Journal Article

Detection of stoichiometric inconsistencies in biomolecular models

Albert Gevorgyan, Mark G. Poolman and David A. Fell

in Bioinformatics

Volume 24, issue 19, pages 2245-2251
Published in print October 2008 | ISSN: 1367-4803
Published online August 2008 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btn425
Detection of stoichiometric inconsistencies in biomolecular models

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Motivation: Metabolic modelling provides a mathematically rigorous basis for system-level analysis of biochemical networks. However, the growing sizes of metabolic models can lead to serious problems in their construction and validation. In this work, we describe a relatively poorly investigated type of modelling error, called stoichiometric inconsistencies. These errors are caused by incorrect definitions of reaction stoichiometries and result in conflicts between two fundamental physical constraints to be satisfied by any valid metabolic model: positivity of molecular masses of all metabolites and mass conservation in all interconversions.

Results: We introduce formal definitions of stoichiometric inconsistencies, inconsistent net stoichiometries, elementary leakage modes and other important fundamental properties of incorrectly defined biomolecular networks. Algorithms are described for the verification of stoichiometric consistency of a model, detection of unconserved metabolites and inconsistent minimal net stoichiometries. The usefulness of these algorithms for effective resolving of inconsistencies and for detection of input errors is demonstrated on a published genome-scale metabolic model of Saccharomyces cerevisiae and one of Streptococcus agalactiae constructed using the KEGG database.

Availability: http://mudshark.brookes.ac.uk/index.php/Albert_Gevorgyan

Contact:dfell@brookes.ac.uk

Journal Article.  5310 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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