Reverse-engineering transcriptional modules from gene expression data

Details Reverse-engineering transcriptional modules from gene expression data Reverse-engineering transcriptional modules from gene expression data

2009-04-08

arxiv.org/abs/0904.1298v1

Ann. N. Y. Acad. of Sci. 1158, 36 - 43 (2009)

Biology

Quantitative Biology

Quantitative Methods

5 pages REVTeX, 4 figures

Scientific paper

10.1111/j.1749-6632.2008.03943.x

"Module networks" are a framework to learn gene regulatory networks from expression data using a probabilistic model in which coregulated genes share the same parameters and conditional distributions. We present a method to infer ensembles of such networks and an averaging procedure to extract the statistically most significant modules and their regulators. We show that the inferred probabilistic models extend beyond the data set used to learn the models.

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