High Performance Computer for Biomedical Research

用于生物医学研究的高性能计算机

• 批准号: 10415619
• 负责人: Carol A Parish
• 金额: $ 24.99万
• 依托单位: UNIVERSITY OF RICHMOND
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10415619
• 关键词: Affinity; Amyloid beta-Protein Precursor; Behavioral Model; Binding; Biology; Biomedical Research; Carbon; DNA-Directed DNA Polymerase; Drug Delivery Systems; Evolution; Faculty; Funding; Genomics; Health; Human; Image; Institution; Malignant Neoplasms; Mediating; Minerals; Minor; Motor; Nature; Neurosciences; Osteoporosis; Performance; Population; Potassium Channel; Protein Engineering; Proteins; RNA Helicase; Research; Resources; Rewards; Rodent; Structure-Activity Relationship; Students; Systems Development; Tick-Borne Diseases; Time; Training; Translations; United States National Institutes of Health; Universities; Work; base; bone; computational chemistry; computing resources; demographics; high end computer; innovation; laptop; molecular dynamics; nanodot; novel; prevent; programs; supercomputer; tumor progression; undergraduate student; voltage

Project Summary The University of Richmond (UR) is a research-intensive predominantly undergraduate institution (PUI). Our faculty are committed to producing cutting-edge research while also providing professionally meaningful training to our students. Unusual for a PUI, we currently have five NIH-funded PIs (major users) working on a variety of important biomedical projects. These faculty, together with six other faculty (minor users), have leading research programs in neuroscience, genomics, cancer, osteoporosis, quantitative biology and computational chemistry. These programs depend on access to compute cycles, but UR does not currently have an institutionally supported compute resource. Our faculty have been supporting their work using laptops, desktops, borrowing compute cycles from collaborators, using cloud resources and supercomputer centers. As the importance of computing in biomedical research increases, this deficiency is limiting the size and nature of the projects that our faculty can envision and complete, preventing them from achieving their full potential or engaging students as deeply as they could. The addition of a nine-node, high-performance, shared computational resource containing CPUs, GPUs, large amounts of RAM, and RAID-protected storage will enable our faculty and their students to perform state-of-the-art computations. This hardware will be used to perform genomic analysis of tick-borne diseases, and to study the evolution of human demographics and populations. The hardware will also support image and/or video analysis related to an RNA helicase important in translation, a carbon nanodot drug delivery system, and the development of a rodent based behavioral model of effort-based rewards. The resource will also be used for molecular dynamics simulations that will unravel the structure-function relationship in voltage and non-voltage gated potassium ion channels, RNA helicase, proteins that mediate cancer progression, the binding affinity of carbon nanodots with mineralized bones, and amyloid precursor protein with a motor protein, and the design of a novel DNA polymerase. Access to the requested resource will allow our faculty and students to spend less time waiting for numerical results and more time formulating important new questions and generating accurate answers. The innovative research will have a direct impact on human health.

项目摘要 里士满大学（UR）是一所研究密集型的大学，主要是本科生。 机构（PUI）。我们的教师致力于生产尖端的研究，同时也 为我们的学生提供专业有意义的培训。对于PUI来说不寻常的是，我们目前 有五个NIH资助的PI（主要用户）从事各种重要的生物医学项目。 这些教师，连同其他六个教师（小用户），有领先的研究计划， 神经科学、基因组学、癌症、骨质疏松症、定量生物学和计算化学。 这些程序依赖于对计算周期的访问，但UR目前没有 机构支持计算机资源。我们的教师一直在支持他们的工作， 笔记本电脑、台式机、借用协作者的计算周期、使用云资源， 超级计算机中心随着计算在生物医学研究中的重要性增加， 不足之处是限制了我们的教师可以设想的项目的规模和性质， 完成，阻止他们充分发挥潜力或吸引学生深入， 他们能.增加一个九节点、高性能、共享计算资源 包含CPU、GPU、大量RAM和受RAID保护的存储， 教师和他们的学生进行国家的最先进的计算。这些硬件将用于 进行蜱传疾病的基因组分析，并研究人类的进化 人口和人口。硬件还将支持图像和/或视频分析 涉及在翻译中重要的RNA解旋酶、碳纳米点药物递送系统，以及 基于努力奖励的啮齿动物行为模型的发展。该资源将 也可用于分子动力学模拟，将解开结构功能 电压和非电压门控钾离子通道、RNA解旋酶、蛋白质之间的关系 介导癌症进展，碳纳米点与矿化骨的结合亲和力， 和淀粉样前体蛋白与马达蛋白，以及一种新的DNA聚合酶的设计。 访问请求的资源将允许我们的教师和学生花更少的时间等待 为数值结果和更多的时间制定重要的新问题，并产生 准确的答案。这项创新研究将对人类健康产生直接影响。