Multi-aspect gene relation analysis.
Recent progress in high-throughput screening technologies has led to the production of massive amounts data that we can use to understand biological systems. To interpret this data, biologists often need to analyze the characteristics of a set of genes by using Gene Ontology (GO) annotation. We are proposing a novel method for assisting such an analysis. Given a set of genes, the method automatically extracts several analyzing aspects in terms of a subset of genes that are attached to some related GO terms. It then creates a gene-attribute bipartite graph that highlights the aspect selected by the user according to his/her interests. We describe this method in detail and report on an experiment where the proposed method is applied to the analysis of rat kidney expression data.
Yamakawa
H
H
Fujitsu Laboratories Ltd, Nakahara-ku, Kawasaki, Kanagawa, Japan.
Maruhashi
K
K
Nakao
Y
Y
Yamaguchi
M
M
D000818:Animals; D019295:Computational Biology / Q000379:methods; D018507:Gene Expression Regulation, Developmental; D005796:Genes; D007668:Kidney / Q000196:embryology; D008957:Models, Genetic; D011336:Probability