Semi-Parallel logistic regression for GWAS on encrypted data

BACKGROUND: The sharing of biomedical data is crucial to enable scientific discoveries across institutions and improve health care. For example, genome-wide association studies (GWAS) based on a large number of samples can identify disease-causing genetic variants. The privacy concern, however, has...

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Detalles Bibliográficos
Autores principales: Kim, Miran, Song, Yongsoo, Li, Baiyu, Micciancio, Daniele
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7372846/
https://www.ncbi.nlm.nih.gov/pubmed/32693798
http://dx.doi.org/10.1186/s12920-020-0724-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7372846/
https://www.ncbi.nlm.nih.gov/pubmed/32693798
http://dx.doi.org/10.1186/s12920-020-0724-z

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