PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Mining Functional Modules in Genetic Networks with Decomposable Graphical Models
Mathaeus Dejori, Anton Schwaighofer, Volker Tresp and Martin Stetter
OMICS A Journal of Integrative Biology Volume 8, Number 2, pp. 176-188, 2004.

Abstract

In recent years graphical models have become an increasingly important tool for the structural analysis of genome-wide expression profiles at the systems level. Here we present a new graphical modelling technique, which is based on decomposable graphical models, and apply it to a set of gene expression profiles from acute lymphoblastic leukemia (ALL). The new method explains probabilistic dependencies of expression levels in terms of the concerted action of underlying genetic functional modules, which are represented as so-called cliques in the graph. In addition, the method uses continuous-valued (instead of discretized) expression levels, and makes no particular assumption about their probability distribution. We show that the method successfully groups members of known functional modules to cliques. Our method allows the evaluation of the importance of genes for global cellular functions based on both link count and the clique membership count.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:707
Deposited By:Anton Schwaighofer
Deposited On:29 December 2004