基因组隐私与信任。

IF 7 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY Annual Review of Biomedical Data Science Pub Date : 2022-08-10 DOI:10.1146/annurev-biodatasci-122120-021311
Gamze Gürsoy
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引用次数: 1

摘要

基因组学数据对于推进生物医学研究、改善临床护理以及为法医学和家谱学等其他学科提供信息非常重要。然而,当基因组数据被共享时,隐私问题就出现了。特别是,遗传信息的识别性质、与健康状况的直接关系以及对个人及其血亲造成的潜在经济损害和污名化,要求调查与共享遗传和相关数据有关的隐私问题以及克服这些问题的可能解决办法。在这项工作中,我们概述了基因组隐私的重要性,从基因组数据中收集的信息,基因组学中潜在的私人信息泄露的来源,以及在研究中利用遗传信息时保护隐私的方法。我们讨论了科学界的信任与保护隐私之间的关系,为数据共享和研究参与指明了未来的路线图。
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Genome Privacy and Trust.

Genomics data are important for advancing biomedical research, improving clinical care, and informing other disciplines such as forensics and genealogy. However, privacy concerns arise when genomic data are shared. In particular, the identifying nature of genetic information, its direct relationship to health status, and the potential financial harm and stigmatization posed to individuals and their blood relatives call for a survey of the privacy issues related to sharing genetic and related data and potential solutions to overcome these issues. In this work, we provide an overview of the importance of genomic privacy, the information gleaned from genomics data, the sources of potential private information leakages in genomics, and ways to preserve privacy while utilizing the genetic information in research. We discuss the relationship between trust in the scientific community and protecting privacy, illuminating a future roadmap for data sharing and study participation.

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来源期刊
CiteScore
11.10
自引率
1.70%
发文量
0
期刊介绍: The Annual Review of Biomedical Data Science provides comprehensive expert reviews in biomedical data science, focusing on advanced methods to store, retrieve, analyze, and organize biomedical data and knowledge. The scope of the journal encompasses informatics, computational, artificial intelligence (AI), and statistical approaches to biomedical data, including the sub-fields of bioinformatics, computational biology, biomedical informatics, clinical and clinical research informatics, biostatistics, and imaging informatics. The mission of the journal is to identify both emerging and established areas of biomedical data science, and the leaders in these fields.
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