Strategic Programs for Innovative Research Field 1 Supercomputational Life Science9

2013.9 Vol.
CONTENTS
Open Up SPECIAL TALK

Discussion meeting

Open Up the Innovative Possibilities ofComputational Life Sciences“Multifactorial,” “dynamic,” and complex life phenomena toanalyze in depth by the “K computer”
Toshio Yanagida ／ Akinori Kidera ／ Yukihiro Eguchi RIKENZOOM IN

2

Close-up on SCLS Research

Theme 1 Simulations of biomolecules under cellular environments

Whole cell simulation of signaling pathway
Kazunari Iwamoto RIKEN

4Theme 2 Simulation Applicable to Drug Design

Molecular recognition mechanism observed
through simulation and drug design
Takefumi Yamashita The University of Tokyo

5

Theme 4 Large-scale analysis of life data

Massively parallel sequence analysis pipeline
for next-generation sequencers
Masanori Kakuta Tokyo Institute of Technology

6

SCLS Gotcha!

Fiscal 2013 Period 1
Peer-reviewed Results for Research Themeson the Use of SCLS Supercomputer System

Co-host Symposium with Okayama University

77

Discussion meeting

Open Up the Innovative Possibilities
of Computational Life Sciences“Multifactorial,” “dynamic,” and complex life phenomena to analyze in depth by the “K computer”
Program Director (PD), HPCI Program for Computational Life Sciences, RIKEN
Deputy PD, HPCI Program for Computational Life Sciences, RIKEN
Deputy PD, HPCI Program for Computational Life Sciences, RIKEN

Toshio Yanagida
Akinori Kidera
Yukihiro Eguchi

Two years and a half have almost passed since the “Supercomputational Life Science(SCLS)” started with the aim ofelucidating the complex life system, in which various hierarchies such as genomes, biomolecules, cells, and organs are
involved, by using the innovative High Performance Computing Infrastructure (HPCI) of Japan with the “K computer”
at the core. A discussion meeting was held between Dr. Toshio Yanagida, Program Director (PD), Dr. Akinori Kidera,
Deputy PD; and Mr. Yukihiro Eguchi, Deputy PD, on the progress of the programs toward their objectives of gathering
numerous researchers from different fields to explore the possibility of predicting and controlling life phenomena bymeans of computational life sciences, and of linking the study results to the contribution to medical treatment anddrug design.

Computational sciences required to comprehend the multifactorial and complex life system
Yanagida: During these two years and ahalf, the direction of study has been focusedmore specifically on all the four themes.
I believe that the themes went smoothly
from the very beginning. A road map forthe use of high performance computers isfinally about to be developed in the field oflife sciences where there had been no such
advanced methods so far.
Kidera: It is quite spectacular that, withthe foundation that was established in
the Life Science Grand Challenge (NextGeneration Integrated Simulation of Living
Matter), which ended in March 2013, the fullfledged study began using the advanced
computational resource called the “Kcomputer” in this Strategic Programs forInnovative Research.
Eguchi: There is increasing attention paid
to the “K computer” and computational life
sciences from the aspect of disseminationof study results as well. More than ten

companies including pharmaceuticalcompanies also started a project last year toevaluate the Massively Parallel Computationof Absolute binding Free Energy “MP-CAFEE”,
developed in Theme 2 from the perspectiveof drug design sites. The participants areengaged in this project very earnestly.
We understand how strongly they wish
to apply computational life sciences withthe “K computer” to the business of theircompanies.

Kidera: SCLS is a milestone project in that it
aims to produce results that would contributeto medical treatment and drug design.
Computational life sciences have just begun
as a research area, and are still immature inthat the sense of values has not been fully
established yet. Under such circumstances,
SCLS is about to take the initiative in forming
this field in the direction of studies basedon values open to the society, viz., medical
treatment and drug design.

