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA.|Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA.|Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA and Howard Hughes Medical Institute, University of California Santa Cruz, 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', 0, 'Computational Biology|Databases, Genetic|Genome, Human|Genomics|Humans|Information Storage and Retrieval|Internet|Sequence Analysis, DNA|Software|Universities|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu712', '25348212', 'Genome Browser in a Box (GBiB) is a small virtual machine version of the popular University of California Santa Cruz (UCSC) Genome Browser that can be run on a researchers own computer. Once GBiB is installed, a standard web browser is used to access the virtual server and add personal data files from the local hard disk. Annotation data are loaded on demand through the Internet from UCSC or can be downloaded to the local computer for faster access.'),
(78811, 2015, 'bio', 'DIANA--algorithmic improvements for analysis of data-independent acquisition MS data', 'Teleman, Johan|Röst, Hannes L|Rosenberger, George|Schmitt, Uwe|Malmström, Lars|Malmström, Johan|Levander, Fredrik', 'Department of Clinical Sciences, Lund University, BMC B14 221 84 Lund, Department of Immunotechnology, Lund University, Medicon Village (Building 406) 223 81 Lund, Sweden, Department of Biology, Institute of Molecular Systems Biology, ITS Scientific IT Services, ETH Zurich and SIT, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland Department of Clinical Sciences, Lund University, BMC B14 221 84 Lund, Department of Immunotechnology, Lund University, Medicon Village (Building 406) 223 81 Lund, Sweden, Department of Biology, Institute of Molecular Systems Biology, ITS Scientific IT Services, ETH Zurich and SIT, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland.|Department of Clinical Sciences, Lund University, BMC B14 221 84 Lund, Department of Immunotechnology, Lund University, Medicon Village (Building 406) 223 81 Lund, Sweden, Department of Biology, Institute of Molecular Systems Biology, ITS Scientific IT Services, ETH Zurich and SIT, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland.|Department of Clinical Sciences, Lund University, BMC B14 221 84 Lund, Department of Immunotechnology, Lund University, Medicon Village (Building 406) 223 81 Lund, Sweden, Department of Biology, Institute of Molecular Systems Biology, ITS Scientific IT Services, ETH Zurich and SIT, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland.|Department of Clinical Sciences, Lund University, BMC B14 221 84 Lund, Department of Immunotechnology, Lund University, Medicon Village (Building 406) 223 81 Lund, Sweden, Department of Biology, Institute of Molecular Systems Biology, ITS Scientific IT Services, ETH Zurich and SIT, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland.|Department of Clinical Sciences, Lund University, BMC B14 221 84 Lund, Department of Immunotechnology, Lund University, Medicon Village (Building 406) 223 81 Lund, Sweden, Department of Biology, Institute of Molecular Systems Biology, ITS Scientific IT Services, ETH Zurich and SIT, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland.|Department of Clinical Sciences, Lund University, BMC B14 221 84 Lund, Department of Immunotechnology, Lund University, Medicon Village (Building 406) 223 81 Lund, Sweden, Department of Biology, Institute of Molecular Systems Biology, ITS Scientific IT Services, ETH Zurich and SIT, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland.|Department of Clinical Sciences, Lund University, BMC B14 221 84 Lund, Department of Immunotechnology, Lund University, Medicon Village (Building 406) 223 81 Lund, Sweden, Department of Biology, Institute of Molecular Systems Biology, ITS Scientific IT Services, ETH Zurich and SIT, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Algorithms|Bacterial Proteins|Data Mining|Databases, Protein|Humans|Markov Chains|Peptide Fragments|Proteomics|Software|Streptococcus pyogenes|Tandem Mass Spectrometry', 'Journal Article', '10.1093/bioinformatics/btu686', '25348213', 'Data independent acquisition mass spectrometry has emerged as a reproducible and sensitive alternative in quantitative proteomics, where parsing the highly complex tandem mass spectra requires dedicated algorithms. Recently, targeted data extraction was proposed as a novel analysis strategy for this type of data, but it is important to further develop these concepts to provide quality-controlled, interference-adjusted and sensitive peptide quantification.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78812, 2015, 'bio', 'PPDMs-a resource for mapping small molecule bioactivities from ChEMBL to Pfam-A protein domains', 'Kruger, Felix A|Gaulton, Anna|Nowotka, Michal|Overington, John P', 'ChEMBL group, EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, UK.|ChEMBL group, EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, UK.|ChEMBL group, EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, UK.|ChEMBL group, EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Databases, Chemical|Databases, Protein|Drug Discovery|Humans|Protein Structure, Tertiary|Proteins|Small Molecule Libraries|Software', 'Journal Article', '10.1093/bioinformatics/btu711', '25348214', 'PPDMs is a resource that maps small molecule bioactivities to protein domains from the Pfam-A collection of protein families. Small molecule bioactivities mapped to protein domains add important precision to approaches that use protein sequence searches alignments to assist applications in computational drug discovery and systems and chemical biology. We have previously proposed a mapping heuristic for a subset of bioactivities stored in ChEMBL with the Pfam-A domain most likely to mediate small molecule binding. We have since refined this mapping using a manual procedure. Here, we present a resource that provides up-to-date mappings and the possibility to review assigned mappings as well as to participate in their assignment and curation. We also describe how mappings provided through the PPDMs resource are made accessible through the main schema of the ChEMBL database.'),
