若手研究者インターナショナル・トレーニング・プログラム(ITP)
バイオインフォマティクスとシステムズバイオロジーの国際連携教育研究プログラム 応募書類

Name: Risa Uechi
Title: RMT assessments of the latent Information embedded in the large-scale data
Institute: Bioinformatics Center, Institute for Chemical Research, Kyoto University
Partner institute of your choice： Center for Polymer Studies, Boston University
Duration of your choice: April 4, 2013 – July 2, 2013

Research Objectives
I will learn statistical methods to evaluate large-scale data such as gene transcriptomic
data, market stock exchange data under the supervision of Dr. H. Eugene Stanley and Dror Y.
Kenett at Center for Polymer Studies, Boston University. Dr. H. Eugene Stanley has
contributed many research fields such as economics, molecular biology especially DNA
modeling and physical and social networks theory. He is also the pioneer of econophysics
which is the interdisciplinary research field of both physics and economics. In the laboratoryof Dr. H. Eugene Stanley, there are a lot of people who came from variable research fields
such as bioinformatics, astrophysics and economics, therefore, numerous unique researches
are possible. It should be variable experience to stay in Dr. H. Eugene Stanley's laboratory.
This is the reason why I would like to apply for the ITP program and choose the hostsupervisor as Dr. H. Eugene Stanley.
It is remarkable in the field of theoretical biology such as bioinformactics, systems biology
and biophysics, the properties or 'common law' behind the complex nonlinear phenomena. Itis also one of the primary topics in complex phenomena. Especially in complex network
systems, the power law is studied and investigated in many network system and known as
the 'common law' in complex network systems. If the study of 'common law' improved, therewill be benefits to many research fields not only to bioinformatics. Akutsu laboratory has
been studied many theoretical model and softwares to examine metabolic networks using
KEGG data base such as impact degree calculating program and so on. I also studied theconservation law in complex phenomena, mainly in competitive systems, at Akutsu
laboratory as previous research projects. My research results indicate that there exists other'common law' in complex nonlinear phenomena including biology, ecology and economics
using calculus of variations. My research objective in three-month ITP program is to learn themethod of RMT assessments to evaluate latent information in transcriptomic data and recent
network percolation theory and search another relation in large-scale data. I will alsointerchange opinions with other members of Boston University and discuss the research
topics. I will also join international communications and expand my knowledge. Afterlearning these statistical methods, I will devote the analysis of impact degree using RMTassessments.

若手研究者インターナショナル・トレーニング・プログラム(ITP)
バイオインフォマティクスとシステムズバイオロジーの国際連携教育研究プログラム 応募書類

Research Plan
1. Research Background
Nonlinear dynamical systems characterized by self-interactions, self-organizations,spontaneous emergence of order, dissipative structure and nonlinear cooperative
phenomena have shown essential roles in natural sciences, as well as economy, ecology,
and environmental sciences [1]. Nonlinear dynamical systems are difficult to handle unlike
linear dynamical systems because their complex interactions and structures make it so hardto understand a response of a system, which may exhibit no simple laws or orders. However,in terms of natural sciences, conservation laws, symmetries and orders in nonlinear
dynamical systems are expected to exist even in biology, ecology, and economy. The
important examples in the field of ecology are those of Malthus for a population analysis,Alfred Lotka and Vito Volterra for predator-prey differential equations known as LotkaVolterra (LV) equation. Also, in the field of economy, a conserved quantity in the system ofbusiness cycle is studied and this business cycle model is regarded as a predator-prey typecompetitive system, and also a mathematical model for Lanchester Strategic Management isknown as a predator-prey type competitive system.
2. Model and Methods
Random Matrix Theory (RMT) is a tool that was originally developed and used in nuclear
physics by Wigner and Dirac, et al., in order to explain the statistics of the energy levels ofcomplex quantum systems. Recently, it has been applied to many fields other than physics
such as biology (transcriptomic data) and economic data. By using RMT, we are able todiscern to what extent the data

correlation are a result of random noise rather thanimportant system information [2-3].
We set the research plan is to focus on RMT, and work on better understanding themeaningful eigenvectors, and how these change when the state of the market changes.
3. References[1] Lisa Uechi and Tatsuya Akutsu, Conservation Laws and Symmetries in Competitive
Systems, Progress of Theoretical Physics Supplement, No. 195, 2012, 210.
[2] H. E. Stanley, V. Afanasyev, L. A. N. Amaral, S. V. Buldyrev, A. L. Goldberger, S. Havlin,
H. Leschhorn, P. Maass, R. N. Mantegna, C.-K. Peng, P. A. Prince, M. A. Salinger,
M. H. R. Stanley, and G. M. Viswanathan, "Anomalous Fluctuations in the Dynamics ofMI.

Complex Systems: From DNA and Physiology to Econophysics," Physica A
224,302-321 (1996).

[3] Dror Y. Kenett, Yoash Shapira, and Eshel Ben-Jacob, RMT Assessments of the Market
Latent Information Embedded in the Stocks' Raw, Normalized, and Partial Correlations,
Journal of Probability and Statistics (2009).

若手研究者インターナショナル・トレーニング・プログラム(ITP)
バイオインフォマティクスとシステムズバイオロジーの国際連携教育研究プログラム 応募書類