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敏感人类蛋白质组学数据的数据管理:当前实践、建议和未来展望。

Data Management of Sensitive Human Proteomics Data: Current Practices, Recommendations, and Perspectives for the Future.

机构信息

Center for Computational Mass Spectrometry, University of California, San Diego (UCSD), La Jolla, California, USA; Department Computer Science and Engineering, University of California, San Diego (UCSD), La Jolla, California, USA; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego (UCSD), La Jolla, California, USA.

Institute for Systems Biology, Seattle, Washington, USA.

出版信息

Mol Cell Proteomics. 2021;20:100071. doi: 10.1016/j.mcpro.2021.100071. Epub 2021 Mar 10.

Abstract

Today it is the norm that all relevant proteomics data that support the conclusions in scientific publications are made available in public proteomics data repositories. However, given the increase in the number of clinical proteomics studies, an important emerging topic is the management and dissemination of clinical, and thus potentially sensitive, human proteomics data. Both in the United States and in the European Union, there are legal frameworks protecting the privacy of individuals. Implementing privacy standards for publicly released research data in genomics and transcriptomics has led to processes to control who may access the data, so-called "controlled access" data. In parallel with the technological developments in the field, it is clear that the privacy risks of sharing proteomics data need to be properly assessed and managed. In our view, the proteomics community must be proactive in addressing these issues. Yet a careful balance must be kept. On the one hand, neglecting to address the potential of identifiability in human proteomics data could lead to reputational damage of the field, while on the other hand, erecting barriers to open access to clinical proteomics data will inevitably reduce reuse of proteomics data and could substantially delay critical discoveries in biomedical research. In order to balance these apparently conflicting requirements for data privacy and efficient use and reuse of research efforts through the sharing of clinical proteomics data, development efforts will be needed at different levels including bioinformatics infrastructure, policymaking, and mechanisms of oversight.

摘要

如今,所有支持科学出版物结论的相关蛋白质组学数据都在公共蛋白质组学数据库中公开,这已成为一种常态。然而,鉴于临床蛋白质组学研究数量的增加,一个重要的新兴话题是管理和传播临床蛋白质组学数据,因为这些数据可能涉及敏感的人类信息。在美国和欧盟,都有保护个人隐私的法律框架。在基因组学和转录组学领域,实施公开研究数据的隐私标准导致了控制谁可以访问数据的流程,即所谓的“受控访问”数据。随着该领域技术的发展,显然需要对蛋白质组学数据共享的隐私风险进行适当评估和管理。在我们看来,蛋白质组学领域必须积极解决这些问题。但必须保持谨慎的平衡。一方面,如果忽视人类蛋白质组学数据中潜在的可识别性,可能会导致该领域的声誉受损;另一方面,如果对临床蛋白质组学数据的开放访问设置障碍,将不可避免地减少蛋白质组学数据的重复使用,并可能严重延迟生物医学研究中的关键发现。为了平衡这些对数据隐私的明显冲突要求,以及通过共享临床蛋白质组学数据有效利用和重复使用研究成果的要求,需要在不同层面上进行开发工作,包括生物信息学基础设施、决策制定以及监督机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f2c/8056256/b1a372507916/fx1.jpg

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