Extracting reaction networks from databases-opening Pandora's box

Fearnley, Liam, Davis, Melissa, Ragan, Mark A. and Nielsen, Lars K. (2013) Extracting reaction networks from databases-opening Pandora's box. Briefings in Bioinformatics, 15 6: 973-983. doi:10.1093/bib/bbt058

Author Fearnley, Liam
Davis, Melissa
Ragan, Mark A.
Nielsen, Lars K.
Title Extracting reaction networks from databases-opening Pandora's box
Journal name Briefings in Bioinformatics   Check publisher's open access policy
ISSN 1467-5463
Publication date 2013-08-14
Year available 2013
Sub-type Article (original research)
DOI 10.1093/bib/bbt058
Open Access Status Not yet assessed
Volume 15
Issue 6
Start page 973
End page 983
Total pages 11
Place of publication Oxford, United Kingdom
Publisher Oxford University Press
Language eng
Subject 1710 Information Systems
1312 Molecular Biology
Abstract Large quantities of information describing the mechanisms of biological pathways continue to be collected in publicly available databases. At the same time, experiments have increased in scale, and biologists increasingly use pathways defined in online databases to interpret the results of experiments and generate hypotheses. Emerging computational techniques that exploit the rich biological information captured in reaction systems require formal standardized descriptions of pathways to extract these reaction networks and avoid the alternative: time-consuming and largely manual literature-based network reconstruction. Here, we systematically evaluate the effects of commonly used knowledge representations on the seemingly simple task of extracting a reaction network describing signal transduction from a pathway database. We show that this process is in fact surprisingly difficult, and the pathway representations adopted by various knowledge bases have dramatic consequences for reaction network extraction, connectivity, capture of pathway crosstalk and in the modelling of cell–cell interactions. Researchers constructing computational models built from automatically extracted reaction networks must therefore consider the issues we outline in this review to maximize the value of existing pathway knowledge.
Keyword Databases
Signal transduction
Reaction networks
Q-Index Code C1
Q-Index Status Confirmed Code
Grant ID DP110103384
Institutional Status UQ
Additional Notes Published online ahead of print 14 August 2013.

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Created: Tue, 17 Dec 2013, 01:49:04 EST by Susan Allen on behalf of Institute for Molecular Bioscience