Language
English
Publication Date
10-10-2025
Journal
Clinical Epigenetics
DOI
10.1186/s13148-025-01967-0
PMID
41074112
PMCID
PMC12512482
PubMedCentral® Posted Date
10-10-2025
PubMedCentral® Full Text Version
Post-print
Abstract
DNA methylation is an epigenetic modification that regulates gene expression by adding methyl groups to DNA, affecting cellular function and disease development. Machine learning, a subset of artificial intelligence, analyzes large datasets to identify patterns and make predictions. Over the past two decades, advances in bioinformatics technologies for arrays and sequencing have generated vast amounts of data, leading to the widespread adoption of machine learning methods for analyzing complex biological information for medical problems. This review explores recent advancements in DNA methylation studies that leverage emerging machine learning techniques for more precise, comprehensive, and rapid patient diagnostics based on DNA methylation markers. We present a general workflow for researchers, from clinical research questions to result interpretation and monitoring. Additionally, we showcase successful examples in diagnosing cancer, neurodevelopmental disorders, and multifactorial diseases. Some of these studies have led to the development of diagnostic platforms that have entered the global healthcare market, highlighting the promising future of this field.
Keywords
Humans, DNA Methylation, Machine Learning, Epigenesis, Genetic, Neoplasms, Epigenomics, Computational Biology, Neurodevelopmental Disorders, DNA methylation, Machine learning, Epigenetics, CpG sites, Clinical application
Published Open-Access
yes
Recommended Citation
Aref-Eshghi, Erfan; Abadi, Arash B; Farhadieh, Mohammad-Erfan; et al., "DNA Methylation and Machine Learning: Challenges and Perspective Toward Enhanced Clinical Diagnostics" (2025). Faculty and Staff Publications. 5174.
https://digitalcommons.library.tmc.edu/baylor_docs/5174
Included in
Genetic Phenomena Commons, Genetic Processes Commons, Genetic Structures Commons, Medical Genetics Commons, Medical Molecular Biology Commons, Medical Specialties Commons