FRG: Collaborative Research: Variational multiscale approaches to biomolecular structure, dynamics and transport

FRG：协作研究：生物分子结构、动力学和运输的变分多尺度方法

• 批准号: 1160352
• 负责人: Guowei Wei
• 金额: $ 31.95万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-15 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1160352&HistoricalAwards=false
• 关键词: FRG; Collaborative; Research; Variational; multiscale

A major feature of biological science in the 21st Century will be its transition from a phenomenological and descriptive discipline to a quantitative and predictive one. Revolutionary opportunities have emerged for mathematically driven advances in biological research. Experimental exploration of self-organizing biomolecular systems, such as HIV viruses, molecular motors and proteins in Alzheimer's disease, has been a dominating driven force in scientific discovery and innovation in the past few decades. However, the emergence of complexity in self-organizing biological systems poses fundamental challenges to their quantitative description because of the excessively high dimensionality. This Focused Research Group (FRG) will provide a platform, led by leading researchers from Michigan State University, University of Wisconsin-Madison and Pennsylvania State University, who will synergistically merge their expertise in theoretical modeling, scientific computing and mathematical analysis, for quantitative descriptions of biomolecular systems. The research addresses grand challenges in the structure, function and dynamics of self-organizing biomolecular systems due to exceptionally massive data sets. These challenges are tackled through the introduction of new variational multiscale models, which reduces the dimensionality and number of degrees of freedom by a macroscopic continuum description of the aquatic/membrane environment, and a microscopic discrete description of biomolecules. Additionally, to further reduce the dimensionality of excessively large biomolecular systems, the investigators introduce a coarse-grained approach based on the density cluster dynamics which extracts stable manifolds in molecular dynamics simulations. This FRG project offers innovative new approaches to the massive data management, dimensionality reduction, computer simulation, theoretical modeling and mathematical analysis of biomolecular systems.This project is a timely effort to promote the quantitative transition of biological science, which will lead to emerging new fields in both mathematical and biological sciences. In particular, the proposed effort will significantly strengthen the leading role that the U.S. researchers can play in mathematical molecular biosciences by aggressively pursuing cutting-edge research and collaboratively training a new generation of mathematicians in this emerging interdisciplinary field. Three annual workshops and international meeting will be held in Michigan State (Year 1), Wisconsin (Year 2) and Penn State (Year 3) to strengthen the collaboration and extend the societal impact.

21世纪生物科学的一个主要特征将是从现象学和描述性学科向定量和预测性学科过渡。在生物研究中，数学驱动的进步出现了革命性的机会。在过去的几十年里，对自组织生物分子系统的实验探索，如艾滋病毒病毒、分子马达和阿尔茨海默病中的蛋白质，一直是科学发现和创新的主要驱动力。然而，自组织生物系统中复杂性的出现给其定量描述带来了根本性的挑战，因为其维度过高。这个重点研究小组(FRG)将提供一个平台，由来自密歇根州立大学、威斯康星大学麦迪逊分校和宾夕法尼亚州立大学的领先研究人员领导，他们将协同融合他们在理论建模、科学计算和数学分析方面的专业知识，用于生物分子系统的定量描述。这项研究解决了由于异常海量的数据集而在自组织生物分子系统的结构、功能和动力学方面的巨大挑战。这些挑战是通过引入新的变分多尺度模型来解决的，该模型通过对水/膜环境的宏观连续描述和对生物分子的微观离散描述来降低维度和自由度数。此外，为了进一步降低超大生物分子系统的维度，研究人员引入了一种基于密度簇动力学的粗粒度方法，该方法在分子动力学模拟中提取稳定的流形。FRG计划为生物分子系统的海量数据管理、降维、计算机模拟、理论建模和数学分析提供了创新的新方法。该计划是促进生物科学的量化转变的及时努力，这将导致数学和生物科学的新领域的出现。特别是，拟议的努力将显著加强美国研究人员在数学分子生物科学中的领先地位，方法是积极开展尖端研究，并合作培训这一新兴跨学科领域的新一代数学家。将在密歇根州(一年级)、威斯康星州(二年级)和宾夕法尼亚州立大学(三年级)举办三次年度讲习班和国际会议，以加强合作并扩大社会影响。