ArticlePloS one2012
PairMotif: A new pattern-driven algorithm for planted (l, d) DNA motif search.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- A Review on Planted (Sensors (Basel, Switzerland) · 2022Review
- A Clustering Approach for Motif Discovery in ChIP-Seq Dataset.Entropy (Basel, Switzerland) · 2019Article
- Novel algorithms for LDD motif search.BMC genomics · 2019Article
- SamSelect: a sample sequence selection algorithm for quorum planted motif search on large DNA datasets.BMC bioinformatics · 2018Article
- Efficient sequential and parallel algorithms for finding edit distance based motifs.BMC genomics · 2016Article
- RefSelect: a reference sequence selection algorithm for planted (l, d) motif search.BMC bioinformatics · 2016Article
- Article
- PairMotifChIP: A Fast Algorithm for Discovery of Patterns Conserved in Large ChIP-seq Data Sets.BioMed research international · 2016Article
- qPMS9: an efficient algorithm for quorum Planted Motif Search.Scientific reports · 2015Article
- An Affinity Propagation-Based DNA Motif Discovery Algorithm.BioMed research international · 2015Article
- Efficient sequential and parallel algorithms for planted motif search.BMC bioinformatics · 2014Article
- Article
- PairMotif+: a fast and effective algorithm for de novo motif discovery in DNA sequences.International journal of biological sciences · 2013Article
- Review of Different Sequence Motif Finding Algorithms.Avicenna journal of medical biotechnologyReview
Corrections and comments
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4 authors.
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Abstract
Motif search is a fundamental problem in bioinformatics with an important application in locating transcription factor binding sites (TFBSs) in DNA sequences. The exact algorithms can report all (l, d) motifs and find the best one under a specific objective function. However, it is still a challenging task to identify weak motifs, since either a large amount of memory or execution time is required by current exact algorithms. A new exact algorithm, PairMotif, is proposed for planted (l, d) motif search (PMS) in this paper. To effectively reduce both candidate motifs and scanned l-mers, multiple pairs of l-mers with relatively large distances are selected from input sequences to restrict the search space. Comparisons with several recently proposed algorithms show that PairMotif requires less storage space and runs faster on most PMS instances. Particularly, among the algorithms compared, only PairMotif can solve the weak instance (27, 9) within 10 hours. Moreover, the performance of PairMotif is stable over the sequence length, which allows it to identify motifs in longer sequences. For the real biological data, experimental results demonstrate the validity of the proposed algorithm.
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