An Algorithm for Generating Representative Functional Annotations Based on Gene Ontology
DEXA '03 Proceedings of the 14th International Workshop on Database and Expert Systems Applications
Bioinformatics
GOMIT: A Generic and Adaptive Annotation Algorithm Based on Gene Ontology Term Distributions
BIBE '05 Proceedings of the Fifth IEEE Symposium on Bioinformatics and Bioengineering
Kernel: based visualisation of genes with the gene ontology
AusDM '08 Proceedings of the 7th Australasian Data Mining Conference - Volume 87
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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.