Evidence map›Paper›PMID 40109445›Full record

ArticleComputational and structural biotechnology journal2025

CAP-m7G: A capsule network-based framework for specific RNA N7-methylguanosine site identification using image encoding and reconstruction layers.

Peilin Xie, Jiahui Guan, Xuxin He, Zhihao Zhao, Yilin Guo, Zhenglong Sun, Lantian Yao, Tzong-Yi Lee, Ying-Chih Chiang

Abstract read
In one paragraph

Article 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 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. Review
  3. 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

9 authors.

Peilin XieKobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China.
Jiahui GuanKobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China.
Xuxin HeSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China.
Zhihao ZhaoKobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China.
Yilin GuoKobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China.
Zhenglong SunSchool of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China.
Lantian YaoKobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China.
Tzong-Yi LeeInstitute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
Ying-Chih ChiangKobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

N7-methylguanosine (m7G) modifications play a pivotal role in RNA stability, mRNA export, and protein translation. They are closely associated with ribosome function and the regulation of gene expression. Dysregulation of m7G has been implicated in various diseases, including cancers and neurodegenerative disorders, where the loss of m7G can lead to genomic instability and uncontrolled cell proliferation. Accurate identification of m7G sites is thus essential for elucidating these mechanisms. Due to the high cost of experimentally validating m7G sites, several artificial intelligence models have been developed to predict these sites. However, the performance of these models is not yet optimal, and a user-friendly web server is still needed. To address these issues, we developed CAP-m7G, an innovative model that integrates Chaos Game Representation, Capsule Networks, and reconstruction layers. CAP-m7G achieved an accuracy of 96.63%, a specificity of 95.07%, and a Matthews correlation coefficient (MCC) of 0.933 on independent test data. Our results demonstrate that the integration of Chaos Game Representation with Capsule Network can effectively capture the crucial sequence information associated with m7G sites. The web server can be accessed at https://awi.cuhk.edu.cn/~biosequence/CAP-m7G/index.php.

Indexed as

BioinformaticsCapsule networkCGR encodingN7-methylguanosine

Identifiers

PMID40109445
PMCPMC11919597

What Socratic holds

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LicenceCC BY
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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 Socratic graph.