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A multistep bioinformatic approach detects putative regulatory elements in gene promoters.

Bortoluzzi S, Coppe A, Bisognin A, Pizzi C, Danieli GA - BMC Bioinformatics (2005)

Bottom Line: Searching for approximate patterns in large promoter sequences frequently produces an exceedingly high numbers of results.Methodology and results were tested by analysing 1,000 groups of putatively unrelated sequences, randomly selected among 17,156 human gene promoters.The approach described in this paper seems effective for identifying a tractable number of sequence motifs with putative regulatory role.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Biology, University of Padova - Via Bassi 58/B, 35131, Padova, Italy. stefibo@bio.unipd.it

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.

Conclusion: The approach described in this paper seems effective for identifying a tractable number of sequence motifs with putative regulatory role.

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Flow-chart of COOP program. Input, output and main steps are shown.
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Figure 1: Flow-chart of COOP program. Input, output and main steps are shown.

Mentions: Since sequence signals with biological significance are frequently subtle, stringency of pattern discovery analyses in biological sequences cannot be set too high. This implies that results are often too numerous. A novel tool for Clustering Overlapping Occurrences of approximate Patterns (COOP) was implemented in Python (Figure 1). This software allows identification of tractable numbers of possibly interesting motifs, starting from large numbers of exact or approximate patterns.


A multistep bioinformatic approach detects putative regulatory elements in gene promoters.

Bortoluzzi S, Coppe A, Bisognin A, Pizzi C, Danieli GA - BMC Bioinformatics (2005)

Flow-chart of COOP program. Input, output and main steps are shown.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC1173081&req=5

Figure 1: Flow-chart of COOP program. Input, output and main steps are shown.
Mentions: Since sequence signals with biological significance are frequently subtle, stringency of pattern discovery analyses in biological sequences cannot be set too high. This implies that results are often too numerous. A novel tool for Clustering Overlapping Occurrences of approximate Patterns (COOP) was implemented in Python (Figure 1). This software allows identification of tractable numbers of possibly interesting motifs, starting from large numbers of exact or approximate patterns.

Bottom Line: Searching for approximate patterns in large promoter sequences frequently produces an exceedingly high numbers of results.Methodology and results were tested by analysing 1,000 groups of putatively unrelated sequences, randomly selected among 17,156 human gene promoters.The approach described in this paper seems effective for identifying a tractable number of sequence motifs with putative regulatory role.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Biology, University of Padova - Via Bassi 58/B, 35131, Padova, Italy. stefibo@bio.unipd.it

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.

Conclusion: The approach described in this paper seems effective for identifying a tractable number of sequence motifs with putative regulatory role.

Show MeSH