Mohammad Shahedur Rahman

This study investigates KCNN4 gene expression in pancreatic adenocarcinoma using bioinformatics, finding its expression correlates with survival and identifies associated biological functions.

This study computationally evaluates 53 phytochemicals targeting CCR5 and CXCR4 receptors for anti-HIV potential, identifying six with favorable druglikeness and ADMET properties.

The paper designs hyperglycosylated analogs of human erythropoietin using computational methods and identifies Analog-71.1 as a promising candidate with strong receptor interaction and structural stability.

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