A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology |
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Authors: | Herrgård Markus J Swainston Neil Dobson Paul Dunn Warwick B Arga K Yalçin Arvas Mikko Blüthgen Nils Borger Simon Costenoble Roeland Heinemann Matthias Hucka Michael Le Novère Nicolas Li Peter Liebermeister Wolfram Mo Monica L Oliveira Ana Paula Petranovic Dina Pettifer Stephen Simeonidis Evangelos Smallbone Kieran Spasić Irena Weichart Dieter Brent Roger Broomhead David S Westerhoff Hans V Kirdar Betül Penttilä Merja Klipp Edda Palsson Bernhard Ø Sauer Uwe Oliver Stephen G Mendes Pedro Nielsen Jens Kell Douglas B |
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Affiliation: | Department of Bioengineering, University of California, San Diego, La Jolla, California 92093-0412, USA. |
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Abstract: | Genomic data allow the large-scale manual or semi-automated assembly of metabolic network reconstructions, which provide highly curated organism-specific knowledge bases. Although several genome-scale network reconstructions describe Saccharomyces cerevisiae metabolism, they differ in scope and content, and use different terminologies to describe the same chemical entities. This makes comparisons between them difficult and underscores the desirability of a consolidated metabolic network that collects and formalizes the 'community knowledge' of yeast metabolism. We describe how we have produced a consensus metabolic network reconstruction for S. cerevisiae. In drafting it, we placed special emphasis on referencing molecules to persistent databases or using database-independent forms, such as SMILES or InChI strings, as 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 (http://www.comp-sys-bio.org/yeastnet). It can be maintained as a resource that serves as a common denominator for studying the systems biology of yeast. Similar strategies should benefit communities studying genome-scale metabolic networks of other organisms. |
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