ReviewTrends in biochemical sciences2014
Absence of a simple code: how transcription factors read the genome.
Review in Trends in biochemical sciences, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 313 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
313 citing papers in PubMed, 568 citations in OpenAlex.
- A transcription factor by any other name - function beyond DNA binding and transactivation.EMBO reports · 2026Review
- Exchange dynamics and kinetic control of gene regulation complexes.Nature reviews. Molecular cell biology · 2026Review
- An atlas of transcription factor cooperation reveals how motif readers shape regulatory output.bioRxiv : the preprint server for biology · 2026Article
- UnlockingNAR genomics and bioinformatics · 2026Article
- Nonconsensus flanking sequence of hundreds of base pairs around in vivo binding sites: statistical beacons for transcription factor scanning.Nucleic acids research · 2026Article
- Challenges in predicting chromatin accessibility differences between species.NAR genomics and bioinformatics · 2026Article
- Unstructured transcription factor interactions enable emergent specificity.Science (New York, N.Y.) · 2026Article
- ChromBERT: A foundation model for learning interpretable representations for context-specific transcriptional regulatory networks.Cell genomics · 2026Article
- Sequence-based modeling of low-affinity transcription factor-DNA binding through deep learning.NAR genomics and bioinformatics · 2026Article
- High-resolution map of chromatin accessibility - insights into the focused binding of a large number of transcription factors.Epigenetics & chromatin · 2026Article
- A Deep Learning Framework with Multi-perspective Feature Fusion for Transcription Factor Binding Site Prediction.Interdisciplinary sciences, computational life sciences · 2026Article
- inMOTIFin: a lightweight end-to-end simulation software for regulatory sequences.Bioinformatics (Oxford, England) · 2026Article
- Chromatin state architecture governs transcription factor accessibility across plant genomes.PLoS genetics · 2026Article
- Decoding the Central Dogma: Quantitative Insights into Transcription and Translation Dynamics in the p53-Mediated DNA Damage Response.Journal of molecular biology · 2026Review
- The Glucocorticoid Receptor Inhibits NRF2-Mediated Expression of SLC7A11.Free radical biology & medicine · 2025Article
- Multimodal single cell analyses reveal gene networks of planarian stem cell differentiation.Nature communications · 2025Article
- Challenges in Predicting Chromatin Accessibility Differences between Species.bioRxiv : the preprint server for biology · 2025Article
- DMRU: generative deep learning to unravel condition-specific cytosine methylation in plants.Briefings in bioinformatics · 2025Article
- Computational design of sequence-specific DNA-binding proteins.Nature structural & molecular biology · 2025Article
- Combining Motifs, CRE Activity, And Gene Expression Data Using ML Greatly Improves the Accuracy of Tissue-Specific TF Network Maps.bioRxiv : the preprint server for biology · 2025Article
253 more citing papers are in PubMed but not listed here.
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 1 country.
Funding
Abstract
Transcription factors (TFs) influence cell fate by interpreting the regulatory DNA within a genome. TFs recognize DNA in a specific manner; the mechanisms underlying this specificity have been identified for many TFs based on 3D structures of protein-DNA complexes. More recently, structural views have been complemented with data from high-throughput in vitro and in vivo explorations of the DNA-binding preferences of many TFs. Together, these approaches have greatly expanded our understanding of TF-DNA interactions. However, the mechanisms by which TFs select in vivo binding sites and alter gene expression remain unclear. Recent work has highlighted the many variables that influence TF-DNA binding, while demonstrating that a biophysical understanding of these many factors will be central to understanding TF function.
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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.