Efficient sequential and parallel algorithms for planted motif search.
Identifieur interne : 001A68 ( PubMed/Corpus ); précédent : 001A67; suivant : 001A69Efficient sequential and parallel algorithms for planted motif search.
Auteurs : Marius Nicolae ; Sanguthevar RajasekaranSource :
- BMC bioinformatics [ 1471-2105 ] ; 2014.
English descriptors
- KwdEn :
- MESH :
- chemical , chemistry : DNA, Proteins.
- chemical , genetics : DNA, Proteins.
- methods : Computational Biology, Sequence Analysis, DNA, Sequence Analysis, Protein.
- Algorithms, Software.
Abstract
Motif searching is an important step in the detection of rare events occurring in a set of DNA or protein sequences. One formulation of the problem is known as (l,d)-motif search or Planted Motif Search (PMS). In PMS we are given two integers l and d and n biological sequences. We want to find all sequences of length l that appear in each of the input sequences with at most d mismatches. The PMS problem is NP-complete. PMS algorithms are typically evaluated on certain instances considered challenging. Despite ample research in the area, a considerable performance gap exists because many state of the art algorithms have large runtimes even for moderately challenging instances.
DOI: 10.1186/1471-2105-15-34
PubMed: 24479443
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pubmed:24479443Le document en format XML
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One formulation of the problem is known as (l,d)-motif search or Planted Motif Search (PMS). In PMS we are given two integers l and d and n biological sequences. We want to find all sequences of length l that appear in each of the input sequences with at most d mismatches. The PMS problem is NP-complete. PMS algorithms are typically evaluated on certain instances considered challenging. Despite ample research in the area, a considerable performance gap exists because many state of the art algorithms have large runtimes even for moderately challenging instances.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Curated" Owner="NLM"><PMID Version="1">24479443</PMID><DateCompleted><Year>2014</Year><Month>06</Month><Day>15</Day></DateCompleted><DateRevised><Year>2018</Year><Month>12</Month><Day>02</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1471-2105</ISSN><JournalIssue CitedMedium="Internet"><Volume>15</Volume><PubDate><Year>2014</Year><Month>Jan</Month><Day>31</Day></PubDate></JournalIssue><Title>BMC bioinformatics</Title><ISOAbbreviation>BMC Bioinformatics</ISOAbbreviation></Journal><ArticleTitle>Efficient sequential and parallel algorithms for planted motif search.</ArticleTitle><Pagination><MedlinePgn>34</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/1471-2105-15-34</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Motif searching is an important step in the detection of rare events occurring in a set of DNA or protein sequences. One formulation of the problem is known as (l,d)-motif search or Planted Motif Search (PMS). In PMS we are given two integers l and d and n biological sequences. We want to find all sequences of length l that appear in each of the input sequences with at most d mismatches. The PMS problem is NP-complete. PMS algorithms are typically evaluated on certain instances considered challenging. Despite ample research in the area, a considerable performance gap exists because many state of the art algorithms have large runtimes even for moderately challenging instances.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">This paper presents a fast exact parallel PMS algorithm called PMS8. PMS8 is the first algorithm to solve the challenging (l,d) instances (25,10) and (26,11). PMS8 is also efficient on instances with larger l and d such as (50,21). We include a comparison of PMS8 with several state of the art algorithms on multiple problem instances. This paper also presents necessary and sufficient conditions for 3 l-mers to have a common d-neighbor. The program is freely available at http://engr.uconn.edu/~man09004/PMS8/.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">We present PMS8, an efficient exact algorithm for Planted Motif Search. PMS8 introduces novel ideas for generating common neighborhoods. We have also implemented a parallel version for this algorithm. 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