ArticleBMC bioinformatics2007
fREDUCE: detection of degenerate regulatory elements using correlation with expression.
Article in BMC bioinformatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 14 citations in OpenAlex.
- MixMir: microRNA motif discovery from gene expression data using mixed linear models.Nucleic acids research · 2014Article
- Microfluidic affinity and ChIP-seq analyses converge on a conserved FOXP2-binding motif in chimp and human, which enables the detection of evolutionarily novel targets.Nucleic acids research · 2013Article
- Modeling the specificity of protein-DNA interactions.Quantitative biology (Beijing, China) · 2013Article
- Identification and manipulation of the molecular determinants influencing poliovirus recombination.PLoS pathogens · 2013Article
- Basic leucine zipper transcription factor Hac1 binds DNA in two distinct modes as revealed by microfluidic analyses.Proceedings of the National Academy of Sciences of the United States of America · 2012Article
- Active motif finder - a bio-tool based on mutational structures in DNA sequences.Journal of biomedical research · 2011Article
- Insights gained from the reverse engineering of gene networks in keloid fibroblasts.Theoretical biology & medical modelling · 2011Article
- De novo identification and biophysical characterization of transcription-factor binding sites with microfluidic affinity analysis.Nature biotechnology · 2010Article
- A primer on regression methods for decoding cis-regulatory logic.PLoS computational biology · 2009Article
- c-REDUCE: incorporating sequence conservation to detect motifs that correlate with expression.BMC bioinformatics · 2008Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThe precision of transcriptional regulation is made possible by the specificity of physical interactions between transcription factors and their cognate binding sites on DNA. A major challenge is to decipher transcription factor binding sites from sequence and functional genomic data using computational means. While current methods can detect strong binding sites, they are less sensitive to degenerate motifs.
resultsWe present fREDUCE, a computational method specialized for the detection of weak or degenerate binding motifs from gene expression or ChIP-chip data. fREDUCE is built upon the widely applied program REDUCE, which elicits motifs by global statistical correlation of motif counts with expression data. fREDUCE introduces several algorithmic refinements that allow efficient exhaustive searches of oligonucleotides with a specified number of degenerate IUPAC symbols. On yeast ChIP-chip benchmarks, fREDUCE correctly identified motifs and their degeneracies with accuracies greater than its predecessor REDUCE as well as other known motif-finding programs. We have also used fREDUCE to make novel motif predictions for transcription factors with poorly characterized binding sites.
conclusionWe demonstrate that fREDUCE is a valuable tool for the prediction of degenerate transcription factor binding sites, especially from array datasets with weak signals that may elude other motif detection methods.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.