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Project Summary Genomics data sharing is of paramount importance to accelerate biomedical research and facilitate higher power in analysis. However, privacy and security concerns can hinder large scale data sharing across institutions and nations. Human genomics data contain unique information that is identifiable, and inappropriate sharing would put individual’s privacy at risk and potentially lead to leakage of sensitive personal information. Also, patients’ consents are crucial for genomic studies, and therefore novel sociotechnical methods are also essential for researchers to consider while conducting human genomic research. We intend to close the technology gap and bring advanced enabling technology to support human genomic research. We have organized a series of competitions to evaluate state-of-the-art privacy and security models with real-world motivated analysis tasks with companion workshops. As an emerging interdisciplinary community, we are pushing the frontiers of genomic privacy and security research. Motivated by our previous successes, we are proposing to continue the effort. We plan to engage and support researchers from nationally underrepresented groups to participate in our competitions and attend the workshops.
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Robust privacy preserving distributed analysis platform for cancer research: addressing data bias and disparities
  • 批准号:
    10642562
  • 项目类别:
  • 资助金额:
    $41.19万
  • 财政年份:
    2023
  • 负责人:
    Xiaoqian Jiang
  • 依托单位:
Harmonizing multiple clinical trials for Alzheimer's disease to investigate differential responses to treatment via federated counterfactual learning
Decentralized differentially-private methods for dynamic data release and analysis
  • 批准号:
    10740597
  • 项目类别:
  • 资助金额:
    $61.37万
  • 财政年份:
    2023
  • 负责人:
    Xiaoqian Jiang
  • 依托单位:
Decentralized differentially-private methods for dynamic data release and analysis
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