ReviewBriefings in functional genomics2015
Using protein-binding microarrays to study transcription factor specificity: homologs, isoforms and complexes.
Review in Briefings in functional genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- DNA methylation shapes transcription factor binding beyond canonical CpG contexts.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Thermal shift engagement assay for Class IIA histone deacetylase inhibitor screening.Results in chemistry · 2025Article
- Experimental approaches to investigate biophysical interactions between homeodomain transcription factors and DNA.Biochimica et biophysica acta. Gene regulatory mechanisms · 2025Review
- Protein target search diffusion-association/dissociation free energy landscape around DNA binding site with flanking sequences.Biophysical journal · 2025Article
- Review
- Prediction and Experimental Validation of a New Salinity-Responsive Cis-Regulatory Element (CRE) in a Tilapia Cell Line.Life (Basel, Switzerland) · 2022Article
- Review
- Inferring primase-DNA specific recognition using a data driven approach.Nucleic acids research · 2021Article
- Custom DNA Microarrays Reveal Diverse Binding Preferences of Proteins and Small Molecules to Thousands of G-Quadruplexes.ACS chemical biology · 2020Article
- NextPBM: a platform to study cell-specific transcription factor binding and cooperativity.Nucleic acids research · 2019Article
- DNA-binding landscape of IRF3, IRF5 and IRF7 dimers: implications for dimer-specific gene regulation.Nucleic acids research · 2018Article
- Insights from resolving protein-DNA interactions at near base-pair resolution.Briefings in functional genomics · 2018Review
- Modeling protein-DNA binding via high-throughput in vitro technologies.Briefings in functional genomics · 2017Article
- Dry and wet approaches for genome-wide functional annotation of conventional and unconventional transcriptional activators.Computational and structural biotechnology journal · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Protein-DNA binding is central to specificity in gene regulation, and methods for characterizing transcription factor (TF)-DNA binding remain crucial to studies of regulatory specificity. High-throughput (HT) technologies have revolutionized our ability to characterize protein-DNA binding by significantly increasing the number of binding measurements that can be performed. Protein-binding microarrays (PBMs) are a robust and powerful HT platform for studying DNA-binding specificity of TFs. Analysis of PBM-determined DNA-binding profiles has provided new insight into the scope and mechanisms of TF binding diversity. In this review, we focus specifically on the PBM technique and discuss its application to the study of TF specificity, in particular, the binding diversity of TF homologs and multi-protein complexes.
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.