Ahmed Al‐Harrasi

This paper develops a machine learning framework to predict antimicrobial resistance using transcriptomics data, emphasizing the need for high-quality datasets and feature reduction methods.

The paper analyzes the chloroplast genome of 5959 species to construct an anticodon table and identifies putative quadruplet anticodons in chloroplast tRNAs.

This study analyzes NAC transcription factors across 160 plant species to uncover their genomic, biochemical, and evolutionary characteristics.