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SQUiD: ultra-secure storage and analysis of genetic data for the advancement of precision medicine

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Τίτλος: SQUiD: ultra-secure storage and analysis of genetic data for the advancement of precision medicine
Συγγραφείς: Blindenbach, Jacob, Kang, Jiayi, Hong, Seungwan, Karam, Caline, Lehner, Thomas, Gürsoy, Gamze
Έτος έκδοσης: 2024
Συλλογή: Columbia University: Academic Commons
Θεματικοί όροι: Personalized medicine, Phenotype, Human genetics--Data processing
Περιγραφή: Cloud computing allows storing the ever-growing genotype-phenotype datasets crucial for precision medicine. Due to the sensitive nature of this data and varied laws and regulations, additional security measures are needed to ensure data privacy. We develop SQUiD, a secure queryable database for storing and analyzing genotype-phenotype data. SQUiD allows storage and secure querying of data in a low-security, low-cost public cloud using homomorphic encryption in a multi-client setting. We demonstrate SQUiD’s practical usability and scalability using synthetic and UK Biobank data.
Τύπος εγγράφου: other/unknown material
Γλώσσα: unknown
DOI: 10.7916/qcbp-a746
Διαθεσιμότητα: https://doi.org/10.7916/qcbp-a746
Αριθμός Καταχώρησης: edsbas.2128DD9F
Βάση Δεδομένων: BASE
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  Data: SQUiD: ultra-secure storage and analysis of genetic data for the advancement of precision medicine
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  Data: <searchLink fieldCode="AR" term="%22Blindenbach%2C+Jacob%22">Blindenbach, Jacob</searchLink><br /><searchLink fieldCode="AR" term="%22Kang%2C+Jiayi%22">Kang, Jiayi</searchLink><br /><searchLink fieldCode="AR" term="%22Hong%2C+Seungwan%22">Hong, Seungwan</searchLink><br /><searchLink fieldCode="AR" term="%22Karam%2C+Caline%22">Karam, Caline</searchLink><br /><searchLink fieldCode="AR" term="%22Lehner%2C+Thomas%22">Lehner, Thomas</searchLink><br /><searchLink fieldCode="AR" term="%22Gürsoy%2C+Gamze%22">Gürsoy, Gamze</searchLink>
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  Data: 2024
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  Data: Columbia University: Academic Commons
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  Data: Cloud computing allows storing the ever-growing genotype-phenotype datasets crucial for precision medicine. Due to the sensitive nature of this data and varied laws and regulations, additional security measures are needed to ensure data privacy. We develop SQUiD, a secure queryable database for storing and analyzing genotype-phenotype data. SQUiD allows storage and secure querying of data in a low-security, low-cost public cloud using homomorphic encryption in a multi-client setting. We demonstrate SQUiD’s practical usability and scalability using synthetic and UK Biobank data.
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