ArticleGenetics2012
Improved models for transcription factor binding site identification using nonindependent interactions.
Article in Genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers.
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Who cites it
87 citing papers in PubMed.
- GHT-SELEX demonstrates unexpectedly high intrinsic sequence specificity and complex DNA binding of many human transcription factors.Nature methods · 2026Article
- The adaptive landscapes of three globaleLife · 2026Article
- Sequence-based modeling of low-affinity transcription factor-DNA binding through deep learning.NAR genomics and bioinformatics · 2026Article
- AmalgaMo: flexible DNA motif merging.Bioinformatics advances · 2026Article
- Quantifying transcription factor specificity with advanced DNA universal microarrays featuring long and modified binding sites.Nucleic acids research · 2025Article
- Ultra-fast variant effect prediction using biophysical transcription factor binding models.Nucleic acids research · 2025Article
- Interfacial water confers transcription factors with dinucleotide specificity.Nature structural & molecular biology · 2025Article
- Article
- Deciphering regulatory architectures of bacterial promoters from synthetic expression patterns.PLoS computational biology · 2024Article
- Article
- Deciphering regulatory architectures from synthetic single-cell expression patterns.bioRxiv : the preprint server for biology · 2024Article
- A statistical approach for identifying single nucleotide variants that affect transcription factor binding.iScience · 2024Article
- Position Weight Matrix or Acyclic Probabilistic Finite Automaton: Which model to use? A decision rule inferred for the prediction of transcription factor binding sites.Genetics and molecular biology · 2024Article
- Widespread effects of DNA methylation and intra-motif dependencies revealed by novel transcription factor binding models.Nucleic acids research · 2023Article
- Article
- Intrinsic bias estimation for improved analysis of bulk and single-cell chromatin accessibility profiles using SELMA.Nature communications · 2022Article
- BML: a versatile web server for bipartite motif discovery.Briefings in bioinformatics · 2022Article
- SAMPDI-3D: predicting the effects of protein and DNA mutations on protein-DNA interactions.Bioinformatics (Oxford, England) · 2021Article
- The complex architecture of p53 binding sites.Nucleic acids research · 2021Article
- Systematic Evaluation of DNA Sequence Variations onFrontiers in genetics · 2021Article
27 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Identifying transcription factor (TF) binding sites is essential for understanding regulatory networks. The specificity of most TFs is currently modeled using position weight matrices (PWMs) that assume the positions within a binding site contribute independently to binding affinity for any site. Extensive, high-throughput quantitative binding assays let us examine, for the first time, the independence assumption for many TFs. We find that the specificity of most TFs is well fit with the simple PWM model, but in some cases more complex models are required. We introduce a binding energy model (BEM) that can include energy parameters for nonindependent contributions to binding affinity. We show that in most cases where a PWM is not sufficient, a BEM that includes energy parameters for adjacent dinucleotide contributions models the specificity very well. Having more accurate models of specificity greatly improves the interpretation of in vivo TF localization data, such as from chromatin immunoprecipitation followed by sequencing (ChIP-seq) experiments.
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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.