The 5-th Week Schedule Program Schedule "Recent Progresses in Complex Networks Research" The Fifth Week (Mar 28-April 1) ====================================== Mar 28 Monday 10:00-11:30 Chairperson ： Bing-Hong Wang B. Kahng （ Seoul National University ） : Explosive percolation transition of complex networks Lunch Break 15 ： 00-16:00 Chairperson ： Tao Zhou Wei Li (Max-Planck-Institute for Mathematics in the Sciences): Statistical Learning in an evolutionary game Mar 29 Tue 10:00-11:30 Chairperson ： Bing-Hong Wang Hawoong Jeong (Korea Advanced Institute of Science and Technology) ： S tructure and dynamics of the directed complex networks Mar 30 Wed 10:00-11:30 Chairperson ： Bing-Hong Wang Zhou, Changsong （ Hong Kong Baptist University ） ： Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations Mar 31 Thursday 10:00-11:30 Chairperson ： Bing-Hong Wang David Saad （ The Non-linearity and ComplexityResearch Group, Aston University ， UK ） Dynamics of Boolean networks - a Generating Functional Analysis Lunch Break 15 ： 00-16:00 Chairperson ： Tao Zhou You-Gui Wang ( Beijing Normal University): Self-Organized Criticality in Market Economies April 1 Friday 10:00-11:30 Chairperson ： Bing-Hong Wang Tao Zhou (University of Electronic Science and Technology of China) : 1, Link prediction in complex networks; 2, Information extracting from networks: ranking and recommending; Lunch Break 15:00-17:00 Chairperson ： Tao Zhou Discussion about recent progresses and future directions in complex networks research : All the participants: Chin-Kun Hu ， B.Kahng ， Beom Jun Kim, Bin Jiang ， Renaud Lambiotte ， Jing Zhao ， Hyunggyu Park, Hawoong Jeong, Sumiyoshi Abe, Jae Dong Noh, David Saad ， Changsong Zhou, Chenping Zhu, Wei Li, Zi-Ke Zhang, Lin-Yuan Lv ， Mingsheng Shang, Tao Zhou ， Bing-Hong Wang
应Lambert Academic Publishing之邀，我写的书 Modularity: The Principle of Evolution in Complex Systems今天出版了。 此书总结了我数年来在复杂网络，金融物理，和免疫系统进化方面的工作。主题围绕着“模块化” (modularity)展开。此书的核心是提出了生物进化中的模块化定律。 Modularity, understanding systems as the combination of separated components, is a prevalent concept in biology, social science and engineering design. This book offers a general theoretical model of emergence of modularity during evolution in changing environments. Evidences from protein interaction network and protein domain network support this theory as a general law of evolution in complex systems. Applying it to animal development, this theory appears to provide an explanation for the occurrence and timing of the Cambrian explosion. Applying it to trade networks, this theory predicts that globalized economy is more sensitive to recessions. This book also introduces a quantitative measure of hierarchy, a statistical method to predict the dominant flu strain and the first theoretical model to explain the bacterial acquired immunity (CRISPR). The information in the book should help shed some light in the study of complex systems, flu vaccine, and bacterial antibiotic resistance. 购买链接: http://www.amazon.com/Modularity-principle-evolution-complex-systems/dp/3844311416 前后封面
Introduction_to_Social_Network_Methods.pdf Introduction to Social Network Methods This page is part of an on-line textbook by Robert A. Hanneman and Mark Riddle of the Department of Sociology at the University of California, Riverside. Feel free to use and reproduce this textbook (with citation). For more information, or to offer comments, you can send me e-mail. Table of Contents l Introduction: What's different about social network data? l Nodes Populations, samples, and boundaries Modality and levels of analysis l Relations Sampling ties Multiple relations l Scales
The 2011 International Symposium on Complex Networks and Systems (ISCNS'11) http://www.ee.cityu.edu.hk/~wwyu/ISCNS11/index.html Welcome The 2011 International Symposium on Complex Networks and Systems (ISCNS'11) will be held on April 23-24 2011 in Nanjing, China, officially organized by the Department of Mathematics , Southeast University , China. The ISCNS'11 focuses on complex systems and networks, multi-agent systems, nonlinear dynamics and control, systems biology, sensor networks, communication networks, networked control systems, and their applications. The symposium will be sponsored by the Department of Mathematics , Southeast University , China. Latest News We will cover the travel (hard-seat tickets if by trains) and accommodation fees (in the reserved hotel) for some students and young teachers. Note that there are limited quota. Please send your registration form to us as soon as possible. All Rights Reserved 2011 - By ISCNS'2011 General Chairs Jinde Cao (SEU, China) Jijun Liu (SEU, China) Organizing Committees Jinling Liang (SEU, China) Qingshan Liu (SEU, China) Jianquan Lu (SEU, China) Xingmei Xue (SEU, China) Wenwu Yu (SEU, China) Invited Speakers (listed not in any particular order) Confirmed Guanrong Chen (CityU, HK) Zhisheng Duan (Peking University, China) Jinhu Lv (Chinese Academy of Sciences, China) Daniel W. C. Ho (CityU, HK) Yuanqing Xia (Beijing Institute of Technology, China) Unconfirmed Program Schedule 23-24 April, 2011: Two-day Workshop Related Download under construction Send Registration Form To Wenwu Yu Email: wenwuyu@gmail.com ; wwyu@seu.edu.cn Telephone: 0086-15051861330 Registration Form Download Sponsors Department of Mathematics , Southeast University , China Contact Dr. Wenwu Yu Department of Mathematics , Southeast University Nanjing 210096, P. R. China Tel: +86-25-52090596-8531 Fax: +86-25-83792316 Email: wenwuyu@gmail.com ; wwyu@seu.edu.cn
