Modeling and Simulation of Complex Systems

复杂系统的建模与仿真

• 批准号: 0903787
• 负责人: Sandra Harpole
• 金额: $ 2000万
• 依托单位: Mississippi State University
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0903787&HistoricalAwards=false
• 关键词: Modeling; Simulation; Complex; Systems

Proposal Title: Modeling and Simulation of Complex Systems Institution: Mississippi State UniversityGoals: The major focus of this RII Track-1 project is the merging of biology and chemistry through computational investigation and simulation. The project seeks to do this by 1) linking molecular modeling to macroscale physiology, 2) deploying high-level data mining, and 3) modeling nanoscale structures to understand binding interactions and catalytic processes. The biological simulation efforts are broad, ranging from whole body physiological modeling methods to specific modeling of problems such as particle deposition in upper lung airways. The computational biology effort centers on developing new methods for integrating functional genomics information from high-throughput sources such as microarrays and next generation gene sequencers. The computational chemistry effort is geared towards theoretical characterization of nanomaterials for sensor technologies, and the development of models to predict the effects of nanomaterials on health and the environment. This project seeks to capitalize on previous Research Infrastructure Improvement (RII) investments by strengthening the quality of research in each of the research foci, increasing the statewide collaborations in each area, and establishing meaningful collaborations in the emerging research areas. Underpinning all of the research components are the establishment of needed cyberinfrastructure and the integration of education at all levels.Intellectual MeritThis project will integrate research in modeling and simulation of complex systems to advance the understanding of complex biological systems and networks, and the understanding of the effects of nanoparticles on specific functions of the biological systems/networks. As such the projects focus on problems of practical significance (simulation of inhalation exposure to nanoparticles and the resulting deleterious effects on respiratory and cardiovascular function); propose new models for learning biological networks that combine Bayesian learning and numerical optimization and can lead to novel approaches for explaining model response; and explore new theoretical characterization of nanoscale materials with particular emphasis on using quantum mechanics (QM) to predict changes in structure and electronic properties of nanomaterials for sensors, and use Quantitative Structure-Property Relationship (QSPR) and Quantitative Structure-Activity Relationship (QSAR) models to predict nanotoxicity. Broader ImpactsThis project will impact the diversity of the computational sciences community of faculty and students in Mississippi and contribute to the development of a skilled workforce that will assist Mississippi in transitioning to a knowledge-based economy. It will also contribute to the broader computational sciences community by investigating specific complex biological systems and processes with significant societal impact.

提案标题：复杂系统的建模和仿真 机构：密西西比州立大学 目标：RII Track-1 项目的主要重点是通过计算研究和仿真将生物学和化学结合起来。该项目旨在通过 1) 将分子建模与宏观生理学联系起来，2) 部署高级数据挖掘，以及 3) 建模纳米级结构以了解结合相互作用和催化过程来实现这一目标。生物模拟工作范围广泛，从全身生理建模方法到上肺气道颗粒沉积等问题的特定建模。计算生物学工作的重点是开发新方法来整合来自高通量来源（例如微阵列和下一代基因测序仪）的功能基因组学信息。计算化学工作致力于传感器技术纳米材料的理论表征，以及开发模型来预测纳米材料对健康和环境的影响。 该项目旨在通过加强每个研究重点的研究质量、增加每个领域的全州范围内的合作以及在新兴研究领域建立有意义的合作来利用之前的研究基础设施改善（RII）投资。所有研究组成部分的基础是建立所需的网络基础设施和整合各级教育。智力优势该项目将整合复杂系统建模和模拟的研究，以促进对复杂生物系统和网络的理解，以及纳米颗粒对生物系统/网络特定功能的影响的理解。因此，这些项目侧重于具有实际意义的问题（模拟吸入纳米颗粒以及由此对呼吸和心血管功能产生的有害影响）；提出结合贝叶斯学习和数值优化的学习生物网络的新模型，并可以产生解释模型响应的新方法；探索纳米材料的新理论表征，特别强调利用量子力学（QM）来预测传感器用纳米材料的结构和电子性质的变化，并利用定量结构-性质关系（QSPR）和定量结构-活性关系（QSAR）模型来预测纳米毒性。更广泛的影响该项目将影响密西西比州教师和学生计算科学社区的多样性，并有助于培养熟练的劳动力，从而帮助密西西比州向知识经济转型。它还将通过研究具有重大社会影响的特定复杂生物系统和过程，为更广泛的计算科学界做出贡献。