Eguchi: Human network development isalso progressing smoothly in that direction.
In Theme 3 and so on, the human network
began to expand through collaboration withclinicians, etc. Obtaining collaboration fromclinicians with computational life sciences
was almost unprecedented.
Yanagida: Molecular biologists seem tohave deepened their understanding of theneed for studies using computers thesedays. One of the reasons is that it was
revealed that the world of organisms is
not monofactorial, but multifactorial withfluctuating conditions dependent on theenvironment. The multifactorial world meansthat it is a complex system that cannot be
elucidated further only through conventional
gene analysis. I believe they came to knowthat it is necessary to do experimentswith the assistance of a new method toaddress the issue of complexity, specificallycomputational sciences.

Studies progressing smoothly in four themes
Kidera: The four themes in SCLS, which
intend to elucidate life structured in a
multifactorial, complex, and dynamic
manner, by means of computational
sciences, are largely divided into two.
Themes 1 to 3 simulate objects apparently
with physical substances. These approaches
aim to clarify how biomolecules, cells, andorgans function. On the other hand, Theme
4 aims to elucidate the regulatory networkof the genome sequence system behind thelife system not by means of a physical model,
but by means of large-scale data analysis
methodology. It remains to be seen how

2 BioSupercomputing Newsletter Vol.9

the two methods, which are significantly
different in direction, will be linked together.

Yanagida: It is very interesting to see how
the control network will function when
dynamics and fluctuations are added to thelife substance. It is likely that such a complex
substance may actually be controlled easily
in future.
Eguchi: It is not possible to connect Themes
1 to 4 in one stroke only among researchersof computational life sciences. We need tobuild collaboration with various researchers
including biologists and clinicians. To that

end, we need to produce attractive resultsthat encourage researchers to participate in
SCLS as a seemingly attractive project.

Yanagida: Such results have begun to beobtained in the respective themes.
Kidera: In Theme 4 “Large-scale analysis oflife data,” software technology to analyze
the huge amount of genome data by the “Kcomputer” has already been developed. On
the other hand, in Theme 1 “Simulations of
biomolecules under cellular environments,”
which intends to analyze intracellularconditions, where numerous molecules are

Open Up SPECIAL TALK
Toshio Yanagida
In order to clarify the multifactorial and complex life system,
vast computational resources are required to analyze thehuge amount of data obtained from experiments. It is amajor role of SCLS to develop a new world of life sciencesby combining experiments and computational sciences.

Akinori Kidera

Yukihiro Eguchi
Computational sciences may change medical treatment
in future. I hope to produce results that will encourage
many health care workers to be keenly aware of that fact.
I hope that many people such as pharmaceuticalcompanies and clinicians may feel like supporting
computational life sciences.

jammed into a limited space at the atomic ormolecular level, computation is proceeding
to analyze and predict the functions ofproteins within cells.

Eguchi: This is a very challenging activity,
intending to simulate entire cells by making
full use of the “K computer.”Yanagida: This program tries to approach
cellular functions. Given the hierarchicaljumps, however, it remains to be decided
what should be reproduced to what extent.
Kidera: Theme 2 “Simulation applicableto drug design” succeeded in discovering
compounds, which are new cancer drugcandidates, after high-precision computation

The Strategic Programs forInnovative Research are headingin the direction of exploiting
the computational resourcesof the “K computer” to pass theresults on to the society, and to
manufacture products that are
useful for medical treatment
and drug design. We need tofurther develop an environment
appropriate for larger calculations.
SCLS also serves as a trigger forsuch development.

of approximately 300 novel compounds.

Yanagida: Theme 3 “Hierarchical integrated
simulation for predictive medicine” is a study
implemented to understand Parkinson’s
disease. It is progressing smoothly withsuccess in integrating the simulation ofneural signal generation, and the simulationof skeletal muscle contraction on induced bysignal transmission.
Kidera: In the heart simulation performed
with three hierarchies, viz. molecules,
cardiac muscle cells, and the whole heart
linked together, we simulated hypertrophic
cardiomyopathy, and are about to succeed
in reproducing the pathology. The results
are expected to be applied to treatment

at clinical sites. In addition, preparation
for simulating the integration of the heart
simulator and the vascular simulator issteadily progressing toward medical
application to myocardial infarction.