(78813, 2015, 'bio', 'MetMSLine: an automated and fully integrated pipeline for rapid processing of high-resolution LC-MS metabolomic datasets', 'Edmands, William M B|Barupal, Dinesh K|Scalbert, Augustin', 'Department of Biomarkers, Nutrition and Metabolism Section, International Agency for Research on Cancer (IARC), F-69372 Cedex 08, Lyon, France.|Department of Biomarkers, Nutrition and Metabolism Section, International Agency for Research on Cancer (IARC), F-69372 Cedex 08, Lyon, France.|Department of Biomarkers, Nutrition and Metabolism Section, International Agency for Research on Cancer (IARC), F-69372 Cedex 08, Lyon, France.', 'France|France|France', 0, 'Automation|Chromatography, Liquid|Databases, Factual|Datasets as Topic|Electronic Data Processing|Humans|Metabolomics|Programming Languages|Software|Tandem Mass Spectrometry', 'Journal Article', '10.1093/bioinformatics/btu705', '25348215', 'MetMSLine represents a complete collection of functions in the R programming language as an accessible GUI for biomarker discovery in large-scale liquid-chromatography high-resolution mass spectral datasets from acquisition through to final metabolite identification forming a backend to output from any peak-picking software such as XCMS. MetMSLine automatically creates subdirectories, data tables and relevant figures at the following steps: (i) signal smoothing, normalization, filtration and noise transformation (PreProc.QC.LSC.R), (ii) PCA and automatic outlier removal (Auto.PCA.R), (iii) automatic regression, biomarker selection, hierarchical clustering and cluster ion/artefact identification (Auto.MV.Regress.R), (iv) Biomarker-MS/MS fragmentation spectra matching and fragment/neutral loss annotation (Auto.MS.MS.match.R) and (v) semi-targeted metabolite identification based on a list of theoretical masses obtained from public databases (DBAnnotate.R).'),
(78814, 2015, 'bio', 'WebPSN: a web server for high-throughput investigation of structural communication in biomacromolecules', 'Seeber, Michele|Felline, Angelo|Raimondi, Francesco|Mariani, Simona|Fanelli, Francesca', 'Department of Life Sciences, University of Modena and Reggio Emilia, via Campi 183, 41125 Modena, Italy.|Department of Life Sciences, University of Modena and Reggio Emilia, via Campi 183, 41125 Modena, Italy.|Department of Life Sciences, University of Modena and Reggio Emilia, via Campi 183, 41125 Modena, Italy.|Department of Life Sciences, University of Modena and Reggio Emilia, via Campi 183, 41125 Modena, Italy.|Department of Life Sciences, University of Modena and Reggio Emilia, via Campi 183, 41125 Modena, Italy.', 'Italy|Italy|Italy|Italy|Italy', 20, 'High-Throughput Screening Assays|Humans|Internet|Molecular Dynamics Simulation|Protein Interaction Domains and Motifs|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Structural Homology, Protein', 'Journal Article', '10.1093/bioinformatics/btu718', '25355786', 'We developed a mixed Protein Structure Network (PSN) and Elastic Network Model-Normal Mode Analysis (ENM-NMA)-based strategy (i.e. PSN-ENM) to investigate structural communication in biomacromolecules. The approach starts from a Protein Structure Graph and searches for all shortest communication pathways between user-specified residues. The graph is computed on a single preferably high-resolution structure. Information on systems dynamics is supplied by ENM-NMA. The PSN-ENM methodology is made of multiple steps both in the setup and analysis stages, which may discourage inexperienced users. To facilitate its usage, we implemented WebPSN, a freely available web server that allows the user to easily setup the calculation, perform post-processing analyses and both visualize and download numerical and 3D representations of the output. Speed and accuracy make this server suitable to investigate structural communication, including allosterism, in large sets of bio-macromolecular systems.'),
