Exploring NS5A Protein of Hepatitis C Virus Through Computational Deep Learning Models and Phylogenetic Analysis for Sequence Variability

Background

Hepatitis C Virus (HCV) remains a global health threat, causing severe liver diseases such as cirrhosis and hepatocellular carcinoma. Protein sequences are essential for exploring genetic variability and improving detection. This study presents a generative LSTM model, AI-VNA, for generating and analyzing NS5A protein sequences to enhance understanding of sequence diversity and improve predictive modeling.