Weighted-LASSO for structured network inference from time course data.

Abstract:

: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).

authors

Charbonnier C,Chiquet J,Ambroise C

doi

10.2202/1544-6115.1519

subject

Has Abstract

pub_date

2010-01-01 00:00:00

pages

Article 15

eissn

2194-6302

issn

1544-6115

journal_volume

9

pub_type

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