综述 A journey to highly dynamic, self-adaptive service-based applications Abstract: Future software systems will operate in a highly dynamic world. Systems will need to operate correctly despite of unespected changes in factors such as environmental conditions, user requirements, technology, legal regulations, and market opportunities. They will have to operate in a constantly evolving environment that includes people, content, electronic devices, and legacy systems. They will thus need the ability to continuously adapt themselves in an automated manner to react to those changes. To realize dynamic, self-adaptive systems, the service concept has emerged as a suitable abstraction mechanism. Together with the concept of the service-oriented architecture (SOA), this led to the development of technologies, standards, and methods to build service-based applications by flexibly aggregating individual services. This article discusses how those concepts came to be by taking two complementary viewpoints. On the one hand, it evaluates the progress in software technologies and methodologies that led to the service concept and SOA. On the other hand, it discusses how the evolution of the requirements, and in particular business goals, influenced the progress towards highly dynamic self-adaptive systems. Finally, based on a discussion of the current state of the art, this article points out the possible future evolution of the field. Keywords: Service-oriented computing · Services · Adaptive systems ·Self-adaptation 文章： 1）a historical perspective 2）Current technology and methods for service-based applications 该部分围绕 （Figure 5）Layers and aspects relevant for service-based applications 3）Today’s technology and methods vs. application scenarios present two application scenarios： Federated organizations A pervasive computing scenario 4）Open issues and challenges 从以下六个方面讨论 Business process management Service composition and coordination Service infrastructure Analysis, design, and development Service quality definition, negotiation, and assurance Run-time adaptation Context beamer_journey_serivces.pdf A journey to highly dynamic, self-adaptive service-based applications.pdf
ISCNS 2011 nApril 23-24 Nanjing · Home · Organizing Committee · Invited Speakers · Program Schedule · Registration · Location and Sightseeing · Sponsors · Contact 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 Due the limit budget, we cannot afford your travel fees in this workshop. What we can afford are the following: 1. your living cost (including 2 buffet lunch 自助餐 +1 banquet) 2. your accommodation fees in the reserved hotel 3. tour fee in Zhongshan Ling （中山陵） on 25 April after the workshop Please send me the filled accommodation form with some detailed information by 11 April so that we can reserve the accommodation for you. Program Schedule 23-24 April, 2011: Two-day Workshop Registration Apr. 22, 2011 （ Friday ） 9:00-21:00 Registration : Nanjing Shijiyuan Hotel (jinxianghe road 20) 南京世纪缘大酒店 ( 进香河路 20 号 ) 东南大学四牌楼校区 西门向南大约 800 米 Apr. 23, 2011 （ Saturday ） 9:00-17:40 Registration : Chunhui Hall ( 东南大学四牌楼校区春晖堂 ) 南京市四牌楼 2 号东南大学 Apr. 23, 2011(Saturday) Chunhui Hall(春晖堂) 09:00-09:30 OpenCeremony Session1 Chair:JindeCao 09:30- 10:20 Guanrong Chen LaplacianSpectra ofComplexNetworks andTheirEffects onSynchronization Performances 10:20- 10:40 TeaBreak 10:40- 11:30 Yusheng Xue TBD 12:00- 14:00 Lunch Session2 Chair:JinqingFang 14:00-14:50 Xiaofan Wang SocialLearningin ComplexNetworks 14:50-15:40 Binghong Wang TransportationDynamics onMobileNodeNetwork 15:40-16:00 TeaBreak 16:00-16:50 Jinqing Fang AFrameworkof Non-Equilibriumand EquilibriumStatistical EnsembleFormalism forComplexQuantumSystems 16:50-17:40 Fuchun Sun UniversalApproximationand ControlofMulti-Time-Scale DynamicalSystems 18:00 Banquet Apr.24,2011(Sunday) ChunhuiHall( 春晖堂 ) Session3 Chair:YuanqingXia 09:00-09:50 Jun-an Lu Synchronization-based ScalabilityofRingsand ChainsofDenseLumps 09:50-10:10 TeaBreak 10:10-11:00 Zhihong Guan ImpulsiveAlgorithms forConsensusof Multi-agentSystems 11:00-11:50 Yuanqing Xia AnalysisandSynthesisof NetworkedControlSystems 12:00- 14:00 Lunch Session4 Chair:WenwuYu 14:00-14:50 Zhisheng Duan Synchronizationof ComplexNetworksand ConsensusofMulti-AgentSystems: AUnifiedViewpoint 14:50-15:40 Daniel Ho APinningSchemeand AggregationApproach toComplexNetworks 15:40-16:00 TeaBreak 16:00-16:50 Guangming Xie ControlTheory forSmartSwarms 16:50-17:40 Wei Ren DistributedControl ofNetworkedMulti-agent Systems:Algorithms andApplications 17:40-18:00 ConclusionRemarks Apr. 25, 2011(Monday) Tourism in Zhongshan Ling（中山陵） All Rights Reserved 2011 - By ISCNS'2011
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
