ArticleBioinformatics (Oxford, England)2013
Identification of transcription factor binding sites from ChIP-seq data at high resolution.
Article in Bioinformatics (Oxford, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
38 citing papers in PubMed, 69 citations in OpenAlex.
- Molecular Genetics and Epigenetics Regulatory Role of miRNAs on Adipogenesis and Intramuscular Fat Development in Beef Cattle: In the Context of Meat Quality.Molecular biotechnology · 2026Review
- Variability in intrinsic promoter strength underlies the temporal hierarchy of the Caulobacter SOS response induction.PLoS biology · 2025Article
- Synergistic roles of NFATc1 and c-Jun in immunomodulation.Biochemistry and biophysics reports · 2025Review
- Widespread prevalence of a methylation-dependent switch to activate an essential DNA damage response in bacteria.PLoS biology · 2024Article
- MAE-seq refines regulatory elements across the genome.Nucleic acids research · 2024Article
- Epigenetic targets in B- and T-cell lymphomas: latest developments.Therapeutic advances in hematology · 2023Review
- An ancestral Wnt-Brachyury feedback loop in axial patterning and recruitment of mesoderm-determining target genes.Nature ecology & evolution · 2022Article
- Pan-cancer predictions of transcription factors mediating aberrant DNA methylation.Epigenetics & chromatin · 2022Article
- Uncovering the mesendoderm gene regulatory network through multi-omic data integration.Cell reports · 2022Article
- Genome-wide mapping of Vibrio cholerae VpsT binding identifies a mechanism for c-di-GMP homeostasis.Nucleic acids research · 2022Article
- Theoretical characterisation of strand cross-correlation in ChIP-seq.BMC bioinformatics · 2020Article
- TFmotifView: a webserver for the visualization of transcription factor motifs in genomic regions.Nucleic acids research · 2020Article
- Comparative analysis of ChIP-exo peak-callers: impact of data quality, read duplication and binding subtypes.BMC bioinformatics · 2020Article
- RECAP reveals the true statistical significance of ChIP-seq peak calls.Bioinformatics (Oxford, England) · 2019Article
- Signal peptide peptidase activity connects the unfolded protein response to plant defense suppression by Ustilago maydis.PLoS pathogens · 2019Article
- CG dinucleotides enhance promoter activity independent of DNA methylation.Genome research · 2019Article
- Characterizing protein-DNA binding event subtypes in ChIP-exo data.Bioinformatics (Oxford, England) · 2019Article
- Differential analysis of chromatin accessibility and histone modifications for predicting mouse developmental enhancers.Nucleic acids research · 2018Article
- Disentangling transcription factor binding site complexity.Nucleic acids research · 2018Article
- Base-pair resolution detection of transcription factor binding site by deep deconvolutional network.Bioinformatics (Oxford, England) · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
motivationChromatin immunoprecipitation coupled to next-generation sequencing (ChIP-seq) is widely used to study the in vivo binding sites of transcription factors (TFs) and their regulatory targets. Recent improvements to ChIP-seq, such as increased resolution, promise deeper insights into transcriptional regulation, yet require novel computational tools to fully leverage their advantages.
resultsTo this aim, we have developed peakzilla, which can identify closely spaced TF binding sites at high resolution (i.e. resolves individual binding sites even if spaced closely), as we demonstrate using semisynthetic datasets, performing ChIP-seq for the TF Twist in Drosophila embryos with different experimental fragment sizes, and analyzing ChIP-exo datasets. We show that the increased resolution reached by peakzilla is highly relevant, as closely spaced Twist binding sites are strongly enriched in transcriptional enhancers, suggesting a signature to discriminate functional from abundant non-functional or neutral TF binding. Peakzilla is easy to use, as it estimates all the necessary parameters from the data and is freely available. AVAILABILITY AND IMPLEMENTATION: The peakzilla program is available from https://github.com/steinmann/peakzilla or http://www.starklab.org/data/peakzilla/. CONTACT: stark@starklab.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Indexed as
Identifiers
What OpenQuestion holds
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.