(78815, 2014, 'bio', 'KmerStream: streaming algorithms for k-mer abundance estimation', 'Melsted, Páll|Halldórsson, Bjarni V', 'Faculty of Industrial Engineering, Mechanical Engineering and Computer Science, University of Iceland, Reykjavík, Iceland, deCODE Genetics/Amgen, Reykjavík, Iceland and School of Science and Engineering, Reykjavík University, Reykjavík, Iceland Faculty of Industrial Engineering, Mechanical Engineering and Computer Science, University of Iceland, Reykjavík, Iceland, deCODE Genetics/Amgen, Reykjavík, Iceland and School of Science and Engineering, Reykjavík University, Reykjavík, Iceland.|Faculty of Industrial Engineering, Mechanical Engineering and Computer Science, University of Iceland, Reykjavík, Iceland, deCODE Genetics/Amgen, Reykjavík, Iceland and School of Science and Engineering, Reykjavík University, Reykjavík, Iceland Faculty of Industrial Engineering, Mechanical Engineering and Computer Science, University of Iceland, Reykjavík, Iceland, deCODE Genetics/Amgen, Reykjavík, Iceland and School of Science and Engineering, Reykjavík University, Reykjavík, Iceland.', 'Iceland|Iceland', 21, 'Algorithms|Genome Size|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu713', '25355787', 'Several applications in bioinformatics, such as genome assemblers and error corrections methods, rely on counting and keeping track of k-mers (substrings of length k). Histograms of k-mer frequencies can give valuable insight into the underlying distribution and indicate the error rate and genome size sampled in the sequencing experiment.'),
(78816, 2015, 'bio', 'Automatic prediction of polysaccharide utilization loci in Bacteroidetes species', 'Terrapon, Nicolas|Lombard, Vincent|Gilbert, Harry J|Henrissat, Bernard', 'Centre National de la Recherche Scientifique, CNRS UMR 7257, 13288 Marseille, France, Aix-Marseille Université, AFMB, 13288 Marseille, France, Institute for Cell and Molecular Biosciences, The Medical School, Newcastle University, Newcastle upon Tyne NE2 4HH, UK and Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia Centre National de la Recherche Scientifique, CNRS UMR 7257, 13288 Marseille, France, Aix-Marseille Université, AFMB, 13288 Marseille, France, Institute for Cell and Molecular Biosciences, The Medical School, Newcastle University, Newcastle upon Tyne NE2 4HH, UK and Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.|Centre National de la Recherche Scientifique, CNRS UMR 7257, 13288 Marseille, France, Aix-Marseille Université, AFMB, 13288 Marseille, France, Institute for Cell and Molecular Biosciences, The Medical School, Newcastle University, Newcastle upon Tyne NE2 4HH, UK and Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.|Centre National de la Recherche Scientifique, CNRS UMR 7257, 13288 Marseille, France, Aix-Marseille Université, AFMB, 13288 Marseille, France, Institute for Cell and Molecular Biosciences, The Medical School, Newcastle University, Newcastle upon Tyne NE2 4HH, UK and Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.|Centre National de la Recherche Scientifique, CNRS UMR 7257, 13288 Marseille, France, Aix-Marseille Université, AFMB, 13288 Marseille, France, Institute for Cell and Molecular Biosciences, The Medical School, Newcastle University, Newcastle upon Tyne NE2 4HH, UK and Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia Centre National de la Recherche Scientifique, CNRS UMR 7257, 13288 Marseille, France, Aix-Marseille Université, AFMB, 13288 Marseille, France, Institute for Cell and Molecular Biosciences, The Medical School, Newcastle University, Newcastle upon Tyne NE2 4HH, UK and Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.', 'France|France|France|France', 83, 'Animals|Automation|Bacteroidetes|Dogs|Gastrointestinal Tract|Genetic Loci|Genome, Bacterial|Humans|Microbiota|Polysaccharides|Symbiosis', 'Journal Article', '10.1093/bioinformatics/btu716', '25355788', 'A bacterial polysaccharide utilization locus (PUL) is a set of physically linked genes that orchestrate the breakdown of a specific glycan. PULs are prevalent in the Bacteroidetes phylum and are key to the digestion of complex carbohydrates, notably by the human gut microbiota. A given Bacteroidetes genome can encode dozens of different PULs whose boundaries and precise gene content are difficult to predict.'),
(78817, 2014, 'bio', 'Characterization of structural variants with single molecule and hybrid sequencing approaches', 'Ritz, Anna|Bashir, Ali|Sindi, Suzanne|Hsu, David|Hajirasouliha, Iman|Raphael, Benjamin J', 'Department of Computer Science, Brown University, RI Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, NY Institute for Genomics and Multiscale Biology, Icahn School of Medicine, Mount Sinai, NY School of Natural Sciences, University of California, Merced, CA Pacific Biosciences, Menlo Park, CA Center for Computational Molecular Biology, Brown University, RI.|Department of Computer Science, Brown University, RI Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, NY Institute for Genomics and Multiscale Biology, Icahn School of Medicine, Mount Sinai, NY School of Natural Sciences, University of California, Merced, CA Pacific Biosciences, Menlo Park, CA Center for Computational Molecular Biology, Brown University, RI Department of Computer Science, Brown University, RI Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, NY Institute for Genomics and Multiscale Biology, Icahn School of Medicine, Mount Sinai, NY School of Natural Sciences, University of California, Merced, CA Pacific Biosciences, Menlo Park, CA Center for Computational Molecular Biology, Brown University, RI.|Department of Computer Science, Brown University, RI Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, NY Institute for Genomics and Multiscale Biology, Icahn School of Medicine, Mount Sinai, NY School of Natural Sciences, University of California, Merced, CA Pacific Biosciences, Menlo Park, CA Center for Computational Molecular Biology, Brown University, RI.