CONVERGENT PATHWAYS IN HUMAN DISEASE: AI-DRIVEN BIOINFORMATICS AND TRANSLATIONAL OPPORTUNITIES

Advances in bioinformatics, machine learning, and translational experimental biology have transformed the way we study complex diseases.Integrated analysis of multi-omics data now enables the identification of shared genetic signatures, immune alterations, and therapeutic targets across seemingly distinct disorders such as sarcopenia, atherosclerosis, Crohn's disease, myocardial infarction, and so on.These integrative studies highlight recurrent roles for inflammatory signaling, immune dysregulation, and metabolic shifts while also showcasing how computational pipelines can accelerate therapeutic discovery, ranging from CRISPR-based antiviral screening to nanopore sequencing-driven viral surveillance and bioinformatics-guided vaccine development.This review synthesizes recent findings where computational pipelines, experimental validation, and artificial intelligence align to reveal common molecular crosstalk and novel translational opportunities, ultimately underscoring the growing role of digital biology in advancing precision medicine.