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

拟议的研究将推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。拟议的研究对于防止研究参与者和普通个人因发布汇总统计数据和结果而侵犯隐私至关重要。这项研究的主要成果将是一套新的工具和技术，以及一个用于基因组数据隐私保护分析的门户网站，这将有助于研究人员奋进满足人们对保护隐私的日益增长的期望，并在普通人分享他们的基因图谱时提供隐私保证。 拟议的研究将大大有助于创造性地保护隐私的遗传分析领域的知识基础有限。这项研究将涉及，通过课程和论文项目，研究生和本科生，以提高他们的知识和技能，解决数据挖掘，统计分析，隐私和生物信息学的问题。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，以验证所开发工具的有效性。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做出根本性贡献。建议的研究活动包括以下三个主要任务：1）开发新的差异隐私保护技术，以在研究人员发布基因组汇总统计和/或进行高级分析时为遗传参与者提供严格的隐私保证; 2）系统地评估由于发布基因组统计和分析结果而对普通个体造成的潜在隐私泄露;和3）与合作者一起使用真实的基因组数据（癌症和阿尔茨海默病？的疾病），并建立一个集成的门户网站环境，为研究人员提供安全，可靠和隐私保护访问（匿名）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.