Abstract
With the increasing availability of genomic sequence data, numerous methods have been proposed for finding DNA motifs. The discovery of DNA motifs serves a critical step in many biological applications. However, the privacy implication of DNA analysis is normally neglected in the existing methods. In this work, we propose a private DNA motif finding algorithm in which a DNA owner's privacy is protected by a rigorous privacy model, known as {small element of}- differential privacy. It provides provable privacy guarantees that are independent of adversaries' background knowledge. Our algorithm makes use of the n-gram model and is optimized for processing large-scale DNA sequences. We evaluate the performance of our algorithm over real-life genomic data and demonstrate the promise of integrating privacy into DNA motif finding.
Original language | English |
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Pages (from-to) | 122-132 |
Number of pages | 11 |
Journal | Journal of Biomedical Informatics |
Volume | 50 |
DOIs | |
Publication status | Published - 1 Jan 2014 |
Externally published | Yes |
Keywords
- Motif finding
- N-gram model
- Privacy protection
- {small element of}-Differential privacy
ASJC Scopus subject areas
- Computer Science Applications
- Health Informatics