Ahmed Abdul Quadeer

This study introduces a back-projection model to improve inference from sparse genomic surveillance data by estimating infection times and accounting for sampling biases in SARS-CoV-2 variants.

IFNBoost is a machine learning model that predicts IFNγ-inducing peptides with high accuracy, outperforming existing models and using both peptide sequences and metadata features.

The paper investigates how E1-E2 interactions in HCV affect viral fitness and antibody escape, identifying mutations and antibodies with implications for vaccine development.

The paper introduces a web-based platform called COVIDep that provides immune target recommendations for SARS-CoV-2 vaccine development by integrating genetic and epitope data.

This study identifies conserved B and T cell epitopes between SARS-CoV and SARS-CoV-2 to guide vaccine development against the novel coronavirus.

The paper identifies modular co-evolution networks in HIV and HCV proteins linked to structural and functional domains using sparse principal component analysis.