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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: Zeitschriftenartikel
Alternativer Titel : Nat Biotech

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 Urheber:
Herrgård, Markus J, Autor
Swainston, Neil, Autor
Dobson, Paul, Autor
Dunn, Warwick B, Autor
Arga, K Yalçin, Autor
Arvas, Mikko, Autor
Büthgen, Nils, Autor
Borger, Simon, Autor
Costenoble, Roeland, Autor
Heinemann, Matthias, Autor
Hucka, Michael, Autor
Le Novère, Nicolas, Autor
Li, Peter, Autor
Liebermeister, Wolfram, Autor
Mo, Monica L, Autor
Oliveira, Ana Paula, Autor
Petranovic, Dina, Autor
Pettifer, Stephen, Autor
Simeonidis, Evangelos, Autor
Smallbone, Kieran, Autor
Spasié, Irena, AutorWeichart, Dieter, AutorBrent, Roger, AutorBroomhead, David S, AutorWesterhoff, Hans V, AutorKürdar, Betül, AutorPenttilä, Merja, AutorKlipp, Edda1, Autor           Palsson, Bernhard Ø, AutorSauer, Uwe, AutorOliver, Stephen G, AutorMendes, Pedro, AutorNielsen, Jens, AutorKell, Douglas B, Autor mehr..
Affiliations:
1Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433554              

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 Zusammenfassung: 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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Sprache(n): eng - English
 Datum: 2008-10-09
 Publikationsstatus: Erschienen
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Titel: Nature Biotechnology
  Alternativer Titel : Nat Biotech
Genre der Quelle: Zeitschrift
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Seiten: - Band / Heft: 26 (10) Artikelnummer: - Start- / Endseite: 1155 - 1160 Identifikator: ISSN: 1087-0156