Kenta Nakai / Professor / Division of Biosciences
Department of Medical Genome Sciences / / Computational analyses of genetic information encoded in genome DNA

Career Summary
1986: Graduated/BSc (Faculty of Science, Kyoto University)
1989-1991: Research Associate (Kyoto University)
1992: PhD (Kyoto University)
1992-1995: Research Associate (National Institute for Basic Biology)
1995-1999: Associate Professor (Osaka University)
1999-2003: Associate Professor (University of Tokyo)
2003-present: Professor (University of Tokyo)
Educational Activities
Graduate School: Bioinformatics Basics for Biomedical Students
Graduate School of Information Science and Technology: Functional Genome Informatics Primer
Research Activities
Prediction of subcellular localization sites of proteins:
I am a pioneer of this research topic. Literature (1) has been cited more than 1000 times so far.
Sequence analyses of transcriptional regulatory regions:
As an example of this topic, we constructed a probabilistic model of muscle-specific promoters in ascidians. Several novel genes predicted using the model were experimentally verified by a collaborator (2).
1) Nakai and Kanehisa: A knowledge base for predicting protein localization sites in eukaryotic cells, Genomics 14, 897-911 (1992).
2) Vandenbon, Miyamoto, Takimoto, Kusakabe, and Nakai: Markov chain-based promoter structure modeling for tissue-specific expression pattern prediction, DNA Res., 15(1), 3-11 (2008).
Other Activities
Secretary/Board Member: Japanese Society for Bioinformatics (JSBi), Chem-Bio Informatics Society (CBI), Genomic Drug Discovery Forum
Member: Japanese Society of Molecular Biology, Society of Genome Microbiology, International Society of Computational Biology (ISCB)
Editorial Board Member: DNA Research (Oxford Univ. Press), Mathematical Biosciences (Elsevier), Journal of Biomedical Science and Engineering (Sci. Res. Pub.)
Future Plan
We will continue our attempts to computationally interpret genetic information encoded in genome DNA sequences using various approaches.
Messages to Students
If you become my graduate student, I will do my best to ensure that you made the right choice.