ArticleMolecular systems biology2018
A unified approach for quantifying and interpreting DNA shape readout by transcription factors.
Article in Molecular systems biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
29 citing papers in PubMed, 43 citations in OpenAlex.
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- Gauge fixing for sequence-function relationships.bioRxiv : the preprint server for biology · 2024Article
- Discovering DNA shape motifs with multiple DNA shape features: generalization, methods, and validation.Nucleic acids research · 2024Article
- Predicting DNA structure using a deep learning method.Nature communications · 2024Article
- Three new LmbU targets outside lmb cluster inhibit lincomycin biosynthesis in Streptomyces lincolnensis.Microbial cell factories · 2024Article
- The presence of a G-quadruplex prone sequence upstream of a minimal promoter increases transcriptional activity in the yeast Saccharomyces cerevisiae.Bioscience reports · 2023Article
- Structural underpinnings of mutation rate variations in the human genome.Nucleic acids research · 2023Article
- DNA binding specificity of all four Saccharomyces cerevisiae forkhead transcription factors.Nucleic acids research · 2023Article
- Structural predictions of protein-DNA binding: MELD-DNA.Nucleic acids research · 2023Article
- Flexibility of flanking DNA is a key determinant of transcription factor affinity for the core motif.Biophysical journal · 2022Article
- Comprehensive understanding of Tn5 insertion preference improves transcription regulatory element identification.NAR genomics and bioinformatics · 2021Article
- Insight into the sequence-specific elements leading to increased DNA bending and ligase-mediated circularization propensity by antitumor trabectedin.Journal of computer-aided molecular design · 2021Article
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- LogoJS: a Javascript package for creating sequence logos and embedding them in web applications.Bioinformatics (Oxford, England) · 2020Article
- Atomistic insight into sequence-directed DNA bending and minicircle formation propensity in the absence and presence of phased A-tracts.Journal of computer-aided molecular design · 2020Article
- Mechanistic insights into transcription factor cooperativity and its impact on protein-phenotype interactions.Nature communications · 2020Article
- Motif grammar: The basis of the language of gene expression.Computational and structural biotechnology journal · 2020Review
- Low-Affinity Binding Sites and the Transcription Factor Specificity Paradox in Eukaryotes.Annual review of cell and developmental biology · 2019Review
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
Transcription factors (TFs) interpret DNA sequence by probing the chemical and structural properties of the nucleotide polymer. DNA shape is thought to enable a parsimonious representation of dependencies between nucleotide positions. Here, we propose a unified mathematical representation of the DNA sequence dependence of shape and TF binding, respectively, which simplifies and enhances analysis of shape readout. First, we demonstrate that linear models based on mononucleotide features alone account for 60-70% of the variance in minor groove width, roll, helix twist, and propeller twist. This explains why simple scoring matrices that ignore all dependencies between nucleotide positions can partially account for DNA shape readout by a TF Adding dinucleotide features as sequence-to-shape predictors to our model, we can almost perfectly explain the shape parameters. Building on this observation, we developed a
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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 Socratic graph.