ArticlePLoS computational biology2007
MORPH: probabilistic alignment combined with hidden Markov models of cis-regulatory modules.
Article in PLoS computational biology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- regCNN: identifyingComputational and structural biotechnology journal · 2022Article
- Article
- Efficient representation of uncertainty in multiple sequence alignments using directed acyclic graphs.BMC bioinformatics · 2015Article
- GAMI-CRM: Using de novo motif inference to detect cis-regulatory modules.Proceedings of the ... Congress on Evolutionary Computation. Congress on Evolutionary Computation · 2014Article
- cisMEP: an integrated repository of genomic epigenetic profiles and cis-regulatory modules in Drosophila.BMC systems biology · 2014Article
- A synthetic biology approach to the development of transcriptional regulatory models and custom enhancer design.Methods (San Diego, Calif.) · 2013Article
- Computational identification of active enhancers in model organisms.Genomics, proteomics & bioinformatics · 2013Review
- Genomic approaches towards finding cis-regulatory modules in animals.Nature reviews. Genetics · 2012Review
- A classification of bioinformatics algorithms from the viewpoint of maximizing expected accuracy (MEA).Journal of computational biology : a journal of computational molecular cell biology · 2012Review
- Use of ChIP-Seq data for the design of a multiple promoter-alignment method.Nucleic acids research · 2012Article
- Integrating overlapping structures and background information of words significantly improves biological sequence comparison.PloS one · 2011Article
- Assessing computational methods of cis-regulatory module prediction.PLoS computational biology · 2010Article
- Most transcription factor binding sites are in a few mosaic classes of the human genome.BMC genomics · 2010Article
- BigFoot: Bayesian alignment and phylogenetic footprinting with MCMC.BMC evolutionary biology · 2009Article
- DISCOVER: a feature-based discriminative method for motif search in complex genomes.Bioinformatics (Oxford, England) · 2009Article
- Fast statistical alignment.PLoS computational biology · 2009Article
- Finding evolutionarily conserved cis-regulatory modules with a universal set of motifs.BMC bioinformatics · 2009Article
- Alignment and prediction of cis-regulatory modules based on a probabilistic model of evolution.PLoS computational biology · 2009Article
- On calculating the probability of a set of orthologous sequences.Advances and applications in bioinformatics and chemistry : AABC · 2009Article
- Evolution of regulatory sequences in 12 Drosophila species.PLoS genetics · 2009Article
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2 authors.
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Abstract
The discovery and analysis of cis-regulatory modules (CRMs) in metazoan genomes is crucial for understanding the transcriptional control of development and many other biological processes. Cross-species sequence comparison holds much promise for improving computational prediction of CRMs, for elucidating their binding site composition, and for understanding how they evolve. Current methods for analyzing orthologous CRMs from multiple species rely upon sequence alignments produced by off-the-shelf alignment algorithms, which do not exploit the presence of binding sites in the sequences. We present here a unified probabilistic framework, called MORPH, that integrates the alignment task with binding site predictions, allowing more robust CRM analysis in two species. The framework sums over all possible alignments of two sequences, thus accounting for alignment ambiguities in a natural way. We perform extensive tests on orthologous CRMs from two moderately diverged species Drosophila melanogaster and D. mojavensis, to demonstrate the advantages of the new approach. We show that it can overcome certain computational artifacts of traditional alignment tools and provide a different, likely more accurate, picture of cis-regulatory evolution than that obtained from existing methods. The burgeoning field of cis-regulatory evolution, which is amply supported by the availability of many related genomes, is currently thwarted by the lack of accurate alignments of regulatory regions. Our work will fill in this void and enable more reliable analysis of CRM evolution.
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