Title :
A new method for measuring the semantic similarity on gene ontology
Author :
Shen, Ying ; Zhang, Shaohong ; Wong, Hau-San
Author_Institution :
Dept. of Comput. Sci., City Univ. of Hong Kong, Hong Kong, China
Abstract :
Semantic similarity defined on Gene Ontology (GO) aims to provide the functional relationship between different biological processes, molecular functions, or cellular components. In this paper, a novel method, namely the Shortest Path (SP) algorithm, for measuring the semantic similarity on GO is proposed based on both the GO structure information and the term´s property. The proposed algorithm searches for the shortest path that connects two terms and uses the sum of weights on the shortest path to compute the semantic similarity for GO terms. A method for evaluating the nonlinear correlation between two variables is also introduced for validation. Extensive experiments conducted on two public gene expression datasets demonstrate the overall superiority of SP method over the other state-of-the-art methods evaluated.
Keywords :
bioinformatics; cellular biophysics; genetics; molecular biophysics; ontologies (artificial intelligence); biological processes; cellular components; gene ontology; molecular functions; public gene expression datasets; semantic similarity; shortest path algorithm; Bioinformatics; Correlation; Gene expression; Integrated circuits; Joining processes; Ontologies; Semantics;
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2010 IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-8306-8
Electronic_ISBN :
978-1-4244-8307-5
DOI :
10.1109/BIBM.2010.5706623