ArticleFrontiers in microbiology2023
Evaluation and development of deep neural networks for RNA 5-Methyluridine classifications using autoBioSeqpy.
Article in Frontiers in microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed.
- A robust deep learning framework for RNA 5-methyluridine modification prediction using integrated features.BMC biology · 2025Article
- Deep-m5U: a deep learning-based approach for RNA 5-methyluridine modification prediction using optimized feature integration.BMC bioinformatics · 2024Article
- A robust deep learning approach for identification of RNA 5-methyluridine sites.Scientific reports · 2024Article
- m5U-GEPred: prediction of RNA 5-methyluridine sites based on sequence-derived and graph embedding features.Frontiers in microbiology · 2023Article
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Authors and funding
6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Post-transcriptionally RNA modifications, also known as the epitranscriptome, play crucial roles in the regulation of gene expression during development. Recently, deep learning (DL) has been employed for RNA modification site prediction and has shown promising results. However, due to the lack of relevant studies, it is unclear which DL architecture is best suited for some pyrimidine modifications, such as 5-methyluridine (m
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Registered trials
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