Evidence map›Paper›PMID 40396374›Full record

ArticleNucleic acids research2025

RegRNA 3.0: expanding regulatory RNA analysis with new features for motif, interaction, and annotation.

Yixian Huang, Zhiyong Zhang, Zhengkai Zou, Lingquan Zhang, Yigang Chen, Jingting Wan, Zihao Zhu, Sicong Yu, Huali Zuo, Yang-Chi-Dung Lin and 2 more

Abstract read
In one paragraph

Article in Nucleic acids research, 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

12 authors.

Yixian HuangSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Longgang District, Shenzhen, Guangdong 518172, China.
Zhiyong ZhangSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Longgang District, Shenzhen, Guangdong 518172, China.
Zhengkai ZouSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Longgang District, Shenzhen, Guangdong 518172, China.
Lingquan ZhangSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Longgang District, Shenzhen, Guangdong 518172, China.
Yigang ChenSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Longgang District, Shenzhen, Guangdong 518172, China.
Jingting WanSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Longgang District, Shenzhen, Guangdong 518172, China.
Zihao ZhuSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Longgang District, Shenzhen, Guangdong 518172, China.
Sicong YuSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Longgang District, Shenzhen, Guangdong 518172, China.
Huali ZuoSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Longgang District, Shenzhen, Guangdong 518172, China.
Yang-Chi-Dung LinSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Longgang District, Shenzhen, Guangdong 518172, China.
Hsi-Yuan HuangSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Longgang District, Shenzhen, Guangdong 518172, China.ORCID 0000-0001-8453-4939
Hsien-Da HuangSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Longgang District, Shenzhen, Guangdong 518172, China.

Funding

Chinese University of Hong Kong HUUF-MS-202308 and HUUF-MS-202309Guangdong Science and Technology Programme 2024A0505050001Guangdong Science and Technology Programme 2024A0505050002Guangdong Young Scholar Development Fund 2021E0005Guangdong Young Scholar Development Fund 2022E0035Shenzhen-Hong Kong Cooperation Zone for Technology and Innovation HZQB-KCZYB-2020056Shenzhen-Hong Kong Cooperation Zone for Technology and Innovation P2-2022-HDH-001-AShenzhen Science and Technology Program JCYJ20220530143615035Warshel Institute for Computational Biology LGKCSDPT2024001
6 · The paper itself

Abstract

Functional RNA molecules are crucial for biological processes from gene regulation to protein synthesis, and analyzing functional motifs and elements is essential for understanding RNA regulation. Building on RegRNA 1.0 and 2.0, we present RegRNA 3.0, a sophisticated meta-workflow that integrates 26 computational tools and 28 databases for annotation, enabling one-step and customizable RNA motif predictions. RegRNA streamlines multi-step analysis and enhances result interpretation with interactive visualizations and comprehensive reporting tools. When provided with an RNA sequence, RegRNA 3.0 generates predictions for RNA functional motifs, RNA interaction motifs, and comprehensive RNA annotations. Specifically, RNA functional motifs include core promoter elements, RNA decay, G-quadruplex, and 14 previous types. RNA interaction motifs include newly added RNA-ligand interactions and RNA-binding protein predictions, along with three previous types. RNA annotation includes RNA family classification, blood exosomes RNA, subcellular localizations, A-to-I editing events, modifications, and 3D structures, along with four previously supported features. RegRNA 3.0 accelerates gene regulation and RNA biology discoveries by offering a user-friendly platform for identifying and analyzing RNA motifs and interactions. The web interface has been improved for intuitive visualizations of predicted motifs and structures, with flexible download options in multiple formats. It is available at http://awi.cuhk.edu.cn/∼RegRNA/.

Indexed as

Computational BiologyRNASoftwareG-QuadruplexesHumansInternetMolecular Sequence AnnotationNucleotide MotifsRNA-Binding ProteinsSequence Analysis, RNARNARNA-Binding Proteins

Identifiers

PMID40396374
PMCPMC12230662

What Socratic 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 Socratic graph.