SynthesisBriefings in bioinformatics2023
Application of deep learning in cancer epigenetics through DNA methylation analysis.
Synthesis in Briefings in bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- Harnessing Deep Learning Models for Guide RNA Optimization and Off-Target Prediction in CRISPR Systems.Biotechnology journal · 2026Review
- Deep learning in multi-omics integration for gastrointestinal cancer biomarker discovery.Frontiers in oncology · 2026Review
- Review
- DNA methylation and machine learning: challenges and perspective toward enhanced clinical diagnostics.Clinical epigenetics · 2025Review
- Artificial intelligence for comprehensive DNA methylation analysis: overview, challenges, and future directions.Briefings in bioinformatics · 2025Review
- A Comprehensive Review of Deep Learning Applications with Multi-Omics Data in Cancer Research.Genes · 2025Review
- The role of nanomedicine and artificial intelligence in cancer health care: individual applications and emerging integrations-a narrative review.Discover oncology · 2025Review
- Identification of gene signatures associated with lactation for predicting prognosis and treatment response in breast cancer patients through machine learning.Scientific reports · 2025Article
- Methylation profiling in neuropathological tumors diagnosis: a comprehensive review.Frontiers in oncology · 2025Review
- Epigenetic regulatory mechanism of macrophage polarization in diabetic wound healing (Review).Molecular medicine reports · 2025Review
- Subtypes detection of papillary thyroid cancer from methylation assay via Deep Neural Network.Computational and structural biotechnology journal · 2025Article
- Methods in DNA methylation array dataset analysis: A review.Computational and structural biotechnology journal · 2024Review
- Advancing epigenetic profiling in cervical cancer: machine learning techniques for classifying DNA methylation patterns.3 Biotech · 2024Article
- Young Onset Colorectal Cancer.South Asian journal of cancer · 2024Article
- Microarray-Based DNA Methylation Profiling: Validation Considerations for Clinical Testing.The Journal of molecular diagnostics : JMD · 2024Article
- Exploring Potential Epigenetic Biomarkers for Colorectal Cancer Metastasis.International journal of molecular sciences · 2024Review
- Mechanisms and technologies in cancer epigenetics.Frontiers in oncology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
DNA methylation is a fundamental epigenetic modification involved in various biological processes and diseases. Analysis of DNA methylation data at a genome-wide and high-throughput level can provide insights into diseases influenced by epigenetics, such as cancer. Recent technological advances have led to the development of high-throughput approaches, such as genome-scale profiling, that allow for computational analysis of epigenetics. Deep learning (DL) methods are essential in facilitating computational studies in epigenetics for DNA methylation analysis. In this systematic review, we assessed the various applications of DL applied to DNA methylation data or multi-omics data to discover cancer biomarkers, perform classification, imputation and survival analysis. The review first introduces state-of-the-art DL architectures and highlights their usefulness in addressing challenges related to cancer epigenetics. Finally, the review discusses potential limitations and future research directions in this field.
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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.