Evidence map›Paper›PMID 37961712›Full record

ArticlebioRxiv : the preprint server for biology2023

Exploring the Roles of RNAs in Chromatin Architecture Using Deep Learning.

Shuzhen Kuang, Katherine S Pollard

Open access · greenAbstract 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, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Shuzhen KuangGladstone Institute of Data Science and Biotechnology, San Francisco, CA.ORCID 0009-0008-3844-3647
Katherine S PollardGladstone Institute of Data Science and Biotechnology, San Francisco, CA.ORCID 0000-0002-9870-6196
Gladstone Institutes · US

Funding

Genetic determinants of 4D genome folding in human cardiac developmentU01HL157989 · NHLBI · J. DAVID GLADSTONE INSTITUTES · PI BRUNEAU, BENOIT GAETAN, POLLARD, KATHERINE S. · 2020 to 2024
$3.8M
NHLBI NIH HHS U01 HL157989
6 · The paper itself

Abstract

Recent studies have highlighted the impact of both transcription and transcripts on 3D genome organization, particularly its dynamics. Here, we propose a deep learning framework, called AkitaR, that leverages both genome sequences and genome-wide RNA-DNA interactions to investigate the roles of chromatin-associated RNAs (caRNAs) on genome folding in HFFc6 cells. In order to disentangle the

Identifiers

PMID37961712
PMCPMC10634726
OpenAlexW4387928405

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.