Literature DB >> 24597706

Finding motifs in DNA sequences using low-dispersion sequences.

Xun Wang1, Ying Miao, Minquan Cheng.   

Abstract

Motif finding problems, abstracted as the planted (l, d)-motif finding problem, are a major task in molecular biology--finding functioning units and genes. In 2002, the random projection algorithm was introduced to solve the challenging (15, 4)-motif finding problem by using randomly chosen templates. Two years later, a so-called uniform projection algorithm was developed to improve the random projection algorithm by means of low-dispersion sequences generated by coverings. In this article, we introduce an improved projection algorithm called the low-dispersion projection algorithm, which uses low-dispersion sequences generated by developed almost difference families. Compared with the random projection algorithm, the low-dispersion projection algorithm can solve the (l, d)-motif finding problem with fewer templates without decreasing the success rate.

Mesh:

Year:  2014        PMID: 24597706      PMCID: PMC3962653          DOI: 10.1089/cmb.2013.0054

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  10 in total

1.  Identifying DNA and protein patterns with statistically significant alignments of multiple sequences.

Authors:  G Z Hertz; G D Stormo
Journal:  Bioinformatics       Date:  1999 Jul-Aug       Impact factor: 6.937

2.  Finding motifs using random projections.

Authors:  Jeremy Buhler; Martin Tompa
Journal:  J Comput Biol       Date:  2002       Impact factor: 1.479

3.  Combinatorial approaches to finding subtle signals in DNA sequences.

Authors:  P A Pevzner; S H Sze
Journal:  Proc Int Conf Intell Syst Mol Biol       Date:  2000

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Authors:  D J Galas; A Schmitz
Journal:  Nucleic Acids Res       Date:  1978-09       Impact factor: 16.971

5.  A uniform projection method for motif discovery in DNA sequences.

Authors:  Benjamin Raphael; Lung-Tien Liu; George Varghese
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2004 Apr-Jun       Impact factor: 3.710

6.  An expectation maximization (EM) algorithm for the identification and characterization of common sites in unaligned biopolymer sequences.

Authors:  C E Lawrence; A A Reilly
Journal:  Proteins       Date:  1990

7.  Detecting subtle sequence signals: a Gibbs sampling strategy for multiple alignment.

Authors:  C E Lawrence; S F Altschul; M S Boguski; J S Liu; A F Neuwald; J C Wootton
Journal:  Science       Date:  1993-10-08       Impact factor: 47.728

8.  A gel electrophoresis method for quantifying the binding of proteins to specific DNA regions: application to components of the Escherichia coli lactose operon regulatory system.

Authors:  M M Garner; A Revzin
Journal:  Nucleic Acids Res       Date:  1981-07-10       Impact factor: 16.971

9.  Analysis of computational approaches for motif discovery.

Authors:  Nan Li; Martin Tompa
Journal:  Algorithms Mol Biol       Date:  2006-05-19       Impact factor: 1.405

Review 10.  A survey of DNA motif finding algorithms.

Authors:  Modan K Das; Ho-Kwok Dai
Journal:  BMC Bioinformatics       Date:  2007-11-01       Impact factor: 3.169

  10 in total
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Review 6.  Review of Different Sequence Motif Finding Algorithms.

Authors:  Fatma A Hashim; Mai S Mabrouk; Walid Al-Atabany
Journal:  Avicenna J Med Biotechnol       Date:  2019 Apr-Jun
  6 in total

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