Finding hidden relationship among biological concepts in gene ontology

Authors:
Jovan David Rebolledo-Mendez;Masanori Higashihara;Yoichi Yamada;Kenji Satou
Affiliations:
Graduate School of Natural Science and Technology, Kanazawa University, Kanazawa, Japan;Graduate School of Knowledge Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan;Graduate School of Natural Science and Technology, Kanazawa University, Kanazawa, Japan;Graduate School of Natural Science and Technology, Kanazawa University, Kanazawa, Japan
Venue:
BEBI'08 Proceedings of the 1st WSEAS international conference on Biomedical electronics and biomedical informatics
Year:
2008

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Abstract

A novel method of microarray data analysis using Gene Ontology (GO) is proposed in this paper. Through the discrimination and feature ranking at each GO term, it was characterized as a feature importance vector with respect to the gene expression pattern contained in a microarray data. In combination with the use of hierarchical clustering on the vectors, it is demonstrated that the method could help to discover hidden relationship among GO terms not only the ones in the same category but also inter-category relationships.