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Understanding signaling in yeast: Insights from network analysis
Author(s) -
Arga K Yalçın,
Önsan Z İlsen,
Kırdar Betül,
Ülgen Kutlu Ö,
Nielsen Jens
Publication year - 2007
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.21317
Subject(s) - saccharomyces cerevisiae , computational biology , signal transduction , biology , function (biology) , identification (biology) , interaction network , protein–protein interaction , biological pathway , yeast , gene , microbiology and biotechnology , genetics , gene expression , botany
Reconstruction of protein interaction networks that represent groups of proteins contributing to the same cellular function is a key step towards quantitative studies of signal transduction pathways. Here we present a novel approach to reconstruct a highly correlated protein interaction network and to identify previously unknown components of a signaling pathway through integration of protein–protein interaction data, gene expression data, and Gene Ontology annotations. A novel algorithm is designed to reconstruct a highly correlated protein interaction network which is composed of the candidate proteins for signal transduction mechanisms in yeast Saccharomyces cerevisiae . The high efficiency of the reconstruction process is proved by a Receiver Operating Characteristic curve analysis. Identification and scoring of the possible linear pathways enables reconstruction of specific sub‐networks for glucose‐induction signaling and high osmolarity MAPK signaling in S. cerevisiae . All of the known components of these pathways are identified together with several new “candidate” proteins, indicating the successful reconstructions of two model pathways involved in S. cerevisiae . The integrated approach is hence shown useful for (i) prediction of new signaling pathways, (ii) identification of unknown members of documented pathways, and (iii) identification of network modules consisting of a group of related components that often incorporate the same functional mechanism. Biotechnol. Bioeng. 2007; 97: 1246–1258. © 2007 Wiley Periodicals, Inc.