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 Coestenoble; Matthias Heinemann; Michael Hucka; Nicolas Le Novère; Peter Li; Wolfram Liebermeister; Monica L Mo; Ana Paula Oliveira; Dina Petranovic Nielsen; Stephen Pettifer; Evangelos Simeonidis; Kieran Smallbone; Irena Spasić; Dieter Weichart; Roger Brent; David S Broomhead; Hans W Westerhoff; Betül Kırdar; Merja Penttilä; Edda Klipp; Bernhard Ø Palsson; Uwe Sauer; Stephen G Oliver; Pedro Mendes; Jens B Nielsen; Douglas B Kell

A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology
Journal article, 2008

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 make 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 InChl 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.

Author

Markus J Herrgård

Neil Swainston

Paul Dobson

Warwick B Dunn

K Yalçin Arga

Mikko Arvas

Nils Blüthgen

Simon Borger

Roeland Coestenoble

Matthias Heinemann

Michael Hucka

Nicolas Le Novère

Peter Li

Wolfram Liebermeister

Monica L Mo

Ana Paula Oliveira

Dina Petranovic Nielsen

Chalmers, Chemical and Biological Engineering, Life Sciences

Other publications Research

Stephen Pettifer

Evangelos Simeonidis

Kieran Smallbone

Irena Spasić

Dieter Weichart

Roger Brent

David S Broomhead

Hans W Westerhoff

Betül Kırdar

Merja Penttilä

Edda Klipp

Bernhard Ø Palsson

Uwe Sauer

Stephen G Oliver

Pedro Mendes

Jens B Nielsen