110221-Complex_systems_A_survey.pdf Complex Systems: A Survey M. E. J. Newman Department of Physics, University of Michigan, Ann Arbor, MI 48109 and Center for the Study of Complex Systems, University of Michigan, Ann Arbor, MI 48109 A complex system is a system composed of many interacting parts, often called agents, which displays collective behavior that does not follow trivially from the behaviors of the individual parts. Examples include condensed matter systems, ecosystems, stock markets and economies, biological evolution, and indeed the whole of human society. Substantial progress has been made in the quantitative understanding of complex systems, particularly since the 1980s, using a combination of basic theory, much of it derived from physics, and computer simulation. The subject is a broad one, drawing on techniques and ideas from a wide range of areas. Here I give a short survey and an annotated bibliography of resources for those interested in learning about complex systems. I. INTRODUCTION Complex systems is a relatively new and broadly interdisciplinary field that deals with systems composed of many interacting units, often called “agents.” The foundational elements of the field predate the current surge of interest in it, which started in the 1980s, but substantial recent advances in the area coupled with increasing interest both in academia and industry have created new momentum for the study and teaching of the science of complex systems. There is no precise technical definition of a “complex system,” but most researchers in the field would probably agree that it is a system composed of many interacting parts, such that the collective behavior of those parts together is more than the sum of their individual behaviors. The collective behaviors are sometimes also called “emergent” behaviors, and a complex system can thus be said to be a system of interacting parts that displays emergent behavior. Classic examples of complex systems include condensed matter systems, ecosystems, the economy and financial markets, the brain, the immune system, granular materials, road traffic, insect colonies, flocking or schooling behavior in birds or fish, the Internet, and even entire human societies. Unfortunately, complex systems are, as their name makes clear, complex, which makes them difficult to treat scientifically. Experimental observations are of course possible, though these fall largely within the realm of the traditional scientific disciplines and are usually not considered a part of the field of complex systems itself, which is primarily devoted to theoretical developments. Complex systems theory is divided between two contrasting approaches. The first involves the creation and study of simplified mathematical models that do not claim to mimic quantitatively the behavior of real systems but instead try to abstract their most important qualitative elements into a solvable framework from which we can gain scientific insight. The tools used in such studies include dynamical systems theory, information theory, cellular automata, networks, computational complexity theory, and numerical methods. The second approach is to create systematic computer simulations of the interacting parts of a complex system, often down to minute details, and then watch and measure the emergent behaviors that appear. The primary tool for this approach is agent-based simulation, around which a community of computer scientist scientists and software developers has grown up to create software tools for sophisticated computational research in complex systems. This resource letter focuses on the methods and theoretical tools of complex systems, including both the modeling and simulation approaches above, though I also include a short section of references to individual specific complex systems, such as economies or ecosystems, which can serve as a concrete foundation motivating the theoretical studies.
Call for Papers The 8 th International Conference on Service Systems and Service Management ICSSSM1 1 June 25-27, 2011 Tianjin , China http://ibs.nankai.edu.cn/ICSSSM11 Co-Sponsored by : IEEE SMC Nankai University The Chinese University of Hong Kong Tsinghua University National Natural Science Foundation of China (NSFC) Hosted by : Business School , Nankai University , China Conference Co-Chairs: Weian Li, Nankai University , China Jian Chen , Tsinghua University , China International Advisory Committee : James A. Fitzsimmons, The University of Texas at Austin , USA William A. Gruver, Simon Fraser University , Canada Chung-Yee LEE, Hong Kong University of Science and Technology, Hong Kong , China Roland RUST, University of Maryland , USA J. M. Tien, University of Miami , USA D. S. Yeung, IEEE Systems, Man and Cybernetics Society International Program Committee : Chair: Jian Chen , Tsinghua University , China