Standardisation of stoichiometric models: how and why

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• Swainston, N (University of Manchester)
• Tuesday 04 November 2014, 11:30-11:45
• Seminar Room 1, Newton Institute.

If you have a question about this talk, please contact Mustapha Amrani.

Understanding Microbial Communities; Function, Structure and Dynamics

Interest in constraint-based modelling of metabolism using stoichiometric models has grown significantly over the last 10-15 years. Hundreds of curated models [1], and thousands of automatically generated models [2] are now publicly available, covering organisms in all three domains.

Despite attempts of standardising their representation, using community-developed formats such as the Systems Biology Markup Language, SBML [3], many tasks surrounding model building and analysis are hampered by a lack of interoperability between models.

Based on the speaker’s experience in co-leading two large international community efforts in the development of consensus models for yeast [4] and human [5], approaches to model standardisation will be discussed. Moreover, the benefits of adopting a disciplined approach to model standardisation – automated model building, model checking, and ‘omics data integration – will be demonstrated.

Such reliance on automated techniques will be of particular relevance to stoichiometric modelling of microbial communities, where the complexity of such models is likely to far exceed that of even the largest existing models of mammalian metabolism.

[1] Optimizing genome-scale network reconstructions. Monk J, et al. Nat Biotechnol. 2014, 32(5):447-52. [2] Path2Models: large-scale generation of computational models from biochemical pathway maps. Büchel F, et al. BMC Syst Biol. 7:116. [3] The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Hucka M, et al. Bioinformatics. 2003, 19(4):524-31. [4] A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology. Herrgård MJ, et al. Nat Biotechnol. 2008, 26(10):1155-60. [5] A community-driven global reconstruction of human metabolism. Thiele I, et al. Nat Biotechnol. 2013, 31(5):419-25.

This talk is part of the Isaac Newton Institute Seminar Series series.

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