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- W1969133767 abstract "Abstract 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 the pathway level, and that this information can be used for the construction of meta-networks where it is possible to assess new relations among functionally distant sets of molecular functions." @default.
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- W1969133767 date "2007-03-01" @default.
- W1969133767 modified "2023-10-08" @default.
- W1969133767 title "Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation" @default.
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- W1969133767 doi "https://doi.org/10.1186/1471-2105-8-s1-s16" @default.
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