Determining the Properties of Gene Regulatory Networks from Expression Data

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Author(s): Larry S. Liebovitch (Florida Atlantic University, USA), Lina A. Shehadeh (University of Miami, USA), Viktor K. Jirsa (Florida Atlantic University, USA), Marc-Thorsten Hütt (Jacobs University, Germany)and Carsten Marr (Helmholtz Zentrum München, Germany)
Copyright: 2010
Pages: 24
Source title: Handbook of Research on Computational Methodologies in Gene Regulatory Networks
Source Author(s)/Editor(s): Sanjoy Das (Kansas State University, USA), Doina Caragea (Kansas State University, USA), Stephen Welch (Kansas State University, USA)and William H. Hsu (Kansas State University, USA)
DOI: 10.4018/978-1-60566-685-3.ch017

Keywords: Biologically-Inspired Computing / Medical Information Science Reference / Medical Technologies / Medicine & Healthcare

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Abstract

The expression of genes depends on the physical structure of DNA, how the function of DNA is regulated by the transcription factors expressed by other genes, RNA regulation, such as that through RNA interference, and protein signals mediated by protein-protein interaction networks. We illustrate different approaches to determining information about the network of gene regulation from experimental data. First, we show that we can use statistical information of the mRNA expression values to determine the global topological properties of the gene regulatory network. Second, we show that analyzing the changes in expression due to mutations or different environmental conditions can give us information on the relative importance of the different mechanisms involved in gene regulation.

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Determining the Properties of Gene Regulatory Networks from Expression Data

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