Biocomplexity -- Incubation Activity: Collaborative Research: Networking the 'Invisible Colleges': Application of Network Theory to Biocomplexity

该讲习班将汇集多学科的数学家、统计学家、计算机科学家、生物科学家和社会科学家，以开发人类和生物系统中的复杂网络模型，特别强调社会网络和生态网络的整合。用于组织讲习班的具体目标是：(1)建立共同点；(2)复杂系统的建模；(3)接口和扩展；(4)可视化和探索；以及(5)数据质量问题。各学科的30名专家应邀参加了2001年3月在杜克海洋实验室举行的为期三天的讲习班。在会议之前，为了建立共同立场，我们将向每位与会者分发一份目的声明、主要读物和不同学科中使用的类似术语词典。讲习班将以一整天的重点介绍开始，第二天专门讨论分组讨论，重点放在最后四个目标上，最后一天将利用报告员综合分组总结和建议。与会者将：确定跨学科复杂性的共同问题、思想交叉培养的局限性以及克服这些局限性的方法；探讨数学家、统计学家以及社会和生物学科学家开发的各种数学和统计网络模型和分析是否适用于复杂生物系统的研究；探索将营养和非营养性质的人类系统动力学纳入复杂生物系统模型的问题；开发和改进基于计算机的工具，用于对复杂生物系统进行探索性可视化分析；以及，解决有关在食物网和营养网络中模拟生物复杂性所使用的数据质量问题。社会科学家和生态学家都使用网络模型来研究复杂性。然而，目前基于计算机的研究人类和生物系统复杂性的方法还没有完全发展起来。最重要的是，这些模型缺乏人与生态网络的整合。到目前为止，在复杂的各种领域已经做了很多工作，但各个领域的研究人员很少有联系，每个领域都形成了一所“隐形学院”。最近，社会科学家和生态学家已经认识到他们的并行努力，并开始合作。这次研讨会的短期产品将包括与会者的出版物，但从长远来看，更重要的意义将来自不同背景的科学家之间加强合作。这次研讨会将有助于促进这种合作，并有可能大大有助于更好地了解生物复杂性研究中的各种问题。这项孵化活动是作为2000财年生物复杂性特别竞赛的一部分得到资助的。

This workshop will bring together a multidisciplinary collection of mathematicians, statisticians, computer scientists, biological scientists, and social scientists for the purpose of developing models of complex networks in both human and biological systems, with special emphasis given to integration of social and ecological networks. The specific objectives used to structure the workshop are: (1) establishing common ground; (2) modeling of complex systems; (3) interfacing and extension; (4) visualization and exploration; and (5) data quality issues. Thirty experts in the various disciplines have been invited to participate in a three-day workshop at the Duke Marine Laboratory in March of 2001. Prior to the meeting, in order to establish common ground, we will distribute to each participant a statement of purpose, key readings, and a lexicon of analogous terms used in the various disciplines. The workshop will commence with a full day of focused presentations, a second day devoted to breakout groups focusing on the last four objectives, and a final day where breakout group summaries and recommendations will be synthesized using rapporteurs. The attendees will: identify the common issues of complexity across disciplines, the limitations to cross fertilizations of ideas, and ways to overcome these limitations; explore the appropriateness of various mathematical and statistical network models and analyses developed by mathematicians, statisticians, and social and biological scientists applicable to the study of complex biological systems; explore the inclusion of human system dynamics, both of a trophic and non-trophic nature, into models of complex biological systems; develop and improve computer based tools for the exploratory visual analysis of complex biological systems; and, address issues concerning the quality of data used in modeling biocomplexity in food webs and trophic networks. Both social scientists and ecologists use network models to study complexity. However, current computer-based methods of the study of complexity in human and biological systems are not fully developed. Most significantly, these models lack integration of human and ecological networks. Until now, there has been much work done on a variety of fields in complexity, but there has been little contact among researchers in the various fields, each field forming an "invisible college." Recently, social scientists and ecologists have recognized their parallel efforts and have begun collaboration. Short-term products of this workshop will include publications from the attendees, but the greater significance will come in the long-term with increased collaboration among scientists from different backgrounds. This workshop will aid in promoting such collaboration and has the potential to contribute significantly to a better understanding of various problems in the study of biocomplexity. This incubation activity was funded as part of the FY2000 Biocomplexity Special Competition.