ArticleGenome research2009
An ensemble model of competitive multi-factor binding of the genome.
Article in Genome research, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.
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Who cites it
59 citing papers in PubMed, 111 citations in OpenAlex.
- Inferring differential protein binding from time-series chromatin accessibility data.Bioinformatics advances · 2025Article
- Deep molecular learning of transcriptional control of a synthetic CRE enhancer and its variants.iScience · 2024Article
- High-throughput data and modeling reveal insights into the mechanisms of cooperative DNA-binding by transcription factor proteins.Nucleic acids research · 2023Article
- Profiling the quantitative occupancy of myriad transcription factors across conditions by modeling chromatin accessibility data.Genome research · 2022Article
- Cooperative kinetics of ligand binding to linear polymers.Computational and structural biotechnology journal · 2022Article
- Quantitative-enhancer-FACS-seq (QeFS) reveals epistatic interactions among motifs within transcriptional enhancers in developing Drosophila tissue.Genome biology · 2021Article
- High throughput screening identifies SOX2 as a super pioneer factor that inhibits DNA methylation maintenance at its binding sites.Nature communications · 2021Article
- Molecular Co-occupancy Identifies Transcription Factor Binding Cooperativity In Vivo.Molecular cell · 2021Article
- Thermodynamic modeling of genome-wide nucleosome depleted regions in yeast.PLoS computational biology · 2021Article
- A High-Resolution Map of Human Enhancer RNA Loci Characterizes Super-enhancer Activities in Cancer.Cancer cell · 2020Article
- Diffusion of DNA-Binding Species in the Nucleus: A Transient Anomalous Subdiffusion Model.Biophysical journal · 2020Article
- RoboCOP: Multivariate State Space Model Integrating Epigenomic Accessibility Data to Elucidate Genome-Wide Chromatin Occupancy.Research in computational molecular biology : ... Annual International Conference, RECOMB ... : proceedings. RECOMB (Conference : 2005- ) · 2020Article
- Nascent chromatin occupancy profiling reveals locus- and factor-specific chromatin maturation dynamics behind the DNA replication fork.Genome research · 2019Article
- The Role of Chromatin Accessibility in cis-Regulatory Evolution.Genome biology and evolution · 2019Article
- Application of Computational Biology and Artificial Intelligence Technologies in Cancer Precision Drug Discovery.BioMed research international · 2019Review
- Canonical and single-cell Hi-C reveal distinct chromatin interaction sub-networks of mammalian transcription factors.Genome biology · 2018Article
- Single-molecule DNA unzipping reveals asymmetric modulation of a transcription factor by its binding site sequence and context.Nucleic acids research · 2018Article
- Inherent limitations of probabilistic models for protein-DNA binding specificity.PLoS computational biology · 2017Article
- Quantitative modeling of gene expression using DNA shape features of binding sites.Nucleic acids research · 2016Article
- Mapping nucleosome positions using DNase-seq.Genome research · 2016Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Hundreds of different factors adorn the eukaryotic genome, binding to it in large number. These DNA binding factors (DBFs) include nucleosomes, transcription factors (TFs), and other proteins and protein complexes, such as the origin recognition complex (ORC). DBFs compete with one another for binding along the genome, yet many current models of genome binding do not consider different types of DBFs together simultaneously. Additionally, binding is a stochastic process that results in a continuum of binding probabilities at any position along the genome, but many current models tend to consider positions as being either binding sites or not. Here, we present a model that allows a multitude of DBFs, each at different concentrations, to compete with one another for binding sites along the genome. The result is an "occupancy profile," a probabilistic description of the DNA occupancy of each factor at each position. We implement our model efficiently as the software package COMPETE. We demonstrate genome-wide and at specific loci how modeling nucleosome binding alters TF binding, and vice versa, and illustrate how factor concentration influences binding occupancy. Binding cooperativity between nearby TFs arises implicitly via mutual competition with nucleosomes. Our method applies not only to TFs, but also recapitulates known occupancy profiles of a well-studied replication origin with and without ORC binding. Importantly, the sequence preferences our model takes as input are derived from in vitro experiments. This ensures that the calculated occupancy profiles are the result of the forces of competition represented explicitly in our model and the inherent sequence affinities of the constituent DBFs.
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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.