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

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. © The Author 2010. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org.