期刊
PATTERN RECOGNITION LETTERS
卷 31, 期 14, 页码 2073-2082出版社
ELSEVIER
DOI: 10.1016/j.patrec.2010.04.011
关键词
Gene ontology; Protein interaction networks; Bayesian networks; Classification
In recent years there has been a growing trend towards the inclusion of diverse genomic information to support comprehensive large-scale prediction of protein-protein interaction networks. The Gene Ontology (GO) is one such functional knowledge resource, which consists of three hierarchies to describe functional attributes of gene products: Molecular function, biological process, and cellular component. Using Bayesian networks, this paper presents a framework for the probabilistic combination of semantic similarity knowledge extracted from the three GO hierarchies for analysis of protein-protein interaction networks and demonstrates its application in yeast. The results indicate that by integrating information encoded in the GO hierarchies a better result can be achieved in terms of both statistical prediction capability and potential biological relevance. (C) 2010 Elsevier B.V. All rights reserved.
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