Date :

 19-20 March 2010

Place :

 19 March: Room 312, Department of Physics, National Taiwan University, Taipei

 20 March: the meeting room on 7th floor, Institute of Physics, Academia Sinica, Taipei

 National Center for Theoretical Sciences (Critical Phenomena and Complex Systems focus group)

 Institute of Physics, Academia Sinica (Taipei)

Miss Chia-Chi Liu (Secretary, Physics Division, NCTS)
Tel:(886)-2-33665566; Fax:(886)-2-33665565; E-mail: ccliu@phys.ntu.edu.tw

Speakers :

Prof. Chia-Ching Chang

Email: ccchang01@mail.nctu.edu.tw

Structural and Functional Analysis of Intrinsic Disordered Protein: Cyclin I and Securin

    Human cyclin I and securing are intrinsic disordered proteins which do not possess stable tertiary structures. These unstable tertiary structures play the roles of adapters to bind with several different proteins and then to regulate their functions. It is intriguing to reveal the folding paths effect of these unique proteins both in structural and functional features. By analyzing their structural and functional properties, we find that the folding paths may affect the stability of their hydrophobic cores. Meanwhile, the functional analysis also indicates that different folding pathways may affect their functions vitally.

Prof. Longyan Gong

Nanjing University of Posts and Telecommunications, CHINA

Email:

Von Neumann Entropy, Fidelity and Localization-Delocalization Transitions

Dr. N.Sh. Izmailian
Center for Nonlinear and Complex Systems and Department of Physics, Chung-Yuan Christian University, TAIWAN
E-mail: izmailan@phys.sinica.edu.tw

Universal Ratios among Correction-to-Scaling Amplitudes

Prof. Chung-Kang Peng

Rey Institute for Nonlinear Dynamics in Physiology & Medicine, Beth Israel Deaconess Medical Center / Harvard Medical School

E-mail: cpeng@bidmc.harvard.edu

Understanding Health and Diseases: A Complex System Approach (I)

     One of the great challenges of contemporary biomedical science is to understand more fully the dynamics of living systems in health and disease. The importance of this challenge is highlighted by headlines announcing unexpected, life-threatening side effects of once-promising drugs, as well as the serendipitous discoveries deriving from “outside the box” approaches to major public health problems, for example, in heart disease. The basis of such unexpected findings, both negative and positive, is the extraordinary complexity of physiologic systems. These systems defy understanding based on traditional mechanistic models and conventional biostatistical analyses.

    In this first talk, I will introduce a generic framework to study biological systems, especially human physiology, as complex systems. With this framework, we can derive useful measures that best reflect the emergent properties of the integrative systems, and to identify system-level behaviors that are critical to our understanding of a healthy system and its pathological perturbations.

Understanding Health and Diseases: A Complex System Approach (II)

    In this second talk, I will apply a computational algorithm developed by our group (based on the complex system framework), call multiscale entropy (MSE) analysis, to quantify the dynamical complexity of a biological system based on its spontaneous fluctuations in time. It is an interdisciplinary approach that combines concepts and tools from statistical physics and applied mathematics. It has a wide range of biomedical applications: to be used as a quantitative index of frailty for aging study; to predict survival rate in intensive care unit; to discover drug toxicity; and to monitor effectiveness of medical interventions. The dynamical complexity, as measured by the MSE, may provide useful information about system adaptability.

Statistical Physics Approach to Categorize Biologic Signals: From Heart Rate Dynamics to DNA Sequences

    I will introduce a novel approach to categorize information carried by symbolic sequences based on their usage of repetitive patterns. A simple quantitative index to measure the dissimilarity between two symbolic sequences can be defined. This information dissimilarity index, defined by our formula, is closely related to the Shannon entropy and rank order of the repetitive patterns in the symbolic sequences. I will also discuss the underlying statistical physics assumptions of this dissimilarity index. I will use human heart beat interval time series, DNA sequences, and human texts as examples to illustrate the applicability of this generic approach to real-world problems.

Dr. Karen Petrosyan
Institute of Physics, Academia Sinica, TAIWAN
E-mail: pkaren@phys.sinica.edu.tw

Noise-Induced Escape of Polymers with Random Loops

    We study the problem of potential barrier surmounting for polymers with random loops under the influence of an external field and noise. First, we derive the Kramers rate for the polymer with random loops for the case of thermally activated escape in the absence of external field. Then we consider the escape of the polymer in the presence of an external periodic field. We found that the loops make qualitative difference and allow the polymers to escape for lower noise intensities.  Potential applications of the phenomenon may include various processes that involve biopolymers, e.g., ejection and translocation of DNA molecules with protein-mediated loops.
　

Mr. Po-Cheng Wang

Purdue University, USA

E-mail: pcrwtk01@gmail.com

Complex Root Networks in the Ancient Chinese Characters: Oracle Bone Inscriptions, Chu characters, and  Traditional Chinese Characters

    In 1991, a large number of Oracle Bone Inscriptions (circa 1200 - 1050 B.C.) preserved in nearly complete condition were discovered and unearthed at East of Huayuan Village, Henan Province of China. Traces of the languages contained in the inscriptions live on in modern Chinese characters. Occurring between these, Chu characters (circa 500 - 150 B.C.) share certain qualities of both, and therefore play an important role in translation. The Oracle Bone Inscriptions are constructed of combinations of meaningful images, i.e. roots. According to the defined roots, we can utilize the characters of the Oracle Bone Inscriptions to construct a complex root network, and a network analysis can then be mapped on to the system of Chu characters. The complex root network constructed from Chu characters can then be mapped to the traditional Chinese characters we use today. We find that all three kinds of root networks share the property of scale-free and are both small world networks, though they do not enjoy hierarchical structures. In our study, the complete sets of Oracle Bones inscribed with ancient Chinese sentences are understood, by analyzing the word frequencies, as the earliest case of Zipf’s law.

Mr. Shih-Chieh Wang

Institute of Physics, Academia Sinica, TAIWAN; Department of Physics, National Chung-Hsing University, TAIWAN

Email: d9454104@mail.nchu.edu.tw

Multivariate Transfer Entropy Analysis on Cytokine Density Time Series in Healthy Controls and Patients with Fibromyalgia

    Fibromyalgia (FM) is a syndrome without a clear pathogenesis, one hypothesis for the pathogenesis of FM is cytokine dysregulation in the human immune system. Multivariate transfer entropy method has been developed and used to find phenomenology coupling among 5 cytokine density time series in different time scales (5min ~ 200 min). The result shows that 1) largest eigenvalues shows that cytokines coupled strongly in FM patients than healthy controls, 2) eigenvector components statistics shows that cytokines coupled homogeneously in FM patients than healthy controls.