title: A multistep bioinformatic approach detects putative regulatory elements in gene promoters.
abstract: BACKGROUND
  Searching for approximate patterns in large promoter sequences frequently produces an exceedingly high numbers of results. Our aim was to exploit biological knowledge for definition of a sheltered search space and of appropriate search parameters, in order to develop a method for identification of a tractable number of sequence motifs.
  
  
  RESULTS
  Novel software (COOP) was developed for extraction of sequence motifs, based on clustering of exact or approximate patterns according to the frequency of their overlapping occurrences. Genomic sequences of 1 Kb upstream of 91 genes differentially expressed and/or encoding proteins with relevant function in adult human retina were analyzed. Methodology and results were tested by analysing 1,000 groups of putatively unrelated sequences, randomly selected among 17,156 human gene promoters. When applied to a sample of human promoters, the method identified 279 putative motifs frequently occurring in retina promoters sequences. Most of them are localized in the proximal portion of promoters, less variable in central region than in lateral regions and similar to known regulatory sequences. COOP software and reference manual are freely available upon request to the Authors.
  
  
  CONCLUSIONS
  The approach described in this paper seems effective for identifying a tractable number of sequence motifs with putative regulatory role.
authors.affiliation: Department of Biology, University of Padova - Via Bassi 58/B, 35131, Padova, Italy. stefibo@bio.unipd.it
authors.forename: Stefania
authors.initials: S
authors.lastname: Bortoluzzi
authors.forename: Alessandro
authors.initials: A
authors.lastname: Coppe
authors.forename: Andrea
authors.initials: A
authors.lastname: Bisognin
authors.forename: Cinzia
authors.initials: C
authors.lastname: Pizzi
authors.forename: Gian Antonio
authors.initials: GA
authors.lastname: Danieli
mesh_terms: D000465:Algorithms; D020816:Amino Acid Motifs; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D017124:Conserved Sequence; D030541:Databases, Genetic; D030562:Databases, Protein; D020224:Expressed Sequence Tags; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D015894:Genome, Human; D006801:Humans; D008969:Molecular Sequence Data; D011401:Promoter Regions, Genetic; D050436:Regulatory Elements, Transcriptional; D012045:Regulatory Sequences, Nucleic Acid; D020218:Response Elements; D017422:Sequence Analysis, DNA; D012984:Software