Confidential computing for population-scale genome-wide association studies with SECRET-GWAS

Reference. Confidential computing for population-scale genome-wide association studies with SECRET-GWAS

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Cite as @rosenblum-2025-confidential (helia, typst) · \cite{rosenblum-2025-confidential} (LaTeX)

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@article{rosenblum-2025-confidential, title={Confidential computing for population-scale genome-wide association studies with SECRET-GWAS}, volume={5}, ISSN={2662-8457}, url={http://dx.doi.org/10.1038/s43588-025-00856-z}, DOI={10.1038/s43588-025-00856-z}, number={9}, journal={Nature Computational Science}, publisher={Springer Science and Business Media LLC}, author={Rosenblum, Jonah and Dong, Juechu and Narayanasamy, Satish}, year={2025}, month=Sept, pages={825–835} }

hayagriva YAML (typst)

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rosenblum-2025-confidential:
  type: article
  title: Confidential computing for population-scale genome-wide association studies with SECRET-GWAS
  author:
  - Rosenblum, Jonah
  - Dong, Juechu
  - Narayanasamy, Satish
  date: 2025-09
  page-range: 825-835
  serial-number:
    doi: 10.1038/s43588-025-00856-z
  parent:
    type: periodical
    title: Nature Computational Science
    publisher: Springer Science, Business Media LLC
    issue: 9
    volume: 5

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Toleo: Scaling Freshness to Tera-scale Memory Using CXL and PIM dong-2024-toleoASPLOS · 2024

DOI · arXiv

External (48)

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