Evidence map›Paper›PMID 40599241›Full record

ReviewComputational and structural biotechnology journal2025

Computational modeling of cotranscriptional RNA folding.

Lei Jin, Shi-Jie Chen

Abstract readReview
In one paragraph

Review in Computational and structural biotechnology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Lei JinDepartment of Physics and Astronomy, Department of Biochemistry, Institute of Data Sciences and Informatics, University of Missouri, Columbia, MO 65211, USA.
Shi-Jie ChenDepartment of Physics and Astronomy, Department of Biochemistry, Institute of Data Sciences and Informatics, University of Missouri, Columbia, MO 65211, USA.

Funding

Center for Structural Biology of HIV RNAU54AI170660 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ALICE TELESNITSKY · 2022 to 2026
$32.1M
New methods for computational modeling of RNA structuresR35GM134919 · NIGMS · UNIVERSITY OF MISSOURI-COLUMBIA · PI SHI-JIE CHEN · 2020 to 2026
$3.3M
NIAID NIH HHS U54 AI170660NIGMS NIH HHS R35 GM134919
6 · The paper itself

Abstract

An RNA folds as it is transcribed. RNA folding during transcription differs fundamentally from thermodynamic folding. While thermodynamic folding reaches an equilibrium ensemble of structures, cotranscriptional folding is a kinetic process where the RNA structure evolves as the chain elongates during transcription. This dynamic folding pathway causes cotranscriptional structures often to deviate from thermodynamic predictions, as the system rarely reaches equilibrium. Since these cotranscriptional effects can persist in the mature RNA's structure, understanding this kinetic process is crucial. While experimental studies of cotranscriptional folding have been successful, they remain resource-intensive. Computational modeling has emerged as an increasingly practical and powerful approach for investigating these dynamics. This short review examines current computational methods and tools for simulating cotranscriptional folding, with the goal of advancing our understanding of RNA folding mechanisms.

Indexed as

Computational modelingCotranscriptional foldingKinetic pathwayRNA foldingStructure prediction

Identifiers

PMID40599241
PMCPMC12212151

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Registered trials

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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.