ArticleFrontiers in genetics2018
M6AMRFS: Robust Prediction of N6-Methyladenosine Sites With Sequence-Based Features in Multiple Species.
Article in Frontiers in genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
What it found
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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.
The trial behind it
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Who cites it
53 citing papers in PubMed, 115 citations in OpenAlex.
- MCLCBA: multi-view contrastive learning network for RNA methylation site prediction.BMC bioinformatics · 2025Article
- Cross-RNA transferable sequence representation learning for lncRNA m6A site detection via novel deep domain separation networks.Briefings in bioinformatics · 2025Article
- Small open reading frame-encoded microproteins in cancer: identification, biological functions and clinical significance.Molecular cancer · 2025Review
- Micropeptides Encoded by Noncoding RNAs: Biological Functions and Roles in Diseases.Research (Washington, D.C.) · 2025Review
- MLA-ac4C: A N4-Acetylcytidine Site Prediction Model Based on Multi-Layer Attention, Bidirectional GRU, and DenseNet.Current genomics · 2025Article
- Article
- Multi-kernel feature extraction with dynamic fusion and downsampled residual feature embedding for predicting rice RNA N6-methyladenine sites.Briefings in bioinformatics · 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
- Interpretable Multi-Scale Deep Learning for RNA Methylation Analysis across Multiple Species.International journal of molecular sciences · 2024Article
- Analysis approaches for the identification and prediction ofEpigenetics · 2023Review
- Interpretable prediction models for widespread m6A RNA modification across cell lines and tissues.Bioinformatics (Oxford, England) · 2023Article
- MLACNN: an attention mechanism-based CNN architecture for predicting genome-wide DNA methylation.Theory in biosciences = Theorie in den Biowissenschaften · 2023Article
- Optimizing Hyperparameter Tuning in Machine Learning to Improve the Predictive Performance of Cross-Species N6-Methyladenosine Sites.ACS omega · 2023Article
- Review
- ATTIC is an integrated approach for predicting A-to-I RNA editing sites in three species.Briefings in bioinformatics · 2023Article
- Concepts and methods for transcriptome-wide prediction of chemical messenger RNA modifications with machine learning.Briefings in bioinformatics · 2023Review
- m6Aminer: Predicting the m6Am Sites on mRNA by Fusing Multiple Sequence-Derived Features into a CatBoost-Based Classifier.International journal of molecular sciences · 2023Article
- An Optimized Ensemble Deep Learning Model for Predicting Plant miRNA-IncRNA Based on Artificial Gorilla Troops Algorithm.Sensors (Basel, Switzerland) · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As one of the well-studied RNA methylation modifications, N6-methyladenosine (m
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.