Yanagida: Everyone wishes to be healthy. To
this end, everybody has great expectations
for the development of medical treatment
and life sciences. I am keenly aware thatthey also have significant expectations ofcomputational life sciences that have justbegun. We are committed to do our bestin SCLS for the remaining two years and ahalf, always keeping in mind that we areplaying an important role in meeting suchexpectations.

BioSupercomputing Newsletter Vol.9 3

Close-up on SCLS Research

Theme 1 Simulations of biomolecules under cellular environments

Whole cell simulation of signaling pathway
Laboratory for Biochemical Simulation, RIKEN Quantitative Biology Center

Kazunari Iwamoto

Cells have an ability to respond to theon cancerous changes of the cells, drug

can survive in different environments. Theof response inhomogeneity is very crucial

environment appropriately, so that they

resistance and so on. Therefore, clarification

response is called “signaling”, and the routefor understanding this influence. However,involved is called a signaling pathway. A

since numerous proteins participate in thesignaling pathway is a network of serial

signaling pathway, its understanding isreactions consisting of chemical reactions

becoming increasingly difficult by using

between intracellular proteins, and a cellonly conventional biochemical or molecular

has numerous pathways. Since it is known

biological techniques. Therefore, virtualthat breakdown of the signaling pathway

cell simulation on a computer, called cellmakes a cell cancerous, it is an importantsimulation, has come to be increasingly

task to reveal under what circumstances theused. Our goal is the clarification of response

signaling pathway breaks down.

inhomogeneity of the EGF signaling pathway

One widely known signaling pathway

through this technique.

is the Epidermal Growth Factor (EGF)

Our cell simulation technique is different

signaling pathway. This pathway receives

from conventional ones, and describes

and transmits information into the cell

(called fluctuation or noise) per intracellular

external stimulation from an EGF protein

random movement, collision, and reaction

to promote cell growth, division andprotein molecule. Such a simulationdifferentiation. Recently, it has become

was difficult due to the limitation of a

possible to observe intracellular proteins atcomputer’s computing power. However, it

the monomolecular level. Observation of theis now becoming possible by utilizing the

EGF signaling pathway response revealed

computing power of the K computer. Ourthat there was a wide variety of cellularlaboratory is developing cell simulation

responses, even though cells with the same

software, “pSpatiocyte,” and conducting

genes were cultivated under the same

research through the use of this software.

conditions and received the same stimulation

This is the latest result of our simulation.

(Fig. 1, left). Such a variation in response

In the EGF signaling pathway, information

has been suggested to have an influence“ E G F → R a f → E R K .” T h e E R K p r o t e i nbetween cells (response inhomogeneity)

Cell-by-cell variationin cell response

is transmitted through the route,

EGF signaling pathway

eventually accumulates in the cell nucleus(Fig. 1, Center). Fig. 1 right shows thesimulation result of visualized ERK protein.
These two cells were under the same
conditions, but their ERK response wasfound to be different. The number of protein

molecules was different among EGF, Raf
and ERK (EGF > Raf < ERK). Raf molecules are
the smallest in number. In general, noise

associated with signal transduction is more

amplified as the number of molecules
becomes smaller. Therefore, it is believedthat noises amplified at Raf are transmitted
downstream to ERK without modification,and produced intercellular variation.

Presently, we cannot assure that real
response inhomogeneity occurs through thesame mechanism, but we are aiming at thewhole cell simulation of the EGF signaling

pathway while demonstrating thosefindings.

Simulation results
Cell 1
EGF

Cell 2

Fig.1: Cell-by-cell variation incell response (Left), Pattern
diagram of EGF signaling
pathway (Center), An example ofsimulation results (Right)(great number of molecules)

Cytomembrane
Green: ERK protein

Phosphorylation
Raf

Intranuclear amount of ERK protein

Cytoplasm

Cell nucleus
Transcriptional factor
The lines shows each cell(small number of molecules)

ERK(great number of molecules)

Cell growth and proliferation●See the URL on the right for detailed information on this report.

