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Genome Biol. 2006;7(3):R25. Epub 2006 Mar 31.

Ranked prediction of p53 targets using hidden variable dynamic modeling.

Author information

  • 1Institute of Child Health, University College London, Guilford Street, London WC1N 1EH, UK.

Abstract

Full exploitation of microarray data requires hidden information that cannot be extracted using current analysis methodologies. We present a new approach, hidden variable dynamic modeling (HVDM), which derives the hidden profile of a transcription factor from time series microarray data, and generates a ranked list of predicted targets. We applied HVDM to the p53 network, validating predictions experimentally using small interfering RNA. HVDM can be applied in many systems biology contexts to predict regulation of gene activity quantitatively.

PMID:
16584535
[PubMed - indexed for MEDLINE]
PMCID:
PMC1557743
Free PMC Article

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