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      The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 2 Core Release 2

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          Abstract

          Computational models can help researchers to interpret data, understand biological functions, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that different software systems can exchange. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Release 2 of Version 2 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. Release 2 corrects some errors and clarifies some ambiguities discovered in Release 1. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project website at http://sbml.org/.

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          Asymptotic analysis of multiscale approximations to reaction networks

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            Author and article information

            Contributors
            Journal
            J Integr Bioinform
            J Integr Bioinform
            jib
            jib
            jib
            Journal of Integrative Bioinformatics
            De Gruyter
            1613-4516
            20 June 2019
            June 2019
            : 16
            : 2
            : 20190021
            Affiliations
            California Institute of Technology , Pasadena, CA, USA
            Aix-Marseille University, CNRS, I2M , Marseille, France
            deptDepartment of Computer Science , University of Tübingen , Tübingen, Germany
            Computational Systems Biology of Infection and Antimicrobial-Resistant Pathogens, Institute for Biomedical Informatics (IBMI), University of Tübingen , Tübingen, Germany
            German Center for Infection Research (DZIF) , Tübingen, Germany
            Virginia Bioinformatics Institute , Blacksburg, VA, USA
            European Bioinformatics Institute , Cambridge, UK
            Humboldt University Berlin , Berlin, Germany
            Babraham Institute , Cambridge, UK
            University of Utah , Salt Lake City, UT, USA
            VU University Amsterdam , Amsterdam, Netherlands
            University of Heidelberg , Heidelberg, Germany
            University of Connecticut , Storrs, CT, USA
            University of Washington , Seattle, WA, USA
            University Medicine Greifswald , Greifswald, Germany
            Newcastle University , Newcastle, Germany
            NIAID/NIH , Bethesda, MD, USA
            Author information
            https://orcid.org/0000-0001-9105-5960
            https://orcid.org/0000-0001-5553-4702
            https://orcid.org/0000-0003-2350-0756
            https://orcid.org/0000-0002-1240-5553
            https://orcid.org/0000-0001-8503-8371
            https://orcid.org/0000-0002-3356-3542
            https://orcid.org/0000-0003-1725-179X
            https://orcid.org/0000-0002-6309-7327
            https://orcid.org/0000-0002-8762-8444
            https://orcid.org/0000-0002-5293-5321
            https://orcid.org/0000-0003-3286-7736
            https://orcid.org/0000-0003-0705-9809
            https://orcid.org/0000-0001-7002-6386
            https://orcid.org/0000-0002-5886-5563
            https://orcid.org/0000-0003-0736-802X
            https://orcid.org/0000-0001-7112-9328
            Article
            jib-2019-0021
            10.1515/jib-2019-0021
            6798823
            31219795
            5a0576ed-030b-4bb6-897d-c1cb77d9b5c7
            © 2019, Michael Hucka et al., published by Walter de Gruyter GmbH, Berlin/Boston

            This work is licensed under the Creative Commons Attribution 4.0 Public License.

            History
            : 30 March 2019
            : 20 May 2019
            Page count
            Pages: 183
            Categories
            Research Articles

            systems biology markup language,standards,visualization,representation

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