Evidence map›Paper›PMID 41659490›Full record

ArticlebioRxiv : the preprint server for biology2026

Lukas Herron, Yunrui Qiu, Anjali Verma, Venkata Sai Sreyas Adury, Richard John, Suemin Lee, Shams Mehdi, Disha Sanwal, John S Schneekloth, Pratyush Tiwary

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. 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

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

10 authors.

Lukas HerronInstitute for Physical Science and Technology, University of Maryland, College Park, MD, 20742, USA.
Yunrui QiuInstitute for Physical Science and Technology, University of Maryland, College Park, MD, 20742, USA.
Anjali VermaInstitute for Physical Science and Technology, University of Maryland, College Park, MD, 20742, USA.
Venkata Sai Sreyas AduryInstitute for Physical Science and Technology, University of Maryland, College Park, MD, 20742, USA.
Richard JohnInstitute for Physical Science and Technology, University of Maryland, College Park, MD, 20742, USA.
Suemin LeeInstitute for Physical Science and Technology, University of Maryland, College Park, MD, 20742, USA.
Shams MehdiInstitute for Physical Science and Technology, University of Maryland, College Park, MD, 20742, USA.
Disha SanwalInstitute for Physical Science and Technology, University of Maryland, College Park, MD, 20742, USA.
John S SchneeklothChemical Biology Laboratory, National Cancer Institute, Frederick, MD 21702, USA.
Pratyush TiwaryInstitute for Physical Science and Technology, University of Maryland, College Park, MD, 20742, USA.

Funding

Supplement to promote diversity: From atoms to mechanisms - Artificial Intelligence augmented molecular simulations for mechanistic ligand design.R35GM142719 · NIGMS · UNIV OF MARYLAND, COLLEGE PARK · PI TIWARY, PRATYUSH · 2021 to 2025
$2.0M
NIGMS NIH HHS R35 GM142719
6 · The paper itself

Abstract

RNA utilizes three-dimensional structure in addition to sequence to carry out diverse functions in gene expression and disease. Much like well-folded proteins, RNAs adopt specific three-dimensional structures to carry out their function. Yet comparatively few RNA structures have been solved by atomic resolution structural techniques, in part because unlike structured proteins, RNAs fold into heterogeneous ensembles of interconverting structures that pose a challenge for high-resolution structure probing methods. In this work, we introduce RNAnneal as a method for RNA structural ensemble prediction that seamlessly integrates generative deep learning with statistical physics and molecular dynamics modeling. Given the primary sequence, RNAnneal uses

Identifiers

PMID41659490
PMCPMC12874061

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.