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PMID: 17503356 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't Review

SBMLmerge, a system for combining biochemical network models.

Genome informatics. International Conference on Genome Informatics ·Vol. 17 ·No. 1 ·2006-00-00 ·Pages 62-71

Schulz M, Uhlendorf J, Klipp E, Liebermeister W

Abstract

The Systems Biology Markup Language (SBML) is an XML-based format for representing mathematical models of biochemical reaction networks, and it is likely to become a main standard in the systems biology community. As published mathematical models in cell biology are growing in number and size, modular modelling approaches will gain additional importance. The main issue to be addressed in computer-assisted model combination is the specification and handling of model semantics. The software SBMLmerge assists the user in combining models of biological subsystems to larger biochemical networks. First, the program helps the user in annotating all model elements with unique identifiers pointing to databases such as KEGG or Gene Ontology. Second, during merging, SBMLmerge detects and resolves various syntactic and semantic problems. Typical problems are conflicting variable names, elements which appear in more than one input model, and mathematical problems arising from the combination of equations. If the input models make contradicting statements about a biochemical quantity, the user is asked to choose between them. In the end the merging process results in a new, valid SBML model.

MeSH Terms
Computer Simulation Metabolic Networks and Pathways Models, Biological Models, Chemical Software
Authors & Affiliations
4 authors, click to expand affiliations / ORCID
Schulz Marvin
Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, 14195 Berlin, Germany. [email protected]
Uhlendorf Jannis
Klipp Edda
Liebermeister Wolfram
Article Info
Journal
Genome informatics. International Conference on Genome Informatics
Abbr.
Genome Inform
ISSN
0919-9454
Published
2006-00-00
Pages
62-71
Language
English
Region
Japan
NLM ID
101280573
Subset
IM
External Links
PubMed source
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