Data Science Facility Core

数据科学设施核心

基本信息

  • 批准号:
    10617826
  • 负责人:
  • 金额:
    $ 31.98万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-05-01 至 2025-03-31
  • 项目状态:
    未结题

项目摘要

DATA SCIENCE FACILITY CORE (DSFC) ABSTRACT The proposed Texas A&M Center for Environmental Health Research (TiCER) is focused on “Enhancing Public Health by Identifying, Understanding and Reducing Adverse Environmental Health Risks.” The Data Science Facility Core (DSFC) will provide key enabling services in data collection, storage, analysis, and integration to assist members of the Center to fulfill this mission. Key data science challenges that the DSFC will address include the high dimensionality of novel biological and chemical data streams, the mixture of structured and unstructured data at the level of local communities, and the need to translate data into actionable knowledge for environmental health decision-making. The DSFC will support these needs by leveraging data science expertise and resources across Texas A&M. There is a nearly ubiquitous need for such services across the Center’s four research themes: Stressors to Responses; Environment and Metabolism; Individuals to Populations; and Community, Regulation, and Policy. Thus, the DSFC will serve as a key facilitator of interactions across the entire Center. The DSFC’s overarching goals are to provide novel and state-of-the-art data science services to support and integrate the Center’s scientific and outreach activities. This goal will be accomplished by providing services in several specialized and complex areas of data science—computational toxicology, bioinformatics, and statistics/biostatistics—as well as providing a central data repository for Center investigators. In the computational toxicology area, the focus will be on characterizing and predicting chemical toxicity through both mechanistic and data-driven mathematical/statistical models that integrate multiple diverse data sets. In the bioinformatics area, emphasis will be placed on guiding investigators in navigating the many available commercial and open-source analysis options, developing customized analytical workflows, and addressing any needs for new methods development. Statistics and biostatistics support will be provided both for basic services such as study design and routine analysis, as well as for custom needs for collecting, processing, integrating, and drawing conclusions from diverse data sets. Integration of data will be facilitated through a common data repository, the design and development of which will be closely coordinated with the rest of the Center, and which be indexed for searching and data mining. The DSFC will provide these services through a flexible combination of direct support from Core personnel and vouchers to allocate as needed ($138,000/year from NIEHS and $20,000/year from Texas A&M commitment). The DSFC will work closely with the Administrative Core to encourage investigators’ use of the DSFC and access and track the Core’s operation and funding allocations. The leaders of the DSFC have an established track record of collaborative, interdisciplinary, and translational research, and are well positioned to support the data science needs across the Center to address public health risks from environmental exposures in Texas and beyond.
数据科学设施核心(dsfc)摘要

项目成果

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Weihsueh A Chiu其他文献

Weihsueh A Chiu的其他文献

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{{ truncateString('Weihsueh A Chiu', 18)}}的其他基金

Risk and Geospatial Sciences Core
风险与地理空间科学核心
  • 批准号:
    10707485
  • 财政年份:
    2022
  • 资助金额:
    $ 31.98万
  • 项目类别:
Risk and Geospatial Sciences Core
风险与地理空间科学核心
  • 批准号:
    10349760
  • 财政年份:
    2022
  • 资助金额:
    $ 31.98万
  • 项目类别:
Data Science Facility Core
数据科学设施核心
  • 批准号:
    10400883
  • 财政年份:
    2019
  • 资助金额:
    $ 31.98万
  • 项目类别:
Data Science Facility Core
数据科学设施核心
  • 批准号:
    9918405
  • 财政年份:
  • 资助金额:
    $ 31.98万
  • 项目类别:
Decision Science Core
决策科学核心
  • 批准号:
    9903365
  • 财政年份:
  • 资助金额:
    $ 31.98万
  • 项目类别:
Decision Science Core
决策科学核心
  • 批准号:
    9257877
  • 财政年份:
  • 资助金额:
    $ 31.98万
  • 项目类别:

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