A. B. Z. N. Rahman

This study uses whole-genome sequencing and pan-genome analysis of Bangladeshi diarrheal pathogens to identify core genes involved in pathogenesis and antibiotic resistance.

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.

This study analyzes 100 whole genomes of diarrheal pathogens, including Plesiomonas shigelloides, to identify coinfection patterns and shared hypothetical proteins with other diarrheal bacteria.

This study explores the genetic mechanisms of Providencia stuartii in microbial interactions with diarrheal pathogens and identifies potential therapeutic targets.

The paper investigates the genomic features of C. werkmanii strain NIB003, identifying antibiotic resistance genes, virulent genes, and genetic variation that may contribute to disease pathogenesis.

This study investigates the anti-diabetic potential of Mitragyna speciosa using in vivo and in silico methods, finding that extracts reduce blood glucose levels and four compounds bind effectively to the DPP4 receptor.