4 BioSupercomputing Newsletter Vol.9

http://www.kobe.riken.jp/stpr1-life/en/newsletter/Vol.9/zoomin01.html

Close-up on SCLS Research

Theme 2 Simulation Applicable to Drug Design

Molecular recognition mechanism observed
through simulation and drug design
Research Center for Advanced Science and Technology, The University of Tokyo

Takefumi Yamashita

Our study is focused on “Drug Development

and attack its target protein, so it is amolecules acting strongly on disease-causing

accurate prediction of absolute bindingby use of the supercomputer.” We search forproteins through large-scale computation
using the supercomputer, and apply the

analysis results to drug development. For

this purpose, we also develop new analysis
techniques and theories. Simulation

Applicable to Drug Design ranges fromthe basic/academic aspect to applicative/
technical aspects. (Fig. 1)

From the perspective of the academic

aspect, drug design may be summarized
as “gaining knowledge about themolecular recognition mechanism.” Many

pharmaceutical products serve as drugs by
suppressing the function of disease-causing
proteins. What would happen if a drug
affects not only the target protein, but also

promising drug candidate. We believe that

free energy will be an effective tool for drug
development. We are making an attempt

to apply the idea to a real cancer-causing
protein by the computation of absolutebinding free energy, proposed by Fujitani etal.[1] In this computational method, even an
assessment of absolute binding free energy
between a molecule and its target protein
requires a massive computational resource.

We have to make calculations for many
molecules to find the one best suited for adrug, but it has been very difficult by use of
conventional computers. Nowadays, it has

become practicable to some extent due tothe advent of the K computer.

Thanks to super large-scale calculation

various other proteins? It would trigger a

by use of the K computer, we are gradually

drug must recognize and attack only thewe sometimes face unexpected problems.

life-threatening adverse reaction. Therefore,target protein (Fig. 2).

“Absolute binding free energy” is one ofthe physical quantities that indicate how

strongly a molecule recognizes its target

protein. A molecule with high absolutebinding free energy can strongly recognize

New theory

Drug design

accumulating new knowledge, though
We believe we are able to understand themolecular recognition mechanism “moredeeply” and “more accurately” by gaining
such knowledge. We consider that we will

simply through a theoretical approach
when we come to understand the molecular
recognition mechanism.

One of the merits of molecular simulationis that we can view what we cannot see
directly, for example proteins in the water,

as if we are observing it through a highprecision microscope. What makes it moreinteresting is that we can create physicallyimpossible virtual states. By making themost of the virtual states, we can contrive
ways to calculate real physical quantities athigher speed. In reality, we use this idea inour computation of absolute binding freeenergy. The development of a computational

simulation method that is possible only byusing computers is also the great attractionof this field.

be able to step out of conventional empirical
drug development and develop drugs more

New computational
simulation method

Reference[1] H. Fujitani, Y. Tanida, and A. Matsuura: Phys. Rev. E ,79 021914 (2009), H. Fujitani, K. Shinoda, T. Yamashita,
and T. Kodama: J. Phys. Conf. Ser . 454 012018(2013)

Understanding ofmolecular recognition

Fig. 1: Image of Simulation Applicable to Drug Design●See the URL on the right for detailed information on this report.

Fig. 2: Relenza (shown in red) bound to the influenza
protein (shown in blue)

http://www.kobe.riken.jp/stpr1-life/en/newsletter/Vol.9/zoomin02.html

BioSupercomputing Newsletter Vol.9 5

Close-up on SCLS Research

Theme 4 Large-scale analysis of life data

Massively parallel sequence analysis pipeline
for next-generation sequencers
Akiyama Laboratory, Department of Computer Science, Graduate School of Information Scienceand Engineering, Tokyo Institute of Technology

