Nithya Ramakrishnan

This paper introduces multivariate mutual information (MMI) for selecting histone PTM features to predict epigenetic data, showing improved accuracy over traditional methods.

This study uses explainable machine learning to identify critical histone PTMs and their positions in gene regulation using yeast ChIP-seq data.

The paper models how antagonistic histone PTMs improve epigenetic inheritance fidelity using Bayesian methods and simulations.

The paper models the biological evolution of faithful epigenetic inheritance using a neural network to simulate histone PTM pattern reconstruction during DNA replication.