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PairMotifChIP: A Fast Algorithm for Discovery of Patterns Conserved in Large ChIP-seq Data Sets
Joint Authors
Huo, Hongwei
Yu, Qiang
Feng, Dazheng
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-10-24
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
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 l-mers in the input with relatively small Hamming distance.
In particular, a method for rapidly extracting pairs of l-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.
American Psychological Association (APA)
Yu, Qiang& Huo, Hongwei& Feng, Dazheng. 2016. PairMotifChIP: A Fast Algorithm for Discovery of Patterns Conserved in Large ChIP-seq Data Sets. BioMed Research International،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1097971
Modern Language Association (MLA)
Yu, Qiang…[et al.]. PairMotifChIP: A Fast Algorithm for Discovery of Patterns Conserved in Large ChIP-seq Data Sets. BioMed Research International No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1097971
American Medical Association (AMA)
Yu, Qiang& Huo, Hongwei& Feng, Dazheng. PairMotifChIP: A Fast Algorithm for Discovery of Patterns Conserved in Large ChIP-seq Data Sets. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1097971
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1097971