Masanori Kakuta

DNA, responsible for genetic information,

it is relatively easy to obtain an enormous

called nucleotide. Identification of the

speed analysis system for such informationconsists of chain combinations of monomers
nucleotide sequence enables the estimationof the RNAs synthesized based on theDNAs, and the proteins synthesized basedon the RNAs. Since DNA, RNA and proteinsinteract and participate in various vitalfunctions and chemical reactions, nucleotide

sequence determination gives a clue to theclarification of complex interactions between

amount of DNA information, a high-is now required. Our team is therefore

developing a high-speed analysis algorithm
and information-processing system whichenables the analysis of an enormous

amount of DNA information through parallel

computing using multiple computation
nodes.

Recently, metagenome, genomes inbiomolecules. In addition, similar nucleotide

microbial communities, in the environment

within and across species. Their comparison

soil, water sphere, etc.) has been actively

sequences are sometimes observed bothprovides knowledge about the functions andevolution of similar parts of the sequences.

Thanks to the development of the DNA

sequencer, an instrument that automaticallyreads nucleotide sequences, the speedof sequencing and the cost per base are
improving rapidly. A commercially-available
sequencer has the capacity to read about

100 billion base pairs per day. The humangenome consists of about 3 billion base pairs,

so its speed is obviously very high. Since(surface and inside of the human body,studied following the progress of the DNA
sequencing techniques. By comparing
the composition of environmental

microorganisms (phylogenetic analysis)or gene composition (functional analysis)
between different environments, researchers

are trying to obtain knowledge about therelationship between microorganisms andhuman health, the interaction between theenvironment and microbial communities,
or the interaction among microorganisms.

In order to estimate the microorganisms

present in the environment and their genes,
we search sequence databases for sequences

similar to the one we read. It was the timeconsuming process.

We developed GHOSTX, which is morethan 100-times faster than conventional
techniques, through improvement of thesearch algorithm, and then developed
GHOST-MP, which performs parallel analysis
based on GHOSTX. GHOSTX constructs a

data structure called a suffix array both inquery sequences and database sequences.
By using it as an index, we can search forsimilar sequences without scanning all

sequences. GHOST-MP reduces the searchtime by overlapping communication andcomputation. The many computation

nodes of the K computer and its high-speed
inter-node network allow to process largescale metagenomic data in a short time.

By using GHOST-MP as a search technique,
we are developing an analysis pipeline,

which performs phylogenetic analysis andSample acquisition

DNA extraction

DNA sequencing

functional analysis based on the sequences
obtained from the microbial communities,

and analyzing real data utilizing the analysis
pipeline.

Estimation of microorganisms and their genes throughutilization of known nucleotide sequences

Comparison of composition of existing
microorganisms
and their genes（系統解析）(phylogenetic analysis)

Reconstruction and comparison of
metabolicpathway（機能解析）(functional analysis)●See the URL on the right for detailed information on this report.

6 BioSupercomputing Newsletter Vol.9

Fig. 1: Pattern diagram of
metagenome analysis

http://www.kobe.riken.jp/stpr1-life/en/newsletter/Vol.9/zoomin03.html

SCLS
Fiscal 2013 Period 1
Peer-reviewed Results for Research Themeson the Use of SCLS Supercomputer System
Supercomputational Life Science(SCLS) aims to broadly
form user communities for computational life sciences throughresearch support, human resource development, and so on, as
well as to promote creation of landmark results in life scienceareas including medical care and drug development through theuse of HPCI. Towards achievement of this objective, as one way
to make use of HPCI easy for external life science researchers
SCLS Theme No.

Nameand engineers, SCLS seeks research theme on the use of SCLS
supercomputer systems highly compatible with the“K computer”
on a peer-reviewed basis. Upcoming applications will be posted
in September. For details, see the Information on Acceptanceof Applications from the Public to Use SCLS supercomputer
system (http://www.kobe.riken.jp/stpr1-life/outreach/sclsuse/application.html).

