DNA methylation patterns Analysis through K-Nearest Neighbors-based Method
Liam Hawthorne, Sarah Ngata, J van Veen · Journal of Computational Biology and Medicine · 2025
DNA methylation patterns play a crucial role in gene regulation and disease development. Understanding these patterns is essential for advancing personalized medicine and disease diagnosis. Current research in DNA methylation analysis faces challenges such as high dimensionality and computational complexity. This paper proposes a novel approach utilizing a K-Nearest Neighbors-based method for analyzing DNA methylation patterns. The innovative method aims to improve accuracy and efficiency in identifying methylation patterns associated with specific biological processes or diseases. By integrating machine learning techniques with DNA methylation data, this research contributes to the development of more effective tools for studying epigenetic modifications and their implications in human health.