Identification of Activated Transcription Factors from Microarray Gene Expression Data of Kampo Medicine-Treated Mice

Rui Yamaguchi[1] (ruiy@ims.u-tokyo.ac.jp)
Masahiro Yamamoto[2][3] (yamamoto_masahiro@mail.tsumura.co.jp)
Seiya Imoto[1] (imoto@ims.u-tokyo.ac.jp)
Masao Nagasaki[1] (masao@ims.u-tokyo.ac.jp)
Ryo Yoshida[4] (yoshidar@ism.ac.jp)
Kenji Tsuiji[2] (di055036@sc.itc.keio.ac.jp)
Atsushi Ishige[2] (ishige@sc.itc.keio.ac.jp)
Hiroaki Asou[3] (asou@tmig.or.jp)
Kenji Watanabe[2] (toyokeio@sc.itc.keio.ac.jp)
Satoru Miyano[1] (miyano@ims.u-tokyo.ac.jp)

[1]Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan
[2]Department of Kampo medicine, Keio University School of Medicine 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
[3]Department of Neuro-glia cell biology, Tokyo Metropolitan Institute of Gerontology, 35-2 Sakaecho, Itabashi-ku, Tokyo 173-0015, Japan
[4]The Institute of Statistical Mathematics 4-6-7 Minami-Azabu, Minato-ku, Tokyo 106-8569, Japan


Abstract

We propose an approach to identify activated transcription factors from gene expression data using a statistical test. Applying the method, we can obtain a synoptic map of transcription factor activities which helps us to easily grasp the systemfs behavior. As a real data analysis, we use a case-control experiment data of mice treated by a drug of Kampo medicine remedying degraded myelin sheath of nerves in central nervous system. Kampo medicine is Japanese traditional herbal medicine. Since the drug is not a single chemical compound but extracts of multiple medicinal herb, the effector sites are possibly multiple. Thus it is hard to understand the action mechanism and the systemfs behavior by investigating only few highly expressed individual genes. Our method gives summary for the systemfs behavior with various functional annotations, e.g. TFAs and gene ontology, and thus offer clues to understand it in more holistic manner.

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Japanese Society for Bioinformatics