A huge orchestra without a conductor. Each musician is a gene, and the melody is the cell's complex work. Previously, looking at a tissue photo, a computer tried to guess each instrument's part individually. It didn't know that violins usually play with violas, and trumpets with trombones. The program just output a list of notes, without sensing the harmony.

A team of developers proposed giving the program a "score"—a scheme of gene relationships. It's called the Gene Ontology (GO). This isn't just a list, but a true family tree. Genes are grouped by "families" and "professions," from the most general tasks to narrow specializations. The new system MSGR (Multi-Scale Gene Refiner) uses this tree as a hint. It starts with a rough sketch — which major biological processes are underway. Then, step by step, like an artist, it fills in details, refining the activity of each individual gene. Each next level of the tree adds precision, correcting errors from the previous one.

This "smart" add-on can be attached to already working algorithms. Like a new processor for an old computer. You don't need to change the program's "eye" that analyzes the image. Experiments on thousands of samples from nine different collections showed: predictions with this tree-like hint are consistently more accurate than without it. The improvement was nearly three hundredths on the key metric — a small but confident win. The trick is that it's the real biological hierarchy that works. When scientists shuffled the genes in the tree randomly, stripping it of biological meaning, all the advantage vanished. Structure matters not on its own, but only when it reflects real connections honed by evolution. And then the orchestra finally sounds in harmony.