from    
to    
search  

 


超分子体系中的对称与不对称问题
Textile Electronic Bioengineering: Towards Digital Health
清华大学材料科学与工程研究院《材料科学论坛》:Spin-orbital angular momentum m...
Emergent spacetime from generalized freefields
报告题目:
the Example of Computational Molecular Biology
 报告人:
Richard Karp 教授
世界著名计算机科学家
报告时间:
2006-09-11 16:30
报告地点:
理学院报告厅
主办单位:
清华大学高等研究中心
  简介:

清华大学高等研究中心

杨振宁讲坛

 

报告人:Richard Karp 教授

 

报告题目:Theory of Computation as a Lens on the Sciences: the Example of Computational Molecular Biology

 

时间:2006年9月11日(星期一)下午4:30

地点:清华大学理学院报告厅(郑裕彤讲堂)

 

赞助单位:Microsoft Research Asia, Cheng Endowment, 国家自然科学基金委员会

 

Richard Karp 教授简介

世界著名计算机科学家

荣获 1985年ACM Turing Award

荣获 1996年美国National Medal of Science

1980年当选美国National Academy of Sciences院士

1985年当选美国Academy of Arts and Sciences院士

1935年生于美国

1959年获Harvard大学应用数学博士学位

1999年至今在UC Berkeley电子工程与计算机科学系任职University Professor

研究领域:Combinatorial algorithms, Parallel algorithms, Probabilistic analysis of combinatorial optimization, Construction of randomized algorithms, algorithmic methods in genomics and computer networking

 

报告内容摘要

This talk will trace the growing influence of fundamental ideas from computer science on the nature of research in a number of scientific fields. There is a growing awareness that information processing lies at the heart of the processes studied in fields as diverse as quantum mechanics, statistical physics, nanotechnology, neuroscience, linguistics, economics and sociology. Increasingly, mathematical models in these fields are expressed in algorithmic languages and describe algorithmic processes. The speaker will briefly describe connections between quantum computing and the foundations of quantum mechanics, and between statistical mechanics and phase transitions in computation. He will indicate how the growth of the Web has created new phenomena to be investigated by sociologists and economists. He will then focus in greater detail on computational molecular biology, where the view of living cells as complex information processing systems has become the dominant paradigm, and will discuss specific algorithmic problems arising in the sequencing of genomes, the comparative analysis of the resulting genomic sequences,  the modeling of networks of interacting proteins, and the associations between genetic variation and disease.

今日相关信息
Failure Analyses of Non-Ceramic Compo...
Transgranular Stress Corrosion Cracki...
 
同类别相关信息
数学系海外学者讲学:计数组合及应用
思廉讲座——The Oldest Problem
水木烙印,我的清华
清华论坛第66讲:3
CAM Seminar--Optimal error estimate...
学术活动