Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation

Time course gene expression experiments are a popular means to infer co-expression. Many methods have been proposed to cluster genes or to build networks based on similarity measures of their expression dynamics. In this paper we apply a correlation based approach to network reconstruction to three datasets of time series gene expression following system perturbation: 1) Conditional, Tamoxifen dependent, activation of the cMyc proto-oncogene in rat fibroblast; 2) Genomic response to nutrition changes in D. melanogaster; 3) Patterns of gene activity as a consequence of ageing occurring over a life-span time series (25y–90y) sampled from T-cells of human donors. We show that the three datasets undergo similar transitions from an "uncorrelated" regime to a positively or negatively correlated one that is symptomatic of a shift from a "ground" or "basal" state to a "polarized" state. In addition, we show that a similar transition is conserved at th...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: Nicola Neretti, Daniel Remondini, Marc Tatar, John M. Sedivy, Michela Pierini, Dawn Mazzatti, Jonathan Powell, Claudio Franceschi, Gastone C. Castellani
• Keywords: BMCBI 2007, Gene Expression, Similar Transition, Time Series