ArticleBMC bioinformatics2009
Finding evolutionarily conserved cis-regulatory modules with a universal set of motifs.
Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 28 citations in OpenAlex.
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- RGT: a toolbox for the integrative analysis of high throughput regulatory genomics data.BMC bioinformatics · 2023Article
- Identification of transcription factor binding sites using ATAC-seq.Genome biology · 2019Article
- Sox5 regulates beta-cell phenotype and is reduced in type 2 diabetes.Nature communications · 2017Article
- Taking promoters out of enhancers in sequence based predictions of tissue-specific mammalian enhancers.BMC medical genomics · 2017Article
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- Analysis of computational footprinting methods for DNase sequencing experiments.Nature methods · 2016Article
- Enhanceosome transcription factors preferentially dimerize with high mobility group proteins.BMC systems biology · 2016Article
- Optimally choosing PWM motif databases and sequence scanning approaches based on ChIP-seq data.BMC bioinformatics · 2015Article
- Replicative senescence is associated with nuclear reorganization and with DNA methylation at specific transcription factor binding sites.Clinical epigenetics · 2015Article
- The interaction of MYC with the trithorax protein ASH2L promotes gene transcription by regulating H3K27 modification.Nucleic acids research · 2014Article
- Active enhancer positions can be accurately predicted from chromatin marks and collective sequence motif data.BMC systems biology · 2013Article
- Bioinformatics and computational biology in Poland.PLoS computational biology · 2013Article
- Evolutionary divergence and limits of conserved non-coding sequence detection in plant genomes.Nucleic acids research · 2011Article
- Phylogeny disambiguates the evolution of heat-shock cis-regulatory elements in Drosophila.PloS one · 2010Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFinding 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.
resultsWe 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.
conclusionWe 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.
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