Acquisition of a high-throughput compute cluster for biological data analysis
Acquisition of a high-throughput compute cluster for biological data analysis
批准号:
8247532
负责人:
Gregory J Hannon
金额:
$51.98万
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-04-01 至 2013-03-31
关键词:
AddressAreaBase SequenceBasic ScienceBiologicalBiologyBiomedical ResearchCancer BiologyData AnalysesData SetDiseaseEpigenetic ProcessGenomicsHealthHumanHuman GeneticsImageInterdisciplinary StudyLaboratoriesLaboratory ResearchMemoryNeurosciencesNucleic acid sequencingProcessProteomicsResearchResearch InfrastructureResearch InstituteSequence Analysiscluster computingcomputing resourcesdata acquisitionprogramsrelating to nervous systemscientific computing
中文摘要
描述(由申请人提供):冷泉港实验室(CSHL)是一个领先的研究机构,从事广泛的基础科学研究,重点是基本的生物医学问题。其中包括癌症生物学、神经科学、人类遗传学、基因组学和表观遗传学各个方面的领先项目。CSHL最近还开始了一项新的定量生物学多学科研究计划,以认识到需要整合来自核酸序列分析和神经成像等不同领域的大型数据集。所有这些研究领域都正在被大型生物数据集所改变,这些数据集是由于最近数据采集率的急剧增加,包括核酸测序、成像和蛋白质组学。此外,所有迹象都表明,在今后几年及以后,数据采集的速度将继续呈指数级增长。分析这些大型数据集,现在几乎所有生物医学研究领域的基本组成部分都依赖于大规模的计算资源。所要求的54节点科学计算集群对于CSHL利用这些大型数据集并使用它们来了解影响健康和疾病的基本过程至关重要。具体来说,CSHL研究人员进行的许多计算分析都有很大的内存需求,但CSHL目前的基础设施没有足够数量的高内存节点来及时执行这些关键分析,或者在某些情况下根本没有执行这些分析。所要求的集群将是满足这一需要的总体计划中专门用于人类生物医学研究的一个组成部分。
英文摘要
DESCRIPTION (provided by applicant): Cold Spring Harbor Laboratory (CSHL) is a leading research institute that is engaged in a wide range of basic science studies focused on fundamental biomedical problems. These include leading programs in various aspects of cancer biology, neuroscience, human genetics, genomics and epigenetics. CSHL has also recently started a new multidisciplinary research program in quantitative biology in recognition of the need to integrate large data sets from such diverse areas as nucleic acid sequence analysis and neural imaging. All of these research areas are being transformed by large biological data sets resulting from recent dramatic increases in data acquisition rates including in nucleic acid sequencing, imaging, and proteomics. Further, every indication is that the rate of data acquisition will continue to increase exponentially for the next several years and beyond. Analyzing these large data sets, now a fundamental component of almost all areas of biomedical research is dependent on large-scale computational resources. The requested 54-node scientific compute cluster is essential for CSHL to capitalize on these large data sets and use them to understand basic processes impacting health and disease. Specifically, many of the computational analyses carried out by CSHL researches have significant memory requirements, but the current infrastructure at CSHL does not have adequate numbers of high memory nodes to perform these crucial analyses in a timely fashion, or in some cases, perform them at all. The requested cluster would be one component, dedicated to human biomedical research, in an overall plan to address this need.
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