Co-Chair : Xiaoqiang Cai, The Chinese University of Hong Kong , Hong Kong , China Local Organizing Committee: C hair :Jianyuan Yan Nankai University , China Co-Chair: Yongjian Li Nankai University , China Topics of Interest : The topics of interest include, but are not limited, to those listed in the following tracks: Track 1 Theory and Principle of Service Sciences Service concepts and strategies, quality assurance, performance metrics. Track 2 Service System Design, Operations, and Management Service system and network design, service process engineering/reengineering, service planning and scheduling, service management based on emergency, modeling and analysis of service systems. Track 3 Supply Chain Management for Service Supply chain planning, value delivery, supply chain management based on emergency, supply chain cluster, transportation management systems, return logistics, supplier relationship management, logistics visibility and control, procurement. Track 4 Service Marketing and Financial Management Demand forecasting, customer relationship management, public relations, customer behavior, satisfaction, and retention, service cost evaluation and analysis, profitability of service investment, risk management, revenue management. Track 5 Specific Industrial Service Management Information service, tourism and hotel management, public service, hospital, finance and insurance service, sports service, exhibitions. Track 6Service Information Technology and Decision Making Integrated information management systems, real-time identification and tracking technology, agent theory and technology, software agent based systems, intelligent decision support systems, artificial intelligence, RFID technology and applications, data warehousing and data mining, systems integration, e-business/e-service. Track 7 Service Experiential Studies and Case Studies Healthcare, education, public service, transportation, telecommunication, maintenance, finance/ insurance/real estate, distribution/retail, service for social, economical, and cultural events (e.g., exhibitions, sports, festivals). Important Dates : 30 Jan 2011 Full papers submission (maximum 6 pages) deadline 20 Mar 2011 Notification of paper acceptance or rejection 10 May 2011 Final camera-ready papers sub mission deadline 10 May 2011 Early bird registration deadline 25-27 Jun 2011 Conference Call for Contributed Papers : Papers on issues related to service systems and service management are welcome. All submissions should be written in English. The first page of each paper must include the following information: title of the paper; name(s) and affiliation(s) of the author(s); abstract of the paper; postal address, and email address of the corresponding author. Papers will be peer-reviewed. To be eligible for publication in the conference proceedings, an accepted paper must be presented at the conference by one of the authors. The conference proceedings will be published in CD-ROM with ISBN and submitted for EI indexing after the conference. All previous ICSSSM proceedings published from 2005 to 2010 have been indexed by EI Compendex . Selected good papers will be recommended to potential publication in the journal Nankai Business Review International or Journal of Systems Science and Systems Engineering . Call for Invited Sessions and Tracks : The goal of invited sessions (5 papers for each session) and invited tracks (at least two sessions) is to provide focused discussions on new topics or innovative applications. Each prospective session/track organizer is invited to submit a proposal, including the title of the session/track, and a list of authors with extended abstracts. Paper Submission : Please send papers (in PDF or Word) to: ICSSSM11 ， Business School , Nankai University , Tianjin 300071, P.R. China. Email: ICSSSM11@gmail.com. Tel ： +86 22 23498052 Please indicate Track Number in the subject during your submission.
New England Complex Systems Institute Winter School on Complex Systems We are pleased to announce the dates of our upcoming courses on complex systems: Jan. 3-7, 2011 / Complex Physical, Biological Social Systems Jan. 9, 2011 / Computer Programming and Complex Systems Jan. 10-14, 2011 / Complex Systems Modeling and Networks Target Audience These courses are intended for faculty, graduate students, post- doctoral fellows, professionals and others who would like to gain an understanding of the fundamentals of complex systems, and develop methodological tools for conducting research in their respective fields, or as a basis for pursuing complex systems research. The winter school offers two intensive week-long courses. The courses consist of lectures, discussions, and supervised group projects. Though the second week builds on material covered