Recursive regularization for inferring gene networks from time-course gene expression profiles.

ABSTRACT:

Background

Inferring gene networks from time-course microarray experiments with vector autoregressive (VAR) model is the process of identifying functional associations between genes through multivariate time series. This problem can be cast as a variable selection problem in Statistics. One of the promising methods for variable selection is the elastic net proposed by Zou and Hastie (2005). However, VAR modeling with the elastic net succeeds in increasing the number of true positives while it also results in increasing the number of false positives.

Results

By incorporating relative importance of the VAR coefficients into the elastic net, we propose a new class of regularization, called recursive elastic net, to increase the capability of the elastic net and estimate gene ne

SUBMITTER: Shimamura T 

PROVIDER: S-EPMC2686685 | biostudies-literature | 2009 Apr

REPOSITORIES: biostudies-literature