Computational tools for genomic data de-identification: facilitating data protection law compliance
In this opinion piece, we discuss why computational tools to limit the identifiability of genomic data are a promising avenue for privacy-preservation and legal compliance. Even where these technologies do not eliminate all residual risk of individual identification, the law may still consider such...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2021-11-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-021-27219-2 |
| _version_ | 1818719034845167616 |
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| author | Alexander Bernier Hanshi Liu Bartha Maria Knoppers |
| author_facet | Alexander Bernier Hanshi Liu Bartha Maria Knoppers |
| author_sort | Alexander Bernier |
| collection | DOAJ |
| description | In this opinion piece, we discuss why computational tools to limit the identifiability of genomic data are a promising avenue for privacy-preservation and legal compliance. Even where these technologies do not eliminate all residual risk of individual identification, the law may still consider such data anonymised. |
| first_indexed | 2024-12-17T20:00:32Z |
| format | Article |
| id | doaj.art-042e5e2b86a747b5a4ba90e724c1b108 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-12-17T20:00:32Z |
| publishDate | 2021-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-042e5e2b86a747b5a4ba90e724c1b1082022-12-21T21:34:29ZengNature PortfolioNature Communications2041-17232021-11-011211310.1038/s41467-021-27219-2Computational tools for genomic data de-identification: facilitating data protection law complianceAlexander Bernier0Hanshi Liu1Bartha Maria Knoppers2Centre of Genomics and Policy, McGill University, Faculty of MedicineCentre of Genomics and Policy, McGill University, Faculty of MedicineCentre of Genomics and Policy, McGill University, Faculty of MedicineIn this opinion piece, we discuss why computational tools to limit the identifiability of genomic data are a promising avenue for privacy-preservation and legal compliance. Even where these technologies do not eliminate all residual risk of individual identification, the law may still consider such data anonymised.https://doi.org/10.1038/s41467-021-27219-2 |
| spellingShingle | Alexander Bernier Hanshi Liu Bartha Maria Knoppers Computational tools for genomic data de-identification: facilitating data protection law compliance Nature Communications |
| title | Computational tools for genomic data de-identification: facilitating data protection law compliance |
| title_full | Computational tools for genomic data de-identification: facilitating data protection law compliance |
| title_fullStr | Computational tools for genomic data de-identification: facilitating data protection law compliance |
| title_full_unstemmed | Computational tools for genomic data de-identification: facilitating data protection law compliance |
| title_short | Computational tools for genomic data de-identification: facilitating data protection law compliance |
| title_sort | computational tools for genomic data de identification facilitating data protection law compliance |
| url | https://doi.org/10.1038/s41467-021-27219-2 |
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