in the previous week, CX201 is not a prerequisite for CX202. You may register for either or both weeks. If desired, arrangements for credit at a home institution may be made in advance. See course descriptions below or online at: www.necsi.edu/education/school.html WEEK ONE CX201: Complex Physical, Biological and Social Systems Dates: January 3-7, 2011|Location: MIT, Cambridge, MA This course offers an introduction to the essential concepts of complex systems and related mathematical methods and simulation strategies with application to physical, biological and social systems. The course will particularly focus on the use of multiscale representations as a unifying approach to complex systems concepts, methods and applications. Concepts to be discussed include: emergence, complexity, networks, self-organization, pattern formation, evolution, adaptation, fractals, chaos, cooperation, competition, attractors, interdependence, scaling, dynamic response, information, and function. Methods to be discussed include: statistical methods, cellular automata, agent-based modeling, pattern recognition, system representation and informatics. LAB CX102: Computer Programming and Complex Systems Date: January 9, 2011|Location: MIT, Cambridge, MA This course introduces computer programming in the Python language for those with little or no computer programming experience. It is designed as a precursor to CX202. The course will present programming concepts and hands-on exercises. Topics to be covered include: data structures, algorithms, variables and assignments, numerical and logical operations, lists and dictionaries, user-defined functions, flow control, loops, and visualization. WEEK TWO CX202: Complex Systems Modeling and Networks Dates: January 10-14, 2011|Location: MIT, Cambridge, MA This course provides (a) an introduction to building models of complex systems (physical, biological, social and engineered), and (b) the study of networks, including topologies and dynamics of real world networks. The course will cover the basic construction and analysis of models including identifying what is to be modeled, constructing a mathematical representation, analysis tools and implementing and simulating the model in a computer program. Particular attention will be paid to choosing the right level of detail for the model, testing its robustness, and discussing which questions a given model can or cannot answer. The study of networks will introduce the use of network topologies and the characterization of networks describing complex systems, including such concepts as small worlds, degree distribution, diameter, clustering coefficient, modules, and motifs. Different types of network topologies and network behaviors that model aspects of real complex systems will be described including: modular, sparse, random, scale-free, influence, transport, transformation, and structure. NOTE: Students without a background in programming are strongly recommended to attend CX102: Computer Programming and Complex Systems in conjunction with CX202. Comments from past students Excellent course... useful thematic overview... applications in diverse contexts were exciting. Particularly appreciated the group project - excellent experiential pedagogy. The course was an eye-opening framework to analyze my work through a different lens. Presentations were extremely useful for me in understanding how to begin modeling complex systems and assessing them. Helped me understand a lot of things I have been doing so far without clearly understanding the principles. This class very much stretched my mind to apply the ideas of complexity to the world... I believe I learned more on a grander scale...will help enrich my vocabulary and the way of thinking in the world with respect to complexity. Excellent class. I hope to take a more active role in the community. For more information and registration: www.necsi.edu/education/school.html
在一 前文 中，我谈到西方大学很注重培养学生的创新思维。这也与西人的性格有关，性格较外向，喜欢表达自己。只要不出格，不抄袭，是自己的独创，教授一般都很宽容。刚好一位博士生的汇报演讲很好地说明了这一点。Daniel的课题是系统生物(systems biology), 基因网络方面的研究。他的本行是IT, 转为生物信息学的研究。以前开会，曾与他共处过，知道这个人比较讲'情调'，会议晚上喜欢饮点好葡萄酒，甚至点几根蜡烛之类。以前听过他的一个小talk, 确实是演讲好手，喜欢把问题往浅里说。 读了四年，终于可以毕业了。他的毕业汇报题目'Gene network inference and application', 题目吸引人，所以房间坐满了人，听众来自几个系，院。 的确是好好准备过的，一开始就把大家吸引住了：他一个橄榄球为例（现场有一真正橄榄球），要从众多基因之间理清它们互相之间如何相互作用，正如一个不知橄榄球为何物的人要从那二十个跑来跑去的人总结出游戏规则一样。在这千头万绪之中，可能有个别基因出轨的事，Daniel则用了一张橄榄球场上一个裸奔的球迷照片作为analog. 全场大笑。 类似的例子还不少。就在听众的笑声中，他把他过去四年做过些什么，有什么突破，有哪些挑战，有哪些没搞清楚的问题，基本上介绍完了。尤其他提到在MIT参与过GenePattern项目。 最后到了致谢环节，正琢磨这家伙要搞些什么花招的时候，Daniel拿出了一把电吉他，挎在身上，逢要谢谢某个人或组织，则弹一个曲调，把讲演气氛搞向高潮。 象这样的在一个比较正规的学术演讲场合的表演可能在国内很难看到。从科学上讲，这种风格适合于轻松的open talk, 很多听众对这个题目不了解的情形。对小同行，则需要更学术一些。 