Title :
CLUGO: a clustering algorithm for automated functional annotations based on gene ontology
Author :
Lee, In-Yee ; Ho, Jan-Ming ; Chen, Ming-Syan
Author_Institution :
Dept. of Electr. Eng., National Taiwan Univ., Taiwan
Abstract :
We address the issue of providing highly informative and comprehensive annotations using information revealed by the structured vocabularies of gene ontology (GO). For a target, a set of candidate terms for inferring target properties is collected and form a unique distribution on the GO directed acyclic graph (DAG). We propose a novel ontology-based clustering algorithm $CLUGO, which considers GO hierarchical characteristics and the clustering of term distributions. By identifying significant groups in the distributions, CLUGO assigns comprehensive and correct annotations for a target. According to the results of experiments with automated sequence functional annotations, CLUGO represents a considerable improvement over our previous work - GOMIT in terms of recall while maintaining a similar level of precision. We conclude that given a GO candidate term distribution, CLUGO is an efficient ontology-based clustering algorithm for selecting comprehensive and correct annotations.
Keywords :
biology computing; directed graphs; genetics; ontologies (artificial intelligence); pattern clustering; vocabulary; CLUGO; automated sequence functional annotation; directed acyclic graph; gene ontology; ontology-based clustering algorithm; structured vocabulary; term distribution; Accuracy; Clustering algorithms; Data mining; Databases; Filtering algorithms; Information retrieval; Information science; Ontologies; Performance gain; Vocabulary;
Conference_Titel :
Data Mining, Fifth IEEE International Conference on
Print_ISBN :
0-7695-2278-5
DOI :
10.1109/ICDM.2005.42