IT융합연구소는 10월 8일 'KI 정기 세미나를 아래와 같이 개최하였다. KI 정기 세미나는 첨단 연구 동향 및 기술 파악, KI간 연구 내용 및 정보교루, 수행연구의 한계 및 문제점 토의, 새로운 융합 연구 과제 발굴을 위한 아이디어 탐색을 목적으로 개최되고 있다. 이번 세미나에는 IT융합연구소의 조동호 소장을 비롯하여 KAIST의 여러 교수들과 학생들이 참석한 가운데 바이오 및 뇌공학과의 조광현 교수가 'Systems Biology and Bio-Inspired Engineering'라는 주제로 강연을 하였다.  

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<KI Regular Seminar>

- KAIST Institute for Information Technology Convergence –

 Speaker: Professor Kwang-Hyun Cho

 Department of Bio and Brain Engineering

 Korea Advanced Institute of Science and Technology (KAIST)

 Talk Title: "Systems Biology and Bio-Inspired Engineering"

 Time/Date: 14:00 ~ 16:00 / October 8

 Venue: Room 2201, Electrical Engineering B/D(E3-2)

Abstract:

The fundamental goal of life sciences is to understand the hidden mechanisms of living systems, i.e., to investigate the ‘spatial and temporal relationships’between molecules, cells, tissues, organs, and organizations that give rise to cause and effect in a living system. A major problem is that networks of cellular processes are regulated through complex interactions among a large number of genes, proteins, and other molecules. The fundamental problem, addressed by Systems Biology, is to understand the nature of this regulation. This is achieved not by cataloguing and characterizing physical components but mainly through mathematical modeling and computer simulation of the signal- and information-flow in ‘pathways and networks’ that are the result of interacting components. In this presentation, dynamic modeling of a signal transduction pathway and reverse engineering of regulatory networks are to be used as a guide for discussion on what the challenges are if we are to get a system-level understanding for cellular dynamics through interdisciplinary research between IT and BT. It will also be discussed how systems biology can eventually lead to developing a new realm of engineering to be called ‘Bio-inspired engineering based on molecular Systems Biology’. The key concept is applying system-level knowledge on cellular mechanisms to engineering. This includes, for instance, developing signal processing systems that mimic cellular signal transduction mechanisms or designing large complex systems by applying cellular developmental processes. The eventual goal is to invent self-organizing systems that can overcome unexpected environmental changes or system failures by reconfiguring internal structures and thereby can behave almost autonomously under noisy environments.