ArticleBriefings in bioinformatics2024
Precision DNA methylation typing via hierarchical clustering of Nanopore current signals and attention-based neural network.
Article in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
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- Structural Variation and 3D Genome-Driven DNA/RNA Methylation Divergence Contributing to Cotton Fiber Domestication.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Single-Cell transcriptomic analysis reveals distinct cellular and molecular signatures of human oral mucosa and skin.Cellular and molecular life sciences : CMLS · 2026Article
- Coevolutionary signals in multiple sequence alignments improve virulence factor prediction with an MSA Transformer.Scientific reports · 2025Article
- Cross-RNA transferable sequence representation learning for lncRNA m6A site detection via novel deep domain separation networks.Briefings in bioinformatics · 2025Article
- Article
- Identifying DNA methylation types and methylated base positions from bacteria using nanopore sequencing with multi-scale neural network.Bioinformatics (Oxford, England) · 2025Article
- NANOME: A Nextflow pipeline for haplotype-aware allele-specific consensus DNA methylation detection by nanopore long-read sequencing.bioRxiv : the preprint server for biology · 2025Article
- Computational strategies in tumor phylogenetics: evaluating multimodal integration and methodological trade-offs across study designs.Bioinformatics advances · 2025Review
- Comprehensive pan-cancer analysis reveals CGB5 is a potential promising predictive and immunotherapeutic biomarker.Frontiers in medicine · 2025Article
- Multimodal deep learning for predicting protein ubiquitination sites.Bioinformatics advances · 2025Article
- Comprehensive Bioinformatics Analysis for the Identification of Hub Genes and Critical Signaling Pathways Differentiating Latent and Active Tuberculosis.Combinatorial chemistry & high throughput screening · 2025Article
- MethylomeMiner: A novel tool for high-resolution analysis of bacterial methylation patterns from nanopore sequencing.Computational and structural biotechnology journal · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Decoding DNA methylation sites through nanopore sequencing has emerged as a cutting-edge technology in the field of DNA methylation research, as it enables direct sequencing of native DNA molecules without the need for prior enzymatic or chemical treatments. During nanopore sequencing, methylation modifications on DNA bases cause changes in electrical current intensity. Therefore, constructing deep neural network models to decode the electrical signals of nanopore sequencing has become a crucial step in methylation site identification. In this study, we utilized nanopore sequencing data containing diverse DNA methylation types and motif sequence diversity. We proposed a feature encoding method based on current signal clustering and leveraged the powerful attention mechanism in the Transformer framework to construct the PoreFormer model for identifying DNA methylation sites in nanopore sequencing. The model demonstrated excellent performance under conditions of multi-class methylation and motif sequence diversity, offering new insights into related research fields.
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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.