|Department of Computer Science, Brown University, RI Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, NY Institute for Genomics and Multiscale Biology, Icahn School of Medicine, Mount Sinai, NY School of Natural Sciences, University of California, Merced, CA Pacific Biosciences, Menlo Park, CA Center for Computational Molecular Biology, Brown University, RI.|Department of Computer Science, Brown University, RI Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, NY Institute for Genomics and Multiscale Biology, Icahn School of Medicine, Mount Sinai, NY School of Natural Sciences, University of California, Merced, CA Pacific Biosciences, Menlo Park, CA Center for Computational Molecular Biology, Brown University, RI.|Department of Computer Science, Brown University, RI Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, NY Institute for Genomics and Multiscale Biology, Icahn School of Medicine, Mount Sinai, NY School of Natural Sciences, University of California, Merced, CA Pacific Biosciences, Menlo Park, CA Center for Computational Molecular Biology, Brown University, RI Department of Computer Science, Brown University, RI Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, NY Institute for Genomics and Multiscale Biology, Icahn School of Medicine, Mount Sinai, NY School of Natural Sciences, University of California, Merced, CA Pacific Biosciences, Menlo Park, CA Center for Computational Molecular Biology, Brown University, RI.', '-|-|-|-|-|-', 37, 'Algorithms|Genomic Structural Variation|Genomics|High-Throughput Nucleotide Sequencing|Humans|Repetitive Sequences, Nucleic Acid|Sequence Analysis, DNA|Sequence Deletion', 'Journal Article', '10.1093/bioinformatics/btu714', '25355789', 'Structural variation is common in human and cancer genomes. High-throughput DNA sequencing has enabled genome-scale surveys of structural variation. However, the short reads produced by these technologies limit the study of complex variants, particularly those involving repetitive regions. Recent third-generation sequencing technologies provide single-molecule templates and longer sequencing reads, but at the cost of higher per-nucleotide error rates.'),
(78818, 2015, 'bio', 'Detecting time periods of differential gene expression using Gaussian processes: an application to endothelial cells exposed to radiotherapy dose fraction', 'Heinonen, Markus|Guipaud, Olivier|Milliat, Fabien|Buard, Valérie|Micheau, Béatrice|Tarlet, Georges|Benderitter, Marc|Zehraoui, Farida|dAlché-Buc, Florence', 'IBISC, Universite dÉvry Val dEssonne, 23 Boulevard de France, 91025 Évry, France, AMIB, INRIA-Saclay, LRI UMR CNRS 8623, Université Paris Sud, Orsay, France, and Institut de Radioprotection et de Sûreté Nucléaire, LRTE, 92262 Fontenay-aux-roses, France IBISC, Universite dÉvry Val dEssonne, 23 Boulevard de France, 91025 Évry, France, AMIB, INRIA-Saclay, LRI UMR CNRS 8623, Université Paris Sud, Orsay, France, and Institut de Radioprotection et de Sûreté Nucléaire, LRTE, 92262 Fontenay-aux-roses, France.|IBISC, Universite dÉvry Val dEssonne, 23 Boulevard de France, 91025 Évry, France, AMIB, INRIA-Saclay, LRI UMR CNRS 8623, Université Paris Sud, Orsay, France, and Institut de Radioprotection et de Sûreté Nucléaire, LRTE, 92262 Fontenay-aux-roses, France.|IBISC, Universite dÉvry Val dEssonne, 23 Boulevard de France, 91025 Évry, France, AMIB, INRIA-Saclay, LRI UMR CNRS 8623, Université Paris Sud, Orsay, France, and Institut de Radioprotection et de Sûreté Nucléaire, LRTE, 92262 Fontenay-aux-roses, France.|IBISC, Universite dÉvry Val dEssonne, 23 Boulevard de France, 91025 Évry, France, AMIB, INRIA-Saclay, LRI UMR CNRS 8623, Université Paris Sud, Orsay, France, and Institut de Radioprotection et de Sûreté Nucléaire, LRTE, 92262 Fontenay-aux-roses, France.|IBISC, Universite dÉvry Val dEssonne, 23 Boulevard de France, 91025 Évry, France, AMIB, INRIA-Saclay, LRI UMR CNRS 8623, Université Paris Sud, Orsay, France, and Institut de Radioprotection et de Sûreté Nucléaire, LRTE, 92262 Fontenay-aux-roses, France.|IBISC, Universite dÉvry Val dEssonne, 23 Boulevard de France, 91025 Évry, France, AMIB, INRIA-Saclay, LRI UMR CNRS 8623, Université Paris Sud, Orsay, France, and Institut de Radioprotection et de Sûreté Nucléaire, LRTE, 92262 Fontenay-aux-roses, France.|IBISC, Universite dÉvry Val dEssonne, 23 Boulevard de France, 91025 Évry, France, AMIB, INRIA-Saclay, LRI UMR CNRS 8623, Université Paris Sud, Orsay, France, and Institut de Radioprotection et de Sûreté Nucléaire, LRTE, 92262 Fontenay-aux-roses, France.|IBISC, Universite dÉvry Val dEssonne, 23 Boulevard de France, 91025 Évry, France, AMIB, INRIA-Saclay, LRI UMR CNRS 8623, Université Paris Sud, Orsay, France, and Institut de Radioprotection et de Sûreté Nucléaire, LRTE, 92262 Fontenay-aux-roses, France.|IBISC, Universite dÉvry Val dEssonne, 23 Boulevard de France, 91025 Évry, France, AMIB, INRIA-Saclay, LRI UMR CNRS 8623, Université Paris Sud, Orsay, France, and Institut de Radioprotection et de Sûreté Nucléaire, LRTE, 92262 Fontenay-aux-roses, France IBISC, Universite dÉvry Val dEssonne, 23 Boulevard de France, 91025 Évry, France, AMIB, INRIA-Saclay, LRI UMR CNRS 8623, Université Paris Sud, Orsay, France, and Institut de Radioprotection et de Sûreté Nucléaire, LRTE, 92262 Fontenay-aux-roses, France.', 'France|France|France|France|France|France|France|France|France', 16, 'Bayes Theorem|Cells, Cultured|Dose-Response Relationship, Radiation|Gene Expression Profiling|Gene Expression Regulation|Human Umbilical Vein Endothelial Cells|Humans|Neoplasms|Normal Distribution|Oligonucleotide Array Sequence Analysis|Radiotherapy|Time Factors', 'Journal Article', '10.1093/bioinformatics/btu699', '25355790', 'Identifying the set of genes differentially expressed along time is an important task in two-sample time course experiments. Furthermore, estimating at which time periods the differential expression is present can provide additional insight into temporal gene functions. The current differential detection methods are designed to detect difference along observation time intervals or on single measurement points, warranting dense measurements along time to characterize the full temporal differential expression patterns.'),
