Collaborative Proposal: SI2-CHE: ExTASY Extensible Tools for Advanced Sampling and analYsis
合作提案:SI2-CHE:用于高级采样和分析的 ExTASY 可扩展工具
基本信息
- 批准号:1265920
- 负责人:
- 金额:$ 14.8万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-09-01 至 2017-01-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Collaborative Research: SI2-CHEExTASY Extensible Tools for Advanced Sampling and analYsisAn international team consisting of Cecilia Clementi(Rice University), Mauro Maggioni (Duke University) Shantenu Jha (Rutgers University), Glenn Martyna (BM T. J. Watson Laboratory ), Charlie Laughton (University of Nottingham), Ben Leimkuhler ( University of Edinburgh), Iain Bethune (University of Edinburgh) and Panos Parpas(Imperial College) are supported through the SI2-CHE program for the development of ExTASY -- Extensible Toolkit for Advanced Sampling and analYsis, -- a conceptual and software framework that provides a step-change in the sampling of the conformational space of macromolecular systems. Specifically, ExTASY is a lightweight toolkit to enable first-class support for ensemble-based simulations and their seamless integration with dynamic analysis capabilities and ultra-large time step integration methods, whilst being extensible to other community software components via well-designed and standard interfaces. The primary impacts of this project are in the biological sciences. This software advances our understanding of biologically important systems, as it can be used to obtain fast and accurate sampling of the conformational dynamics of stable proteins; a prerequisite for the accurate prediction of thermodynamic parameters and biological functions. It also allows tackling systems like intrinsically disordered proteins, which can be beyond the reach of classical structural biology. Along with the research itself, the PIs are involved with outreach programs to attract high school students to science.
合作研究:SI 2-CHEExTASY用于高级采样和分析的可扩展工具一个由塞西莉亚·克莱门蒂(赖斯大学)、毛罗·马焦尼(杜克大学)、尚特努·杰哈(罗格斯大学)、格伦·马丁纳(BM T.沃森实验室),查理劳顿(诺丁汉大学),本·莱姆库勒(爱丁堡大学)伊恩·白求恩(爱丁堡大学)和Panos Parpas(帝国理工学院)通过SI 2-CHE计划支持开发ExTASY --高级采样和分析的可扩展工具包,--一个概念和软件框架,提供了一个大分子系统的构象空间采样的步骤变化。具体来说,ExTASY是一个轻量级的工具包,可以为基于集成的仿真提供一流的支持,并与动态分析功能和超大时间步长集成方法无缝集成,同时可以通过精心设计的标准接口扩展到其他社区软件组件。 该项目的主要影响是在生物科学。 该软件推进了我们对生物学重要系统的理解,因为它可用于获得稳定蛋白质构象动力学的快速准确采样;这是准确预测热力学参数和生物学功能的先决条件。它还允许处理像内在无序的蛋白质这样的系统,这可能超出了经典结构生物学的范围。沿着研究本身,PI参与了外展计划,以吸引高中生的科学。
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 }}
Mauro Maggioni其他文献
A scalable framework for learning the geometry-dependent solution operators of partial differential equations
用于学习偏微分方程的几何依赖解算符的可扩展框架
- DOI:
10.1038/s43588-024-00732-2 - 发表时间:
2024-12-09 - 期刊:
- 影响因子:18.300
- 作者:
Minglang Yin;Nicolas Charon;Ryan Brody;Lu Lu;Natalia Trayanova;Mauro Maggioni - 通讯作者:
Mauro Maggioni
Critical Exponent of Short Even Filters andBurt-Adelson Biorthogonal Wavelets
- DOI:
10.1007/s006050070024 - 发表时间:
2000-11-15 - 期刊:
- 影响因子:0.800
- 作者:
Mauro Maggioni - 通讯作者:
Mauro Maggioni
DH-482888-001 PREDICTING PERSONALIZED CARDIAC ELECTROPHYSIOLOGY USING DEEP LEARNING
DH-482888-001 使用深度学习预测个性化心脏电生理学
- DOI:
10.1016/j.hrthm.2024.03.261 - 发表时间:
2024-05-01 - 期刊:
- 影响因子:5.700
- 作者:
Minglang Yin;Nicolas Charon;Ryan Brody;Lu Lu;Mauro Maggioni;Natalia A. Trayanova - 通讯作者:
Natalia A. Trayanova
PO-01-212 strongA NOVEL DEEP LEARNING MODEL FOR PATIENT-SPECIFIC COMPUTATIONAL MODELING OF CARDIAC ELECTROPHYSIOLOGY/strong
PO-01-212 一种用于患者特异性心脏电生理计算建模的强大新型深度学习模型
- DOI:
10.1016/j.hrthm.2023.03.530 - 发表时间:
2023-05-01 - 期刊:
- 影响因子:5.700
- 作者:
Minglang Yin;Lu Lu;Mauro Maggioni;Natalia A. Trayanova - 通讯作者:
Natalia A. Trayanova
Mauro Maggioni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 }}
{{ truncateString('Mauro Maggioni', 18)}}的其他基金
BIGDATA: F: Compositional Learning, Maps and Transfer: Statistical and Machine Learning on Collections of Data Sets
