Boolean networks using the chi-square test for inferring large-scale gene regulatory networks.

ABSTRACT:

Background

Boolean network (BN) modeling is a commonly used method for constructing gene regulatory networks from time series microarray data. However, its major drawback is that its computation time is very high or often impractical to construct large-scale gene networks. We propose a variable selection method that are not only reduces BN computation times significantly but also obtains optimal network constructions by using chi-square statistics for testing the independence in contingency tables.

Results

Both the computation time and accuracy of the network structures estimated by the proposed method are compared with those of the original BN methods on simulated and real yeast cell cycle microarray gene expression data sets. Our results reveal that the proposed chi-square

SUBMITTER: Kim H 

PROVIDER: S-EPMC1802094 | biostudies-literature | 2007 Feb

REPOSITORIES: biostudies-literature