ArticlePloS one2009
Modeling the quantitative specificity of DNA-binding proteins from example binding sites.
Article in PloS one, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- From biophysics to 'omics and systems biology.European biophysics journal : EBJ · 2019Review
- Inherent limitations of probabilistic models for protein-DNA binding specificity.PLoS computational biology · 2017Article
- P-value-based regulatory motif discovery using positional weight matrices.Genome research · 2013Article
- Improved models for transcription factor binding site identification using nonindependent interactions.Genetics · 2012Article
- Article
- Thermodynamics-based models of transcriptional regulation by enhancers: the roles of synergistic activation, cooperative binding and short-range repression.PLoS computational biology · 2010Article
- Inferring binding energies from selected binding sites.PLoS computational biology · 2009Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundThe binding of transcription factors to their respective DNA sites is a key component of every regulatory network. Predictions of transcription factor binding sites are usually based on models for transcription factor specificity. These models, in turn, are often based on examples of known binding sites. METHODOLOGY/PRINCIPAL
findingsCollections of binding sites are obtained in simulation experiments where the true model for the transcription factor is known and various sampling procedures are employed. We compare the accuracies of three different and commonly used methods for predicting the specificity of the transcription factor based on example binding sites. Different methods for constructing the models can lead to significant differences in the accuracy of the predictions and we show that commonly used methods can be positively misleading, even at large sample sizes and using noise-free data. Methods that minimize the number of predicted binding sequences are often significantly more accurate than the other methods tested. CONCLUSIONS/SIGNIFICANCE: Different methods for generating motifs from example binding sites can have significantly different numbers of false positive and false negative predictions. For many different sampling procedures models based on quadratic programming are the most accurate.
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Registered trials
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