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PLIGHT: A tool to assess privacy risk by inferring identifying characteristics from sparse, noisy genotypes
View ORCID ProfilePrashant S. Emani, View ORCID ProfileGamze Gürsoy, View ORCID ProfileAndrew Miranker, View ORCID ProfileMark B. Gerstein
doi: https://doi.org/10.1101/2021.07.18.452853
Prashant S. Emani
1Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
2Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
Gamze Gürsoy
1Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
2Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
Andrew Miranker
2Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
Mark B. Gerstein
1Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
2Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
3Department of Computer Science, Yale University, New Haven, CT 06520, USA
4Department of Statistics & Data Science, Yale University, New Haven, CT 06520, USA
Posted July 19, 2021.
PLIGHT: A tool to assess privacy risk by inferring identifying characteristics from sparse, noisy genotypes
Prashant S. Emani, Gamze Gürsoy, Andrew Miranker, Mark B. Gerstein
bioRxiv 2021.07.18.452853; doi: https://doi.org/10.1101/2021.07.18.452853
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