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Bioinformatics Advance Access published online on November 5, 2004
Bioinformatics, doi:10.1093/bioinformatics/bti118
Bioinformatics © Oxford University Press 2004; all rights reserved
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Received April 16, 2004
Revised September 29, 2004
Accepted October 20, 2004

Article

Sensitivity, principal component and flux analysis applied to signal transduction: the case of epidermal growth factor mediated signaling

Gang Liu 1, Mark T. Swihart 1, and Sriram Neelamegham 1*

1 Department of Chemical and Biological Engineering, State University of New York at Buffalo, Buffalo, NY 14260, USA

* To whom correspondence should be addressed.
Sriram Neelamegham, E-mail: neel{at}eng.buffalo.edu


  Abstract

Motivation: Novel high-throughput genomic and proteomic tools are allowing the integration of information from a range of biological assays into a single conceptual framework. This framework is often described as a network of biochemical reactions. We present strategies for the analysis of such networks.

Results: The direct differential method is described for the systematic evaluation of scaled sensitivity coefficients in reaction networks. Principal component analysis, based on an eigenvalue-eigenvector analysis of the scaled sensitivity coefficient matrix, is applied to rank individual reactions in the network based on their effect on system output. When combined with flux analysis, sensitivity analysis allows model reduction or simplification. Using epidermal growth factor (EGF) mediated signaling and trafficking as an example of signal transduction, we demonstrate that sensitivity analysis quantitatively reveals the dependence of dual-phosphorylated ERK concentration on individual reaction rate constants. It predicts that EGF mediated reactions proceed primarily via an Shc-dependent pathway. Further, it suggests that receptor internalization and endosomal signaling are important features regulating signal output only at low EGF dosages and at later times.

Supplemental Data: http://www.eng.buffalo.edu/~neel/bio_reaction_network.html.


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