Title :
A hybrid measure for the semantic similarity of gene ontology terms
Author :
Shu-Bo Zhang ; Jian-Huang Lai
Author_Institution :
Dept. of Comput. Sci., Guangzhou Maritime Inst., Guangzhou, China
Abstract :
Measuring the semantic similarity between pairs of terms in Gene Ontology (GO) can help to compare genes that can not be compared by other computational methods. In this study, we proposed a hybrid method to calculate the semantic similarity between two GO terms by taking into account multiple common ancestors of they have in common, and aggregating the semantic information and depth information of the non-redundant common ancestors. Our method searches for non-redundant common ancestors in an effective way. Validation experiments were conducted on both expression dataset and pathway dataset, and the experimental results suggest the superiority of our method against some existing methods.
Keywords :
biology computing; genetics; ontologies (artificial intelligence); GO terms; depth information; gene ontology; hybrid measure; nonredundant common ancestors; semantic information; semantic similarity; Biomedical measurement; Databases; Degradation; Gene expression; Ontologies; Semantics; GO terms; Gene Ontology (GO); biological pathways; gene expression profile; semantic similarity;
Conference_Titel :
Systems and Informatics (ICSAI), 2014 2nd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4799-5457-5
DOI :
10.1109/ICSAI.2014.7009415