ArticleMolecular therapy. Nucleic acids2018
iRNA-3typeA: Identifying Three Types of Modification at RNA's Adenosine Sites.
Article in Molecular therapy. Nucleic acids, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.
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Who cites it
64 citing papers in PubMed.
- Functional Prediction of Epitranscriptome.Methods in molecular biology (Clifton, N.J.) · 2026Article
- MCLCBA: multi-view contrastive learning network for RNA methylation site prediction.BMC bioinformatics · 2025Article
- YModPred: an interpretable prediction method for multi-type RNA modification sites in S. cerevisiae based on deep learning.BMC biology · 2025Article
- MLA-ac4C: A N4-Acetylcytidine Site Prediction Model Based on Multi-Layer Attention, Bidirectional GRU, and DenseNet.Current genomics · 2025Article
- Methyladenine as a regulator of biomolecular condensation.Frontiers in molecular biosciences · 2025Review
- Domain-knowledge enabled ensemble learning of 5-formylcytosine (f5C) modification sites.Computational and structural biotechnology journal · 2024Article
- Comprehensive Review and Assessment of Computational Methods for Prediction of N6-Methyladenosine Sites.Biology · 2024Review
- Bioinformatics for Inosine: Tools and Approaches to Trace This Elusive RNA Modification.Genes · 2024Review
- BiLSTM- and CNN-Based m6A Modification Prediction Model for circRNAs.Molecules (Basel, Switzerland) · 2024Article
- Interpretable Multi-Scale Deep Learning for RNA Methylation Analysis across Multiple Species.International journal of molecular sciences · 2024Article
- m1A-Ensem: accurate identification of 1-methyladenosine sites through ensemble models.BioData mining · 2024Article
- MSCAN: multi-scale self- and cross-attention network for RNA methylation site prediction.BMC bioinformatics · 2024Article
- The role of ADAR1 through and beyond its editing activity in cancer.Cell communication and signaling : CCS · 2024Review
- m7GRegpred: substrate prediction of N7-methylguanosine (m7G) writers and readers based on sequencing features.Frontiers in genetics · 2024Article
- DLC-ac4C: A Prediction Model for N4-acetylcytidine Sites in Human mRNA Based on DenseNet and Bidirectional LSTM Methods.Current genomics · 2023Article
- Review
- Novel insight into RNA modifications in tumor immunity: Promising targets to prevent tumor immune escape.Innovation (Cambridge (Mass.)) · 2023Review
- ATTIC is an integrated approach for predicting A-to-I RNA editing sites in three species.Briefings in bioinformatics · 2023Article
- A novel RNA modification prognostic signature for predicting the characteristics of the tumor microenvironment in gastric cancer.Frontiers in oncology · 2023Article
- Predicting N6-Methyladenosine Sites in Multiple Tissues of Mammals through Ensemble Deep Learning.International journal of molecular sciences · 2022Review
4 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
RNA modifications are additions of chemical groups to nucleotides or their local structural changes. Knowledge about the occurrence sites of these modifications is essential for in-depth understanding of the biological functions and mechanisms and for treating some genomic diseases as well. With the avalanche of RNA sequences generated in the post-genomic age, many computational methods have been proposed for identifying various types of RNA modifications one by one. However, so far no method whatsoever has been developed for simultaneously identifying several different types of RNA modifications. To address such a challenge, we developed a predictor called "iRNA-3typeA," by which we can simultaneously identify the occurrence sites of the following three most frequently observed modifications in RNA: (1) N
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