Inference of gene regulatory networks and compound mode of action from time course gene expression profiles

Bioinformatics. 2006 Apr 1;22(7):815-22. doi: 10.1093/bioinformatics/btl003. Epub 2006 Jan 17.

Abstract

Motivation: Time series expression experiments are an increasingly popular method for studying a wide range of biological systems. Here we developed an algorithm that can infer the local network of gene-gene interactions surrounding a gene of interest. This is achieved by a perturbation of the gene of interest and subsequently measuring the gene expression profiles at multiple time points. We applied this algorithm to computer simulated data and to experimental data on a nine gene network in Escherichia coli.

Results: In this paper we show that it is possible to recover the gene regulatory network from a time series data of gene expression following a perturbation to the cell. We show this both on simulated data and on a nine gene subnetwork part of the DNA-damage response pathway (SOS pathway) in the bacteria E. coli.

Contact: dibernardo@tigem.it SUPLEMENTARY INFORMATION: Supplementary data are available at http://dibernado.tigem.it

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Bayes Theorem
  • Cell Physiological Phenomena
  • Computer Simulation
  • Escherichia coli / genetics
  • Escherichia coli / metabolism
  • Gene Expression Profiling / methods*
  • Models, Biological
  • Models, Statistical
  • Time Factors