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Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Transcription profiling time series of gene expression following irradiation to identify P53 activity

ABSTRACT: The purpose of the experiment was to generate a time course of gene expression following irradiation. The goal was then to model this data to extract hidden variables - chiefly, the activity profiles of the p53 transcription factor. Using this information the aim was to predict which transcripts changed by IR were targets of p53. Cells in log phase (1 x 106 ml-1) were ?-irradiated with 5 Gy at room temperature (RT) at a dose rate of 2.45 Gy per minute with a 137Cs ?-irradiator. Cells were harvested at 0, 2, 4, 6, 8, 10 and 12 hours, and RNA and protein were extracted (Trizol, Invitrogen). Affymetrix U133A arrays were hybridized as standard (www.affymetrix.co.uk). Array quality was determined using R and GCOS .rpt file values. The time course was replicated three times from independent cell preparations.

ORGANISM(S): Homo sapiens

SUBMITTER: Martino Barenco

PROVIDER: E-MEXP-549 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Ranked prediction of p53 targets using hidden variable dynamic modeling.

Barenco Martino M Tomescu Daniela D Brewer Daniel D Callard Robin R Stark Jaroslav J Hubank Michael M

Genome biology 20060331 3

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 pr ...[more]

PMID: 16584535

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