Evidence map›Paper›PMID 26136240›Full record

ReviewGenes2015

From Structural Variation of Gene Molecules to Chromatin Dynamics and Transcriptional Bursting.

Hinrich Boeger, Robert Shelansky, Heta Patel, Christopher R Brown

Open access · goldAbstract readReview
In one paragraph

Review in Genes, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.6field-weighted citation impact, top 32% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Gene transcription in bursting: a unified mode for realizing accuracy and stochasticity.Biological reviews of the Cambridge Philosophical Society · 2019
    Article
  7. Article
  8. Article
  9. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Hinrich BoegerDepartment of Molecular, Cell and Developmental Biology, University of California, Santa Cruz, CA 95064, USA. hboeger@ucsc.edu.
Robert ShelanskyDepartment of Molecular, Cell and Developmental Biology, University of California, Santa Cruz, CA 95064, USA. rshelans@ucsc.edu.
Heta PatelDepartment of Molecular, Cell and Developmental Biology, University of California, Santa Cruz, CA 95064, USA. hppatel@ucsc.edu.
Christopher R BrownDepartment of Molecular, Cell and Developmental Biology, University of California, Santa Cruz, CA 95064, USA. crb2012@gmail.com.
University of California, Santa Cruz · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcriptional activation of eukaryotic genes is accompanied, in general, by a change in the sensitivity of promoter chromatin to endonucleases. The structural basis of this alteration has remained elusive for decades; but the change has been viewed as a transformation of one structure into another, from "closed" to "open" chromatin. In contradistinction to this static and deterministic view of the problem, a dynamical and probabilistic theory of promoter chromatin has emerged as its solution. This theory, which we review here, explains observed variation in promoter chromatin structure at the level of single gene molecules and provides a molecular basis for random bursting in transcription-the conjecture that promoters stochastically transition between transcriptionally conducive and inconducive states. The mechanism of transcriptional regulation may be understood only in probabilistic terms.

Indexed as

chromatin dynamicsgene expression noisestochastic processtranscriptional bursting

Identifiers

PMID26136240
PMCPMC4584311
OpenAlexW1512021852

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.