ArticleBiophysical journal2014
Promoter-mediated transcriptional dynamics.
Article in Biophysical journal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 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
28 citing papers in PubMed, 111 citations in OpenAlex.
- Article
- Article
- Association and functional study ofWorld journal of psychiatry · 2025Article
- Quantifying cell fate change under different stochastic gene activation frameworks.Quantitative biology (Beijing, China) · 2025Article
- Deciphering HIV-1 Transcription Initiation and Elongation from Single-Molecule Imaging Data.Research (Washington, D.C.) · 2025Article
- Marker genes reveal dynamic features of cell evolving processes.Bioinformatics advances · 2025Article
- Energy Aware Technology Mapping of Genetic Logic Circuits.ACS synthetic biology · 2024Article
- Energy Aware Technology Mapping of Genetic Logic Circuits.bioRxiv : the preprint server for biology · 2024Article
- What can we learn when fitting a simple telegraph model to a complex gene expression model?PLoS computational biology · 2024Article
- Power-law behavior of transcriptional bursting regulated by enhancer-promoter communication.Genome research · 2024Article
- Transcriptional bursting dynamics in gene expression.Frontiers in genetics · 2024Review
- 4D nucleome equation predicts gene expression controlled by long-range enhancer-promoter interaction.PLoS computational biology · 2023Article
- Quantifying Information of Dynamical Biochemical Reaction Networks.Entropy (Basel, Switzerland) · 2023Article
- Inferring transcriptional bursting kinetics from single-cell snapshot data using a generalized telegraph model.Royal Society open science · 2023Article
- Regulatory Mechanisms for Transcriptional Bursting Revealed by an Event-Based Model.Research (Washington, D.C.) · 2023Article
- Queuing Models of Gene Expression: Analytical Distributions and Beyond.Biophysical journal · 2020Article
- Effects of cell cycle variability on lineage and population measurements of messenger RNA abundance.Journal of the Royal Society, Interface · 2020Article
- Stochastic fluctuations in apoptotic threshold of tumour cells can enhance apoptosis and combat fractional killing.Royal Society open science · 2020Article
- Markovian approaches to modeling intracellular reaction processes with molecular memory.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- Article
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 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genes in eukaryotic cells are typically regulated by complex promoters containing multiple binding sites for a variety of transcription factors, but how promoter dynamics affect transcriptional dynamics has remained poorly understood. In this study, we analyze gene models at the transcriptional regulation level, which incorporate the complexity of promoter structure (PS) defined as transcriptional exits (i.e., ON states of the promoter) and the transition pattern (described by a matrix consisting of transition rates among promoter activity states). We show that multiple exits of transcription are the essential origin of generating multimodal distributions of mRNA, but promoters with the same transition pattern can lead to multimodality of different modes, depending on the regulation of transcriptional factors. In turn, for similar mRNA distributions in the models, the mean ON or OFF time distributions may exhibit different characteristics, thus providing the supplemental information on PS. In addition, we demonstrate that the transcriptional noise can be characterized by a nonlinear function of mean ON and OFF times. These results not only reveal essential characteristics of promoter-mediated transcriptional dynamics but also provide signatures useful for inferring PS based on characteristics of transcriptional outputs.
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.