Representative’s affiliation

Theme title

201301101

Toru Hyakutake

Faculty of Engineering,
Yokohama National University

Development of numerical technique on estimation of oxygen
transport effect by tailor-made artificial red blood cell201301102

Kenji Takizawa

Waseda Institute for Advanced Study

201301103

Kenji Mizuguchi

National Institute of Biomedical Innovation

201301104

Ryuichi Shimizu

BioGrid Center Kansai

Utilization of parallel computational software,and Study on possibility
for the software to facilitate drug discovery

201301105

Kazuya Yasuo

Shionogi & Co., Ltd.

Improvement of binding affinity prediction with Quantum mechanics

201301106

Huynh Quang Huy Viet

Graduate School of Environmental
and Life Science, Okayama University

Parallelization and evaluation of an incompressible Navier Stokes
equation solver for blood flow simulation

201301107

Akira Suyama

Graduate School of Arts and Sciences,
The University of Tokyo

Stability of nucleic acid single-strand base-stacking

201301108

Takuya Hayashi

RIKEN Center for Life Science Technologies

Development of Computer Modeling Techniques for Patient-Specific
Cardiovascular FSI
Construction of a method for screening drug candidates based onprotein-interaction prediction

Exploring functional brain network using non-invasive brain images
and rapid and parallelized computation

SCLS
Co-host Symposium with Okayama
University
In Supercomputational Life Science(SCLS),
in order to encourage life science
communities to understand computational
life sciences in HPCI environments with“Kcomputer”at the core and to form human
networks, SCLS largely divides Japan
into six blocks, and holds symposia incooperation with hub universities and related
academic societies in the blocks.
On Friday, June 1, SCLS held a symposium
entitled‘Promotion of Fusion and Exchanges

Professor Matsuda reports his analytical result
for bimolecular networks that control thebrowning of white fat cells.

among Different Fields Engaged in Life
Sciences:“K Computer”and Life Sciences’in cooperation with Okayama University.
At this second symposium held this year,
lectures were given by 12 researchers,
who are engaged in boundary study fields
between computational sciences and life
sciences, with the objective of setting up aforum, where researchers and engineers in
different fields can exchange their views, andcreate new study fields and joint researcharound Computational Life Sciences, anddiscussing the methods and details of
HPCI use in fields where life sciences andcomputational sciences are combined.
From“Theme 1: Simulations of biomolecules
under cellular environments,” Kazunari
Kaizu, postdoctoral researcher (RIKEN),
reported on the molecular scale simulation ina signaling pathway in consideration of thecellular environment. Then, from“Theme 4:
Large-scale analysis of life data,”Professor
Hideo Matsuda (Osaka University) reported

Dr. Kazunari Kaizu, postdoctoral researcher
of RIKEN, introduces a parallel computation
method for molecular scale simulation.
*He belongs to the same research team as Kazunari
Iwamoto, postdoctoral researcher of RIKEN whose
article appeared in“Zoom in”on page 4 of this issue.

on his analytical result of bimolecular
networks obtained through the use of the“Kcomputer.”
We had more than 100 participants not
only from universities such as students andteaching staff, but also from a wide range ofaffiliations from public research institutions
to enterprises.
We are committed to continue to holdsimilar symposia to set up a forum forreporting studies using the“K computer”
and HPCI environments in computational life
sciences, as well as a forum for informationexchange and transmission.

BioSupercomputing Newsletter Vol.9 7

News & EventsSP

SP Symposium RP

September 19 (Thu) 13:00

Development of a new field of life science andthe “K computer”

We discuss development of a new field of life science involving computing
science with you. ⃝Participation fee : Free

RP

October 2 (Wed)−3 (Thu)Workshop

Location Kyoto International Conference Center (Kyoto-shi, Kyoto)

SP October 31 (Thu) 10:05−11:20
The 2nd Joint Conference on Informatics in Biology, Medicine andPharmacology, Organized Session

Supercomputing with the “K computer” and drug design
HPCI Educational Program of Supercomputational Life Science(SCLS)⃝Organizers: Masao Tanaka (Osaka University), Tsuneaki Sakata (Osaka University)
Location Tower Hall Funabori, 401 Meeting Room (Edogawa-ku, Tokyo)

