Duke Center for Systems Biology

杜克系统生物学中心（DCSB）将支持旨在发现、建模和解释生物网络动力学特性的研究合作。使用高通量技术，生物学家现在可以确定细胞的许多分子组分的几乎完整的列表，测量这些组分的相对浓度，并确定哪些组分相互作用。然而，一个主要的挑战是了解这种复杂的相互作用网络如何产生活细胞和高等生物体特有的协调过程。DCSB将通过涉及广泛的实验技术，分析工具和建模方法的跨学科项目来应对这一挑战。每个项目都将是生物学家和理论家之间的合作，他们在数学，计算机科学，统计学或物理学的相关子领域拥有专业知识。DCSB项目将涉及三个广泛的主题：（1）细胞周期控制;（2）发育和分化;（3）人口变化。在前两个，重点将是由基因调控网络的动力学;在第三，网络结构的进化动力学。已经确定了六个初步项目的支持，涵盖网络参与各种模型系统：酵母细胞周期，哺乳动物细胞周期的进入，拟南芥根的发展，海胆胚胎发育，酵母的人口变化，和海胆的人口变化。分析和建模工作将借鉴贝叶斯统计、非线性动力学、计算拓扑和几何以及可视化方面的专业知识。 DCSB将通过休假和奖学金计划以及关于当前系统生物学主题的年度研讨会，汇集优秀的研究人员作为合作者和客座科学家。DCSB教师将系统生物学主题整合到几个现有的研究生教育计划，培养垂直整合的研究团队和接触跨学科的方法来解决生物问题。与DCSB相关的教师还将教授几门新的本科系统生物学课程，并管理一个为生物学学生和数学/计算专业学生设计的证书课程。这些结果将对通过操纵基因调控系统治疗人类疾病以及基础生物学和复杂系统理论产生重大影响。

The Duke Center for Systems Biology (DCSB) will support research collaborations aimed at discovering, modeling, and explaining the dynamical properties of biological networks. Using high throughput techniques, biologists can now determine nearly complete lists of many of the molecular components of cells, measure relative concentrations of these components, and determine which components interact with each other. A major challenge, however, is to understand how this complex network of interactions produces the orchestrated processes characteristic of living cells and higher organisms. DCSB will approach this challenge through interdisciplinary projects involving a wide array of experimental techniques, analysis tools, and modeling methods. Each project will be a collaboration between biologists and theorists with expertise in a relevant subfield of mathematics, computer science, statistics, or physics. DCSB projects will address three broad themes: (1) cell cycle control; (2) development and differentiation; and (3) population variation. In the first two, the emphasis will be on the dynamics determined by gene regulatory networks; in the third, on evolutionary dynamics of network structure. Six initial projects have been identified for support, covering networks involved in various model systems: the yeast cell cycle, mammalian cell cycle entry, Arabidopsis root development, sea urchin embryonic development, population variation in yeast, and population variation in sea urchin. Analysis and modeling efforts will draw from expertise in Bayesian statistics, nonlinear dynamics, computational topology and geometry, and visualization. DCSB will bring together outstanding researchers as collaborators and guest scientists through sabbatical and fellowship programs and through an annual symposium on a current systems biology theme. DCSB faculty will integrate systems biology themes into several existing graduate education programs that foster vertically integrated research teams and exposure to interdisciplinary approaches to biological problems. Faculty associated with DCSB will also teach several new undergraduate systems biology courses and administer a certificate program designed both for biology students and those students in mathematical/computational majors. The results will have substantial implications for treatment of human disease through manipulation of genetic regulatory systems, as well as for fundamental biology and theories of complex systems.