附Daniel演讲的abstract: My research focuses on inferring regulatory networks from gene expression data, and applying them to problems in human biology. In this talk I shall explain what a gene network is and how it might be useful, describe some new tools and ideas developed to make better use of gene expression data, and show some of the most exciting results we have found in different types of cells. In particular, I shall show some examples of using network inference techniques to study transcription factor interactions in endothelial cells, and explain a new hypothesis we have proposed to account for interactions up- and down-stream of particular transcription factors. Finally, I shall talk about our work on malignant melanoma, and show some results from combining a new gene expression dataset with published clinical data from patient tumours to identify previously unknown master regulators associated with differences in survival of melanoma patients.
如果大家也在研究这一方面的，请大家一起讨论讨论！ Service-oriented systems are not the same as component-oriented systems, but they have some commons. A PPT about Formal Modelling of Service-oriented Systems was at http://www.cs.le.ac.uk/people/jfiadeiro/Tutorials/SFMO09.pdf
连续两篇论文投向了 IEEE Transactions on Fuzzy Systems ，两篇文章中间隔了一个月，不知道主编会不会觉得有点快。IEEE Transactions on Fuzzy Systems 是 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE （计算机科学-人工智能）的顶级期刊，08年IF：3.624 （人工智能领域排第5），难度应该还是挺大的！under review 了，期待有好消息！
MOLECULAR SYSTEMS BIOLOGY 11 May 2010 ********************************************************************** What if you could use 25 ng or less of total RNA for labeling in an expression experiment? Agilent announces the launch of the new Low Input Quick Amp Labeling Kit. Obtain the same high sensitivity performance you expect, but conserve your precious sample, all at the same time. Find out how to use this new product at http://links.ealert.nature.com/ctt?kn=11m=34876418r=Mzg0ODUxNzc1NQS2b=2j=NzM1ODkwMjkS1mt=1rt=0
9 March 2010 Wield the power of next generation sequencingwith workflow tools from Agilent . Designed to streamline and optimize your next gen research, our productsfeaturing sample and library QC, target enrichment, library amplification and automation toolshelp you harness the potential of next gen. Learn how researchers are solving next gen challenges at opengenomics.com/nextgen . Molecular Systems Biology is a partnership between the European Molecular Biology Organization and Nature Publishing Group . We are delighted to announce the journal's new Impact Factor is 12.243*. Molecular Systems Biology appears now within the top 10 journals in the Biochemistry Molecular Biology subject category. Set your research free, submit at http://www.nature.com/msb To view articles in the top ten PDF downloads, please visit: www.nature.com/msb/topten * 2008 Journal Citation Report (Thomson Reuters, 2009) Featured article Synthesizing a novel genetic sequential logic circuit: a push-on push-off switch A bistable switch and NOR gate were constructed and then coupled to form a genetic sequential logic circuit, which functions as push-on push-off switch. Rational design and directed evolution were employed to construct the two sub-modules and fine-tune their interconnecting parts. Latest articles Synthesizing a novel genetic sequential logic circuit: a push-on push-off switch Chunbo Lou, Xili Liu, Ming Ni, Yiqi Huang, Qiushi Huang, Longwen Huang, Lingli Jiang, Dan Lu, Mingcong Wang, Chang Liu, Daizhuo Chen, Chongyi Chen, Xiaoyue Chen, Le Yang, Haisu Ma, Jianguo Chen Qi Ouyang 09 March 2010 Synopsis | Full Text | Supplementary info Bacterial adaptation through distributed sensing of metabolic fluxes Oliver Kotte, Judith B Zaugg Matthias Heinemann 09 March 2010 Synopsis | Full Text | Supplementary info Dynamics within the CD95 death-inducing signaling complex decide life and death of cells Leo Neumann, Carina Pforr, Joel Beaudouin, Alexander Pappa, Nicolai Fricker, Peter H Krammer, Inna N Lavrik Roland Eils 09 March 2010 Synopsis | Full Text | Supplementary info GINS motion reveals replication fork progression is remarkably uniform throughout the yeast genome Matthew D Sekedat, David Feny, Richard S Rogers, Alan J Tackett, John D Aitchison Brian T Chait 09 March 2010 Synopsis | Full Text | Supplementary info Zebrafish Pou5f1-dependent transcriptional networks in temporal control of early development Daria Onichtchouk, Florian Geier, Bozena Polok, Daniel M Messerschmidt, Rebecca Mssner, Bjrn Wendik, Sungmin Song, Verdon Taylor, Jens Timmer Wolfgang Driever 09 March 2010 Synopsis | Full Text | Supplementary info Feedback between p21 and reactive oxygen production is necessary for cell senescence Joo F Passos, Glyn Nelson, Chunfang Wang, Torsten Richter, Cedric Simillion, Carole J Proctor, Satomi Miwa, Sharon Olijslagers, Jennifer Hallinan, Anil Wipat, Gabriele Saretzki, Karl Lenhard