A Dynamic Model of Gene Regulatory Networks Based on Inertia Principle

Florence d'Alché-Buc (1) , Pierre-Jean Lahaye , Bruno-Edouard Perrin , Liva Ralaivola (1) , Todor Vujasinovic , Aurélien Mazurie , Samuele Bottani

1 MALIRE - Machine Learning and Information Retrieval

In molecular biology, functions are produced by a set of macromolecules that interact at different levels. Genes and their products, proteins, participate to regulatory networks that control the response of the cell to external input signals. One of the most important challenge to biologists is undoubtedly to understand the mechanisms that govern this regulation, and to identify among a set of genes which play a regulator role and which are regulated. While the problem used to be approached by a gene to gene approach, this is changed significantly by the development of microarray technology. Expression of thousands of genes of a given organism or a given tissue can now be measured simultaneously on the same chip. This revolution opens a large avenue for research on reconstruction of gene regulatory networks from experimental data.

Domaines: Informatique [cs]

Florence d'Alché-Buc, Pierre-Jean Lahaye, Bruno-Edouard Perrin, Liva Ralaivola, Todor Vujasinovic, et al.. A Dynamic Model of Gene Regulatory Networks Based on Inertia Principle. Bioinformatics using Computational Intelligence Paradigms, 176, Springer, pp.93-117, 2005, Studies in Fuzziness and Soft Computing, ⟨10.1007/10950913_5⟩. ⟨hal-01533420⟩