Evidence map›Paper›PMID 39557706›Full record

ReviewFunctional & integrative genomics2024

Non-coding RNA notations, regulations and interactive resources.

Mengwei Cheng, Yinhuan Zhu, Han Yu, Linlin Shao, Yiming Zhang, Lanxing Li, Haohong Tu, Luyao Xie, Haoyu Chao, Peijing Zhang and 8 more

Abstract readReview
PubMed Publisher
In one paragraph

Review in Functional & integrative genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Predicting RNA Structure Utilizing Attention from Pretrained Language Models.Journal of chemical information and modeling · 2025
    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

18 authors.

Mengwei ChengCollege of Science, Mathematics and Technology, Wenzhou-Kean University, Wenzhou, 325060, China.
Yinhuan ZhuCollege of Science, Mathematics and Technology, Wenzhou-Kean University, Wenzhou, 325060, China.
Han YuCollege of Science, Mathematics and Technology, Wenzhou-Kean University, Wenzhou, 325060, China.
Linlin ShaoCollege of Science, Mathematics and Technology, Wenzhou-Kean University, Wenzhou, 325060, China.
Yiming ZhangCollege of Science, Mathematics and Technology, Wenzhou-Kean University, Wenzhou, 325060, China.
Lanxing LiCollege of Science, Mathematics and Technology, Wenzhou-Kean University, Wenzhou, 325060, China.
Haohong TuCollege of Science, Mathematics and Technology, Wenzhou-Kean University, Wenzhou, 325060, China.
Luyao XieDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
Haoyu ChaoDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
Peijing ZhangDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
Saige XinDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
Cong FengDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China. ventson@zju.edu.cn.
Vladimir IvanisenkoInstitute of Cytology and Genetics, Siberian Branch of Russian Academy of Science, 630060, Novosibirsk, Russia.
Yuriy OrlovInstitute of Cytology and Genetics, Siberian Branch of Russian Academy of Science, 630060, Novosibirsk, Russia.
Dijun ChenSchool of Life Sciences, Nanjing University, Nanjing, 210023, China.
Aloysius WongCollege of Science, Mathematics and Technology, Wenzhou-Kean University, Wenzhou, 325060, China.
Yixin Eric YangCollege of Science, Mathematics and Technology, Wenzhou-Kean University, Wenzhou, 325060, China.
Ming ChenCollege of Science, Mathematics and Technology, Wenzhou-Kean University, Wenzhou, 325060, China. mchen@zju.edu.cn.

Funding

National Key Research and Development Program of China 2023YFE0112300; 2018YFC0310602National Natural Sciences Foundation of China 32261133526; 32270709; 32070677; 32300532Postdoctoral Fellowship Program of CPSF GZC20232322the Science and Technology Innovation Leading Scientist 2022R52035
6 · The paper itself

Abstract

An increasing number of non-coding RNAs (ncRNAs) are found to have roles in gene expression and cellular regulations. However, there are still a large number of ncRNAs whose functions remain to be studied. Despite decades of research, the field continues to evolve, with each newly identified ncRNA undergoing processes such as biogenesis, identification, and functional annotation. Bioinformatics methodologies, alongside traditional biochemical experimental methods, have played an important role in advancing ncRNA research across various stages. Presently, over 50 types of ncRNAs have been characterized, each exhibiting diverse functions. However, there remains a need for standardization and integration of these ncRNAs within a unified framework. In response to this gap, this review traces the historical trajectory of ncRNA research and proposes a unified notation system. Additionally, we comprehensively elucidate the ncRNA interactome, detailing its associations with DNAs, RNAs, proteins, complexes, and chromatin. A web portal named ncRNA Hub ( https://bis.zju.edu.cn/nchub/ ) is also constructed to provide detailed notations of ncRNAs and share a collection of bioinformatics resources. This review aims to provide a broader perspective and standardized paradigm for advancing ncRNA research.

Indexed as

RNA, UntranslatedAnimalsComputational BiologyHumansRNA, UntranslatedBioinformatics resourceInteractomeNon-coding RNANotation

Identifiers

PMID39557706

What OpenQuestion holds

Textmetadata
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.