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Bioinformatics
Article . 2004 . Peer-reviewed
Data sources: Crossref
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Bioinformatics
Article
Data sources: UnpayWall
Bioinformatics
Article . 2005
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Prediction of similarly acting cis-regulatory modules by subsequence profiling and comparative genomics in Drosophila melanogaster and D.pseudoobscura

Authors: Yonatan H, Grad; Frederick P, Roth; Marc S, Halfon; George M, Church;

Prediction of similarly acting cis-regulatory modules by subsequence profiling and comparative genomics in Drosophila melanogaster and D.pseudoobscura

Abstract

Abstract Motivation: To date, computational searches for cis-regulatory modules (CRMs) have relied on two methods. The first, phylogenetic footprinting, has been used to find CRMs in non-coding sequence, but does not directly link DNA sequence with spatio-temporal patterns of expression. The second, based on searches for combinations of transcription factor (TF) binding motifs, has been employed in genome-wide discovery of similarly acting enhancers, but requires prior knowledge of the set of TFs acting at the CRM and the TFs' binding motifs. Results: We propose a method for CRM discovery that combines aspects of both approaches in an effort to overcome their individual limitations. By treating phylogenetically footprinted non-coding regions (PFRs) as proxies for CRMs, we endeavor to find PFRs near co-regulated genes that are comprised of similar short, conserved sequences. Using Markov chains as a convenient formulation to assess similarity, we develop a sampling algorithm to search a large group of PFRs for the most similar subset. When starting with a set of genes involved in Drosophila early blastoderm development and using phylogenetic comparisons of Drosophila melanogaster and D.pseudoobscura genomes, we show here that our algorithm successfully detects known CRMs. Further, we use our similarity metric, based on Markov chain discrimination, in a genome-wide search, and uncover additional known and many candidate early blastoderm CRMs. Availability: Software is available via http://arep.med.harvard.edu/enhancers Supplementary information: Can be accessed at http://arep.med.harvard.edu/enhancers

Keywords

Gene Expression Profiling, DNA Footprinting, Chromosome Mapping, Gene Expression Regulation, Developmental, Sequence Analysis, DNA, Regulatory Sequences, Nucleic Acid, Species Specificity, Sequence Homology, Nucleic Acid, Consensus Sequence, Genes, Regulator, Animals, Drosophila, Sequence Alignment, Algorithms, Phylogeny, Software

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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
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    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
55
Average
Top 10%
Top 10%
gold