Evidence map›Paper›PMID 18846089›Full record

ArticleNature biotechnology2008

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 Blüthgen, Simon Borger, Roeland Costenoble, Matthias Heinemann and 24 more

Abstract read
In one paragraph

Article in Nature biotechnology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 256 papers.

0numbers the graph read from it
0cells of the map it votes in
256citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

256 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. Systems biology of yeast metabolism.FEMS yeast research · 2026
    Review
  7. Computational and structural biotechnology journal · 2026
    Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Gear Shifting in Biological Energy Transduction.Entropy (Basel, Switzerland) · 2023
    Article
  17. Review
  18. Article
  19. Plant and microbial sciences as key drivers in the development of metabolomics research.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Review
  20. Article

196 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

34 authors.

Markus J HerrgårdDepartment of Bioengineering, University of California, San Diego, La Jolla, California 92093-0412, USA.
Neil Swainston
Paul Dobson
Warwick B Dunn
K Yalçin Arga
Mikko Arvas
Nils Blüthgen
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
Irena Spasić
Dieter Weichart
Roger Brent
David S Broomhead
Hans V Westerhoff
Betül Kirdar
Merja Penttilä
Edda Klipp
Bernhard Ø Palsson
Uwe Sauer
Stephen G Oliver
Pedro Mendes
Jens Nielsen
Douglas B Kell

Funding

A Genome-Scale Regulated Metabolic Model of YeastR01GM071808 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PALSSON, BERNHARD O · 2004 to 2007
$2.3M
Dynamics of gradient sensing in single cellsR01GM097479 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI BRENT, ROGER · 2011 to 2014
$2.1M
Biotechnology and Biological Sciences Research Council BB/C008219/1Biotechnology and Biological Sciences Research Council BB/E006248/1Biotechnology and Biological Sciences Research Council BB/E016065/1Biotechnology and Biological Sciences Research Council BB/F010516/1NIGMS NIH HHS R01 GM071808NIGMS NIH HHS R01 GM097479
6 · The paper itself

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.

Indexed as

Databases, ProteinModels, BiologicalComputer SimulationInformation Storage and RetrievalSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsSignal TransductionSystems BiologySystems IntegrationSaccharomyces cerevisiae Proteins

Identifiers

PMID18846089
PMCPMC4018421

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.