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Statistical Applications in Genetics and Molecular Biology

Editor-in-Chief: Stumpf, Michael P.H.

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Volume 9, Issue 1 (Feb 2010)

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Weighted-LASSO for Structured Network Inference from Time Course Data

Camille Charbonnier / Julien Chiquet / Christophe Ambroise
Published Online: 2010-02-01 | DOI: https://doi.org/10.2202/1544-6115.1519

We present a weighted-LASSO method to infer the parameters of a first-order vector auto-regressive model that describes time course expression data generated by directed gene-to-gene regulation networks. These networks are assumed to own prior internal structures of connectivity which drive the inference method. This prior structure can be either derived from prior biological knowledge or inferred by the method itself. We illustrate the performance of this structure-based penalization both on synthetic data and on two canonical regulatory networks (the yeast cell cycle regulation network and the E. coli S.O.S. DNA repair network).

Keywords: biological networks; vector auto-regressive model; LASSO

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Published Online: 2010-02-01


Citation Information: Statistical Applications in Genetics and Molecular Biology, ISSN (Online) 1544-6115, DOI: https://doi.org/10.2202/1544-6115.1519.

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©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston. Copyright Clearance Center

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