Mining published lists of cancer related microarray experiments: Identification of a gene expression signature having a critical

Background: Routine application of gene expression microarray technology is rapidly producing large amounts of data that necessitate new approaches of analysis. The analysis of a specific microarray experiment profits enormously from cross-comparing to other experiments. This process is generally performed by numerical meta-analysis of published data where the researcher chooses the datasets to be analyzed based on assumptions about the biological relations of published datasets to his own data, thus severely limiting the possibility of finding surprising connections. Here we propose using a repository of published gene lists for the identification of interesting datasets to be subjected to more detailed numerical analysis. Results: We have compiled lists of genes that have been reported as differentially regulated in cancer related microarray studies. We searched these gene lists for statistically significant overlaps with lists of genes regulated by the tumor suppressors p16 and pRB...

• Type: Journal
• Year: 2005
• Where: BMCBI
• Authors: Giacomo Finocchiaro, Francesco Mancuso, Heiko Müller
• Keywords: BMCBI 2005, Gene Expression, Gene Expression Microarray, Gene Lists