Rudolph, Tom B L Kirkwood Thomas von Zglinicki 16 February 2010 Synopsis | Full Text | Supplementary info Different sets of QTLs influence fitness variation in yeast Gal Hagit Romano, Yonat Gurvich, Ofer Lavi, Igor Ulitsky, Ron Shamir Martin Kupiec 16 February 2010 Synopsis | Full Text | Supplementary info Revealing a signaling role of phytosphingosine-1-phosphate in yeast L Ashley Cowart, Matthew Shotwell, Mitchell L Worley, Adam J Richards, David J Montefusco, Yusuf A Hannun Xinghua Lu 16 February 2010 Synopsis | Full Text | Supplementary info Intracellular transactivation of HIV can account for the decelerating decay of virus load during drug therapy Christian L Althaus Rob J De Boer 16 February 2010 Synopsis | Full Text | Supplementary info Reports Precision and scaling in morphogen gradient read-out Aitana Morton de Lachapelle Sven Bergmann 09 March 2010 Full Text | Supplementary info A side effect resource to capture phenotypic effects of drugs Michael Kuhn, Monica Campillos, Ivica Letunic, Lars Juhl Jensen Peer Bork 19 January 2010 Full Text | Supplementary info
19 January 2010 Molecular Systems Biology is a partnership between the European Molecular Biology Organization and Nature Publishing Group . We are delighted to announce the journal's new Impact Factor is 12.243*. Molecular Systems Biology appears now within the top 10 journals in the Biochemistry Molecular Biology subject category. Set your research free, submit at http://www.nature.com/msb To view articles in the top ten PDF downloads, please visit: www.nature.com/msb/topten * 2008 Journal Citation Report (Thomson Reuters, 2009) Featured article Systematic image-driven analysis of the spatial Drosophila embryonic expre ssion landscape To analyze spatial gene expre ssion patterns in Drosophila , we created a computationally virtual representation for a large in situ hybridization expre ssion dataset. We identified distinct regions in the embryo defined by gene expre ssion, organized expre ssion patterns and used them for identifying putative interacting genes and gene functions. Latest articles Systematic image-driven analysis of the spatial Drosophila embryonic expre ssion landscape Erwin Frise, Ann S Hammonds Susan E Celniker 19 January 2010 Synopsis | Full Text | Supplementary info Control of ATP homeostasis during the respiro-fermentative transition in yeast Thomas Walther, Maite Novo, Katrin Rssger, Fabien Ltisse, Marie-Odile Loret, Jean-Charles Portais Jean-Marie Franois 19 January 2010 Synopsis | Full Text | Supplementary info GroEL dependency affects codon usagesupport for a critical role of misfolding in gene evolution Tobias Warnecke Laurence D Hurst 19 January 2010 Synopsis | Full Text | Supplementary info Deciphering a transcriptional regulatory code: modeling short-range repression in the Drosophila embryo Walid D Fakhouri, Ahmet Ay, Rupinder Sayal, Jacqueline Dresch, Evan Dayringer David N Arnosti 19 January 2010 Synopsis | Full Text | Supplementary info Chemogenomic profiling predicts antifungal synergies Gregor Jansen, Anna Y Lee, Elias Epp, Amlie Fredette, Jamie Surprenant, Doreen Harcus, Michelle Scott, Elaine Tan, Tamiko Nishimura, Malcolm Whiteway, Michael Hallett David Y Thomas 22 December 2009 Synopsis | Full Text | Supplementary info Theoretical and experimental analysis links isoform- specific ERK signalling to cell fate decisions Marcel Schilling, Thomas Maiwald, Stefan Hengl, Dominic Winter, Clemens Kreutz, Walter Kolch, Wolf D Lehmann, Jens Timmer Ursula Klingmller 22 December 2009 Synopsis | Full Text | Supplementary info Rapid and sustained nuclearcytoplasmic ERK oscillations induced by epidermal growth factor Harish Shankaran, Danielle L Ippolito, William B Chrisler, Haluk Resat, Nikki Bollinger, Lee K Opresko H Steven Wiley 01 December 2009 Synopsis | Full Text | Supplementary info Comparison of substrate specificity of the ubiquitin ligases Nedd4 and Nedd4-2 using proteome arrays Avinash Persaud, Philipp Alberts, Eva M Amsen, Xuejian Xiong, James Wasmuth, Zachary Saadon, Chris Fladd, John Parkinson Daniela Rotin 01 December 2009 Synopsis | Full Text | Supplementary info Discrete logic modelling as a means to link protein signalling networks with functional analysis of mammalian signal transduction Julio Saez-Rodriguez, Leonidas G Alexopoulos, Jonathan Epperlein, Regina Samaga, Douglas A Lauffenburger, Steffen Klamt Peter K Sorger 01 December 2009 Synopsis | Full Text | Supplementary info Reports A side effect resource to capture phenotypic effects of drugs Michael Kuhn, Monica Campillos, Ivica Letunic, Lars Juhl Jensen Peer Bork 19 January 2010 Full Text | Supplementary info A global view of protein expre ssion in human cells, tissues, and organs Fredrik Pontn, Marcus Gry, Linn Fagerberg, Emma Lundberg, Anna Asplund, Lisa Berglund, Per Oksvold, Erik Bjrling, Sophia Hober, Caroline Kampf, Sanjay Navani, Peter Nilsson, Jenny Ottosson, Anja Persson, Henrik Wernrus, Kenneth Wester Mathias Uhln 22 December 2009 Full Text | Supplementary info
