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-activated kinase 1, we validated α-tubulin and early endosome antigen 1 as its novel interactors. © 2007 Zanivan et al.; licensee BioMed Central Ltd.
CITATION STYLE
Zanivan, S., Cascone, I., Peyron, C., Molineris, I., Marchio, S., Caselle, M., & Bussolino, F. (2007). A new computational approach to analyze human protein complexes and predict novel protein interactions. Genome Biology, 8(12). https://doi.org/10.1186/gb-2007-8-12-r256
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