Cristian Robert Munteanu

This paper introduces a machine learning framework to classify phylogenetic patterns in interkingdom horizontal gene transfer, achieving high accuracy and outperforming existing methods.

VirSentAI automatically surveils new viral genomes and identifies potential drug repurposing candidates for zoonotic threats.

This study identifies essential genes in breast cancer using OncoOmics approaches, revealing 144 genes with 33% being cancer hallmarks and 14% significant across multiple methods.

The paper develops an artificial neural network model to predict breast cancer-related proteins, achieving high accuracy and identifying top-ranked proteins in three categories.

The paper develops a machine learning model to predict druggable proteins, achieving high accuracy, and identifies potential targets in cancer and RNA-binding proteins.