仅限学术研究使用，严禁商业用途，作者和出版社如有异议，我立即删除附件。如果觉得本书比较好，请购买正版图书。也欢迎各位博友讨论本书内容。欢迎学术交流。 Preface Many problems in science involve the solving of differential equations or systems of differential equations. Moreover, many of these equations and systems come from variational considerations involvingmappings (called functionals) into the real number system. Thus, in such cases, solutions of the equations or systems are critical points of the corresponding functional. As a result, anyone who is interested in obtaining solutions of the equations or systems is also interested in obtaining critical points of the corresponding functionals. The latter problem is the subject of this book. The classical way of obtaining critical points was to search for maxima or minima. This is possible if the functional is bounded from above or below. However, when this is not the case, there is no organized way of finding critical points. Linking theory is an attempt to level the playing field, i.e., to find a substitute for semiboundedness. It finds a pair of subsets A, B of the underlying space that allow the functional to have the same advantages as semibounded functionals if the subsets separate the functional. This is the theme of the book , which records much of the work of researchers on this approach up to that time. There are several methods of obtaining linking sets (some will be outlined later in Chapters 3 and 6). The purpose of the present volume is to unify some of these approaches and to study results and applications that were obtained since the publication of . The underlying theme is to consider minimax systems depending on a set A. These are collections K of subsets such that if the functional G satisfies. then it has the same advantages as a semibounded functional. We show that the main approaches to linking can be combined by using minimax systems. Minimax Systems and Critical Point Theory
Rami Matarneh Department of Management Information Systems, Faculty of Administrative and Financial Sciences, Al-Isra Private University, Amman , P.O. 11622, Jordan Abstract: Problem statement: In the midst of the huge development in processors industry as a response to the increasing demand for high-speed processors manufacturers were able to achieve the goal of producing the required processors, but this industry disappointed hopes, because it faced problems not amenable to solution, such as complexity, hard management and large consumption of energy. These problems forced themanufacturers to stop the focus on increasing the speed of processors and go toward parallel processing to increase performance. This eventually produced multi-core processors with high-performance, if used properly.Unfortunately, until now, these processors did not use as it should be used; because of lack support of operating system and software applications. Approach: The approach based on the assumption that single-kernel operating system was not enough to manage multi-core processors to rethink the construction of multi-kernel operating system. One of these kernels serves as the master kernel and the others serve as slave kernels. Results: Theoretically, the proposed model showed that it can do much better than the existing models; because it supported single-threaded processing and multi-threaded processing at the same time, in addition, it can make better use of multi-core processors because it divided the load almost equally between the cores and the kernels which will lead to a significant improvement in the performance of the operating system. Conclusion: Software industry needed to get out of the classical framework to be able to keep pace with hardware development, this objective was achieved by re-thinking building operating systems and software in a new innovative methodologies and methods, where the current theories of operating systems were no longer capable of achieving the aspirations of future. Key words: Microkernel, multi-microkernel, multi-core processors, inter-process communication Multi Microkernel Operating Systems for Multi - Core Processors
The Symposium on Systems Biology: Integrative, Comparative, and Multi-Scale Modeling has received additional funding that will provide for substantial travel grants for students and post-docs. Therefore, we are extending both the travel grant deadline and the abstract deadline until April 27. Please share this information with any students or post-docs that would be interested in attending this exciting meeting! To register and apply for a travel grant , see our website at http://www.bb.iastate.edu/~ gfst/phomepg.html
