Finding evolutionarily conserved cis-regulatory modules with a universal set of motifs
<p>Abstract</p> <p>Background</p> <p>Finding functional regulatory elements in DNA sequences is a very important problem in computational biology and providing a reliable algorithm for this task would be a major step towards understanding regulatory mechanisms on genome...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2009-03-01
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| Series: | BMC Bioinformatics |
| Online Access: | http://www.biomedcentral.com/1471-2105/10/82 |
| _version_ | 1818529393894490112 |
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| author | Patelak Mateusz Dojer Norbert Wilczynski Bartek Tiuryn Jerzy |
| author_facet | Patelak Mateusz Dojer Norbert Wilczynski Bartek Tiuryn Jerzy |
| author_sort | Patelak Mateusz |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>Finding functional regulatory elements in DNA sequences is a very important problem in computational biology and providing a reliable algorithm for this task would be a major step towards understanding regulatory mechanisms on genome-wide scale. Major obstacles in this respect are that the fact that the amount of non-coding DNA is vast, and that the methods for predicting functional transcription factor binding sites tend to produce results with a high percentage of false positives. This makes the problem of finding regions significantly enriched in binding sites difficult.</p> <p>Results</p> <p>We develop a novel method for predicting regulatory regions in DNA sequences, which is designed to exploit the evolutionary conservation of regulatory elements between species without assuming that the order of motifs is preserved across species. We have implemented our method and tested its predictive abilities on various datasets from different organisms.</p> <p>Conclusion</p> <p>We show that our approach enables us to find a majority of the known CRMs using only sequence information from different species together with currently publicly available motif data. Also, our method is robust enough to perform well in predicting CRMs, despite differences in tissue specificity and even across species, provided that the evolutionary distances between compared species do not change substantially. The complexity of the proposed algorithm is polynomial, and the observed running times show that it may be readily applied.</p> |
| first_indexed | 2024-12-11T17:06:18Z |
| format | Article |
| id | doaj.art-3580332898aa40298538a68d29cade28 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-11T17:06:18Z |
| publishDate | 2009-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-3580332898aa40298538a68d29cade282022-12-22T00:57:40ZengBMCBMC Bioinformatics1471-21052009-03-011018210.1186/1471-2105-10-82Finding evolutionarily conserved cis-regulatory modules with a universal set of motifsPatelak MateuszDojer NorbertWilczynski BartekTiuryn Jerzy<p>Abstract</p> <p>Background</p> <p>Finding functional regulatory elements in DNA sequences is a very important problem in computational biology and providing a reliable algorithm for this task would be a major step towards understanding regulatory mechanisms on genome-wide scale. Major obstacles in this respect are that the fact that the amount of non-coding DNA is vast, and that the methods for predicting functional transcription factor binding sites tend to produce results with a high percentage of false positives. This makes the problem of finding regions significantly enriched in binding sites difficult.</p> <p>Results</p> <p>We develop a novel method for predicting regulatory regions in DNA sequences, which is designed to exploit the evolutionary conservation of regulatory elements between species without assuming that the order of motifs is preserved across species. We have implemented our method and tested its predictive abilities on various datasets from different organisms.</p> <p>Conclusion</p> <p>We show that our approach enables us to find a majority of the known CRMs using only sequence information from different species together with currently publicly available motif data. Also, our method is robust enough to perform well in predicting CRMs, despite differences in tissue specificity and even across species, provided that the evolutionary distances between compared species do not change substantially. The complexity of the proposed algorithm is polynomial, and the observed running times show that it may be readily applied.</p>http://www.biomedcentral.com/1471-2105/10/82 |
| spellingShingle | Patelak Mateusz Dojer Norbert Wilczynski Bartek Tiuryn Jerzy Finding evolutionarily conserved cis-regulatory modules with a universal set of motifs BMC Bioinformatics |
| title | Finding evolutionarily conserved cis-regulatory modules with a universal set of motifs |
| title_full | Finding evolutionarily conserved cis-regulatory modules with a universal set of motifs |
| title_fullStr | Finding evolutionarily conserved cis-regulatory modules with a universal set of motifs |
| title_full_unstemmed | Finding evolutionarily conserved cis-regulatory modules with a universal set of motifs |
| title_short | Finding evolutionarily conserved cis-regulatory modules with a universal set of motifs |
| title_sort | finding evolutionarily conserved cis regulatory modules with a universal set of motifs |
| url | http://www.biomedcentral.com/1471-2105/10/82 |
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