MRI: Acquisition of an Advanced Computational Infrastructure for Modeling Biological Systems

提案编号：CNS 08- 21625 PI：Clark，Terry W. Kieweg，Sarah L.;放大图片作者：Kuczera，Krzysztof; Lushington，Gerry H. Peterson，A. Townsend机构：堪萨斯大学 Lawrence，KS 66045- 7563标题： MRI/采集：获取生物系统建模的先进计算基础设施项目建议：该项目获得一个并行集群，供科学家对生物系统进行建模，目的是-部署集群并将其与现有的高容量存储设施集成，用于项目，-通过跨学科项目的研究人员小组利用设备，以及-提高集体计算专业知识。集群将被管理，以根据需要向参与该项目的研究人员提供最少的资源，并向社区分配额外的资源，以促进新用户和教育计划的计算增长。该资源使计算生物科学的关键领域取得质的进步。物种生态位建模和DNA的上下文相关进化是通过在宏观和微观水平上扩展对生物体对环境因子的响应的理解来进行环境资源下游管理的基础。其他工作旨在设计用于防治艾滋病流行病的微生物递送剂。分子研究推进了精确建模蛋白质和DNS分子相互作用的现象学和微观性质的方法，其他工作包括开发小分子反应性的高通量预测模型。该项目增加了学生获得并行计算经验的机会，作为课程工作的一部分，增强了研究生的研究机会，支持初级教师的职业发展，并在大学和周边地区建立更广泛的高性能并行计算基础的潜力。一名教师协调员专门负责协助从代表性不足的群体中招聘和留住学生。

Proposal #: CNS 08-21625PI(s): Clark, Terry W. Kieweg, Sarah L.; Kuczera, Krzysztof; Lushington, Gerry H.; Peterson, A. TownsendInstitution: University of Kansas Lawrence, KS 66045-7563Title: MRI/Acq.: Acq. of an Advanced Computational Infrastructure for Modeling Biological SystemsProject Proposed:This project, acquiring a parallel cluster for scientist to conduct modeling on biological systems, aims to- Deploy the cluster and integrate it with an existing high-capacity storage facility for projects, - Leverage the equipment through the group of investigators towards interdisciplinary projects, and- Advance collective computing expertise.The cluster will be managed to provide a minimal set of resources on demand to investigators participating on the proposal with additional resources allocated to the community for promoting computational growth for new users and educational programs. The resource enables qualitative advancements in critical areas in the computational biosciences. Species niche modeling and context-dependent evolution of DNA is fundamental to downstream management of environmental resources through broadening understanding of organism response to environmental factors at macroscopic and microscopic levels. Other work aims to engineer microbial delivery agents for use in combating the AIDS epidemic. Molecular studies advance methodologies for accurately modeling phenomenological and microscopic properties of molecular interactions of protein and DNS, with other work including development of high throughput predictive models for small molecule reactivity.Broader Impacts: This project increases opportunities for students to gain experience in parallel computing as part of course work, enhances research opportunities for graduate students, supports the career development of junior faculty, and establishes a potential for a broader high performance parallel computing base within the university and surrounding area. A faculty coordinator is specifically assigned to assist in recruitment and retention of students from underrepresented groups.