http://www.answers.com/topic/network-science#See_also Network science is a new and emerging scientific discipline that examines the interconnections among diverse physical or engineered networks , information networks , biological networks , cognitive and semantic networks , and social networks . This field of science seeks to discover common principles, algorithms and tools that govern network behavior. The National Research Council defines Network Science as the study of network representations of physical, biological, and social phenomena leading to predictive models of these phenomena. Contents 1 Background and history 2 Department of Defense Initiatives 3 See also 4 References 5 Further reading 6 External links // Background and history The study of networks has emerged in diverse disciplines as a means of analyzing complex relational data. The earliest known paper in this field is the famous Seven Bridges of Knigsberg written by Leonhard Euler in 1736. Euler's mathematical description of vertices and edges was the foundation of graph theory , a branch of mathematics that studies the properties of pairwise relations in a network structure. The field of graph theory continued to develop and found applications in chemistry (Sylvester, 1878). In the 1930s Jacob Moreno , a psychologist in the Gestalt tradition, arrived in the United States. He developed the sociogram and presented it to the public in April 1933 at a convention of medical scholars. Moreno claimed that before the advent of sociometry no one knew what the interpersonal structure of a group 'precisely' looked like (Moreno, 1953). The sociogram was a representation of the social structure of a group of elementary school students. The boys were friends of boys and the girls were friends of girls with the exception of one boy who said he liked a single girl. The feeling was not reciprocated. This network representation of social structure was found so intriguing that it was printed in the The New York Times (April 3, 1933, page 17). The sociogram has found many applications and has grown into the field of social network analysis . Probabilistic theory in network science developed as an off-shoot of graph theory with Paul Erd?s and Alfrd Rnyi 's eight famous papers on random graphs . For social networks the exponential random graph model or p* graph is a notational framework used to represent the probability space of a tie occurring in a social network . An alternate approach to network probability structures is the network probability matrix , which models the probability of edges occurring in a network, based on the historic presence or absence of the edge in a sample of networks. In the 1998, David Krackhardt and Kathleen Carley introduced the idea of a meta-network with the PCANS Model. They suggest that all organizations are structured along these three domains, Individuals, Tasks, and Resources. Their paper introduced the concept that networks occur across multiple domains and that they are interrelated. This field has grown into another sub-discipline of network science called dynamic network analysis . More recently other network science efforts have focused on mathematically describing different network topologies. Duncan Watts reconciled empirical data on networks with mathematical representation, describing the small-world network . Albert-Lszl Barabsi and Reka Albert developed the scale-free network which is a loosely defined network topology that contains hub vertices with many connections, that grow in a way to maintain a constant ratio in the number of the connections versus all other nodes. Although many networks, such as the internet, appear to maintain this aspect, other networks have long tailed distributions of nodes that only approximate scale free ratios. Today, network science is an exciting and growing field. Scientists from many diverse fields are working together. Network science holds the promise of increasing collaboration across disciplines, by sharing data, algorithms, and software tools. Department of Defense Initiatives The U.S. military first became interested in network-centric warfare as an operational concept based on network science in 1996. John A. Parmentola, the U.S. Army Director for Research and Laboratory Management, proposed to the Armys Board on Science and Technology (BAST) on December 1st, 2003 that Network Science become a new Army research area. The BAST, the Division on Engineering and Physical Sciences for the National Research Council (NRC) of the National Academies, serves as a convening authority for the discussion of science and technology issues of importance to the Army and oversees independent Army-related studies conducted by the National Academies. The BAST conducted a study to find out whether identifying and funding a new field of investigation in basic research, Network Science, could help close the gap between what is needed to realize Network-Centric Operations and the current primitive state of fundamental knowledge of networks. As a result, the BAST issued the NRC study in 2005 titled Network Science (referenced above) that defined a new field of basic research in Network Science for the Army. Based on the findings and recommendations of that study and the subsequent 2007 NRC report titled Strategy for an Army Center for Network Science, Technology, and Experimentation, Army basic research resources were redirected to initiate a new basic research program in Network Science. To build a new theoretical foundation for complex networks, some of the key Network Science research efforts now ongoing in Army laboratories address: Mathematical models of network behavior to predict performance with network size, complexity, and environment Optimized human performance required for network-enabled warfare Networking within ecosystems and at the molecular level in cells. As initiated in 2004 by Frederick I. Moxley with support provided by David S. Alberts , the Department of Defense helped to establish the first Network Science Center in conjunction with the U.S. Army at the United States Military Academy. Subsequently, the U.S. Department of Defense has funded numerous research projects in the area of Network Science. Additionally