Refined phylogenetic profiles method for predicting protein-protein interactions

Jingchun Sun, Jinlin Xu, Zhen Liu, Aimin Zhao, Tieliu Shi, Yixue Li

Research output: Contribution to journalArticlepeer-review

100 Scopus citations

Abstract

Motivation: The increasing availability of complete genome sequences provides excellent opportunity for the further development of tools for functional studies in proteomics. Several experimental approaches and in silico algorithms have been developed to cluster proteins into networks of biological significance that may provide new biological insights, especially into understanding the functions of many uncharacterized proteins. Among these methods, the phylogenetic profiles method has been widely used to predict protein-protein interactions. It involves the selection of reference organisms and identification of homologous proteins. Up to now, no published report has systematically studied the effects of the reference genome selection and the identification of homologous proteins upon the accuracy of this method. Results: In this study, we optimized the phylogenetic profiles method by integrating phylogenetic relationships among reference organisms and sequence homology information to improve prediction accuracy. Our results revealed that the selection of the reference organisms set and the criteria for homology identification significantly are two critical factors for the prediction accuracy of this method. Our refined phylogenetic profiles method shows greater performance and potentially provides more reliable functional linkages compared with previous methods.

Original languageEnglish
Pages (from-to)3409-3415
Number of pages7
JournalBioinformatics
Volume21
Issue number16
DOIs
StatePublished - 15 Aug 2005
Externally publishedYes

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