Cargando…
Privacy-preserving genome-wide association studies on cloud environment using fully homomorphic encryption
OBJECTIVE: Developed sequencing techniques are yielding large-scale genomic data at low cost. A genome-wide association study (GWAS) targeting genetic variations that are significantly associated with a particular disease offers great potential for medical improvement. However, subjects who voluntee...
Autores principales: | Lu, Wen-Jie, Yamada, Yoshiji, Sakuma, Jun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4699111/ https://www.ncbi.nlm.nih.gov/pubmed/26732892 http://dx.doi.org/10.1186/1472-6947-15-S5-S1 |
Ejemplares similares
-
Privacy-preserving semi-parallel logistic regression training with fully homomorphic encryption
por: Carpov, Sergiu, et al.
Publicado: (2020) -
Private genome analysis through homomorphic encryption
por: Kim, Miran, et al.
Publicado: (2015) -
FORESEE: Fully Outsourced secuRe gEnome Study basEd on homomorphic Encryption
por: Zhang, Yuchen, et al.
Publicado: (2015) -
Privacy-preserving cancer type prediction with homomorphic encryption
por: Sarkar, Esha, et al.
Publicado: (2023) -
A Review of Homomorphic Encryption for Privacy-Preserving Biometrics
por: Yang, Wencheng, et al.
Publicado: (2023)