CLUGO: A clustering algorithm for automated functional annotations based on gene ontology
Journal
IEEE International Conference on Data Mining, ICDM
Pages
705-708
Date Issued
2005
Author(s)
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. © 2005 IEEE.
SDGs
Type
conference paper