(78819, 2015, 'bio', 'Automated structural classification of lipids by machine learning', 'Taylor, Ryan|Miller, Ryan H|Miller, Ryan D|Porter, Michael|Dalgleish, James|Prince, John T', 'Department of Chemistry and Biochemistry and Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA.|Department of Chemistry and Biochemistry and Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA.|Department of Chemistry and Biochemistry and Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA.|Department of Chemistry and Biochemistry and Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA.|Department of Chemistry and Biochemistry and Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA.|Department of Chemistry and Biochemistry and Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA.', 'United States|United States|United States|United States|United States|United States', 2, 'Algorithms|Artificial Intelligence|Automation|Databases, Factual|Decision Trees|Humans|Lipids|Programming Languages', 'Journal Article', '10.1093/bioinformatics/btu723', '25359887', 'Modern lipidomics is largely dependent upon structural ontologies because of the great diversity exhibited in the lipidome, but no automated lipid classification exists to facilitate this partitioning. The size of the putative lipidome far exceeds the number currently classified, despite a decade of work. Automated classification would benefit ongoing classification efforts by decreasing the time needed and increasing the accuracy of classification while providing classifications for mass spectral identification algorithms.'),
(78820, 2015, 'bio', 'Large-scale binding ligand prediction by improved patch-based method Patch-Surfer20', 'Zhu, Xiaolei|Xiong, Yi|Kihara, Daisuke', 'Department of Biological Science, Purdue University, West Lafayette, IN 47906, USA and Department of Computer Science, Purdue University, West Lafayette, IN 47906, USA.|Department of Biological Science, Purdue University, West Lafayette, IN 47906, USA and Department of Computer Science, Purdue University, West Lafayette, IN 47906, USA.|Department of Biological Science, Purdue University, West Lafayette, IN 47906, USA and Department of Computer Science, Purdue University, West Lafayette, IN 47906, USA Department of Biological Science, Purdue University, West Lafayette, IN 47906, USA and Department of Computer Science, Purdue University, West Lafayette, IN 47906, USA.', 'United States|United States|United States', 28, 'Algorithms|Binding Sites|Computer Simulation|Humans|Ligands|Mathematical Computing|Protein Conformation|Proteins', 'Journal Article', '10.1093/bioinformatics/btu724', '25359888', 'Ligand binding is a key aspect of the function of many proteins. Thus, binding ligand prediction provides important insight in understanding the biological function of proteins. Binding ligand prediction is also useful for drug design and examining potential drug side effects.'),
(78821, 2015, 'bio', 'Computational framework for next-generation sequencing of heterogeneous viral populations using combinatorial pooling', 'Skums, Pavel|Artyomenko, Alexander|Glebova, Olga|Ramachandran, Sumathi|Mandoiu, Ion|Campo, David S|Dimitrova, Zoya|Zelikovsky, Alex|Khudyakov, Yury', 'Division of Viral Hepatitis, Centers of Disease Control and Prevention, Atlanta, GA, USA, Department of Computer Science, Georgia State University, Atlanta, GA, USA and Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA.|Division of Viral Hepatitis, Centers of Disease Control and Prevention, Atlanta, GA, USA, Department of Computer Science, Georgia State University, Atlanta, GA, USA and Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA.|Division of Viral Hepatitis, Centers of Disease Control and Prevention, Atlanta, GA, USA, Department of Computer Science, Georgia State University, Atlanta, GA, USA and Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA.|Division of Viral Hepatitis, Centers of Disease Control and Prevention, Atlanta, GA, USA, Department of Computer Science, Georgia State University, Atlanta, GA, USA and Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA.|Division of Viral Hepatitis, Centers of Disease Control and Prevention, Atlanta, GA, USA, Department of Computer Science, Georgia State University, Atlanta, GA, USA and Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA.|Division of Viral Hepatitis, Centers of Disease Control and Prevention, Atlanta, GA, USA, Department of Computer Science, Georgia State University, Atlanta, GA, USA and Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA.|Division of Viral Hepatitis, Centers of Disease Control and Prevention, Atlanta, GA, USA, Department of Computer Science, Georgia State University, Atlanta, GA, USA and Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA.