FRG: Collaborative research: Variational multiscale approaches to biomolecular structure, dynamics and transport.
FRG:合作研究:生物分子结构、动力学和运输的变分多尺度方法。
基本信息
- 批准号:1160360
- 负责人:
- 金额:$ 32.11万
- 依托单位:
- 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 2017-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
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的转变。 革命性的机会已经出现了数学驱动的生物学研究的进展。自组织生物分子系统的实验探索,如艾滋病毒,分子马达和阿尔茨海默氏病中的蛋白质,在过去几十年中一直是科学发现和创新的主导驱动力。 然而,自组织生物系统的复杂性的出现提出了根本性的挑战,因为它们的定量描述过高的维数。 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,他们将协同合并他们在理论建模,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。 该研究解决了由于异常庞大的数据集而导致的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。这些挑战通过引入新的变分多尺度模型来解决,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自由度的维数和数量。此外,为了进一步降低过大的生物分子系统的维数,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。该项目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性的新方法,为促进生物科学的定量化过渡,从而在数学和生物科学中开辟新的领域做出了及时的努力。特别是,拟议的努力将大大加强美国研究人员在数学分子生物科学中的主导作用,积极开展前沿研究,并在这一新兴的跨学科领域合作培训新一代数学家。 三个年度研讨会和国际会议将在密歇根州(第一年),威斯康星州(第二年)和宾夕法尼亚州(第三年)举行,以加强合作和扩大社会影响。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Julie Mitchell其他文献
Malignant Pain in the Opioid Epidemic: An Unregulated Malady (S761)
- DOI:
10.1016/j.jpainsymman.2017.12.415 - 发表时间:
2018-02-01 - 期刊:
- 影响因子:
- 作者:
Julie Mitchell;Leslie Blackhall;Joshua Barclay - 通讯作者:
Joshua Barclay
Profs-in-Commons: Enhancing Student–Faculty Engagement in a Library Learning Commons
Profs-in-Commons:加强图书馆学习共享空间中师生的参与
- DOI:
10.1108/s2055-364120200000026010 - 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
Julie Mitchell;K. Marken - 通讯作者:
K. Marken
Current Challenges
- DOI:
10.12968/bjhc.2016.22.5.247 - 发表时间:
2020-06 - 期刊:
- 影响因子:0
- 作者:
Julie Mitchell - 通讯作者:
Julie Mitchell
An integrated metagenomic, metabolomic and transcriptomic survey of Populus across genotypes and environments
对跨基因型和环境的杨树进行综合宏基因组学、代谢组学和转录组学调查
- DOI:
10.1038/s41597-024-03069-7 - 发表时间:
2024 - 期刊:
- 影响因子:9.8
- 作者:
C. Schadt;Stanton Martin;Alyssa A. Carrell;Allison Fortner;Daniel Hopp;Daniel A Jacobson;D. Klingeman;Brandon Kristy;Jana Phillips;Bryan T. Piatkowski;M. A. Miller;Montana L Smith;S. Patil;Mark Flynn;Shane Canon;Alicia Clum;Christopher J. Mungall;C. Pennacchio;Benjamin Bowen;Katherine Louie;Trent R. Northen;E. Eloe;M. Mayes;W. Muchero;David J Weston;Julie Mitchell;M. Doktycz - 通讯作者:
M. Doktycz
A SPECIFIC HEALTH INFORMATION SYSTEM FOR ADULT CONGENITAL HEART DISEASE INTEGRATED WITH ELECTRONIC HEALTH RECORDS CAN FACILITATE MULTICENTER RESEARCH
- DOI:
10.1016/s0735-1097(12)60787-6 - 发表时间:
2012-03-27 - 期刊:
- 影响因子:
- 作者:
Craig S. Broberg;Ann Gianola;Julie Mitchell;Joseph Weiss;Anne Marie Valente;Michael Earing;Ariane Marelli;Curtis Daniels;Amy Verstappen;Michelle Gurvitz;Paul Khairy;Stephen Cook;Ali Zaidi;Andrew Grant;David Sahn - 通讯作者:
David Sahn
Julie Mitchell的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
相似海外基金
FRG: Collaborative Research: New birational invariants
FRG:协作研究:新的双有理不变量
- 批准号:
2244978 - 财政年份:2023
- 资助金额:
$ 32.11万 - 项目类别:
Continuing Grant
FRG: Collaborative Research: Singularities in Incompressible Flows: Computer Assisted Proofs and Physics-Informed Neural Networks
FRG:协作研究:不可压缩流中的奇异性:计算机辅助证明和物理信息神经网络
- 批准号:
2245017 - 财政年份:2023
- 资助金额:
$ 32.11万 - 项目类别:
Standard Grant
FRG: Collaborative Research: Variationally Stable Neural Networks for Simulation, Learning, and Experimental Design of Complex Physical Systems
FRG:协作研究:用于复杂物理系统仿真、学习和实验设计的变稳定神经网络
- 批准号:
2245111 - 财政年份:2023
- 资助金额:
$ 32.11万 - 项目类别:
Continuing Grant
FRG: Collaborative Research: Variationally Stable Neural Networks for Simulation, Learning, and Experimental Design of Complex Physical Systems
FRG:协作研究:用于复杂物理系统仿真、学习和实验设计的变稳定神经网络
- 批准号:
2245077 - 财政年份:2023
- 资助金额:
$ 32.11万 - 项目类别:
Continuing Grant
FRG: Collaborative Research: Singularities in Incompressible Flows: Computer Assisted Proofs and Physics-Informed Neural Networks
FRG:协作研究:不可压缩流中的奇异性:计算机辅助证明和物理信息神经网络
- 批准号:
2244879 - 财政年份:2023
- 资助金额:
$ 32.11万 - 项目类别:
Standard Grant
FRG: Collaborative Research: New Birational Invariants
FRG:合作研究:新的双理性不变量
- 批准号:
2245171 - 财政年份:2023
- 资助金额:
$ 32.11万 - 项目类别:
Continuing Grant
FRG: Collaborative Research: Singularities in Incompressible Flows: Computer Assisted Proofs and Physics-Informed Neural Networks
FRG:协作研究:不可压缩流中的奇异性:计算机辅助证明和物理信息神经网络
- 批准号:
2403764 - 财政年份:2023
- 资助金额:
$ 32.11万 - 项目类别:
Standard Grant
FRG: Collaborative Research: Singularities in Incompressible Flows: Computer Assisted Proofs and Physics-Informed Neural Networks
FRG:协作研究:不可压缩流中的奇异性:计算机辅助证明和物理信息神经网络
- 批准号:
2245021 - 财政年份:2023
- 资助金额:
$ 32.11万 - 项目类别:
Standard Grant
FRG: Collaborative Research: Variationally Stable Neural Networks for Simulation, Learning, and Experimental Design of Complex Physical Systems
FRG:协作研究:用于复杂物理系统仿真、学习和实验设计的变稳定神经网络
- 批准号:
2245097 - 财政年份:2023
- 资助金额:
$ 32.11万 - 项目类别:
Continuing Grant
FRG: Collaborative Research: Variationally Stable Neural Networks for Simulation, Learning, and Experimental Design of Complex Physical Systems
FRG:协作研究:用于复杂物理系统仿真、学习和实验设计的变稳定神经网络
- 批准号:
2245147 - 财政年份:2023
- 资助金额:
$ 32.11万 - 项目类别:
Continuing Grant