BIGDATA:F:组合学习、地图和迁移:数据集集合的统计和机器学习
- 批准号:
1837991 - 财政年份:2019
- 资助金额:
$ 14.8万 - 项目类别:
Standard Grant
ATD: Estimation and Anomaly Detection for high-dimensional Data, Maps and Dynamic Processes
ATD:高维数据、地图和动态过程的估计和异常检测
- 批准号:
1737984 - 财政年份:2017
- 资助金额:
$ 14.8万 - 项目类别:
Standard Grant
ATD: Online Multiscale Algorithms for Geometric Density Estimation in High-Dimensions and Persistent Homology of Data for Improved Threat Detection
ATD:用于高维几何密度估计和数据持久同源性的在线多尺度算法,以改进威胁检测
- 批准号:
1756892 - 财政年份:2016
- 资助金额:
$ 14.8万 - 项目类别:
Standard Grant
Collaborative Proposal: SI2-CHE: ExTASY Extensible Tools for Advanced Sampling and analYsis
合作提案:SI2-CHE:用于高级采样和分析的 ExTASY 可扩展工具
- 批准号:
1708353 - 财政年份:2016
- 资助金额:
$ 14.8万 - 项目类别:
Standard Grant
BIGDATA: Collaborative Research: F: From Data Geometries to Information Networks
BIGDATA:协作研究:F:从数据几何到信息网络
- 批准号:
1708553 - 财政年份:2016
- 资助金额:
$ 14.8万 - 项目类别:
Standard Grant
Statistical Learning for High-Dimensional Stochastic Dynamical Systems
高维随机动力系统的统计学习
- 批准号:
1708602 - 财政年份:2016
- 资助金额:
$ 14.8万 - 项目类别:
Continuing Grant
Structured Dictionary Models and Learning for High Resolution Images
高分辨率图像的结构化字典模型和学习
- 批准号:
1724979 - 财政年份:2016
- 资助金额:
$ 14.8万 - 项目类别:
Standard Grant
BIGDATA: Collaborative Research: F: From Data Geometries to Information Networks
BIGDATA:协作研究:F:从数据几何到信息网络
- 批准号:
1546392 - 财政年份:2016
- 资助金额:
$ 14.8万 - 项目类别:
Standard Grant
Statistical Learning for High-Dimensional Stochastic Dynamical Systems
高维随机动力系统的统计学习
- 批准号:
1522651 - 财政年份:2015
- 资助金额:
$ 14.8万 - 项目类别:
Continuing Grant
Structured Dictionary Models and Learning for High Resolution Images
高分辨率图像的结构化字典模型和学习
- 批准号:
1320655 - 财政年份:2013
- 资助金额:
$ 14.8万 - 项目类别:
Standard Grant
相似海外基金
RESEARCH PROPOSAL What is your project title? Development of additive manufactured polymeric seals for low molecular weight gases
研究计划 您的项目名称是什么?
- 批准号:
2908868 - 财政年份:2024
- 资助金额:
$ 14.8万 - 项目类别:
Studentship
Development of a low-pressure loss air purification device using rotating porous media and a proposal for its use in ventilation systems
使用旋转多孔介质的低压损失空气净化装置的开发及其在通风系统中的使用建议
- 批准号:
24K17404 - 财政年份:2024
- 资助金额:
$ 14.8万 - 项目类别:
Grant-in-Aid for Early-Career Scientists
Conference: Supporting Mentoring in STEM Graduate Education: A Proposal for Virtual Workshops and Supporting Activities
会议:支持 STEM 研究生教育辅导:虚拟研讨会和支持活动的提案
- 批准号:
2413980 - 财政年份:2024
- 资助金额:
$ 14.8万 - 项目类别:
Standard Grant
Proposal Title : NemeSys - Smart Multiphasic Nanoreactors Based On Tailored Foams for Direct H2O2 Synthesis
提案标题:NemeSys - 基于定制泡沫的智能多相纳米反应器,用于直接合成 H2O2
- 批准号:
EP/Y034392/1 - 财政年份:2024
- 资助金额:
$ 14.8万 - 项目类别:
Research Grant
Collaborative Research: Time-Sharing Experiments for the Social Sciences (TESS): Proposal for Renewed Support, 2020-2023
合作研究:社会科学分时实验(TESS):2020-2023 年更新支持提案
- 批准号:
2424057 - 财政年份:2024
- 资助金额:
$ 14.8万 - 项目类别:
Continuing Grant
CRCNS US-German Collaborative Research Proposal: Neural and computational mechanisms of flexible goal-directed decision making
CRCNS 美德合作研究提案:灵活目标导向决策的神经和计算机制
- 批准号:
2309022 - 财政年份:2024
- 资助金额:
$ 14.8万 - 项目类别:
Standard Grant
Travel: Texas Power and Energy Conference (TPEC) 2024 Travel Proposal
旅行:德克萨斯州电力与能源会议 (TPEC) 2024 年旅行提案
- 批准号:
2341300 - 财政年份:2024
- 资助金额:
$ 14.8万 - 项目类别:
Standard Grant
Business and Local Government Data Research Centre Legacy Status Proposal
企业和地方政府数据研究中心遗留状态提案
- 批准号:
ES/Y003411/1 - 财政年份:2024
- 资助金额:
$ 14.8万 - 项目类别:
Research Grant
Lite(House) - A Financially Flexible, Adaptive and Efficient Live/Work Housing Proposal
Lite(House) - 财务灵活、适应性强且高效的生活/工作住房提案
- 批准号:
10071140 - 财政年份:2023
- 资助金额:
$ 14.8万 - 项目类别:
Collaborative R&D
Proposal of effective utilization of polyphenols as functional food ingredients for realization of a healthy longevity society
有效利用多酚作为功能性食品成分以实现健康长寿社会的提案
- 批准号:
23K10889 - 财政年份:2023
- 资助金额:
$ 14.8万 - 项目类别:
Grant-in-Aid for Scientific Research (C)