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

Markus J. Herrgård, Neil Swainston, Paul Dobson, Warwick B. Dunn, K. Yalçin Arga, Mikko Arvas, Nils Büthgen, Simon Borger, Roeland Costenoble, Matthias Heinemann, Michael Hucka, Nicolas Le Novère, Peter Li, Wolfram Liebermeister, Monica L. Mo, Ana Paula Oliveira, Dina Petranovic, Stephen Pettifer, Evangelos Simeonidis, Kieran Smallbone & 14 others Irena Spasić, Dieter Weichart, Roger Brent, David S. Broomhead, Hans V. Westerhoff, Betül Kirdar, Merja Penttilä, Edda Klipp, Bernhard Palsson, Uwe Sauer, Stephen G. Oliver, Pedro Mendes, Jens Nielsen, Douglas B. Kell

Research output: Contribution to journalArticleScientificpeer-review

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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.

Original languageEnglish
Pages (from-to)1155-1160
JournalNature Biotechnology
Volume26
Issue number10
DOIs
Publication statusPublished - 1 Oct 2008
MoE publication typeA1 Journal article-refereed

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Systems Biology
Metabolic Networks and Pathways
Yeast
Consensus
Yeasts
Databases
Metabolism
Saccharomyces cerevisiae
Genes
Genome
Markup languages
Knowledge Bases
Terminology
Language
Molecules

Cite this

Herrgård, M. J., Swainston, N., Dobson, P., Dunn, W. B., Arga, K. Y., Arvas, M., ... Kell, D. B. (2008). A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology. Nature Biotechnology, 26(10), 1155-1160. https://doi.org/10.1038/nbt1492
Herrgård, Markus J. ; Swainston, Neil ; Dobson, Paul ; Dunn, Warwick B. ; Arga, K. Yalçin ; Arvas, Mikko ; Büthgen, 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 ; Sauer, Uwe ; Oliver, Stephen G. ; Mendes, Pedro ; Nielsen, Jens ; Kell, Douglas B. / A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology. In: Nature Biotechnology. 2008 ; Vol. 26, No. 10. pp. 1155-1160.
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Herrgård, MJ, Swainston, N, Dobson, P, Dunn, WB, Arga, KY, Arvas, M, Büthgen, 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, B, Sauer, U, Oliver, SG, Mendes, P, Nielsen, J & Kell, DB 2008, 'A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology', Nature Biotechnology, vol. 26, no. 10, pp. 1155-1160. https://doi.org/10.1038/nbt1492

A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology. / Herrgård, Markus J.; Swainston, Neil; Dobson, Paul; Dunn, Warwick B.; Arga, K. Yalçin; Arvas, Mikko; Büthgen, 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; Sauer, Uwe; Oliver, Stephen G.; Mendes, Pedro; Nielsen, Jens; Kell, Douglas B. (Corresponding Author).

In: Nature Biotechnology, Vol. 26, No. 10, 01.10.2008, p. 1155-1160.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology

AU - Herrgård, Markus J.

AU - Swainston, Neil

AU - Dobson, Paul

AU - Dunn, Warwick B.

AU - Arga, K. Yalçin

AU - Arvas, Mikko

AU - Büthgen, Nils

AU - Borger, Simon

AU - Costenoble, Roeland

AU - Heinemann, Matthias

AU - Hucka, Michael

AU - Le Novère, Nicolas

AU - Li, Peter

AU - Liebermeister, Wolfram

AU - Mo, Monica L.

AU - Oliveira, Ana Paula

AU - Petranovic, Dina

AU - Pettifer, Stephen

AU - Simeonidis, Evangelos

AU - Smallbone, Kieran

AU - Spasić, Irena

AU - Weichart, Dieter

AU - Brent, Roger

AU - Broomhead, David S.

AU - Westerhoff, Hans V.

AU - Kirdar, Betül

AU - Penttilä, Merja

AU - Klipp, Edda

AU - Palsson, Bernhard

AU - Sauer, Uwe

AU - Oliver, Stephen G.

AU - Mendes, Pedro

AU - Nielsen, Jens

AU - Kell, Douglas B.

N1 - CA2: TK402 ISI: BIOTECHNOLOGY & APPLIED MICROBIOLOGY

PY - 2008/10/1

Y1 - 2008/10/1

N2 - 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.

AB - 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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U2 - 10.1038/nbt1492

DO - 10.1038/nbt1492

M3 - Article

VL - 26

SP - 1155

EP - 1160

JO - Nature Biotechnology

JF - Nature Biotechnology

SN - 1087-0156

IS - 10

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