ReviewNature reviews. Genetics2009
From DNA sequence to transcriptional behaviour: a quantitative approach.
Review in Nature reviews. Genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 139 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
139 citing papers in PubMed, 274 citations in OpenAlex.
- AlphaGenome-enabled analysis of non-coding regulatory variants underlyingbioRxiv : the preprint server for biology · 2026Article
- Article
- Engineered histones reshape chromatin in human cells.bioRxiv : the preprint server for biology · 2025Article
- OpenSpliceAI: An efficient, modular implementation of SpliceAI enabling easy retraining on non-human species.bioRxiv : the preprint server for biology · 2025Article
- A DNA base-specific sequence interposed between CRX and NRL contributes to RHODOPSIN expression.Scientific reports · 2024Article
- InterpretingNature machine intelligence · 2024Article
- InterpretingbioRxiv : the preprint server for biology · 2024Article
- Article
- Nucleosome breathing facilitates cooperative binding of pluripotency factors Sox2 and Oct4 to DNA.Biophysical journal · 2022Article
- Generating specificity in genome regulation through transcription factor sensitivity to chromatin.Nature reviews. Genetics · 2022Review
- Quantitative Frameworks for Multivalent Macromolecular Interactions in Biological Linear Lattice Systems.Molecules and cells · 2022Review
- Profiling the quantitative occupancy of myriad transcription factors across conditions by modeling chromatin accessibility data.Genome research · 2022Article
- Anticipating response function in gene regulatory networks.Journal of the Royal Society, Interface · 2021Article
- Differential transcriptional regulation of the NANOG gene in chicken primordial germ cells and embryonic stem cells.Journal of animal science and biotechnology · 2021Article
- Runx proteins and transcriptional mechanisms that govern memory CD8 T cell development.Immunological reviews · 2021Review
- Learning the Regulatory Code of Gene Expression.Frontiers in molecular biosciences · 2021Review
- Insights into Transcriptional Repression of the Homologous Toxin-Antitoxin CassettesInternational journal of molecular sciences · 2020Article
- Exercise adaptations: molecular mechanisms and potential targets for therapeutic benefit.Nature reviews. Endocrinology · 2020Review
- Tuning Transcription Factor Availability through Acetylation-Mediated Genomic Redistribution.Molecular cell · 2020Article
- Deciphering eukaryotic gene-regulatory logic with 100 million random promoters.Nature biotechnology · 2020Article
79 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
2 authors at 2 institutions in 2 countries.
Funding
Abstract
Complex transcriptional behaviours are encoded in the DNA sequences of gene regulatory regions. Advances in our understanding of these behaviours have been recently gained through quantitative models that describe how molecules such as transcription factors and nucleosomes interact with genomic sequences. An emerging view is that every regulatory sequence is associated with a unique binding affinity landscape for each molecule and, consequently, with a unique set of molecule-binding configurations and transcriptional outputs. We present a quantitative framework based on existing methods that unifies these ideas. This framework explains many experimental observations regarding the binding patterns of factors and nucleosomes and the dynamics of transcriptional activation. It can also be used to model more complex phenomena such as transcriptional noise and the evolution of transcriptional regulation.
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.