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Secure Scheme for Locating disease-causing genes Based on Multi-Key Homomorphic Encryption

Tsinghua Science and Technology 2022年第2期27卷 333-343页

作者： Tanping Zhou Wenchao Liu Ningbo Li Xiaoyuan Yang Yiliang Han Shangwen Zheng Tanping Zhou is with the College of Cryptography Engineering Engineering University of People’s Armed PoliceXi’an 710086China TCA Laboratory State Key Laboratory of Computer ScienceInstitute of SoftwareChinese Academy of SciencesBeijing 100080China the College of Cryptography Engineering Engineering University of People’s Armed PoliceXi’an 710086China the People’s Armed Police Command College China Tianjin 300100China

genes have great significance for the prevention and treatment of some diseases.A vital consideration is the need to find a way to locate pathogenic genes by analyzing the genetic data obtained from different medical institutions while protecting the privacy of patients’genetic *** this paper,we present a secure scheme for locating disease-causing genes based on Multi-Key Homomorphic Encryption(MKHE),which reduces the risk of leaking genetic ***,we combine MKHE with a frequency-based pathogenic gene location *** medical institutions use MKHE to encrypt their genetic *** cloud then homomorphically evaluates specific gene-locating circuits on the encrypted genetic ***,whereas most location circuits are designed only for locating monogenic diseases,we propose two location circuits(TH-intersection and Top-q)that can locate the disease-causing genes of polygenic ***,we construct a directed decryption protocol in which the users involved in the homomorphic evaluation can appoint a target user who can obtain the final decryption *** experimental results show that compared to the JWB+17 scheme published in the journal Science,our scheme can be used to diagnose polygenic diseases,and the participants only need to upload their encrypted genetic data once,which reduces the communication traffic by a few hundred-fold.

关键词： public key encryption Multi-Key Homomorphic Encryption(MKHE) fully homomorphic encryption disease-causing genes secure location of disease-causing genes

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Prioritization of orphan disease-causing genes using topological feature and GO similarity between proteins in interaction networks

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Science China(Life Sciences) 2014年第11期57卷 1064-1071页

作者： LI Min LI Qi GANEGODA Gamage Upeksha WANG JianXin WU FangXiang PAN Yi School of Information Science and Engineering Central South University College of Engineering University of Saskatchewan Department of Computer Science Georgia State University

Identification of disease-causing genes among a large number of candidates is a fundamental challenge in human disease ***,it is still time-consuming and laborious to determine the real disease-causing genes by biological *** the advances of the high-throughput techniques,a large number of protein-protein interactions have been ***,to address this issue,several methods based on protein interaction network have been *** this paper,we propose a shortest path-based algorithm,named SPranker,to prioritize disease-causing genes in protein interaction *** the fact that diseases with similar phenotypes are generally caused by functionally related genes,we further propose an improved algorithm SPGOranker by integrating the semantic similarity of gene ontology(GO)*** not only considers the topological similarity between protein pairs in a protein interaction network but also takes their functional similarity into *** proposed algorithms SPranker and SPGOranker were applied to 1598 known orphan disease-causing genes from 172 orphan diseases and compared with three state-of-the-art approaches,ICN,VS and *** experimental results show that SPranker and SPGOranker outperform ICN,VS,and RWR for the prioritization of orphan disease-causing ***,for the case study of severe combined immunodeficiency,SPranker and SPGOranker predict several novel causal genes.

关键词： disease-causing genes prioritization gene ontology protein interaction network shortest path

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