Machine Learning in the Prediction of Epigenetic Modifications

Abstract

Epigenetic modifications, such as DNA methylation and histone modification, play a crucial role in gene regulation and are associated with various biological processes, including development, aging, and disease. The prediction of epigenetic modifications from genomic data is a challenging task, as these modifications are context-dependent and influenced by genetic, environmental, and stochastic factors. Machine learning (ML) techniques have emerged as powerful tools for predicting epigenetic modifications by learning patterns from large-scale omics data. This article reviews the use of machine learning methods in predicting epigenetic modifications, focusing on feature selection, data integration, and ML algorithms. We also discuss the potential applications, challenges, and future directions for integrating machine learning into epigenetics research..