ArticleQuantitative biology (Beijing, China)2013
Modeling the specificity of protein-DNA interactions.
Article in Quantitative biology (Beijing, China), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 136 papers.
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Who cites it
136 citing papers in PubMed.
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- GaugeFixer: overcoming parameter non-identifiability in models of sequence-function relationships.bioRxiv : the preprint server for biology · 2026Article
- Sequence-based modeling of low-affinity transcription factor-DNA binding through deep learning.NAR genomics and bioinformatics · 2026Article
- Inference and Visualization of Complex Genotype-Phenotype Maps.Molecular biology and evolution · 2026Article
- Bistability in type I toxin-antitoxin systems may lead to stress-induced persister formation.NPJ systems biology and applications · 2025Article
- QTFPred: robust high-performance quantum machine learning modeling that predicts main and cooperative transcription factor bindings with base resolution.Briefings in bioinformatics · 2025Article
- Predicting gene expression from DNA sequence using deep learning models.Nature reviews. Genetics · 2025Review
- Inference and visualization of complex genotype-phenotype maps withbioRxiv : the preprint server for biology · 2025Article
- Modeling combinatorial regulation from single-cell multi-omics provides regulatory units underpinning cell type landscape using cRegulon.Genome biology · 2025Article
- Explainable AI in Genomics: Transcription Factor Binding Site Prediction with Mixture of Experts.ArXiv · 2025Article
- Benchmarking transcription factor binding site prediction models: a comparative analysis on synthetic and biological data.Briefings in bioinformatics · 2025Article
- ZNF146 accelerates lung adenocarcinoma progression through MDM2/p53 and PHGDH/ferroptosis.Cell & bioscience · 2025Article
- Characterizing DNA recognition preferences of transcription factors using global couplings and high-throughput sequencing.Nucleic acids research · 2025Article
- Collective unstructured interactions drive chromatin binding of transcription factors.bioRxiv : the preprint server for biology · 2025Article
- Identifying deleterious noncoding variation through gain and loss of CTCF binding activity.American journal of human genetics · 2025Article
- Three- and four-stranded nucleic acid structures and their ligands.RSC chemical biology · 2025Review
- Interfacial water confers transcription factors with dinucleotide specificity.Nature structural & molecular biology · 2025Article
- A systematic survey of TF function in E. coli suggests RNAP stabilization is a prevalent strategy for both repressors and activators.Nucleic acids research · 2025Article
76 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
1 author.
Funding
Abstract
The specificity of protein-DNA interactions is most commonly modeled using position weight matrices (PWMs). First introduced in 1982, they have been adapted to many new types of data and many different approaches have been developed to determine the parameters of the PWM. New high-throughput technologies provide a large amount of data rapidly and offer an unprecedented opportunity to determine accurately the specificities of many transcription factors (TFs). But taking full advantage of the new data requires advanced algorithms that take into account the biophysical processes involved in generating the data. The new large datasets can also aid in determining when the PWM model is inadequate and must be extended to provide accurate predictions of binding sites. This article provides a general mathematical description of a PWM and how it is used to score potential binding sites, a brief history of the approaches that have been developed and the types of data that are used with an emphasis on algorithms that we have developed for analyzing high-throughput datasets from several new technologies. It also describes extensions that can be added when the simple PWM model is inadequate and further enhancements that may be necessary. It briefly describes some applications of PWMs in the discovery and modeling of in vivo regulatory networks.
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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.