Evidence map›Paper›PMID 22848493›Full record

ArticlePloS one2012

qPMS7: a fast algorithm for finding (ℓ, d)-motifs in DNA and protein sequences.

Hieu Dinh, Sanguthevar Rajasekaran, Jaime Davila

Abstract read
In one paragraph

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 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. A Review on Planted (Sensors (Basel, Switzerland) · 2022
    Review
  2. Freezing firefly algorithm for efficient planted (ℓ, d) motif search.Medical & biological engineering & computing · 2022
    Article
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  7. Evolution of domain-peptide interactions to coadapt specificity and affinity to functional diversity.Proceedings of the National Academy of Sciences of the United States of America · 2016
    Article
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  16. Review of Different Sequence Motif Finding Algorithms.Avicenna journal of medical biotechnology
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Hieu DinhDepartment of Computer Science and Engineering, University of Connecticut, Storrs, Connecticut, United States of America. hdinh@engr.uconn.edu
Sanguthevar Rajasekaran
Jaime Davila

Funding

Efficient Algorithms for Motif SearchR01LM010101 · NLM · UNIVERSITY OF CONNECTICUT STORRS · PI RAJASEKARAN, SANGUTHEVAR · 2010 to 2013
$1.4M
NLM NIH HHS R01 LM010101NLM NIH HHS R01-LM010101
6 · The paper itself

Abstract

Detection of rare events happening in a set of DNA/protein sequences could lead to new biological discoveries. One kind of such rare events is the presence of patterns called motifs in DNA/protein sequences. Finding motifs is a challenging problem since the general version of motif search has been proven to be intractable. Motifs discovery is an important problem in biology. For example, it is useful in the detection of transcription factor binding sites and transcriptional regulatory elements that are very crucial in understanding gene function, human disease, drug design, etc. Many versions of the motif search problem have been proposed in the literature. One such is the (ℓ, d)-motif search (or Planted Motif Search (PMS)). A generalized version of the PMS problem, namely, Quorum Planted Motif Search (qPMS), is shown to accurately model motifs in real data. However, solving the qPMS problem is an extremely difficult task because a special case of it, the PMS Problem, is already NP-hard, which means that any algorithm solving it can be expected to take exponential time in the worse case scenario. In this paper, we propose a novel algorithm named qPMS7 that tackles the qPMS problem on real data as well as challenging instances. Experimental results show that our Algorithm qPMS7 is on an average 5 times faster than the state-of-art algorithm. The executable program of Algorithm qPMS7 is freely available on the web at http://pms.engr.uconn.edu/downloads/qPMS7.zip. Our online motif discovery tools that use Algorithm qPMS7 are freely available at http://pms.engr.uconn.edu or http://motifsearch.com.

Indexed as

AlgorithmsInternetSoftwareAmino Acid MotifsAnimalsHumansSequence Analysis, DNASequence Analysis, Protein

Identifiers

PMID22848493
PMCPMC3404135

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.