ArticleGenes2020
DNA6mA-MINT: DNA-6mA Modification Identification Neural Tool.
Article in Genes, 2020. 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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Who cites it
17 citing papers in PubMed.
- Deep learning-based identification of N6-methyladenine sites via hybrid feature fusion and SHAP-driven feature selection.Scientific reports · 2026Article
- N6-methyladenine identification using deep learning and discriminative feature integration.BMC medical genomics · 2025Article
- DeepRice6mA: A convolutional neural network approach for 6mA site prediction in the rice Genome.PloS one · 2025Article
- Enhancing Taxonomic Categorization of DNA Sequences with Deep Learning: A Multi-Label Approach.Bioengineering (Basel, Switzerland) · 2023Article
- 4acCPred: Weakly supervised prediction ofMolecular therapy. Nucleic acids · 2022Article
- ENet-6mA: Identification of 6mA Modification Sites in Plant Genomes Using ElasticNet and Neural Networks.International journal of molecular sciences · 2022Article
- Identification of piRNA disease associations using deep learning.Computational and structural biotechnology journal · 2022Article
- DNA N6-Methyladenine Modification in Eukaryotic Genome.Frontiers in genetics · 2022Review
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- A convolution based computational approach towards DNA N6-methyladenine site identification and motif extraction in rice genome.Scientific reports · 2021Article
- 4mCPred-CNN-Prediction of DNA N4-Methylcytosine in the Mouse Genome Using a Convolutional Neural Network.Genes · 2021Article
- BrainSeg-Net: Brain Tumor MR Image Segmentation via Enhanced Encoder-Decoder Network.Diagnostics (Basel, Switzerland) · 2021Article
- DNA sequences performs as natural language processing by exploiting deep learning algorithm for the identification of N4-methylcytosine.Scientific reports · 2021Article
- TS-m6A-DL: Tissue-specific identification of N6-methyladenosine sites using a universal deep learning model.Computational and structural biotechnology journal · 2021Article
- DCNN-4mC: Densely connected neural network based N4-methylcytosine site prediction in multiple species.Computational and structural biotechnology journal · 2021Article
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Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
DNA N6-methyladenine (6mA) is part of numerous biological processes including DNA repair, DNA replication, and DNA transcription. The 6mA modification sites hold a great impact when their biological function is under consideration. Research in biochemical experiments for this purpose is carried out and they have demonstrated good results. However, they proved not to be a practical solution when accessed under cost and time parameters. This led researchers to develop computational models to fulfill the requirement of modification identification. In consensus, we have developed a computational model recommended by Chou's 5-steps rule. The Neural Network (NN) model uses convolution layers to extract the high-level features from the encoded binary sequence. These extracted features were given an optimal interpretation by using a Long Short-Term Memory (LSTM) layer. The proposed architecture showed higher performance compared to state-of-the-art techniques. The proposed model is evaluated on
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Registered trials
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