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.

技术总结该奖项是根据RUI的建议颁发的，旨在支持将非平衡统计力学、分子生物学和人口动力学的基本概念与蒙特卡洛模拟的实用技能相结合的研究和教育。在探索具有类似基础物理的生物启发系统的总体主题下，这些项目旨在让学生接触前沿研究课题，这些课题展示了原创性，与他们的知识基础相关的跨学科性，并有机会在物理系统研究的背景下磨练他们的编程技能。具体项目探索：1.细菌中的蛋白质合成。在细菌的蛋白质合成过程中，当核糖体沿着mRNA模板移动时，形成了一条氨基酸链，将序列中的遗传信息翻译成功能蛋白质。然而，由于遗传密码的简并性，相同的蛋白质可以由不同的mRNA序列以一系列序列依赖性速率产生。这个过程可以用格子气模型来研究：完全不对称的简单排斥过程。 完全不对称的简单排斥过程是非平衡统计力学的一个范例，它非常适合作为本科生第一次接触这个领域。PI计划在E.大肠杆菌和限制其蛋白质生产率首先通过蒙特卡罗模拟。使用分析方法，PI将通过平均场理论研究这些速率。其智力价值包括但不限于：对非最佳序列存在的见解;猝灭随机性对完全不对称简单排除过程的影响;以及指导实验人员“微调”mRNA序列以获得最佳蛋白质生产。宿主-寄生虫动力学 与捕食者-被捕食者模型的普遍应用相反，宿主-寄生虫动力学模型的系统性研究较少，并且有根本的不同。在一个简单的模型中，寄生虫在正方形晶格上进行随机行走，只有在同一晶格位置遇到宿主时才能繁殖。寄生虫种群在系统中不保守。由于它们“发现”宿主的频率控制着它们的种群，寄生虫的空间和时间分布与宿主的空间和时间分布错综复杂地联系在一起。PI计划以系统的方式研究宿主和寄生虫之间的关系。PI的学生之一的初步模拟表明，阐明从不稳定到稳定状态的寄生虫种群的非平凡相变是可能的。研究的其他途径包括对宿主-寄生虫样相互作用的全面描述和在流行病控制中的潜在应用。PI打算在主要的本科院校建立一个高质量的研究计划。 该奖项支持八名本科生，并为他们学习多个科目创造了理想的背景，包括：细胞生物学、非平衡统计物理学、数学模型的公式化和高性能计算，这是传统物理课程中所没有的。技术总结这个奖项是根据RUI的一项提案颁发的，该提案支持系统统计力学接口的理论研究和教育，远离平衡，分子生物学和种群动力学的平衡，同时结合蒙特卡罗计算机模拟的实践技能。在探索具有相似基础物理的生物学启发系统的总体主题下，这些项目旨在让学生接触前沿研究课题，这些课题展示了原创性，与他们的知识基础相关的跨学科性，并有机会在熟悉的物理系统研究的背景下磨练他们的计算机编程技能。具体项目使用统计物理学的定量工具来探索：a）通过粒子运输模型，在细菌例如大肠杆菌中的蛋白质合成过程，和B）宿主-寄生虫动力学，由家庭宠物中的跳蚤感染启发，使用Monte Carlo模拟和分析方法。这两个项目分别侧重于生物学中微观和宏观系统的例子，它们都有一个统一的主题：每个项目都涉及对一个复杂系统的研究，该系统具有许多组件和丰富的特征，可以通过应用统计物理学的工具来阐明。在此过程中，提出了远离平衡态系统的统计力学理论。这一理论将具有从生物系统到材料加工的广泛适用性。前一个项目预计将提供对细菌中存在非最佳基因编码序列的见解。后者的目的是提供一个全面的描述，一些主机寄生虫样的相互作用，并可能有潜在的应用在流行病control.The PI打算建立一个高质量的研究计划，主要是本科院校。 该奖项支持八名本科生，并为他们学习一些科目创造了理想的背景，包括：细胞生物学，非平衡统计物理学，数学模型的制定和高性能计算，这些都是传统物理课程所没有的。