|Division of Viral Hepatitis, Centers of Disease Control and Prevention, Atlanta, GA, USA, Department of Computer Science, Georgia State University, Atlanta, GA, USA and Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA.|Division of Viral Hepatitis, Centers of Disease Control and Prevention, Atlanta, GA, USA, Department of Computer Science, Georgia State University, Atlanta, GA, USA and Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA.', 'Georgia|Georgia|Georgia|Georgia|Georgia|Georgia|Georgia|Georgia|Georgia', 10, 'Algorithms|Computational Biology|DNA, Viral|Genetic Variation|Genome, Viral|Hepacivirus|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA|Viruses', 'Journal Article', '10.1093/bioinformatics/btu726', '25359889', 'Next-generation sequencing (NGS) allows for analyzing a large number of viral sequences from infected patients, providing an opportunity to implement large-scale molecular surveillance of viral diseases. However, despite improvements in technology, traditional protocols for NGS of large numbers of samples are still highly cost and labor intensive. One of the possible cost-effective alternatives is combinatorial pooling. Although a number of pooling strategies for consensus sequencing of DNA samples and detection of SNPs have been proposed, these strategies cannot be applied to sequencing of highly heterogeneous viral populations.'),
(78822, 2015, 'bio', 'Measuring the wisdom of the crowds in network-based gene function inference', 'Verleyen, W|Ballouz, S|Gillis, J', 'Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Woodbury, NY 11797, USA.|Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Woodbury, NY 11797, USA.|Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Woodbury, NY 11797, USA.', 'United States|United States|United States', 10, 'Algorithms|Computational Biology|Databases, Protein|Gene Regulatory Networks|Humans|Metabolic Networks and Pathways|Models, Genetic|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btu715', '25359890', 'Network-based gene function inference methods have proliferated in recent years, but measurable progress remains elusive. We wished to better explore performance trends by controlling data and algorithm implementation, with a particular focus on the performance of aggregate predictions.'),
(78823, 2014, 'bio', 'TIPP: taxonomic identification and phylogenetic profiling', 'Nguyen, Nam-Phuong|Mirarab, Siavash|Liu, Bo|Pop, Mihai|Warnow, Tandy', 'Department of Computer Science, The University of Texas at Austin, Austin, TX USA, Center for Bioinformatics and Computational Biology, University of Maryland at College Park, College Park, MD USA, Department of Bioengineering, The University of Illinois at Urbana-Champaign, Urbana, IL USA and Department of Computer Science, The University of Illinois at Urbana-Champaign, Urbana, IL USA.|Department of Computer Science, The University of Texas at Austin, Austin, TX USA, Center for Bioinformatics and Computational Biology, University of Maryland at College Park, College Park, MD USA, Department of Bioengineering, The University of Illinois at Urbana-Champaign, Urbana, IL USA and Department of Computer Science, The University of Illinois at Urbana-Champaign, Urbana, IL USA.|Department of Computer Science, The University of Texas at Austin, Austin, TX USA, Center for Bioinformatics and Computational Biology, University of Maryland at College Park, College Park, MD USA, Department of Bioengineering, The University of Illinois at Urbana-Champaign, Urbana, IL USA and Department of Computer Science, The University of Illinois at Urbana-Champaign, Urbana, IL USA.|Department of Computer Science, The University of Texas at Austin, Austin, TX USA, Center for Bioinformatics and Computational Biology, University of Maryland at College Park, College Park, MD USA, Department of Bioengineering, The University of Illinois at Urbana-Champaign, Urbana, IL USA and Department of Computer Science, The University of Illinois at Urbana-Champaign, Urbana, IL USA.|Department of Computer Science, The University of Texas at Austin, Austin, TX USA, Center for Bioinformatics and Computational Biology, University of Maryland at College Park, College Park, MD USA, Department of Bioengineering, The University of Illinois at Urbana-Champaign, Urbana, IL USA and Department of Computer Science, The University of Illinois at Urbana-Champaign, Urbana, IL USA Department of Computer Science, The University of Texas at Austin, Austin, TX USA, Center for Bioinformatics and Computational Biology, University of Maryland at College Park, College Park, MD USA, Department of Bioengineering, The University of Illinois at Urbana-Champaign, Urbana, IL USA and Department of Computer Science, The University of Illinois at Urbana-Champaign, Urbana, IL USA Department of Computer Science, The University of Texas at Austin, Austin, TX USA, Center for Bioinformatics and Computational Biology, University of Maryland at College Park, College Park, MD USA, Department of Bioengineering, The University of Illinois at Urbana-Champaign, Urbana, IL USA and Department of Computer Science, The University of Illinois at Urbana-Champaign, Urbana, IL USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|INDEL Mutation|Metagenomics|Phylogeny|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btu721', '25359891', 'Abundance profiling (also called phylogenetic profiling) is a crucial step in understanding the diversity of a metagenomic sample, and one of the basic techniques used for this is taxonomic identification of the metagenomic reads.'),
