A new computational approach to analyze human protein complexes and predict novel protein interactions

Zanivan, S. , Cascone, I., Peyron, C., Molineris, I., Marchio, S., Caselle, M. and Bussolino, F. (2007) A new computational approach to analyze human protein complexes and predict novel protein interactions. Genome Biology, 8, R256. (doi: 10.1186/gb-2007-8-12-r256) (PMID:18053208) (PMCID:PMC2246258)

Abstract

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.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Zanivan, Professor Sara
• Authors: Zanivan, S., Cascone, I., Peyron, C., Molineris, I., Marchio, S., Caselle, M., and Bussolino, F.
• College/School: College of Medical Veterinary and Life Sciences > School of Cancer Sciences
• Journal Name: Genome Biology
• Publisher: BioMed Central
• ISSN: 1474-760X
• ISSN (Online): 1465-6906
• Copyright Holders: Copyright © 2007 Zanivan et al.
• First Published: First published in Genome Biology 8: R256
• Publisher Policy: Reproduced under a Creative Commons License