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• W2100061607 abstract "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.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.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." @default.
• W2100061607 created "2016-06-24" @default.
• W2100061607 creator A5010400627 @default.
• W2100061607 creator A5023573472 @default.
• W2100061607 creator A5038741627 @default.
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• W2100061607 date "2009-03-10" @default.
• W2100061607 modified "2023-10-09" @default.
• W2100061607 title "Finding evolutionarily conserved cis-regulatory modules with a universal set of motifs" @default.
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• W2100061607 doi "https://doi.org/10.1186/1471-2105-10-82" @default.
• W2100061607 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/2669485" @default.
• W2100061607 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/19284541" @default.
• W2100061607 hasPublicationYear "2009" @default.
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