写完系列 1 以后通过和大家的问答发现，发现系统生物学的这一称谓，和目前系统生物学真正的研究内容，有非常大的不同。虽然在英文术语中称作 Systems Biology ，但我觉得，就目前主要的研究内容和需要解决的问题而言，翻译为 系统分子生物学 会更恰当一些，也避免了一些不必要的误解。前文中有人提到的问题，我觉得非常好，故重录于此： 6 系统生态学早于系统生物学近 30 年提出，也是从整体和模型角度研究生态系统。不知系统生物学有何思想创新？ 系统生态学和系统分子生物学是两个完全不同的学科。系统生态学着力于宏，系统分子生物学着力于微与宏的结合。系统分子生物学是弥补分子生物学与生理学之间的空白。比如像癌症，分子生物学已经发现不少的癌症基因与相应的生化路径；生理学也弄清楚了癌症在各阶段细胞的形态与功能会发生什么样的变化。但是，癌症基因是如何与正常细胞的分子机制相互作用，重新触发成年细胞已经停止的生长机制，我们如何才能使这个过程逆向进行等等？都需要我们对这一过程建立定量的、可预测结果的模型，这就是系统分子生物学的工作。系统分子生物学的思想创新之处在于，通过建了动力的、定量的模型，揭示生命现象中 1+12 仅为系统所拥有而对个体不存在的新功能。比如目前研究得最为成熟的控制心脏肌细胞跳动的基因网络中，我们并没有发现控制心脏跳动的基因。相反，基因网络中每一个基因控制一种 Ion Channel 的蛋白质随时间的动态变化，而这些变化之间的相互作用才构成了心脏有节律的跳动。 所以，控制着心脏跳动的，并不是基因本身，而是这个相互作用的基因网络的系统特性。 赵老师补充的很好，系统生物学的核心是研究系统的涌现特性 , 对涌现特性的测量和把握是从整体上理解生物系统的突破口。但系统分子生物学（ Systems Biology ）还不仅仅在于对生物系统 A 研究其涌现特性（ Emerging Properties ） , 再对另一个新的生物系统 B 研究其涌现特性。但系统分子生物学（ Systems Biology ）最有新意的地方在于寻找生物系统产生某种 Emerging Properties 的一般规律，比如产生各种系统功能的 Network Motif ，和细胞的基因控制网络，代谢网络和生物发育中的一般性网络设计规则 (Network design principles) 。这样的例子，在 Uri Alon 的经典教材 An introduction to systems Biology: Design principles of Biological circuits 中不乏精彩的阐述。 7 那么，系统分子生物学是不是等同于，将复杂系统（ Complex Network ）的研究引入到 分子生物学和细胞生物学呢 ？ 复杂系统在系统分子生物学中肯定有应用，但是绝不是直接将 Complex Networks 引入到分子生物学和细胞生物学那样简单。一方面，系统分子生物学的系统是一般复杂系统的子集，只研究在初始条件和动力演进过程中存在大量扰动仍然收敛和稳定的系统。另一方面，细胞中的代谢网络，基因控制网络和信号传导网络，都有其别于一般复杂系统的特征。这些特征在复杂系统的研究中都没有涉及，因此恰好反过来，系统分子生物学的发展，可以促进复杂系统理论研究的进程。 8 那么，系统分子生物学产生的背景和发展简史是什么？系统分子生物学会不会像某些学科一样，成为学术研究得快潮， 30 年后回头一看，一堆垃圾呢？ 任何具有历史意义的研究都有其历史发展背景的。十八世纪末精密天文仪器的出现与大量天文观测的积累，促使人们去思考天体运动的规律。第一个出现的就是 Kepler 的行星运行三定律，然后由 Newton 将其一般化而发展出了牛顿力学体系。十九世纪人们积累了大量关于电学与磁学的知识，电场与磁场如何随时间变化且相互关系如何，这个问题的答案就是由 Maxwell 建立的经典电磁场理论。当人们发现原子不但存在，并且原子可能还有其结构存在。通过 J.J. Thomson 和 Rutherford 等人的大量试验，人们在原子的结构弄清楚以后，自然会问：这些粒子的相互作用和动力演进会如何？这就导致的 Schrdinger 方程和量子力学的诞生。在上个世纪的后五十年中，从 Watson 和 Crick 发现 DNA 的双螺旋结构算起，发现一切生命现象在分子层面具有高度的统一性，通过几代分子生物学家的努力，已经发现了大量的有关细胞生命的各种分子与生化过程的细节。那么我们自然会问，这些生物分子的相互作用与动力演进是如何与生命现象的种种功能联系起来的呢？ 比如细胞的代谢、信号的传导、细胞的生长、细胞的自我凋亡、癌症的产生等等。甚至更进一步，我们如何可以通过改变基因表达模式，或引入功能小分子，或改变 Transcription Factors ，来调节和控制细胞的代谢、信号的传导、细胞的生长和调往，甚至逆转癌细胞的产生呢？比如目前，由 Yamanaka 小组通过超常表达四种基因而使皮肤细胞逆转成为干细胞，以近有人在研究是否可以超常表达某些基因的组合，而使癌细胞逆转为正常细胞。这样的研究常常需要对上千种基因进行选择和组合，如果能够建立细胞的基因表达网络的动力模型，这将对通过改变基因表达从而改变细胞形态和功能的研究提供极大的促进。 Fig. 1 Hans Driesch and his theory for development 最早试图用数理方程来解释生物体发育的是 1907 年德国的 Hans Driesch ，他试图建立一个理想细胞的模型，通过建立一个有关所有物理和化学因素的函数，来预测生物体的发育。试想在一个生物发育的机理尚未弄清楚的年代，他的尝试自然没有成功。 Fig. 2 Schrodinger and his book What is Life 随后 1944 年已经在量子力学领域取得巨大成就的 Schrdinger 对生命现象发生浓厚的兴趣。他通过前人对基因的研究，推测出这种尚未发现其结构的遗传物质应该有哪些特征 。并且从热力学的角度，生命应该具有哪些最基本的功能。他写的 What is Life ，激励了一代又一代的物理研究者进入生命领域。 Fig. 3 Geometrical model for Fish growth 而后来 CH Waddington 在 20 世纪 70 年代创建了理论生物学的 Edinburgh 学派，试图在完全不了解生物体机制的情况下建立纯粹的有关生命的数学理论。其想象力的丰富和脱离实际，和中世纪的僧侣在没有天文观测的情况下建立行星的运行规律如同一辙。比如基于纯几何的鱼的生长模型. Fig. 4 Heart model from Systems Biology 牛津大学的 Denis Noble 是 systems biology 的几个最早的先驱之一。他是最早使用分子生物学和数学模型来建立心脏模型的研究者，他的研究成果发表在 60 年代的 Nature 上，成为这一领域最有影响力的论文之一。 Fig. 5 Systems Biology Pioneer --- Denis Noble 然而 Systems Biology 真正成为生命科学中的新方向是在 1998 年以后，这一方向逐渐得到各大科研基金的支持。而且由于是新兴学科，各种名目，林林种种，不一而齐。比如， NIH 的 Integrative Cancer Biology 项目， 以后的 National Technology Centers for Networks and Pathways ,Metabolomics Technology Development. NSF 的 Quantitative System Biotechnology , Frontiers in Integrative Biological Research 以及 DoE(Department of Energy) 和 DAPRA 的项目。英国的 ESPRC 和 BBSRC 联合支持的 Quantitative and predictive systems biology 。德国教育科技部支持的 Systems Biology of hepatocyte, 详情见另文（ Apoptosis, autophagy 和德国的系统生物学会议 ）。另外，日本的科技文教部斥巨资 Genome Network Programm 等等。 Apoptosis, autophagy 和德国的系统生物学会议 博文链接： http://www.sciencenet.cn/blog/user_content.aspx?id=28308 9 进入系统分子生物学的研究，需要哪些背景知识和专业课呢？ MIT 在 2004 年首先建立了 Computational Systems biology graduate program, University Of California , San Diego (UCSD) 也在其生物工程系中开设了 Systems biology 。开设这一方向的还有： Harvard Medical School, The institute for Systems Biology Oxford university 和 荷兰的 Biocentrum Amsterdam 。感兴趣的话，可以到这些学校的网页上察看更详细的内容。 生物学方面的专业课程应该包括： Genetics, biochemistry, molecular biology, cell biology 等。 理论分析方面的课程有： probability, statistics, information theory, numerical optimization, Ordinary differential equation and partial differential equation, Stochastic dynamics theory, Cell Automata Theory, Graph theory, Complex network theory, nonlinear dynamics 等。 几本不错的入门读物： 1. Uri Alon 的经典教材 , 简单易懂，很适合生物学背景的入门读物，An introduction to systems Biology: Design principles of Biological circuits 2. 数学和物理背景的，感觉读Alon的不过瘾的，可以读读MIT的 Zoltan (EDT)/ Stelling, Jorg (EDT)/ Periwal, Vipul (EDT) Szallasi ， System Modeling in Cell Biology (Hardcover)， Amazon Link: http://www.amazon.com/Modeling-Biology-Stelling-Periwal-Szallasi/dp/B001E0AISY/ref=sr_1_1?ie=UTF8s=booksqid=1223243296sr=1-1 END
标签: Systems
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