Reverse Engineering of Gene Regulatory Networks: A Finite State Linear Model

Thomas Schlitt and Alvis Brazma
European Bioinformatics Institute
EMBL outstation Hinxton, Wellcome Trust
Genome Campus,
Hinxton, Cambridge CB10 1SD, UK
prestype: Poster
presenter: Thomas Schlitt and Alvis Brazma

We propose a new model for describing gene regulatory networks that can capture discrete (boolean) and continuous (differential) aspects of gene regulation. We are giving some illustrations of the model, we study the problem of the reverse engineering of such networks, i.e., how to construct a network from gene expression data. We prove that for our model there exists an algorithm finding a network compatible with the given data. An informal extension of the model can be used as a basis for a language for depicting real-world gene regulatory networks elements. We demonstrate such semi-formal language extension by describing lambda-phage decision making circuit.

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