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Genomics and digital phenotyping (electronic medical records, imaging, self-reported surveys, etc) have the potential to transform our understanding, diagnosis and treatment of human diseases. Realizing the potential of these rich data requires aggregating and sharing data across individual centers where the data is currently siloed. However, sharing data raises concerns about individual privacy. This workshop will explore the foundational algorithmic challenges of protecting individual privacy in this bio-medical context.
This workshop has a number of aims:
To explore both the theoretical and implementation challenges of emerging techniques for protecting the privacy of genomic and phenotyping data. This will include frameworks such as differential privacy, homomorphic encryption, and multiparty computation, as well as key tasks such as computing summary statistics and associations.
To bring together theorists and practitioners from industry, biobanks and hospitals in order to understand what are the real, actionable challenges in privacy and sharing of bio-medical data.
To formulate key foundational questions about privacy raised through new and emerging technologies such as genome editing or DNA storage.
To develop connections between privacy questions in -omics and notions of overfitting and fairness

征稿信息

The workshop will be a mix of talks, posters, and breakout sessions centered around the different focus areas in which participants can work together to identify key challenges that need to be overcome, new theory or algorithms that may be needed, and how to delineate problem classes and solution frameworks. Specific initial focus areas include:
Privacy-preserving analysis in GWAS and population genetics
Adaptive data analysis and bioinformatics
Storage, search, and querying in genomic databases

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重要日期
  • 会议日期

    01月10日

    2018

    01月12日

    2018

  • 01月12日 2018

    注册截止日期

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