Data Science Core
Data Science Core
批准号:
10574562
负责人:
Xintao Wu
金额:
$18.32万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-04-01 至 2026-02-28
关键词:
AccelerationAlgorithmsApplications GrantsArkansasArtificial IntelligenceBig DataBioenergeticsBioinformaticsBiological ModelsBiomedical ResearchCenters of Research ExcellenceChargeCloud ComputingCollaborationsCommunitiesConsultationsCreativenessDataData AnalysesData AnalyticsData Management ResourcesData ScienceData Science CoreData ScientistData SetData Storage and RetrievalDatabasesDisciplineDiseaseEducationEducational workshopEnergy MetabolismExperimental DesignsExplosionFacultyFosteringFundingFutureGenomicsGoalsGrowthHigh Performance ComputingHuman ResourcesHybridsImageInvestmentsMetabolicMetabolismMethodsModelingModernizationPediatric ResearchPerformancePhasePreparationProteomicsResearchResearch MethodologyResearch PersonnelResearch Project GrantsRoleScienceServicesSpectrum AnalysisStructureSystems BiologyTechniquesTechnologyTrainingUnited States National Institutes of HealthUniversitiesVisionWorkbiomedical informaticscohortcomputational platformcomputing resourcesdata managementdesigninnovationinterdisciplinary collaborationinterestlarge datasetsmembermetabolic phenotypemitochondrial metabolismneural networknovelprofessorprogramsrecruitskillssynergismsystems research
中文摘要
项目摘要-数据科学核心
近年来,数据科学领域在生物医学科学中呈爆炸式增长,部分原因是
通过人工智能方法,使用经过训练的神经网络来分析大型数据集。现有高-
阿肯色州大学将整合和扩展性能计算资源,
拟议中的阿肯色州综合代谢研究中心(AIMRC)的数据科学核心。数据
科学核心将是一个独特的核心,以满足AIMRC的研究需求,是一个必不可少的
这是COBRE项目负责人提出的研究项目的组成部分。一个由四名数据科学家组成的团队将
这些专家拥有广泛的专业知识,为AIMRC提供数据科学支持。数据科学核心将
与AIMRC生物能量学和成像与光谱学核心密切合作,
基于智能的方法来阐明大型成像,生物能量学,基因组学和
蛋白质组学数据集,最终可用于预测和了解代谢表型及其
疾病中的作用。这种协调的核心结构将允许数据分析集成到跨学科的
该框架能够支持有效代谢所需的全部技术和专业知识,
系统研究。数据科学核心和COBRE中心项目负责人之间的密切互动将
还将带来新的研究创新,这将有利于未来的COBRE研究人员以及更广泛的
校园研究社区核心主任将提供数据科学方面的机会和培训,
AIMRC成员,校园和研究人员在阿肯色州。
英文摘要
Project Summary – Data Science Core
The field of data science has exploded in growth within the biomedical sciences in recent years, driven in part
by artificial intelligence approaches using trained neural networks to analyze large data sets. Existing high-
performance computing resources will be consolidated and expanded at the University of Arkansas to establish
a Data Science Core in the proposed Arkansas Integrative Metabolic Research Center (AIMRC). The Data
Science Core will be a unique core created to meet the research needs of the AIMRC and is an essential
component of the research projects proposed by the COBRE project leaders. A team of four data scientists will
be assembled that have broad expertise to provide data science support for AIMRC. The Data Science Core will
coordinate closely with the AIMRC Bioenergetics and Imaging and Spectroscopy Cores to provide artificial
intelligence-based approaches to elucidate relationships between large imaging, bioenergetics, genomic, and
proteomic data sets, which can ultimately be used to predict and understand metabolic phenotypes and their
role in disease. This coordinated core structure will allow data analytics to be integrated into a cross-disciplinary
framework capable of supporting the entire range of technologies and expertise needed for an effective metabolic
systems research. Close interaction between the Data Science Core and COBRE Center project leaders will
also lead to new innovations in research that will benefit future COBRE investigators as well as the broader
campus research community. Opportunities and training in data science will be provided by the core directors to
AIMRC members, the campus and researchers in Arkansas.
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