Mohammad Uzzal Hossain

The paper introduces APDeeM, an ensemble machine learning system for identifying antiviral peptide candidates, achieving high accuracy and efficiency compared to existing methods.

The paper identifies shared genes across different breast cancer etiologies and suggests potential therapeutic targets through transcriptomic analysis and computational modeling.

The paper identifies fifteen PTEN mutations in lung cancer, seven of which significantly disrupt structure and function, supported by computational analysis and molecular simulations.