Inferring Gene Networks using Robust Statistical Techniques

Nadadoor Venkat R., Ben-Zvi Amos and Shah Sirish L.

Statistical Applications in Genetics and Molecular Biology, 2011, vol. 10, issue 1, 1-30

Abstract: Inference of gene networks is an important step in understanding cellular dynamics. In this work, a novel algorithm is proposed for inferring gene networks from gene expression data using linear ordinary differential equations. Under the proposed method, a combination of known statistical tools including partial least squares (PLS), leave-one-out jackknifing, and the Akaike information criterion (AIC) are used for robust estimation of gene connectivity matrix. The proposed approach is tested and validated using a computer simulated gene network model and an experimental data on a nine gene network in Eschericia coli.

Keywords: gene network; partial least squares; jackknifing; Akaike information criterion; significance level (search for similar items in EconPapers)
Date: 2011
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DOI: 10.2202/1544-6115.1658

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