Evidence map›Paper›PMID 37398022›Full record

ArticlebioRxiv : the preprint server for biology2023

Dissection and Integration of Bursty Transcriptional Dynamics for Complex Systems.

Cheng Frank Gao, Suriyanarayanan Vaikuntanathan, Samantha J Riesenfeld

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Cheng Frank GaoDepartment of Chemistry, University of Chicago, IL.
Suriyanarayanan VaikuntanathanDepartment of Chemistry, University of Chicago, IL.
Samantha J RiesenfeldInstitute for Biophysical Dynamics, University of Chicago, IL.

Funding

Elucidating biophysical mechanisms for force sensing and control using non-equilibrium statistical mechanics and AIR35GM147400 · NIGMS · UNIVERSITY OF CHICAGO · PI Suriyanarayanan Vaikuntanathan · 2022 to 2026
$1.9M
NIGMS NIH HHS R35 GM147400
6 · The paper itself

Abstract

RNA velocity estimation is a potentially powerful tool to reveal the directionality of transcriptional changes in single-cell RNA-seq data, but it lacks accuracy, absent advanced metabolic labeling techniques. We developed a novel approach,

Identifiers

PMID37398022
PMCPMC10312759

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.