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Impact of environmental inputs on reverse-engineering approach to network structures

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Wu, Jianhua, Sinfield, James Lister, Buchanan-Wollaston, Vicky and Feng, Jianfeng. (2009) Impact of environmental inputs on reverse-engineering approach to network structures. BMC Systems Biology, Vol.3 . Article 113. ISSN 1752-0509

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Official URL: http://dx.doi.org/10.1186/1752-0509-3-113

Abstract

Background: Uncovering complex network structures from a biological system is one of the main topic in system biology. The network structures can be inferred by the dynamical Bayesian network or Granger causality, but neither techniques have seriously taken into account the impact of environmental inputs. Results: With considerations of natural rhythmic dynamics of biological data, we propose a system biology approach to reveal the impact of environmental inputs on network structures. We first represent the environmental inputs by a harmonic oscillator and combine them with Granger causality to identify environmental inputs and then uncover the causal network structures. We also generalize it to multiple harmonic oscillators to represent various exogenous influences. This system approach is extensively tested with toy models and successfully applied to a real biological network of microarray data of the flowering genes of the model plant Arabidopsis Thaliana. The aim is to identify those genes that are directly affected by the presence of the sunlight and uncover the interactive network structures associating with flowering metabolism. Conclusion: We demonstrate that environmental inputs are crucial for correctly inferring network structures. Harmonic causal method is proved to be a powerful technique to detect environment inputs and uncover network structures, especially when the biological data exhibit periodic oscillations.

Item Type:	Journal Article
Subjects:	G Geography. Anthropology. Recreation > GE Environmental Sciences Q Science > QH Natural history
Divisions:	Faculty of Science > Centre for Scientific Computing Faculty of Science > Computer Science Faculty of Science > Molecular Organisation and Assembly in Cells (MOAC) Faculty of Science > Life Sciences (2010- ) > Warwick HRI (2004-2010)
Library of Congress Subject Headings (LCSH):	Arabidopsis thaliana -- Genetics, Plant ecology -- Simulation methods, Bayesian statistical decision theory, Systems biology -- Research
Journal or Publication Title:	BMC Systems Biology
Publisher:	BioMed Central Ltd.
ISSN:	1752-0509
Date:	4 December 2009
Volume:	Vol.3
Page Range:	Article 113
Identification Number:	10.1186/1752-0509-3-113
Status:	Peer Reviewed
Access rights to Published version:	Open Access
Funder:	Engineering and Physical Sciences Research Council (EPSRC), European Union (EU)
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URI:	http://wrap.warwick.ac.uk/id/eprint/2516