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A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology

Journal article published in 2008 by M. J. Herrg\aa{}rd, Hans W. Westerhoff, K. Yalçin Arga, Markus J. Herrgård, Neil Swainston, Paul Dobson, Warwick B. Dunn, K. Yalçin Arga ORCID, Yalcin K. Arga, Mikko Arvas, Nils Blüthgen, Nils Buthgen, Simon Borger, Roeland Costenoble, Roeland Coestenoble and other authors.
This paper is available in a repository.
This paper is available in a repository.

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Abstract

Genomic data now allow the large-scale manual or semi-automated reconstruction of metabolic networks. A network reconstruction represents a highly curated organism-specific knowledge base. A few genome-scale network reconstructions have appeared for metabolism in the baker’s yeast Saccharomyces cerevisiae. These alternative network reconstructions differ in scope and content, and further have used different terminologies to describe the same chemical entities, thus making comparisons between them difficult. The formulation of a ‘community consensus’ network that collects and formalizes the ‘community knowledge’ of yeast metabolism is thus highly desirable. We describe how we have produced a consensus metabolic network reconstruction for S. cerevisiae. Special emphasis is laid on referencing molecules to persistent databases or using database-independent forms such as SMILES or InChI strings, since this permits their chemical structure to be represented unambiguously and in a manner that permits automated reasoning. The reconstruction is readily available via a publicly accessible database and in the Systems Biology Markup Language, and we describe the manner in which it can be maintained as a community resource. It should serve as a common denominator for system biology studies of yeast. Similar strategies will be of benefit to communities studying genome-scale metabolic networks of other organisms.