RUI: Monte Carlo Simulations in Exploring Non-Equilibrium Systems

RUI：探索非平衡系统中的蒙特卡罗模拟

• 批准号: 1248387
• 负责人: Jiajia Dong
• 金额: $ 11.83万
• 依托单位: Bucknell University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-06-05 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1248387&HistoricalAwards=false
• 关键词: RUI; Monte; Carlo; Simulations; Exploring

TECHNICAL SUMMARYThis award made on an RUI proposal supports research and education aimed at integrating fundamental concepts in non-equilibrium statistical mechanics, molecular biology and population dynamics with the practical skills of Monte Carlo simulations. Under the overarching theme of exploring biology-inspired systems with similar underlying physics, the projects are designed to bring students in contact with cutting edge research topics which exhibit originality, interdisciplinary relevance to their knowledge base and opportunities to hone their programming skills in the context of the study of physical systems.The specific projects explore: 1.) Protein synthesis in bacteria. During protein synthesis in bacteria, a chain of amino acids is formed when ribosomes move along the mRNA template, translating genetic information from the sequence to functioning proteins. Due to the degeneracy in the genetic code, however, the same protein can be produced by different mRNA sequences with a range of sequence-dependent rates. This process can be studied using a lattice gas model: The totally asymmetric simple exclusion process. The totally asymmetric simple exclusion process is one of the paradigms in nonequilibrium statistical mechanics; it is well suited to be introduced to undergraduate students as their first exposure to this field. The PI plans to explore over 4000 gene sequences in E. coli and the limits on their protein production rates first through Monte Carlo simulations. Using analytic methods, the PI will investigate these rates by mean field theory. The intellectual merits include but are not limited to: Insights on the existence of non-optimal sequences; effects of quenched randomness on the totally asymmetric simple exclusion process; and guidance to experimentalists on "fine-tuning" mRNA sequence for optimal protein production.2.) Host-parasite dynamics. Contrary to the ubiquitous applications of the predator-prey model, the host-parasite dynamics model is less systematically explored and fundamentally different. In a simple model, parasites conduct a random walk on a square lattice and reproduce only when encountering a host at the same lattice site. The parasite population is not conserved in the system. As the frequency at which they "find" the host controls their population, the spatial and temporal distributions of the parasites are intricately connected to that of the host. The PI plans to study the relation between host and parasites in a methodical manner. Preliminary simulations by one of the PI's students suggest that elucidating a non-trivial phase transition from unstable to steady state parasite population may be possible. The other avenues of study include a comprehensive description on the host-parasite-like interactions and potential applications in epidemics control.The PI intends to establish a quality research program in a primarily undergraduate institution. This award supports eight undergraduate students and creates an ideal backdrop for them to learn a number of subjects, including: cell biology, non-equilibrium statistical physics, formulation of mathematical models, and high performance computation, that are absent from traditional physics curricula.NON-TECHNICAL SUMMARYThis award made on an RUI proposal supports theoretical research and education at the interface of the statistical mechanics of systems that are far from the balance of equilibrium, molecular biology and population dynamics while integrating the practical skills of Monte Carlo computer simulations. Under the overarching theme of exploring biology-inspired systems with similar underlying physics, the projects are designed to bring students in contact with cutting edge research topics which exhibit originality, interdisciplinary relevance to their knowledge base and opportunities to hone their computer programming skills in the context of the study of familiar physical systems.The specific projects use the quantitative tools of statistical physics to explore: a) the protein synthesis process in bacteria, for example E.Coli, through a particle transport model, and b) the host-parasite dynamics, inspired by flea infestation in household pets, using Monte Carlo simulations and analytical approaches. Focused on examples of microscopic and macroscopic systems in biology respectively, both projects share a unifying theme: each involves the study of a complex system of many components and rich features that may be illuminated by applying the tools of statistical physics. In the process, the theory of statistical mechanics for systems far from the balance of equilibrium is advance. Such a theory will have wide applicability from biological systems to materials processing. The former project is expected to provide insights into the existence of non-optimal gene coding sequences in bacteria. The latter is intended to provide a comprehensive description of some host-parasite-like interactions and may have potential applications in epidemics control.The PI intends to establish a quality research program in a primarily undergraduate institution. This award supports eight undergraduate students and creates an ideal backdrop for them to learn a number of subjects, including: cell biology, non-equilibrium statistical physics, formulation of mathematical models, and high performance computation, that are absent from traditional physics curricula.

