KIRYU Hisanori
(Associate Professor/Life Sciences)
Computational Biology and Medical Sciences/Bionetwork Analysis/Mathematical Model of Life Processes
Career Summary
1997: Bachelor of Science, Faculty of Science, Kyoto University.
1999: Master of Philosophy, Graduate School of Arts and Sciences, The University of Tokyo.
1999-2002: Research Fellowship for Young Scientists, Japan Society for the Promotion of Science (JSPS)
2003: Master of Engineering, Graduate School of Information Science, Nara Institute of Science and Technology
2004: Doctor of Philosophy, Graduate School of Arts and Sciences, The University of Tokyo.
2005-2009: AIST Research Staff (Post Doctoral Researcher), Computational Biology Research Center (CBRC), Advanced Industrial Science and Technology (AIST)
2007: Doctor of Science, Graduate School of Information Science, Nara Institute of Science and Technology
2009-2015: Associate Professor, Graduate School of Frontier Sciences, The University of Tokyo
2015-present: Associate Professor, Graduate School of Frontier Sciences, The University of Tokyo
Educational Activities
Advanced Course II
Bioinformatics and Systems Biology
Biostatistics
Basic Computational Exercise
Research Activities
RNA Sequence Analysis
Developing Tools for Comparative Genomics
Understanding Transcriptional Networks of Mammalian Species
Literature
1) Hamada M, Sato K, Kiryu H, Mituyama T, Asai K. "Predictions of RNA secondary structure by combining homologous sequence information." ISMB2009, Bioinformatics 25: i330-i338; doi:10.1093/bioinformatics/btp228 (2009)
2) Hisanori Kiryu, Taishin Kin, and Kiyoshi Asai. "Rfold: an exact algorithm for computing local base pairing probabilities." Bioinformatics, 24: 367-373 (2008)
3) Hisanori Kiryu, Taku Oshima, and Kiyoshi Asai. "Extracting relations between promoter sequences and their strengths from microarray data." Bioinformatics 21: 1062-1068.(2005)
Other Activities
Japanese Society of Bioinformatics (JSBi)
The Molecular Biology Society of Japan
Future Plan
We are developing tools for analyzing the transcriptional regulatory networks of mammals.
Our goal is to decipher the mechanisms of embryogenesis and organ development
from the statistical signatures of genome sequences.
Messages to Students
Computational biology is growing out of its infancy.
There are many biological problems that cannot be tackled without its power.
I recommend that you join this promising field.