Journal Article

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

Bo-Yeong Kang, Song Ko and Dae-Won Kim

in Bioinformatics

Volume 26, issue 10, pages 1384-1385
Published in print May 2010 | ISSN: 1367-4803
Published online March 2010 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btq133
SICAGO: Semi-supervised cluster analysis using semantic distance between gene pairs in Gene Ontology

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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

Journal Article.  1201 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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