Population Variability and Distributions from Absorbing State Dynamics

自组织发生在许多复杂的生命和非生命系统中。理解这些系统中自组织的基本原理，区分生命系统中与非生命系统共有的现象和只有生命系统才有的现象，是一个巨大的挑战。在这个项目中，PI将比较颗粒和软物质系统中的自组织与酵母细胞群中的自组织。这两个系统似乎有着共同的自组织原理，PI将通过与颗粒材料中存在的自组织详细知识进行比较，揭示酵母自组织的基本原理。该计划将让学生参与计算机模拟，并培训他们了解动力系统理论及其各种应用。特别是，该计划将结合实验，计算和理论来研究种群动力学。在实验方面，该计划集中在三个重要方面：首先，PI将测量种群对基因组重新布线的反应。基因组重新布线是一种扰动，暴露了复杂的细胞动力学，超出了在更标准的扰动下观察到的特定快速松弛反应。第二，PI将在受控条件下以高时间分辨率测量许多细胞代的动态，涵盖表征基因相互作用和其他细胞内过程以及群体过程（如适应）的宽动态范围。第三，PI将研究人口与环境之间的动态耦合。他们的计算工作将集中在构建基于细胞随机组织的种群动力学的独特框架，将细胞内复杂动力学与种群过程联系起来。

Self-organization occurs in many complex living and non-living systems. It is a great challenge to understand the basic principles of self-organization in these systems and to distinguish phenomena in living systems that is shared with non-living systems from phenomena that is generic only to living systems. The PIs in this project will compare self-organization in granular and soft matter systems to self-organization in a yeast cell population. Both systems seem to share common principles of self-organization and the PIs will uncover the basic principles of self-organization of yeast by comparing to the detailed knowledge that exists of self-organization in granular materials. The PIs will engage students to participate in computer simulations and train them in dynamical systems theory and its diverse applications.In particular the PIs will study population dynamics combining experiments, computations and theory. On the experimental side, the program is focused on three important aspects: First, the PIs will measure the response of populations to genome rewiring. Genome-rewiring is a perturbation exposing the complex cellular dynamics beyond the specific fast relaxing responses observed under more standard perturbations. Second, the PIs will measure the dynamics under controlled conditions, at high temporal resolution over many cell generations covering the wide dynamic range characterizing gene interactions and other intracellular processes as well as population processes such as adaptation. Third, the PIs will study the dynamic coupling between the population and the environment. Their computational efforts will concentrate on constructing a unique framework for population dynamics based on cellular random organization, connecting the intracellular complex dynamics with population processes.