Protecting the pRivacy Of Genomes in Research StudieS (PROGRESS)

描述（由申请人提供）：随着全基因组测序（WGS）成本的大幅降低，基因组数据变得越来越容易获得，并且具有促进公共卫生和促进个性化医疗的潜力。然而，人类基因组数据通常带有敏感的个人信息，使得数据所有者对共享数据持谨慎态度，基因组隐私正在成为整个生物医学界面临的一个巨大挑战。在本提案中，我们将开发新的基因组隐私保护方法，这将促进基因组研究。我们的第一个目标是开发隐私保护和效率导向的计算模型，用于在基于云的环境中处理、共享和存储基因组数据。这一目标依赖于可扩展的加密技术、联合压缩和加密方案，以及利用高性能计算架构来实现云中的隐私保护分析和存储效率。第二个目标是开发可信的计算模型，使研究人员能够分析分布式基因组数据，而不需要患者级别的数据交换。这些目标致力于国家人类基因组研究所（NHGRI）的使命，即开发资源和技术，加速基因组研究及其对人类健康的应用。美国国立卫生研究院独立之路奖为申请人提供了一个很好的机会，以补充他的计算机工程背景与生物医学知识，以及基因组分析，基因组隐私和高性能计算方面的专业培训。它还将允许他研究新技术，以提高基因组隐私保护。该计划的成功将有助于他的长期职业目标，即在美国一所主要研究型大学的生物医学信息学项目中获得教职，并在基因组隐私领域进行独立资助的研究。

DESCRIPTION (provided by applicant): With the dramatic reduction in the cost of whole genome sequencing (WGS), genomic data are becoming increasingly available and have the potential to advance public health and promote personalized medicine. However, human genomic data usually carry sensitive personal information making data owners cautious about sharing it and genomic privacy is emerging as a big challenge for the entire biomedical community. In this proposal, we will develop novel methods for genomic privacy protection, which will facilitate genomic research. Our first aim is to develop privacy-preserving and efficiency-oriented computational models for processing, sharing, and storing genomic data in a cloud-based environment. This aim relies on scalable cryptographic techniques, joint compression, and encryption schemes, as well as leverage of high-performance computing architecture to achieve privacy-preserving analysis and storage efficiency in the cloud. The second aim is to develop trustworthy computational models that enable researchers to analyze distributed genomic data without requiring patient-level data exchange. These aims are devoted to the mission of the National Human Genome Research Institute (NHGRI) to develop resources and technology that will accelerate genome research and its application to human health. The NIH Pathway to Independence Award provides a great opportunity for the applicant to complement his computer engineering background with biomedical knowledge, and specialized training in genomic analysis, genomic privacy, as well as high-performance computing. It will also allow him to investigate new techniques to advance genomic privacy protection. The success of the proposed project will help his long-term career goal of obtaining a faculty position at a biomedical informatics program at a major US research university and conduct independently funded research in the field of genome privacy.