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Bioinformatics. 2010 May 15;26(10):1384-5. doi: 10.1093/bioinformatics/btq133. Epub 2010 Mar 26.

SICAGO: Semi-supervised cluster analysis using semantic distance between gene pairs in Gene Ontology.

Author information

1
School of Mechanical Engineering, Kyungpook National University, 1370 Sankyuk-dong, Buk-gu, Daegu 702-701, Korea.

Abstract

SUMMARY:

Despite the importance of using the semantic distance to improve the performance of conventional expression-based clustering, there are few freely available software that provides a clustering algorithm using the ontology-based semantic distances as prior knowledge. Here, we present the SICAGO (SemI-supervised Cluster Analysis using semantic distance between gene pairs in Gene Ontology) system that helps to discover the groups of genes more effectively using prior knowledge extracted from Gene Ontology.

AVAILABILITY:

http://ai.cau.ac.kr/sicago.html

CONTACT:

dwkim@cau.ac.kr

PMID:
20348546
DOI:
10.1093/bioinformatics/btq133
[Indexed for MEDLINE]

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