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

Herrgård, M. J., Swainston, N., Dobson, P., Dunn, W. B., Arga, K. Y., Arvas, M., et al. (2008). A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology. Nature Biotechnology, 26(10), 1155-1160. doi:10.1038/nbt1492.

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Genre: Journal Article
Alternative Title : Nat Biotech

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Herrgård, Markus J, Author
Swainston, Neil, Author
Dobson, Paul, Author
Dunn, Warwick B, Author
Arga, K Yalçin, Author
Arvas, Mikko, Author
Büthgen, Nils, Author
Borger, Simon, Author
Costenoble, Roeland, Author
Heinemann, Matthias, Author
Hucka, Michael, Author
Le Novère, Nicolas, Author
Li, Peter, Author
Liebermeister, Wolfram, Author
Mo, Monica L, Author
Oliveira, Ana Paula, Author
Petranovic, Dina, Author
Pettifer, Stephen, Author
Simeonidis, Evangelos, Author
Smallbone, Kieran, Author
Spasié, Irena, AuthorWeichart, Dieter, AuthorBrent, Roger, AuthorBroomhead, David S, AuthorWesterhoff, Hans V, AuthorKürdar, Betül, AuthorPenttilä, Merja, AuthorKlipp, Edda1, Author           Palsson, Bernhard Ø, AuthorSauer, Uwe, AuthorOliver, Stephen G, AuthorMendes, Pedro, AuthorNielsen, Jens, AuthorKell, Douglas B, Author more..
Affiliations:
1Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433554              

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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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Language(s): eng - English
 Dates: 2008-10-09
 Publication Status: Issued
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Title: Nature Biotechnology
  Alternative Title : Nat Biotech
Source Genre: Journal
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Pages: - Volume / Issue: 26 (10) Sequence Number: - Start / End Page: 1155 - 1160 Identifier: ISSN: 1087-0156