Machine Learning Approaches for Epigenetic Biomarker Discovery in Neurological Disorders

Abstract Effects of neurological diseases such as Alzheimer's and Parkinson's affects millions of people, multiple research suggest that ​epigenetic modifications influence gene expression without altering the underlying DNA sequence hold a pivotal position in the development of these conditions. The modifications include chemical alterations to DNA like DNA methylation and to histone proteins, which help package DNA in cells at the same time machine learning, a field in artificial intelligence that identifies patterns in large datasets is opening innovative methods for investigating sophisticated biological information. This paper explores how ML can be applied to uncover distinct epigenetic markers that may indicate the presence or risk of neurological conditions by detailing each step from data acquisition and cleaning to training and testing predictive models. We aim to make these cutting-edge techniques understandable to a broad audience.