Ontology highlight
ABSTRACT:
SUBMITTER: Zanivan S
PROVIDER: S-EPMC2246258 | biostudies-literature | 2007
REPOSITORIES: biostudies-literature
Zanivan Sara S Cascone Ilaria I Peyron Chiara C Molineris Ivan I Marchio Serena S Caselle Michele M Bussolino Federico F
Genome biology 20070101 12
We propose a new approach to identify interacting proteins based on gene expression data. By using hypergeometric distribution and extensive Monte-Carlo simulations, we demonstrate that looking at synchronous expression peaks in a single time interval is a high sensitivity approach to detect co-regulation among interacting proteins. Combining gene expression and Gene Ontology similarity analyses enabled the extraction of novel interactions from microarray datasets. Applying this approach to p21- ...[more]