A private DNA motif finding algorithm

Rui CHEN*, Yun PENG, Koon Kau CHOI, Jianliang XU, Haibo HU

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

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 languageEnglish
Pages (from-to)122-132
Number of pages11
JournalJournal of Biomedical Informatics
Volume50
DOIs
Publication statusPublished - Aug 2014

Scopus Subject Areas

  • Computer Science Applications
  • Health Informatics

User-Defined Keywords

  • Motif finding
  • N-gram model
  • Privacy protection
  • {small element of}-Differential privacy

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