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상호정보와 부울대수를 이용한 복합질환의 SNP 상호작용 예측
임상섭(Sang-Seob Leem),위규범(Kyu-Bum Wee) 한국컴퓨터정보학회 2010 韓國컴퓨터情報學會論文誌 Vol.15 No.11
대부분의 만성질환은 다수의 유전자-유전자 사이의 상호작용에 의해서 발병하는 복합질환이다. 복합질환의 발병에 관여하는 단일염기다형성(single nucleotide polymorphism; SNP)과 유전자 사이의 상호작용을 찾아내는 연구는 질환의 예방과 치료에 기여한다. 기존의 연구 방법은 주로 특정 유전자 내 SNP 조합을 찾아내는 데 그치고 있다. 본 연구에서는 SNP 조합의 구성원 사이에 일어나는 구체적인 상호작용을 나타내는 부울식을 찾는 방법을 제시한다. 본 논문에서 제안하는 방법은 두 단계로 이루어진다. 제 1 단계에서는 엔트로피에 기반한 상호정보를 이용하여 발병에 관여하는 SNP 조합을 찾는다. 제 2단계에서는 제 1 단계에서 찾은 SNP 조합으로 이루어지는 부울식 중에서 발병 예측정확도가 가장 높은 부울식을 찾는다. 제안한 방법을 임상자료에 적용하여 그 효율성을 실험하였으며 기존 연구들과 장단점을 비교하였다. Most chronic diseases are complex diseases which are caused by interactions of several genes. Studies on finding SNPs and gene-gene interactions involved in the development of complex diseases can contribute to prevention and treatment of the diseases. Previous studies mostly concentrate on finding only the set of SNPs involved. In this study we suggest a way to see how these SNPs interact using boolean expressions. The proposed method consists of two stages. In the first stage we find the set of SNPs involved in the development of diseases using mutual information based on entropy. In the second stage we find the highest accuracy boolean expression that consists of the SNP set obtained in the first stage. We experimented with clinical data to demonstrate the effectiveness of the proposed method. We also compared the differences between our method and the previous results on the SNP associations studies.
Privacy-assured Boolean Adjacent Vertex Search over Encrypted Graph Data in Cloud Computing
( Hong Zhu ),( Bin Wu ),( Meiyi Xie ),( Zongmin Cui ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.10
With the popularity of cloud computing, many data owners outsource their graph data to the cloud for cost savings. The cloud server is not fully trusted and always wants to learn the owners` contents. To protect the information hiding, the graph data have to be encrypted before outsourcing to the cloud. The adjacent vertex search is a very common operation, many other operations can be built based on the adjacent vertex search. A boolean adjacent vertex search is an important basic operation, a query user can get the boolean search results. Due to the graph data being encrypted on the cloud server, a boolean adjacent vertex search is a quite difficult task. In this paper, we propose a solution to perform the boolean adjacent vertex search over encrypted graph data in cloud computing (BASG), which maintains the query tokens and search results privacy. We use the Gram-Schmidt algorithm and achieve the boolean expression search in our paper. We formally analyze the security of our scheme, and the query user can handily get the boolean search results by this scheme. The experiment results with a real graph data set demonstrate the efficiency of our scheme.