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

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초록

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.

키워드

CELL-CYCLE; EXPRESSION; IDENTIFICATION; SIMILARITY; KNOWLEDGE
제목
SICAGO: Semi-supervised cluster analysis using semantic distance between gene pairs in Gene Ontology
저자
Kang, Bo-Yeong; Ko, Song; Kim, Dae-Won
DOI
10.1093/bioinformatics/btq133
발행일
2010-05
유형
Article
저널명
Bioinformatics
권
26
호
10
페이지
1384 ~ 1385