Dynamic gene network reconstruction from gene expression data in mice after influenza A (H1N1) infection.

ABSTRACT:

Background

The immune response to viral infection is a temporal process, represented by a dynamic and complex network of gene and protein interactions. Here, we present a reverse engineering strategy aimed at capturing the temporal evolution of the underlying Gene Regulatory Networks (GRN). The proposed approach will be an enabling step towards comprehending the dynamic behavior of gene regulation circuitry and mapping the network structure transitions in response to pathogen stimuli.

Results

We applied the Time Varying Dynamic Bayesian Network (TV-DBN) method for reconstructing the gene regulatory interactions based on time series gene expression data for the mouse C57BL/6J inbred strain after infection with influenza A H1N1 (PR8) virus. Initially, 3500 differentially expre

SUBMITTER: Dimitrakopoulou K 

PROVIDER: S-EPMC3219564 | biostudies-literature | 2011 Oct

REPOSITORIES: biostudies-literature