Everyone in longevity technology is asking a familiar question: What should I take? A supplement? A metabolite? A senolytic candidate? A lifestyle intervention? A drug-repurposing lead? But maybe that is not the best first question. A better one might be: Where, inside my biological network, is there a measurable mismatch that an intervention could plausibly reshape? That is the problem the SEMO algorithm is designed to address. SEMO is not just another recommendation engine. It is a network-medicine algorithmic framework developed by DeepoMe to connect individual omics signals , compound target networks , and personalized intervention hypotheses . The algorithm was introduced by Jianghui Xiong in a bioRxiv preprint titled “Utilizing Pre-trained Network Medicine Models for Generating Biomarkers, Targets, Re-purposing Drugs, and Personalized Therapeutic Regimes: COVID-19 Applications.” In that paper, SEMO stands for Selective Remodeling of Protein Networks by Chemicals .…