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Briefings in Functional Genomics and Proteomics Advance Access originally published online on March 7, 2008
Briefings in Functional Genomics and Proteomics 2008 7(2):136-146; doi:10.1093/bfgp/eln011
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© The Author 2008. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oxfordjournals.org

Special Issue Papers

Automated extraction of meaningful pathways from quantitative proteomics data

Josselin Noirel, Saw Yen Ow, Guido Sanguinetti, Alfonso Jaramillo and Phillip C. Wright

Corresponding author. Phillip C. Wright, Biological and Environmental Systems Group, Department of Chemical and Process Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD, UK. Tel: +44 114 2227577; Fax: +44 114 2227501; E-mail: p.c.wright{at}sheffield.ac.uk

Technological developments in the life sciences have resulted in an ever-accelerating pace of data production. Systems Biology tries to shed light upon these data by building complex models describing the interactions between biological components. However, extracting information from this morass of data requires the use of sophisticated computational techniques. Here, we propose a method suitable to integrate data drawn from quantitative proteomics into a metabolic scaffold and identify the metabolic pathways which are collectively up-regulated or down-regulated. The availability of such a tool is highly desirable as the extracted information could then be taken as a starting point for in-depth analyses, in particular in fields like Synthetic Biology, where datasets need be characterized routinely.

Keywords: metabolic network, quantitative proteomics, data mining


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