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BioMed Research International
Volume 2016 (2016), Article ID 4986707, 10 pages
Research Article

PairMotifChIP: A Fast Algorithm for Discovery of Patterns Conserved in Large ChIP-seq Data Sets

1School of Computer Science and Technology, Xidian University, Xi’an 710071, China
2School of Electronic Engineering, Xidian University, Xi’an 710071, China

Received 22 June 2016; Revised 4 September 2016; Accepted 27 September 2016

Academic Editor: Yudong Cai

Copyright © 2016 Qiang Yu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Identifying conserved patterns in DNA sequences, namely, motif discovery, is an important and challenging computational task. With hundreds or more sequences contained, the high-throughput sequencing data set is helpful to improve the identification accuracy of motif discovery but requires an even higher computing performance. To efficiently identify motifs in large DNA data sets, a new algorithm called PairMotifChIP is proposed by extracting and combining pairs of -mers in the input with relatively small Hamming distance. In particular, a method for rapidly extracting pairs of -mers is designed, which can be used not only for PairMotifChIP, but also for other DNA data mining tasks with the same demand. Experimental results on the simulated data show that the proposed algorithm can find motifs successfully and runs faster than the state-of-the-art motif discovery algorithms. Furthermore, the validity of the proposed algorithm has been verified on real data.