Abstract:
We present our research activities in Systems Biology that 
use the supercomputer system at Human Genome Center of 
University of Tokyo (75 TFLOPS currently, and 225 TFLOPS from 
January 2011). We developed a series of computational methods 
based on Bayesian network with nonparametric regression and 
state space model combined with dimension reduction 
techniques for computing large gene networks from 
transcriptome data.  These computational methods for 
computing gene networks were applied to drug target pathway 
search and analysis. For a given drug, we took time-course 
gene expression data for the drug responses. We also made a 
set of gene expression data obtained by knock-downs of 
several hundreds of carefully selected genes (one knock-down 
for each microarray measurement). From these data, we 
computed Bayesian networks of 1000 genes by intensively using 
the supercomputer system. We show how we could explore these 
computed networks for analyzing dynamic features of the 
networks and for searching drug target genes and hubs in the 
networks.  The dynamic model based on state space model is 
also used for investigating the systems behaviors responding 
an anti-cancer drug and we predicted differentially 
regulated genes that were proven very powerful to prediction 
of survival in lung cancer.  In parallel, we developed a 
software tool Cell Illustrator (CI) which aims at analyzing 
and simulating complex dynamic causal interactions and 
processes such as metabolic pathways, signal transduction 
cascades, gene regulations. We have been developing an XML 
format Cell System Markup Language CSML 
(http://www.csml.org/) for describing biological systems 
with dynamics and ontology (Cell System Ontology). In 2008 
we released a Java web start software Cell Illustrator Online 
4.0 (CIO 4.0) (http://cionline.hgc.jp/) combined with CSML 
databases including TRANSPATH that has more sophisticated 
GUI functions such as automatic pathway layout algorithms 
using ontology information. Furthermore, we developed a 
supercomputer based computational method for automatic 
parameter estimation of dynamic models by using a technology 
called “data assimilation” which "blends" simulation 
models and observational data "rationally". This technology 
will be a strong computational strategy with which we can 
estimate personalized models from general biological models 
by using individual measurement data.


Bio:
Satoru Miyano, Ph.D., is a Professor of Human Genome Center, 
Institute of Medical Science, The University of Tokyo. He 
received the B.S., M.S. and Ph.D. all in Mathematics from 
Kyushu University, Japan, in 1977, 1979 and 1984, 
respectively.  Prior to joining the center in 1996, he held 
tenure professor positions at Kyushu University (1979-1984, 
Assistant Professor; 1987-1993, Associate Professor; 
1993-1996, Professor).  He was also an Alexander von 
Humboldt Research Fellow at the University of Paderborn, 
Germany from 1985 to 1987.  He served as Director of Research 
Institute of Information Science at Kyushu University from 
1994 to 1996 and Vice Director of Institute of Medical Science 
at the University of Tokyo from 2000 and 2003 and then from 
2004 to 2006.  He is a former president of Japanese Society 
for Bioinformatics (2003-2004), a past board of director of 
the International Society for Computational Biology 
(2004-2006), and a past (2003-2004) and current (2009-) 
president of Association of Asian Society for Bioinformatics 
(2003-2004).
Dr. Miyano is an author of more than one hundred peer-reviewed 
journal and conference articles.  He holds an editorial 
position in ten journals: Bioinformatics (Oxford University 
Press), Journal of Bioinformatics and Computational Biology 
(World Scientific), PLoS Computational Biology, Genome 
Informatics (Editor-in-Chief; Universal Academy Press), 
Lecture Notes in Bioinformatics (Springer-Verlag), IEEE/ACM 
Transactions on Computational Biology and Bioinformatics, 
Theoretical Computer Science (Elsevier), New Generation 
Computing, Annual Review of Intelligent Informatics, and 
Bulletin of Informatics.  He is the recipient of IBM Science 
Award in 1994 and of Sakai Special Award in 1994.
Dr. Miyano's research mission is to create computational 
strategy for systems biology and medicine towards 
translational bioinformatics. His activities are 
characterized by (i) development of a series of computational 
methods for mining gene networks from DNA microarry gene 
expression data and various genome-wide information, (ii) 
development of a software tool Cell Illustrator (CI) 
(http://cionline.hgc.jp/) with which we can model and 
simulate various biological mechanisms and pathways in cells 
by organizing and compiling biological data and knowledge, 
and an XML format Cell System Markup Language (CSML) 
(http://www.csml.org/) for describing biological systems 
with dynamics and Cell System Ontology (CSO), (iii) peta 
flops computing for inferring molecular networks of tens of 
thousands nodes and a new statistical and computational 
method called "data assimilation" that "blends" simulation 
models and observational data rationally.