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SBML Level 3: an extensible format for the exchange and reuse of biological models.
Keating, Sarah M; Waltemath, Dagmar; König, Matthias; Zhang, Fengkai; Dräger, Andreas; Chaouiya, Claudine; Bergmann, Frank T; Finney, Andrew; Gillespie, Colin S; Helikar, Tomás; Hoops, Stefan; Malik-Sheriff, Rahuman S; Moodie, Stuart L; Moraru, Ion I; Myers, Chris J; Naldi, Aurélien; Olivier, Brett G; Sahle, Sven; Schaff, James C; Smith, Lucian P; Swat, Maciej J; Thieffry, Denis; Watanabe, Leandro; Wilkinson, Darren J; Blinov, Michael L; Begley, Kimberly; Faeder, James R; Gómez, Harold F; Hamm, Thomas M; Inagaki, Yuichiro; Liebermeister, Wolfram; Lister, Allyson L; Lucio, Daniel; Mjolsness, Eric; Proctor, Carole J; Raman, Karthik; Rodriguez, Nicolas; Shaffer, Clifford A; Shapiro, Bruce E; Stelling, Joerg; Swainston, Neil; Tanimura, Naoki; Wagner, John; Meier-Schellersheim, Martin; Sauro, Herbert M; Palsson, Bernhard; Bolouri, Hamid; Kitano, Hiroaki; Funahashi, Akira; Hermjakob, Henning.
Afiliación
  • Keating SM; Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA, USA.
  • Waltemath D; European Bioinformatics Institute, European Molecular Biology Laboratory (EMBL-EBI), Hinxton, UK.
  • König M; BioQuant/COS, Heidelberg University, Heidelberg, Germany.
  • Zhang F; Medical Informatics, Institute for Community Health, University Medicine Greifswald, Greifswald, Germany.
  • Dräger A; Institute for Theoretical Biology, Humboldt-University Berlin, Berlin, Germany.
  • Chaouiya C; Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA.
  • Bergmann FT; Computational Systems Biology of Infection and Antimicrobial-Resistant Pathogens, Institute for Biomedical Informatics (IBMI), University of Tübingen, Tübingen, Germany.
  • Finney A; Department of Computer Science, University of Tübingen, Tübingen, Germany.
  • Gillespie CS; German Center for Infection Research (DZIF), Tübingen, Germany.
  • Helikar T; Aix-Marseille Université, CNRS, Centrale Marseille, Marseille, France.
  • Hoops S; Instituto Gulbenkian de Ciência, Oeiras, Portugal.
  • Malik-Sheriff RS; BioQuant/COS, Heidelberg University, Heidelberg, Germany.
  • Moodie SL; ANSYS UK Ltd, Milton Park, Oxfordshire, UK.
  • Moraru II; School of Mathematics, Statistics and Physics, Newcastle University, Newcastle upon Tyne, UK.
  • Myers CJ; Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, NE, USA.
  • Naldi A; Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, VA, USA.
  • Olivier BG; European Bioinformatics Institute, European Molecular Biology Laboratory (EMBL-EBI), Hinxton, UK.
  • Sahle S; Eight Pillars Ltd, Edinburgh, UK.
  • Schaff JC; Center for Cell Analysis and Modeling, UConn Health, Farmington, CT, USA.
  • Smith LP; Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, USA.
  • Swat MJ; Institut de Biologie de l'ENS (IBENS), Département de Biologie, École Normale Supérieure, CNRS, INSERM, Université PSL, Paris, France.
  • Thieffry D; Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA, USA.
  • Watanabe L; BioQuant/COS, Heidelberg University, Heidelberg, Germany.
  • Wilkinson DJ; SysBioLab, AIMMS, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
  • Blinov ML; BioQuant/COS, Heidelberg University, Heidelberg, Germany.
  • Begley K; Applied BioMath, LLC, Concord, MA, USA.
  • Faeder JR; Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA, USA.
  • Gómez HF; Department of Bioengineering, University of Washington, Seattle, WA, USA.
  • Hamm TM; Simcyp (a Certara company), Sheffield, South Yorkshire, UK.
  • Inagaki Y; Institut de Biologie de l'ENS (IBENS), Département de Biologie, École Normale Supérieure, CNRS, INSERM, Université PSL, Paris, France.
  • Liebermeister W; Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, USA.
  • Lister AL; School of Mathematics, Statistics and Physics, Newcastle University, Newcastle upon Tyne, UK.
  • Lucio D; The Alan Turing Institute, British Library, London, UK.
  • Mjolsness E; Center for Cell Analysis and Modeling, UConn Health, Farmington, CT, USA.
  • Proctor CJ; California Institute of Technology, Pasadena, CA, USA.
  • Raman K; Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA.
  • Rodriguez N; Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
  • Shaffer CA; Computational Systems Biology of Infection and Antimicrobial-Resistant Pathogens, Institute for Biomedical Informatics (IBMI), University of Tübingen, Tübingen, Germany.
  • Shapiro BE; Department of Computer Science, University of Tübingen, Tübingen, Germany.
  • Stelling J; Management & IT Consulting Division, Mizuho Information & Research Institute, Inc., Tokyo, Japan.
  • Swainston N; Université Paris-Saclay, INRAE, MaIAGE, Jouy-en-Josas, France.
  • Tanimura N; Oxford e-Research Centre (OeRC), Department of Engineering Science, University of Oxford, Oxford, UK.
  • Wagner J; College of Sciences, NC State University, Raleigh, NC, USA.
  • Meier-Schellersheim M; Department of Computer Science, University of California, Irvine, CA, USA.
  • Sauro HM; Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK.
  • Palsson B; Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology (IIT) Madras, Chennai, India.
  • Bolouri H; Initiative for Biological Systems Engineering (IBSE), IIT Madras, Chennai, India.
  • Kitano H; Robert Bosch Centre for Data Science and Artificial Intelligence (RBC-DSAI), IIT Madras, Chennai, India.
  • Funahashi A; The Babraham Institute, Cambridge, UK.
  • Hermjakob H; Department of Computer Science, Virginia Tech, Blacksburg, VA, USA.
Mol Syst Biol ; 16(8): e9110, 2020 08.
Article en En | MEDLINE | ID: mdl-32845085
ABSTRACT
Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Biología de Sistemas Tipo de estudio: Risk_factors_studies Límite: Animals / Humans Idioma: En Revista: Mol Syst Biol Asunto de la revista: BIOLOGIA MOLECULAR / BIOTECNOLOGIA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Biología de Sistemas Tipo de estudio: Risk_factors_studies Límite: Animals / Humans Idioma: En Revista: Mol Syst Biol Asunto de la revista: BIOLOGIA MOLECULAR / BIOTECNOLOGIA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos