Literature DB >> 29522418

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

Michael Hucka1, Frank T Bergmann1, Andreas Dräger2, Stefan Hoops3, Sarah M Keating4, Nicolas Le Novère5, Chris J Myers6, Brett G Olivier7, Sven Sahle8, James C Schaff9, Lucian P Smith10, Dagmar Waltemath11, Darren J Wilkinson12.   

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 Version 2 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML, their encoding in XML (the eXtensible Markup Language), validation rules that determine the validity of an SBML document, and examples of models in SBML form. The design of Version 2 differs from Version 1 principally in allowing new MathML constructs, making more child elements optional, and adding identifiers to all SBML elements instead of only selected elements. Other materials and software are available from the SBML project website at http://sbml.org/.

Entities:  

Keywords:  SBML; computational biology; modeling; standards; systems biology

Mesh:

Year:  2018        PMID: 29522418      PMCID: PMC6167032          DOI: 10.1515/jib-2017-0081

Source DB:  PubMed          Journal:  J Integr Bioinform        ISSN: 1613-4516


  23 in total

1.  Kinetic modeling and the rise of systems pharmacology.

Authors:  Robert D Phair
Journal:  J Lipid Res       Date:  2015-11-20       Impact factor: 5.922

2.  Scaling methods for accelerating kinetic Monte Carlo simulations of chemical reaction networks.

Authors:  Yen Ting Lin; Song Feng; William S Hlavacek
Journal:  J Chem Phys       Date:  2019-06-28       Impact factor: 3.488

3.  Metage2Metabo, microbiota-scale metabolic complementarity for the identification of key species.

Authors:  Arnaud Belcour; Clémence Frioux; Méziane Aite; Anthony Bretaudeau; Falk Hildebrand; Anne Siegel
Journal:  Elife       Date:  2020-12-29       Impact factor: 8.140

4.  BpForms and BcForms: a toolkit for concretely describing non-canonical polymers and complexes to facilitate global biochemical networks.

Authors:  Paul F Lang; Yassmine Chebaro; Xiaoyue Zheng; John A P Sekar; Bilal Shaikh; Darren A Natale; Jonathan R Karr
Journal:  Genome Biol       Date:  2020-05-18       Impact factor: 13.583

5.  Periodic propagating waves coordinate RhoGTPase network dynamics at the leading and trailing edges during cell migration.

Authors:  Alfonso Bolado-Carrancio; Oleksii S Rukhlenko; Elena Nikonova; Mikhail A Tsyganov; Anne Wheeler; Amaya Garcia-Munoz; Walter Kolch; Alex von Kriegsheim; Boris N Kholodenko
Journal:  Elife       Date:  2020-07-24       Impact factor: 8.140

6.  The layer-oriented approach to declarative languages for biological modeling.

Authors:  Ivan Raikov; Erik De Schutter
Journal:  PLoS Comput Biol       Date:  2012-05-17       Impact factor: 4.475

7.  Fluxer: a web application to compute, analyze and visualize genome-scale metabolic flux networks.

Authors:  Archana Hari; Daniel Lobo
Journal:  Nucleic Acids Res       Date:  2020-07-02       Impact factor: 16.971

Review 8.  Omics in a Digital World: The Role of Bioinformatics in Providing New Insights Into Human Aging.

Authors:  Serena Dato; Paolina Crocco; Nicola Rambaldi Migliore; Francesco Lescai
Journal:  Front Genet       Date:  2021-06-10       Impact factor: 4.599

9.  BiPSim: a flexible and generic stochastic simulator for polymerization processes.

Authors:  Stephan Fischer; Marc Dinh; Vincent Henry; Philippe Robert; Anne Goelzer; Vincent Fromion
Journal:  Sci Rep       Date:  2021-07-08       Impact factor: 4.379

Review 10.  Curating and comparing 114 strain-specific genome-scale metabolic models of Staphylococcus aureus.

Authors:  Alina Renz; Andreas Dräger
Journal:  NPJ Syst Biol Appl       Date:  2021-06-29
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