ArticleBioinformatics (Oxford, England)2009
Predicting the binding preference of transcription factors to individual DNA k-mers.
Article in Bioinformatics (Oxford, England), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 28 citations in OpenAlex.
- Structure-based learning to predict and model protein-DNA interactions and transcription-factor co-operativity inNAR genomics and bioinformatics · 2024Article
- DNA binding analysis of rare variants in homeodomains reveals homeodomain specificity-determining residues.Nature communications · 2024Article
- The master regulator MAT1-1-1 of fungal mating binds to its targets via a conserved motif in the human pathogen Aspergillus fumigatus.G3 (Bethesda, Md.) · 2021Article
- The geometric influence on the Cys2His2 zinc finger domain and functional plasticity.Nucleic acids research · 2020Article
- Integrated analysis of motif activity and gene expression changes of transcription factors.Genome research · 2018Article
- Past Roadblocks and New Opportunities in Transcription Factor Network Mapping.Trends in genetics : TIG · 2016Review
- Affinity regression predicts the recognition code of nucleic acid-binding proteins.Nature biotechnology · 2015Article
- Understanding the limits of animal models as predictors of human biology: lessons learned from the sbv IMPROVER Species Translation Challenge.Bioinformatics (Oxford, England) · 2015Article
- Automated genomic context analysis and experimental validation platform for discovery of prokaryote transcriptional regulator functions.BMC genomics · 2014Article
- Article
- An improved predictive recognition model for Cys(2)-His(2) zinc finger proteins.Nucleic acids research · 2014Article
- Modeling DNA affinity landscape through two-round support vector regression with weighted degree kernels.BMC systems biology · 2014Article
- Using topology to tame the complex biochemistry of genetic networks.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2013Article
- An improved SELEX-Seq strategy for characterizing DNA-binding specificity of transcription factor: NF-κB as an example.PloS one · 2013Article
- Computational identification of diverse mechanisms underlying transcription factor-DNA occupancy.PLoS genetics · 2013Article
- Exploring the DNA-recognition potential of homeodomains.Genome research · 2012Article
- Recognition models to predict DNA-binding specificities of homeodomain proteins.Bioinformatics (Oxford, England) · 2012Article
- Increasing coverage of transcription factor position weight matrices through domain-level homology.PloS one · 2012Article
- Article
- Determining the specificity of protein-DNA interactions.Nature reviews. Genetics · 2010Review
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Authors and funding
10 authors at 4 institutions in 2 countries.
Funding
Abstract
motivationRecognition of specific DNA sequences is a central mechanism by which transcription factors (TFs) control gene expression. Many TF-binding preferences, however, are unknown or poorly characterized, in part due to the difficulty associated with determining their specificity experimentally, and an incomplete understanding of the mechanisms governing sequence specificity. New techniques that estimate the affinity of TFs to all possible k-mers provide a new opportunity to study DNA-protein interaction mechanisms, and may facilitate inference of binding preferences for members of a given TF family when such information is available for other family members.
resultsWe employed a new dataset consisting of the relative preferences of mouse homeodomains for all eight-base DNA sequences in order to ask how well we can predict the binding profiles of homeodomains when only their protein sequences are given. We evaluated a panel of standard statistical inference techniques, as well as variations of the protein features considered. Nearest neighbour among functionally important residues emerged among the most effective methods. Our results underscore the complexity of TF-DNA recognition, and suggest a rational approach for future analyses of TF families.
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Registered trials
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.