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Publikation: Zeitschriftenartikel
The Systems Biology Markup Language (SBML)
Grunddaten
Abstract
Autoren
Einrichtung
Grunddaten
Titel
The Systems Biology Markup Language (SBML)
Untertitel
language specification for level 3 version 2 core
Erscheinungsjahr
2018
Seiten (von – bis)
1 – 181
Band
15
Heft-Nr.
1
Jahr
2018
Publikationsform
Elektronische Ressource
Publikationsart
Zeitschriftenartikel
Sprache
Englisch
DOI
10.1515/jib-2017-0081
Letzte Änderung
24.03.2021 06:04:35
Bearbeitungsstatus
durch UB Rostock abschließend validiert
Dauerhafte URL
http://purl.uni-rostock.de/fodb/pub/65460
Links zu Katalogen
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/.
Autoren
Hucka, Michael
Bergmann, Frank T.
Sahle, Sven
Waltemath, Dagmar
Einrichtung
IEF/IN/IFI/Systembiologie und Bioinformatik