in 2006, the U.S. Army and the United Kingdom (UK) formed the Network and Information Science International Technology Alliance , a collaborative partnership among the Army Research Laboratory, UK Ministry of Defense and a consortium of industries and universities in the U.S. and UK. The goal of the alliance is to perform basic research in support of Network- Centric Operations across the needs of both nations. In addition, the Army is in the process of establishing a Network Science and Technology Research Center (NSTRC). The NSTRC will conduct research across the technical areas of information networks, social/cognitive networks, communication networks, and integration research and experiments which will bring the three other technical areas together as a single entity. The NSTRC will conduct these activities in partnership with other Department of Defense and government agencies, industry and academia to find solutions to the hard problems associated with developing adaptable and scalable mobile ad-hoc networks for the Army. See also Network theory Complex network Collaborative innovation network Dynamic Network Analysis Higher category theory Polytely Systems Theory Irregular Warfare References Network Science, http://www.nap.edu/catalog.php?record_id=11516 Network Science Center, http://www.dodccrp.org/files/Network_Science_Center.asf Connected: The Power of Six Degrees, http://ivl.slis.indiana.edu/km/movies/2008-talas-connected.mov Further reading Understanding Network Science, http://www.zangani.com/blog/2007-1030-networkingscience Linked: The New Science of Networks , A.-L. Barabsi (Perseus Publishing, Cambridge (2002). Network Science , Committee on Network Science for Future Army Applications, National Research Council. 2005. The National Academies Press (2005) ISBN 0-309-10026-7 Network Science Bulletin , USMA (2007) ISBN 978-1-934808-00-9 The Structure and Dynamics of Networks Mark Newman, Albert-Lszl Barabsi, Duncan J. Watts (The Princeton Press, 2006) ISBN 0-691-11357-2 Dynamical processes in complex networks , Alain Barrat, Marc Barthelemy, Alessandro Vespignani (Cambridge University Press, 2008) ISBN 978-0-521-87950-7 External links http://www.orwik.com/ http://www.netscience.usma.edu/NSW/Papers/Network_Science_Report_Vol1No1.pdf http://press.princeton.edu/titles/8114.html http://www.cra.org/ccc/NSE.ppt.pdf http://www.ifr.ac.uk/netsci08/ http://www.netsci09.net/ Cyberinfrastructure Network Science Center at the U.S. Military Academy at West Point, NY Prof. Nicholas A Christakis' introduction to network science in Prospect magazine
Some Recent Advances in Complex Networks Synchronization _ Guanrong Chen, Xiaofan Wang, Xiang Li, and Jinhu Lv (陈关荣,汪小帆,李翔,吕金虎) 按语: 我把陈关荣等四位合作的文章推荐到这个专栏,完全是为了推动博文比赛. 因为 他们当中有三位是评委,自然将不参加评选. （方锦清2010、3、27） Abstract. The current study of complex dynamical networks is pervading almost all kinds of science, engineering and technology, ranging from mathematics to computers, physics to biology, even to sociology. Its impacts on the modern high-tech industries, financial markets and human life are prominent and will be far-reaching. Research on fundamental properties and dynamical features of such complex networks has indeed become overwhelming. This Chapter presents a brief overview of some past and current studies on the subject of complex dynamical network synchronization, particularly from an engineering and technological perspective. Some commonly concerned issues in the current research of network synchronization, mainly on Some recent advances in complex network synchroniz
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Today I present a Physics Review Letter paper named Cell fate as a high-dimensional attractor of a complex gene regulatory network in the journal club of our group. To my surprise, the response is quite polarized. For some people, they take for granted that cell types are attractors in gene network (maybe because that we are in the physics institute for complex system anyhow). They think that it is nothing more than just rewriting the biological facts in the physics language ( I dont know how many biologists actually accept this hypothesis. It is more widely accepted that cell types arise from turning on the type-specific Transcription Factors). They also complained that the 2-gene cross-inhibition example is too simple to demonstrate the effects of high-dimensional gene regulation space. They demanded a clear mathematical formula for cell reprogramming in the gene network. However, other people quickly recognized the importance of the paper and began to embrace this idea enthusiastically. We even begin to discuss how to build such a network. One guy even suggest the possibility to invite the author here for giving a talk by himself. Maybe a good journal club presentation is not to get the consensus of everybody. Rather it can arise the true interests of the people.
The Complexity Science Group in the Department of Physics Astronomy at the University of Calgary invites applications for a PhD position in the field of complex network theory with applications to neurosciences. The successful applicant is expected to work closely with other members of the Complexity Science Group and members of the Hotchkiss Brain Institute in an interdisciplinary environment. A background in statistical physics, computational physics, time series analysis, complex network theory and/or information theory is beneficial. Applicants should send an email to davidsen(at)phas.ucalgary.ca that includes a CV with a list of publications and a brief statement of research interests. Review of applications will begin on January 30, 2009 and continue until the position is filled. More information about the group is available at www.ucalgary.ca/complexity More detalis about the job in PDF fie: PhD Complex in neuroscience
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