ArticleBioinformatics (Oxford, England)2022
CpG Transformer for imputation of single-cell methylomes.
Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application of deep learning in cancer epigenetics through DNA methylation analysis.Briefings in bioinformatics · 2023Pooled it
- A systematic benchmarking framework and dual-view optimization strategy for single-cell DNA methylation imputation.Briefings in bioinformatics · 2026Article
- AI-Driven Design Platforms of Next-Generation Antibody Therapeutics.Topics in current chemistry (Cham) · 2026Review
- Transformers for single-cell RNA sequencing: a survey.Briefings in bioinformatics · 2026Review
- Advancing single-cell omics and cell-based therapeutics with quantum computing.Nature reviews. Molecular cell biology · 2026Review
- DepMicroDiff: Diffusion-Based Dependency-Aware Multimodal Imputation for Microbiome Data.Computational and structural biotechnology journal · 2026Article
- Large-scale multi-omic biosequence transformers for modeling protein-nucleic acid interactions.PloS one · 2026Article
- DNA methylation profile to aid in the diagnosis of pancreatic ductal adenocarcinoma and its role in disease progression.Epigenomics · 2025Review
- DMRU: generative deep learning to unravel condition-specific cytosine methylation in plants.Briefings in bioinformatics · 2025Article
- MambaCpG: an accurate model for single-cell DNA methylation status imputation using mamba.Briefings in bioinformatics · 2025Article
- Large-Scale Multi-omic Biosequence Transformers for Modeling Protein-Nucleic Acid Interactions.ArXiv · 2025Article
- A review of transformer models in drug discovery and beyond.Journal of pharmaceutical analysis · 2025Review
- Deep learning imputes DNA methylation states in single cells and enhances the detection of epigenetic alterations in schizophrenia.Cell genomics · 2025Article
- Integration of proteomics profiling data to facilitate discovery of cancer neoantigens: a survey.Briefings in bioinformatics · 2025Review
- DNA promoter task-oriented dictionary mining and prediction model based on natural language technology.Scientific reports · 2025Article
- CpGFuse: a holistic approach for accurate identification of methylation states of DNA CpG sites.Briefings in bioinformatics · 2024Article
- scMeFormer: a transformer-based deep learning model for imputing DNA methylation states in single cells enhances the detection of epigenetic alterations in schizophrenia.bioRxiv : the preprint server for biology · 2024Article
- Research progress and application of single-cell sequencing in head and neck malignant tumors.Cancer gene therapy · 2024Review
- Deep Learning Methods for Omics Data Imputation.Biology · 2023Review
- GraphCpG: imputation of single-cell methylomes based on locus-aware neighboring subgraphs.Bioinformatics (Oxford, England) · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
motivationThe adoption of current single-cell DNA methylation sequencing protocols is hindered by incomplete coverage, outlining the need for effective imputation techniques. The task of imputing single-cell (methylation) data requires models to build an understanding of underlying biological processes.
resultsWe adapt the transformer neural network architecture to operate on methylation matrices through combining axial attention with sliding window self-attention. The obtained CpG Transformer displays state-of-the-art performances on a wide range of scBS-seq and scRRBS-seq datasets. Furthermore, we demonstrate the interpretability of CpG Transformer and illustrate its rapid transfer learning properties, allowing practitioners to train models on new datasets with a limited computational and time budget. AVAILABILITY AND IMPLEMENTATION: CpG Transformer is freely available at https://github.com/gdewael/cpg-transformer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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What Socratic 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 Socratic graph.