ArticleNucleic acids research2013
TherMos: Estimating protein-DNA binding energies from in vivo binding profiles.
Article in Nucleic acids research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Article
- Characterizing the targets of transcription regulators by aggregating ChIP-seq and perturbation expression data sets.Genome research · 2023Article
- Genome-wide mapping of G-quadruplex structures with CUT&Tag.Nucleic acids research · 2022Article
- Insights from resolving protein-DNA interactions at near base-pair resolution.Briefings in functional genomics · 2018Review
- Bayesian Markov models consistently outperform PWMs at predicting motifs in nucleotide sequences.Nucleic acids research · 2016Article
- Structure and decoy-mediated inhibition of the SOX18/Prox1-DNA interaction.Nucleic acids research · 2016Article
- Non-canonical NF-κB signalling and ETS1/2 cooperatively drive C250T mutant TERT promoter activation.Nature cell biology · 2015Article
- Decoupling of evolutionary changes in transcription factor binding and gene expression in mammals.Genome research · 2015Article
- Absence of a simple code: how transcription factors read the genome.Trends in biochemical sciences · 2014Review
- Quality versus accuracy: result of a reanalysis of protein-binding microarrays from the DREAM5 challenge by using BayesPI2 including dinucleotide interdependence.BMC bioinformatics · 2014Article
- Evidence supporting the existence of a NUPR1-like family of helix-loop-helix chromatin proteins related to, yet distinct from, AT hook-containing HMG proteins.Journal of molecular modeling · 2014Article
- A transcription factor network specifying inhibitory versus excitatory neurons in the dorsal spinal cord.Development (Cambridge, England) · 2014Article
- Motif-based analysis of large nucleotide data sets using MEME-ChIP.Nature protocols · 2014Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurately characterizing transcription factor (TF)-DNA affinity is a central goal of regulatory genomics. Although thermodynamics provides the most natural language for describing the continuous range of TF-DNA affinity, traditional motif discovery algorithms focus instead on classification paradigms that aim to discriminate 'bound' and 'unbound' sequences. Moreover, these algorithms do not directly model the distribution of tags in ChIP-seq data. Here, we present a new algorithm named Thermodynamic Modeling of ChIP-seq (TherMos), which directly estimates a position-specific binding energy matrix (PSEM) from ChIP-seq/exo tag profiles. In cross-validation tests on seven genome-wide TF-DNA binding profiles, one of which we generated via ChIP-seq on a complex developing tissue, TherMos predicted quantitative TF-DNA binding with greater accuracy than five well-known algorithms. We experimentally validated TherMos binding energy models for Klf4 and Esrrb, using a novel protocol to measure PSEMs in vitro. Strikingly, our measurements revealed strong non-additivity at multiple positions within the two PSEMs. Among the algorithms tested, only TherMos was able to model the entire binding energy landscape of Klf4 and Esrrb. Our study reveals new insights into the energetics of TF-DNA binding in vivo and provides an accurate first-principles approach to binding energy inference from ChIP-seq and ChIP-exo data.
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