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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2020
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| Materias: | |
| 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 |