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Acquisition of a Scalable Storage Cluster for Data Intensive NIH Research

Acquisition of a Scalable Storage Cluster for Data Intensive NIH Research
为数据密集型 NIH 研究购买可扩展存储集群
批准号:
8640738
负责人:
Thomas Girke
金额:
$59.28万
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-05-01 至 2016-04-30

项目摘要

项目成果

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中文摘要
翻译
描述:加州大学河滨分校的科学家致力于对人类健康至关重要的广泛研究课题,包括神经科学、癌症研究、环境健康、伤口愈合、退行性疾病和传染病。现代大规模基因组学和计算建模方法在这项研究中被常规应用,如下一代测序(NGS)和许多其他高通量技术。由于这些技术输出极大的数据集,高效处理这些“大数据”所需的基于磁盘的数据存储已成为支持NIH资助的生物医学研究的计算需求的主要瓶颈。加州大学河滨分校的研究计算基础设施由位于整合基因组生物学研究所(IIGB)的中央生物信息学设施提供,该研究所拥有另外三个技术核心(基因组学、显微镜和蛋白质组学)。然而,由于需求非常高,生物信息学设施的现有存储系统正在以最大容量运行,影响了其支持数据密集型生物医学研究的能力。这种数据溢出经常导致以省时的方式处理新的研究数据集的延迟,从而减慢了许多项目的发现过程。此应用程序的目标是通过申请资金购买高度可扩展的磁盘存储系统来解决数据存储资源短缺的问题,该系统专门用于为加州大学河滨分校的数据密集型NIH研究提供长期支持。由于我们的磁盘存储需求(目前约为150 TB)每年以近两倍的速度增长,因此需要一个750 GB的存储系统来支持我们当前的存储增长率,以支持未来三年的存储增长。第三年以后的增长资金将由完善的充值系统提供。IIGB的生物信息学设施跨部门运作,致力于为广泛的用户基础服务。因此,为所请求的存储系统提供资金将是一项高成本效益的投资,它将达到加州大学河滨分校NIH调查人员的最大数量。此外,它将使迅速增长的新生物医学研究人员搬到加州大学河滨分校受益,因为它将是加州几十年来第一所新医学院的所在地。结合加州大学河滨分校的不同种族和研究使命,这项投资将使校园内的一系列生物医学研究方向受益,该校园是加利福尼亚州内陆帝国地区的主要经济驱动力。
英文摘要
DESCRIPTION: Scientists at UC Riverside work on a wide spectrum of research topics critical to human health including neuroscience, cancer research, environmental health, wound healing, degenerative and infectious diseases. Modern large-scale genomics and computational modeling approaches are routinely applied in this research, such as next generation sequencing (NGS) and numerous other high- throughput technologies. Because these technologies output extremely large data sets, disk-based data storage required to process these "Big Data" efficiently has become a major bottleneck to support the computational needs of NIH-funded biomedical research. UC Riverside's research compute infrastructure is provided by a central bioinformatics facility located in the Institute for Integrative Genome Biology (IIGB), which houses three additional technology cores (Genomics, Microscopy and Proteomics). However, due to the very high demand, the existing storage systems of the bioinformatics facility are operating at maximum capacity impacting its ability to support data intensive biomedical research. This data overflow results often in delays of processing new research data sets in a time- efficient manner, thus slowing down the discovery process of many projects. The objective of this application is to resolve this shortage of data storage resources by requesting funds for the acquisition of a highly scalable disk storage system dedicated to provide long-term support for data intensive NIH research at UC Riverside. Because our disk storage needs (currently ~150TB) increase by a factor of nearly two every year, a storage system with 750GB is required to support our current storage growth rates for the next three years. Funding for growth well beyond year three will be provided by a well- established recharging system. IIGB's bioinformatics facility operates across departments and is committed to serve a broad user base. Thus, the funding for the requested storage system will be a highly cost-effective investment and it will reach a maximum number of NIH investigators at UC Riverside. Moreover, it will benefit a rapidly growing number of new biomedical researchers moving to UC Riverside, as it will be the site of the first new medical school in California in decades. Combined with UC Riverside's diverse ethnicity and research mission, this investment will benefit a wide array of biomedical research directions at a campus that is a major economic driving force in the Inland Empire region of California.
期刊论文(110)
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会议论文
DOI: 10.1534/g3.117.040691
发表时间: 2017-07-05
期刊: G3 (Bethesda, Md.)
影响因子: --
作者: [Sinha S, Flibotte S, Neira M, Formby S, Plemenitaš A, Cimerman NG, Lenassi M, Gostinčar C, Stajich JE, Nislow C]
通讯作者: Nislow C
Mathematical modeling of chemotaxis guided amoeboid cell swimming
趋化引导变形细胞游泳的数学模型
DOI: 10.1088/1478-3975/abf7d8
发表时间: 2021
期刊: Physical Biology
影响因子: 2
作者: [Wang, Qixuan, Wu, Hao]
通讯作者: Wu, Hao
DOI: 10.1128/microbiolspec.funk-0055-2016
发表时间: 2017-07
期刊: Microbiology spectrum
影响因子: 3.7
作者: [Stajich JE]
通讯作者: Stajich JE
DOI: 10.1371/journal.ppat.1006097
发表时间: 2016-12
期刊: PLoS pathogens
影响因子: 6.7
作者: [Abrahamian M, Ah-Fong AM, Davis C, Andreeva K, Judelson HS]
通讯作者: Judelson HS
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    Chemoinformatics Core
    Chemoinformatics Core
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