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 .

The SEMO framework has…