ArticleiScience2026
Using the simple telegraph model to decipher transcriptional burst regulation across genome-wide data.
Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Integrating zero-inflation correction and transcriptional kinetics for single-cell transcriptomic analysis.PLoS computational biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gene transcription is a stochastic bursting process with burst frequency and size as core parameters. While complex models capture detailed biology, their computational cost limits genome-wide applications. We propose a simple telegraph model-based framework to analyze genome-wide scRNA-seq datasets. When sample size ≥500 and burst parameter change ≥ 3 fold, inferred burst frequency- and size-dominated variations reliably proxy true regulation. Analyses across mouse cells and healthy/hypertrophic cardiomyopathy (HCM) human heart tissues revealed three conserved principles: (1) over 70% of genes with altered burst regulation exhibited burst frequency- or size-dominated regulation; HCM genes show stronger bursting featuring prolonged inactivity and intense transcription; (2) TATA-initiator synergy is lost in HCM; and (3) burst frequency-dominated genes enriched in genome stability/cell cycle/apoptosis (via TFs like
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.