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Opportunities and Challenges in Interpreting and Sharing Personal Genomes
Opinion

Beyond Genes: Re-Identifiability of Proteomic Data and Its Implications for Personalized Medicine

1
VITO Health, Boeretang 200, Mol 2400, Belgium
2
Centre for Proteomics, University of Antwerpen, Antwerp 2020, Belgium
3
Department of Philosophy, University of Antwerp, Antwerp 2000 & Institute of Philosophy, KU Leuven, Leuven 3000, Belgium
4
Biobix, Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent 9000, Belgium
5
Hasselt University, Hasselt 3500, Belgium
*
Authors to whom correspondence should be addressed.
Genes 2019, 10(9), 682; https://doi.org/10.3390/genes10090682
Received: 19 July 2019 / Revised: 30 August 2019 / Accepted: 1 September 2019 / Published: 5 September 2019
(This article belongs to the Special Issue Algorithms for Personal Genomics)
The increasing availability of high throughput proteomics data provides us with opportunities as well as posing new ethical challenges regarding data privacy and re-identifiability of participants. Moreover, the fact that proteomics represents a level between the genotype and the phenotype further exacerbates the situation, introducing dilemmas related to publicly available data, anonymization, ownership of information and incidental findings. In this paper, we try to differentiate proteomics from genomics data and cover the ethical challenges related to proteomics data sharing. Finally, we give an overview of the proposed solutions and the outlook for future studies. View Full-Text
Keywords: proteomics; re-identifiability; privacy; genomics; data; personal medicine proteomics; re-identifiability; privacy; genomics; data; personal medicine
MDPI and ACS Style

Boonen, K.; Hens, K.; Menschaert, G.; Baggerman, G.; Valkenborg, D.; Ertaylan, G. Beyond Genes: Re-Identifiability of Proteomic Data and Its Implications for Personalized Medicine. Genes 2019, 10, 682. https://doi.org/10.3390/genes10090682

AMA Style

Boonen K, Hens K, Menschaert G, Baggerman G, Valkenborg D, Ertaylan G. Beyond Genes: Re-Identifiability of Proteomic Data and Its Implications for Personalized Medicine. Genes. 2019; 10(9):682. https://doi.org/10.3390/genes10090682

Chicago/Turabian Style

Boonen, Kurt, Kristien Hens, Gerben Menschaert, Geert Baggerman, Dirk Valkenborg, and Gokhan Ertaylan. 2019. "Beyond Genes: Re-Identifiability of Proteomic Data and Its Implications for Personalized Medicine" Genes 10, no. 9: 682. https://doi.org/10.3390/genes10090682

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