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PMID: 18846089 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

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

Nature biotechnology ·Vol. 26 ·No. 10 ·2008-10-00 ·Pages 1155-60

Herrgård MJ, Swainston N, Dobson P, Dunn WB, Arga KY, Arvas M, Blüthgen N, Borger S, Costenoble R, Heinemann M, Hucka M, Le Novère N, Li P, Liebermeister W, Mo ML, Oliveira AP, Petranovic D, Pettifer S, Simeonidis E, Smallbone K, Spasić I, Weichart D, Brent R, Broomhead DS, Westerhoff HV, Kirdar B, Penttilä M, Klipp E, Palsson BØ, Sauer U, Oliver SG, Mendes P, Nielsen J, Kell DB

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.

MeSH Terms
Computer Simulation Databases, Protein Information Storage and Retrieval/methods Models, Biological Saccharomyces cerevisiae/metabolism Saccharomyces cerevisiae Proteins/metabolism Signal Transduction/physiology Systems Biology/methods Systems Integration
Chemicals
Saccharomyces cerevisiae Proteins
Authors & Affiliations
34 authors, click to expand affiliations / ORCID
Herrgård Markus J
Department of Bioengineering, University of California, San Diego, La Jolla, California 92093-0412, USA.
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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Article Info
Journal
Nature biotechnology
Abbr.
Nat Biotechnol
ISSN
1546-1696
Published
2008-10-00
Pages
1155-60
Language
English
Region
United States
NLM ID
9604648
PMCID
PMC4018421
Subset
IM
Grants
Biotechnology and Biological Sciences Research Council · BB/E016065/1 · United Kingdom
NIGMS NIH HHS · R01 GM097479 · United States
Biotechnology and Biological Sciences Research Council · BB/F010516/1 · United Kingdom
Biotechnology and Biological Sciences Research Council · BB/E006248/1 · United Kingdom
Biotechnology and Biological Sciences Research Council · BB/C008219/1 · United Kingdom
NIGMS NIH HHS · R01 GM071808 · United States
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