SCH: EXP: Collaborative Research: Preserving Privacy in Human Genomic Data

拟议的研究将促进对基因组数据分析相关基本问题的理论理解，以及有效保护隐私的实用技术的设计和实施。由于公布的汇总统计数据和结果，拟议中的研究对于防止研究参与者和普通人的隐私泄露至关重要。这项研究的主要成果将是一套新颖的工具和技术，以及一个保护基因组数据隐私分析的门户网站，这将有助于研究人员努力满足日益增长的保护隐私的期望，并在普通个人分享他们的基因档案时提供隐私保证。提出的研究将对遗传分析中保护隐私领域有限的知识基础作出重大和创造性的贡献。这项研究将通过课程和论文项目，让研究生和本科生提高他们解决数据挖掘、统计分析、隐私和生物信息学等问题的知识和技能。pi将与贝勒医学院和MD安德森癌症研究所的工业合作伙伴合作，验证开发工具的有效性。拟议的工作与一个关键的健康问题（即遗传隐私）有关，并将对计算机和信息科学以及生物医学研究作出根本性贡献。建议的研究活动包括以下三个主要任务：1)开发新的差分隐私保护技术，在研究人员发表基因组汇总统计和/或进行高级分析时为遗传参与者提供严格的隐私保障；2)系统评估因公布的基因组统计数据和分析结果可能对普通个人造成的隐私泄露；3)与合作者一起评估使用真实基因组数据(癌症和阿尔茨海默病？并建立一个集成的门户网站环境，为研究人员提供安全、可靠和保护隐私的（匿名的）基因组原始数据、统计数据和分析结果。

The proposed research will advance theoretical understanding of fundamental issues related to genomic data analysis, as well as the design and implementation of practical techniques to effectively protect privacy. The proposed research is central to preventing privacy breaches for both study participants and regular individuals due to released summary statistics and results. A primary outcome of this research will be a suite of novel tools and technologies and a Web-portal for privacy preserving analysis of genomic data, which will help researchers in their endeavor to meet growing expectations in protecting privacy and provide privacy assurance when regular individuals share their genetic profiles. The proposed research will contribute significantly and creatively to the limited base of knowledge in the area of preserving privacy in genetic analysis. This research will involve, through courses and thesis projects, graduate and undergraduate students to enhance their knowledge and skills in solving problems in data mining, statistical analysis, privacy, and bioinformatics. The PIs will collaborate with industrial partners at Baylor College of Medicine and MD Anderson Cancer Institute to validate the effectiveness of developed tools. The proposed work is tied to a key health problem (i.e. genetic privacy) and will make a fundamental contribution to computer and information sciences, and biomedical research. The proposed research activities include the following three major tasks: 1) develop novel differential privacy preserving techniques to provide rigorous privacy guarantees for genetic participants when researchers publish genomic summary statistics and/or conduct advanced analysis; 2) systematically evaluate potential privacy breaches for regular individuals due to the released genomic statistics and analysis results; and 3) work with collaborators to evaluate the efficacy of developed methods using real genomic data (cancer and Alzheimer?s disease) and build an integrated Web-portal environment to provide researchers secure, reliable, and privacy preserving access to (anonymized) genomic raw data, statistics, and analysis results.