Gene-network inference by message passing

Details Gene-network inference by message passing Gene-network inference by message passing

2008-12-04

arxiv.org/abs/0812.0936v1

Journal of Physics: Conference Series 95 (2008) 012016

Biology

Quantitative Biology

Quantitative Methods

Proc. of International Workshop on Statistical-Mechanical Informatics 2007, Kyoto

Scientific paper

10.1088/1742-6596/95/1/012016

The inference of gene-regulatory processes from gene-expression data belongs to the major challenges of computational systems biology. Here we address the problem from a statistical-physics perspective and develop a message-passing algorithm which is able to infer sparse, directed and combinatorial regulatory mechanisms. Using the replica technique, the algorithmic performance can be characterized analytically for artificially generated data. The algorithm is applied to genome-wide expression data of baker's yeast under various environmental conditions. We find clear cases of combinatorial control, and enrichment in common functional annotations of regulated genes and their regulators.

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