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

Sara Zanivan, Ilaria Cascone, Chiara Peyron, Ivan Molineris, Serena Marchio, Michele Caselle, Federico Bussolino

Research output: Contribution to journalArticle

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.

Original languageEnglish
Article numberR256
JournalGenome Biology
Volume8
Issue number12
DOIs
Publication statusPublished - Dec 4 2007

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Cell Biology
  • Genetics

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