Year: 2013
Type: article
Abstract: MOTIVATION: Increased availability of various genotyping techniques has initiated a race for finding genetic markers that can be used in diagnostics and personalized medicine. Although many genetic risk factors are known, key causes of common diseases with complex heritage patterns are still unknown. Identification of such complex traits requires a targeted study over a large collection of data. Ideally, such studies bring together data from many biobanks. However, data aggregation on such a large scale raises many privacy issues. RESULTS: We show how to conduct such studies without violating privacy of individual donors and without leaking the data to third parties. The presented solution has provable security guarantees. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Source: Bioinformatics
Authors: Liina Kamm, Dan Bogdanov, Sven Laur, Jaak Vilo
Institution: University of Tartu
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,989
OpenAlex ID: W2166106997