title: cisExpress: motif detection in DNA sequences.
abstract: BACKGROUND
  One of the major challenges for contemporary bioinformatics is the analysis and accurate annotation of genomic datasets to enable extraction of useful information about the functional role of DNA sequences. This article describes a novel genome-wide statistical approach to the detection of specific DNA sequence motifs based on similarities between the promoters of similarly expressed genes. This new tool, cisExpress, is especially designed for use with large datasets, such as those generated by publicly accessible whole genome and transcriptome projects. cisExpress uses a task farming algorithm to exploit all available computational cores within a shared memory node. We demonstrate the robust nature and validity of the proposed method. It is applicable for use with a wide range of genomic databases for any species of interest.
  
  
  BACKGROUND
  cisExpress is available at www.cisexpress.org.
authors.affiliation: Genomics and Computational Biology Research Group, Faculty of Computing, Engineering and Science, University of South Wales, Pontypridd, UK.
authors.forename: Martin
authors.initials: M
authors.lastname: Triska
authors.forename: David
authors.initials: D
authors.lastname: Grocutt
authors.forename: James
authors.initials: J
authors.lastname: Southern
authors.forename: Denis J
authors.initials: DJ
authors.lastname: Murphy
authors.forename: Tatiana
authors.initials: T
authors.lastname: Tatarinova
mesh_terms: D000465:Algorithms; D017360:Arabidopsis / Q000235:genetics; D004247:DNA / Q000737:chemistry*; D023281:Genomics; D059372:Nucleotide Motifs; D011401:Promoter Regions, Genetic; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software
chemical_list: D004247:DNA