For more details, visit our website.

https://www.hpci-office.jp/pages/858
EX

October 9 (Wed)−11 (Fri)Bio Japan 2013 -World Business Forum-

November 9 (Sat)−10 (Sun)

Science Agora

RIKEN research centers in the Kobe area come together to make a jointpresentation with SCLS.
Booth name: Because it is a cell

Location Pacifico Yokohama (Yokohama-shi, Kanagawa)

Presentation at the RIKEN boothEX

Seminar WS⃝Organizer : Yuji Sugita (RIKEN), Koichi Takahashi (RIKEN)

Location TIME 24 building (Koto-ku, Tokyo)

EX

Exhibition SM

Structure, dynamics, and function of nucleosomes andchromatin in nuclear crowded environment(Fukuoka-shi, Fukuoka)

Mid-term reporting session on research themes using HPCI
systems with the “K computer” at the core in 2013EX

SP October 29 (Tue) 13:00−16:00
The 51st Annual Meeting of the Biophysical Society of Japan

Location Centennial Hall Kyushu University School of Medicine

http://www.agr.kyushu-u.ac.jp/sympk/

Reporting session

Location National Museum of Emerging Science and Innovation (Koto-ku, Tokyo)

October 19 (Sat)RIKEN Open House Day at RIKEN AICS (Kobe)
Location RIKEN Advanced Institute for Computational Science (Kobe-shi, Hyogo)EX

November 17 (Sun)−22 (Fri)SC13

A lecture on SCLS is scheduled at the “K computer” booth.

Five fields come together to run a panel exhibition and interactive booth.
(6F Science Square)

Location Colorado Convention Center (Denver, Colorado, USA)WS December 4 (Wed) 13:15−15:45
The 36th Annual Meeting of The Molecular Biology Society of Japan, Biology
of Diseases Workshop

Leveraging Supercomputers for Hierarchical and Systems
Understanding of Life towards Strategic Intervention
against Diseases⃝Organizers: Satoru Miyano (The University of Tokyo), Seiji Ogawa (The University of Tokyo)

Open House Day in 2012SM

October 28 (Mon) 12:30−13:20

The 51st Annual Meeting of the Biophysical Society of Japan, Luncheon Seminar

Future seen from the aspect of Life Science andComputational Science⃝Large-scale computing may be surprisingly important?
⃝Significance of large-scale computing in computational life sciences⃝Invitation to the “K computer” and HPCI

Location Kobe International Conference Center, 4F 401+402 (Kobe-shi, Hyogo)SP

December 17 (Tue)(Tentative title) Strategic Programs for Innovative Research Field 1 x Field 2 Symposium

Computing Biomolecular Complex System
What is brought about by interaction

Location Kyoto International Conference Center Room B-1 (Kyoto-shi, Kyoto)⃝Participation fee : Free

Location Nagoya University (Nagoya-shi, Aichi)

We will notify the details on the website of SCLS as soon as they are fixed.

Strategic Programs for Innovative Research Field 1

Supercomputational Life Science

SPIRE (Strategic Programs for Innovative Research) is a MEXT program aiming to produce ground-breaking results in computer science
technology by maximizing the benefits of the HPCI (High Performance Computing Infrastructure) centered on the supercomputer “Kcomputer”, and encouraging developments in five research fields that need to be strategically addressed.
“Supercomputational Life Science” has conducted research with the mission of understanding and predicting life phenomena based on largescale simulation and advanced data analysis, and to apply these results to design and implement medicine and medical care with its research.

BioSupercomputing Newsletter Vol.9 2013.9
RIKEN HPCI Program for Computational Life Sciences
7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe Hyogo 650-0047, Japan
Tel:+81-78-940-5692 Fax:+81-78-304-8785 http://www.kobe.riken.jp/stpr1-life

Issued: September 2013

RIKEN 2013-071