ArticleBMC bioinformatics2019
NmSEER V2.0: a prediction tool for 2'-O-methylation sites based on random forest and multi-encoding combination.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed, 28 citations in OpenAlex.
- Accelerate the Highly Efficient Development of mRNA Vaccines Through Advanced Computational Methods.MedComm · 2026Review
- OMetaNet: an efficient hybrid deep learning model based on multimodal data fusion and contrastive learning for predicting 2'-O-methylation sites in human RNA.BMC bioinformatics · 2025Article
- 2OMe-LM: predicting 2'-O-methylation sites in human RNA using a pre-trained RNA language model.Bioinformatics (Oxford, England) · 2025Article
- The detection, function, and therapeutic potential of RNA 2'-O-methylation.The innovation life · 2025Article
- MultiV_Nm: a prediction method for 2'-O-methylation sites based on multi-view features.Frontiers in genetics · 2025Article
- A specific domain within the 3' untranslated region of Usutu virus confers resistance to the exonuclease ISG20.Nature communications · 2024Article
- Nmix: a hybrid deep learning model for precise prediction of 2'-O-methylation sites based on multi-feature fusion and ensemble learning.Briefings in bioinformatics · 2024Article
- Bioinformatics for Inosine: Tools and Approaches to Trace This Elusive RNA Modification.Genes · 2024Review
- Meta-2OM: A multi-classifier meta-model for the accurate prediction of RNA 2'-O-methylation sites in human RNA.PloS one · 2024Article
- Nm-Nano: a machine learning framework for transcriptome-wide single-molecule mapping of 2´-O-methylation (Nm) sites in nanopore direct RNA sequencing datasets.RNA biology · 2024Article
- H2Opred: a robust and efficient hybrid deep learning model for predicting 2'-O-methylation sites in human RNA.Briefings in bioinformatics · 2023Article
- Biomarkers of ulcerative colitis disease activity CXCL1, CYP2R1, LPCAT1, and NEU4 and their relationship to immune infiltrates.Scientific reports · 2023Article
- Genetic Associations ofInternational journal of environmental research and public health · 2022Article
- RNADSN: Transfer-Learning 5-Methyluridine (mInternational journal of molecular sciences · 2022Article
- Machine learning applications in RNA modification sites prediction.Computational and structural biotechnology journal · 2021Review
- DeepOMe: A Web Server for the Prediction of 2'-O-Me Sites Based on the Hybrid CNN and BLSTM Architecture.Frontiers in cell and developmental biology · 2021Article
- New Twists in Detecting mRNA Modification Dynamics.Trends in biotechnology · 2021Review
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background2'-O-methylation (2'-O-me or Nm) is a post-transcriptional RNA methylation modified at 2'-hydroxy, which is common in mRNAs and various non-coding RNAs. Previous studies revealed the significance of Nm in multiple biological processes. With Nm getting more and more attention, a revolutionary technique termed Nm-seq, was developed to profile Nm sites mainly in mRNA with single nucleotide resolution and high sensitivity. In a recent work, supported by the Nm-seq data, we have reported a method in silico for predicting Nm sites, which relies on nucleotide sequence information, and established an online server named NmSEER. More recently, a more confident dataset produced by refined Nm-seq was available. Therefore, in this work, we redesigned the prediction model to achieve a more robust performance on the new data.
resultsWe redesigned the prediction model from two perspectives, including machine learning algorithm and multi-encoding scheme combination. With optimization by 5-fold cross-validation tests and evaluation by independent test respectively, random forest was selected as the most robust algorithm. Meanwhile, one-hot encoding, together with position-specific dinucleotide sequence profile and K-nucleotide frequency encoding were collectively applied to build the final predictor.
conclusionsThe predictor of updated version, named NmSEER V2.0, achieves an accurate prediction performance (AUROC = 0.862) and has been settled into a brand-new server, which is available at http://www.rnanut.net/nmseer-v2/ for free.
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