(78824, 2015, 'bio', 'eQTL epistasis: detecting epistatic effects and inferring hierarchical relationships of genes in biological pathways', 'Kang, Mingon|Zhang, Chunling|Chun, Hyung-Wook|Ding, Chris|Liu, Chunyu|Gao, Jean', 'Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 66012, USA and Department of Mathematics, University of Texas at Arlington, Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 66012, USA and Department of Mathematics, University of Texas at Arlington, Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 66012, USA and Department of Mathematics, University of Texas at Arlington, Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 66012, USA and Department of Mathematics, University of Texas at Arlington, Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 66012, USA and Department of Mathematics, University of Texas at Arlington, Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 66012, USA and Department of Mathematics, University of Texas at Arlington, Arlington, TX 76019, USA.', 'United States|United States|United States|United States|United States|United States', 7, 'Brain|Computer Simulation|Epistasis, Genetic|Genes|Genome-Wide Association Study|Humans|Models, Genetic|Quantitative Trait Loci|Schizophrenia|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btu727', '25359893', 'Epistasis is the interactions among multiple genetic variants. It has emerged to explain the missing heritability that a marginal genetic effect does not account for by genome-wide association studies, and also to understand the hierarchical relationships between genes in the genetic pathways. The Fishers geometric model is common in detecting the epistatic effects. However, despite the substantial successes of many studies with the model, it often fails to discover the functional dependence between genes in an epistasis study, which is an important role in inferring hierarchical relationships of genes in the biological pathway.'),
(78825, 2015, 'bio', 'Fast and accurate site frequency spectrum estimation from low coverage sequence data', 'Han, Eunjung|Sinsheimer, Janet S|Novembre, John', 'Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA 90095, USA, Department of Human Genetics and Biomathematics, University of California, Los Angeles, Los Angeles, CA 90095, USA and Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA.|Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA 90095, USA, Department of Human Genetics and Biomathematics, University of California, Los Angeles, Los Angeles, CA 90095, USA and Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA 90095, USA, Department of Human Genetics and Biomathematics, University of California, Los Angeles, Los Angeles, CA 90095, USA and Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA.|Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA 90095, USA, Department of Human Genetics and Biomathematics, University of California, Los Angeles, Los Angeles, CA 90095, USA and Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA.', 'United States|United States|United States', 5, 'Algorithms|Gene Frequency|Genetics, Population|Genome, Human|Genotype|High-Throughput Nucleotide Sequencing|Humans|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btu725', '25359894', 'The distribution of allele frequencies across polymorphic sites, also known as the site frequency spectrum (SFS), is of primary interest in population genetics. It is a complete summary of sequence variation at unlinked sites and more generally, its shape reflects underlying population genetic processes. One practical challenge is that inferring the SFS from low coverage sequencing data in a straightforward manner by using genotype calls can lead to significant bias. To reduce bias, previous studies have used a statistical method that directly estimates the SFS from sequencing data by first computing site allele frequency (SAF) likelihood for each site (i.e. the likelihood a site has each possible allele frequency conditional on observed sequence reads) using a dynamic programming (DP) algorithm. Although this method produces an accurate SFS, computing the SAF likelihood is quadratic in the number of samples sequenced.'),
(78826, 2015, 'bio', 'deML: robust demultiplexing of Illumina sequences using a likelihood-based approach', 'Renaud, Gabriel|Stenzel, Udo|Maricic, Tomislav|Wiebe, Victor|Kelso, Janet', 'Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Saxony D-04103, Germany.|Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Saxony D-04103, Germany.|Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Saxony D-04103, Germany.|Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Saxony D-04103, Germany.|Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Saxony D-04103, Germany.', 'Germany|Germany|Germany|Germany|Germany', 69, 'Algorithms|Humans|Likelihood Functions|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu719', '25359895', 'Pooling multiple samples increases the efficiency and lowers the cost of DNA sequencing. One approach to multiplexing is to use short DNA indices to uniquely identify each sample. After sequencing, reads must be assigned in silico to the sample of origin, a process referred to as demultiplexing. Demultiplexing software typically identifies the sample of origin using a fixed number of mismatches between the read index and a reference index set. This approach may fail or misassign reads when the sequencing quality of the indices is poor.'),
