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In this paper, we analyze and propose a solution for the challenges that come with personalized genomic and, most importantly, of performing queries on sequenced dataset sitting on a cloud server. This work provides scenarios for its application in personalized genomic medicine, and tests homomorphic encryption technique to assist in improving the strength of their privacy at non-prohibitive performance cost. By experimental testing using HElib, we make a first step towards performing practical computation over the relevant portions of the genomic dataset of an individual for a first round of practical diagnosis rules.

Towards Confidentiality-strengthened Personalized Genomic Medicine Embedding Homomorphic Cryptography