A model-based optimization framework for the inference on gene regulatory networks from DNA array data

Bioinformatics
Reuben ThomasVassily Hatzimanikatis

Abstract

Identification of the regulatory structures in genetic networks and the formulation of mechanistic models in the form of wiring diagrams is one of the significant objectives of expression profiling using DNA microarray technologies and it requires the development and application of identification frameworks. We have developed a novel optimization framework for identifying regulation in a genetic network using the S-system modeling formalism. We show that balance equations on both mRNA and protein species led to a formulation suitable for analyzing DNA-microarray data whereby protein concentrations have been eliminated and only mRNA relative concentrations are retained. Using this formulation, we examined if it is possible to infer a set of possible genetic regulatory networks consistent with observed mRNA expression patterns. Two origins of changes in mRNA expression patterns were considered. One derives from changes in the biophysical properties of the system that alter the molecular-interaction kinetics and/or message stability. The second is due to gene knock-outs. We reduced the identification problem to an optimization problem (of the so-called mixed-integer non-linear programming class) and we developed an algorithmic pro...Continue Reading

Citations

Mar 8, 2007·Annual Review of Biomedical Engineering·I P AndroulakisR R Almon
Sep 4, 2012·BMC Systems Biology·Nishanth ChemmangattuvalappilIpsita Banerjee
May 20, 2009·IET Systems Biology·A JuliusG J Pappas
Mar 18, 2010·IET Systems Biology·H WangE Dougherty
Mar 29, 2011·Journal of Theoretical Biology·Jacques DemongeotFlorence Thuderoz
Sep 25, 2007·Computational Biology and Chemistry·Soohee HanKwang-Hyun Cho
Sep 4, 2008·Biotechnology and Bioengineering·Ryan S Senger, Eleftherios T Papoutsakis
Jan 8, 2010·Gene Regulation and Systems Biology·Simon Rosenfeld

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