(78827, 2015, 'bio', 'PALMsiever: a tool to turn raw data into results for single-molecule localization microscopy', 'Pengo, Thomas|Holden, Seamus J|Manley, Suliana', 'Design of Biological Systems, Systems Biology, Center for Genomic Regulation, Dr. Aiguader 88, 08003 Barcelona, Spain, Advanced Light Microscopy Unit, Center for Genomic Regulation, Dr. Aiguader 88, 08003 Barcelona, Spain, and Laboratory for Experimental Biophysics, Institute for Physics of Biological Systems, School of Basic Sciences, Swiss Federal School of Technology, 1015 Lausanne, Switzerland Design of Biological Systems, Systems Biology, Center for Genomic Regulation, Dr. Aiguader 88, 08003 Barcelona, Spain, Advanced Light Microscopy Unit, Center for Genomic Regulation, Dr. Aiguader 88, 08003 Barcelona, Spain, and Laboratory for Experimental Biophysics, Institute for Physics of Biological Systems, School of Basic Sciences, Swiss Federal School of Technology, 1015 Lausanne, Switzerland.|Design of Biological Systems, Systems Biology, Center for Genomic Regulation, Dr. Aiguader 88, 08003 Barcelona, Spain, Advanced Light Microscopy Unit, Center for Genomic Regulation, Dr. Aiguader 88, 08003 Barcelona, Spain, and Laboratory for Experimental Biophysics, Institute for Physics of Biological Systems, School of Basic Sciences, Swiss Federal School of Technology, 1015 Lausanne, Switzerland.|Design of Biological Systems, Systems Biology, Center for Genomic Regulation, Dr. Aiguader 88, 08003 Barcelona, Spain, Advanced Light Microscopy Unit, Center for Genomic Regulation, Dr. Aiguader 88, 08003 Barcelona, Spain, and Laboratory for Experimental Biophysics, Institute for Physics of Biological Systems, School of Basic Sciences, Swiss Federal School of Technology, 1015 Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland', 17, 'Algorithms|Cluster Analysis|Computer Graphics|Humans|Image Interpretation, Computer-Assisted|Microscopy|Microtubules|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu720', '25362091', 'During the past decade, localization microscopy (LM) has transformed into an accessible, commercially available technique for life sciences. However, data processing can be challenging to the non-specialist and care is still needed to produce meaningful results. PALMsiever has been developed to provide a user-friendly means of visualizing, filtering and analyzing LM data. It includes drift correction, clustering, intelligent line profiles, many rendering algorithms and 3D data visualization. It incorporates the main analysis and data processing modalities used by experts in the field, as well as several new features we developed, and makes them broadly accessible. It can easily be extended via plugins and is provided as free of charge open-source software.'),
(78828, 2015, 'bio', 'Mass spectrometry-based protein identification with accurate statistical significance assignment', 'Alves, Gelio|Yu, Yi-Kuo', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.', 'United States|United States', 12, 'Algorithms|Databases, Protein|Humans|Mass Spectrometry|Models, Statistical|Peptide Fragments|Proteins|Proteomics', 'Journal Article', '10.1093/bioinformatics/btu717', '25362092', 'Assigning statistical significance accurately has become increasingly important as metadata of many types, often assembled in hierarchies, are constructed and combined for further biological analyses. Statistical inaccuracy of metadata at any level may propagate to downstream analyses, undermining the validity of scientific conclusions thus drawn. From the perspective of mass spectrometry-based proteomics, even though accurate statistics for peptide identification can now be achieved, accurate protein level statistics remain challenging.'),
(78829, 2015, 'bio', 'JAMSS: proteomics mass spectrometry simulation in Java', 'Smith, Rob|Prince, John T', 'Department of Computer Science, University of Montana, Missoula, MT 59812, USA and Department of Chemistry, Brigham Young University, Provo, UT 84602, USA.|Department of Computer Science, University of Montana, Missoula, MT 59812, USA and Department of Chemistry, Brigham Young University, Provo, UT 84602, USA.', 'United States|United States', 6, 'Algorithms|Chromatography, Liquid|Computational Biology|Computer Simulation|Humans|Mass Spectrometry|Programming Languages|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/btu729', '25371478', 'Countless proteomics data processing algorithms have been proposed, yet few have been critically evaluated due to lack of labeled data (data with known identities and quantities). Although labeling techniques exist, they are limited in terms of confidence and accuracy. In silico simulators have recently been used to create complex data with known identities and quantities. We propose Java Mass Spectrometry Simulator (JAMSS): a fast, self-contained in silico simulator capable of generating simulated MS and LC-MS runs while providing meta information on the provenance of each generated signal. JAMSS improves upon previous in silico simulators in terms of its ease to install, minimal parameters, graphical user interface, multithreading capability, retention time shift model and reproducibility.');
