Meeting report from the fourth meeting of the Computational Modeling in Biology Network (COMBINE)

The Computational Modeling in Biology Network (COMBINE) is an initiative to coordinate the development of community standards and formats in computational systems biology and related fields. This report summarizes the topics and activities of the fourth edition of the annual COMBINE meeting, held in...

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Published inStandards in genomic sciences Vol. 9; no. 3; pp. 1285 - 1301
Main Authors Waltemath, Dagmar, Bergmann, Frank T., Chaouiya, Claudine, Czauderna, Tobias, Gleeson, Padraig, Goble, Carole, Golebiewski, Martin, Hucka, Michael, Juty, Nick, Krebs, Olga, Le Novère, Nicolas, Mi, Huaiyu, Moraru, Ion I., Myers, Chris J., Nickerson, David, Olivier, Brett G., Rodriguez, Nicolas, Schreiber, Falk, Smith, Lucian, Zhang, Fengkai, Bonnet, Eric
Format Journal Article
LanguageEnglish
Published London BioMed Central 15.06.2014
BioMed Central Ltd
Michigan State University
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ISSN1944-3277
1944-3277
DOI10.4056/sigs.5279417

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Summary:The Computational Modeling in Biology Network (COMBINE) is an initiative to coordinate the development of community standards and formats in computational systems biology and related fields. This report summarizes the topics and activities of the fourth edition of the annual COMBINE meeting, held in Paris during September 16–20 2013, and attended by a total of 96 people. This edition pioneered a first day devoted to modeling approaches in biology, which attracted a broad audience of scientists thanks to a panel of renowned speakers. During subsequent days, discussions were held on many subjects including the introduction of new features in the various COMBINE standards, new software tools that use the standards, and outreach efforts. Significant emphasis went into work on extensions of the SBML format, and also into community-building. This year’s edition once again demonstrated that the COMBINE community is thriving, and still manages to help coordinate activities between different standards in computational systems biology.
ISSN:1944-3277
1944-3277
DOI:10.4056/sigs.5279417