Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation
<p>Abstract</p> <p>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 approac...
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doaj-ac0731f9445946389bd077582d560dba2020-11-25T01:01:47ZengBMCBMC Bioinformatics1471-21052007-03-018Suppl 1S1610.1186/1471-2105-8-S1-S16Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbationNeretti NicolaRemondini DanielTatar MarcSedivy John MPierini MichelaMazzatti DawnPowell JonathanFranceschi ClaudioCastellani Gastrone C<p>Abstract</p> <p>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 <it>D. melanogaster</it>; 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.</p> <p>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.</p> <p>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.</p> |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Neretti Nicola Remondini Daniel Tatar Marc Sedivy John M Pierini Michela Mazzatti Dawn Powell Jonathan Franceschi Claudio Castellani Gastrone C |
spellingShingle |
Neretti Nicola Remondini Daniel Tatar Marc Sedivy John M Pierini Michela Mazzatti Dawn Powell Jonathan Franceschi Claudio Castellani Gastrone C Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation BMC Bioinformatics |
author_facet |
Neretti Nicola Remondini Daniel Tatar Marc Sedivy John M Pierini Michela Mazzatti Dawn Powell Jonathan Franceschi Claudio Castellani Gastrone C |
author_sort |
Neretti Nicola |
title |
Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation |
title_short |
Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation |
title_full |
Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation |
title_fullStr |
Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation |
title_full_unstemmed |
Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation |
title_sort |
correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2007-03-01 |
description |
<p>Abstract</p> <p>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 <it>D. melanogaster</it>; 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.</p> <p>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.</p> <p>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.</p> |
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