技术摘要颁发的RUI提案奖支持研究和教育，旨在将非平衡统计力学，分子生物学和种群动态的基本概念与蒙特卡洛模拟的实践技能相结合。在探索具有相似基础物理学的生物学启发的系统的总体主题下，这些项目旨在使学生与尖端研究主题接触，这些研究主题表现出独创性，与知识基础相关的知识基础和机会，以在物理系统研究的背景下培养其编程技能。在细菌中的蛋白质合成过程中，当核糖体沿mRNA模板移动时，形成了一系列氨基酸，将遗传信息从序列转化为功能蛋白。然而，由于遗传密码的变性，可以由具有一系列序列依赖性速率的不同mRNA序列产生相同的蛋白质。可以使用晶格气模型研究此过程：完全不对称的简单排除过程。 完全不对称的简单排除过程是非平衡统计力学中的范式之一。它非常适合将本科生介绍为他们的首次接触该领域。 PI计划首先通过Monte Carlo模拟探索大肠杆菌中超过4000个基因序列及其蛋白质生产率的限制。使用分析方法，PI将通过平均场理论研究这些速率。智力优点包括但不限于：关于非最佳序列存在的见解；淬火随机性对完全不对称的简单排除过程的影响；以及实验者对最佳蛋白质产生的“微调” mRNA序列的指导。2。）宿主 - 寄生虫动力学。 与捕食者 - 纯模型的无处不在应用相反，宿主 - 寄生虫动力学模型的系统探索较少，并且从根本上讲不同。在一个简单的型号中，寄生虫在平方晶格上进行随机步行，并在同一晶格位点遇到宿主时仅繁殖。寄生虫种群在系统中没有保守。随着他们“找到”宿主控制人群的频率，寄生虫的空间和时间分布与宿主的频率分布无关。 PI计划以有条不紊的方式研究宿主与寄生虫之间的关系。 PI的一名学生的初步模拟表明，可以阐明从不稳定到稳态寄生虫种群的非平凡相过渡。研究的其他途径包括有关宿主 - 寄生虫样相互作用的全面描述以及在流行病控制中的潜在应用。PI打算在主要是本科机构中建立优质的研究计划。 该奖项支持八名本科生，并为他们创造理想的背景，以学习许多科目，包括：细胞生物学，非平衡统计物理学，数学模型的表述和高性能计算，而传统物理学课程中则没有这些奖项。平衡，分子生物学和种群动态，同时整合了蒙特卡洛计算机模拟的实际技能。在探索具有相似基础物理学的生物学启发的系统的总体主题下，这些项目旨在使学生与尖端的研究主题接触，这些研究主题表现出独创性，与知识基础的跨学科相关性，并在其知识基础和机会中培养其计算机编程技能，以在熟悉的物理系统的研究中使用熟悉的项目来探索统计的物理学工具：粒子传输模型和b）使用蒙特卡洛模拟和分析方法，受家庭宠物的跳蚤侵染的启发，宿主 - 寄生虫动力学。两个项目分别着重于生物学中的显微镜和宏观系统的示例，共享一个统一的主题：每个项目都涉及对许多组件和丰富特征的复杂系统的研究，这些系统可以通过应用统计物理学工具来阐明。在此过程中，系统的统计力学理论远非平衡的平衡是进步的。从生物系统到材料处理，这种理论将具有广泛的适用性。预计前一个项目将提供有关细菌中非最佳基因编码序列存在的见解。后者旨在提供一些类似宿主 - 寄生虫的互动的全面描述，并可能在流行病控制中具有潜在的应用。 该奖项支持八名本科生，并为他们创造了许多学科的理想背景，包括：细胞生物学，非平衡统计物理学，数学模型的表述和高性能计算，而传统物理学课程则缺乏。