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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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Related in: MedlinePlus

Statistics comparing the accuracy of COOP and of 14 different motif discovery tools on 26 human positive control datasets. Combined measures of correctness over all 26 human datasets, as defined in Methods. The number of datasets (out of 26) for which no motif was predicted by each tool is reported in brackets, following the name of the tool.
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Figure 3: Statistics comparing the accuracy of COOP and of 14 different motif discovery tools on 26 human positive control datasets. Combined measures of correctness over all 26 human datasets, as defined in Methods. The number of datasets (out of 26) for which no motif was predicted by each tool is reported in brackets, following the name of the tool.

Mentions: Moreover, the "combined" statistics summarizing COOP performance over the collection of human datasets, was compared with the same statistics calculated for the 14 different programs tested by Tompa and colleagues on the same datasets [18]. Results are presented in Figure 3 and in Table 7 [see Additional file 2].


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

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

Statistics comparing the accuracy of COOP and of 14 different motif discovery tools on 26 human positive control datasets. Combined measures of correctness over all 26 human datasets, as defined in Methods. The number of datasets (out of 26) for which no motif was predicted by each tool is reported in brackets, following the name of the tool.
© Copyright Policy
Related In: Results  -  Collection

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

Figure 3: Statistics comparing the accuracy of COOP and of 14 different motif discovery tools on 26 human positive control datasets. Combined measures of correctness over all 26 human datasets, as defined in Methods. The number of datasets (out of 26) for which no motif was predicted by each tool is reported in brackets, following the name of the tool.
Mentions: Moreover, the "combined" statistics summarizing COOP performance over the collection of human datasets, was compared with the same statistics calculated for the 14 different programs tested by Tompa and colleagues on the same datasets [18]. Results are presented in Figure 3 and in Table 7 [see Additional file 2].

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
Related in: MedlinePlus