Fast and Scalable Private Genotype Imputation Using Machine Learning and Partially Homomorphic Encryption

Fast and Scalable Private Genotype Imputation Using Machine Learning and Partially Homomorphic Encryption

The recent advances in genome sequencing technologies provide unprecedented opportunities to understand the relationship between human genetic variation and diseases. However, genotyping whole genomes from a large cohort of individuals is still cost prohibitive. Imputation methods to predict genotyp...

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Bibliographic Details
Main Authors: Esha Sarkar, Eduardo Chielle, Gamze Gursoy, Oleg Mazonka, Mark Gerstein, Michail Maniatakos
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Genotype imputation
machine learning
privacy-preserving computation
Online Access:https://ieeexplore.ieee.org/document/9466098/

Internet

https://ieeexplore.ieee.org/document/9466098/

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