Multievidence microarray mining

Trends Genet. 2005 Oct;21(10):553-8. doi: 10.1016/j.tig.2005.07.011.


Microarray mining is a challenging task because of the superposition of several processes in the data. We believe that the combination of microarray data-based analyses (statistical significance analysis of gene expression) with array-independent analyses (literature-mining and promoter analysis) enables some of the problems of traditional array analysis to be overcome. As a proof-of-principle, we revisited publicly available microarray data derived from an experiment with platelet-derived growth factor (PDGF)-stimulated fibroblasts. Our strategy revealed results beyond the detection of the major metabolic pathway known to be linked to the PDGF response: we were able to identify the crosstalking regulatory networks underlying the metabolic pathway without using a priori knowledge about the experiment.

Publication types

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

MeSH terms

  • Computational Biology / methods*
  • Databases, Genetic
  • Fibroblasts / metabolism
  • Models, Genetic*
  • Oligonucleotide Array Sequence Analysis / methods*
  • Platelet-Derived Growth Factor / genetics*
  • Platelet-Derived Growth Factor / metabolism
  • Promoter Regions, Genetic / genetics
  • Signal Transduction / genetics*
  • Transcription Factors / genetics


  • Platelet-Derived Growth Factor
  • Transcription Factors