Genetic algorithms are functions that utilize processes observed in nature to produce algorithms and solutions that survive the evolutionary constrains in which the algorithm was produced.

[Kory] has been experimenting with genetic algorithms. Normally we’d expect his experiments to deal with tuning the variables in a control system or something, but he’s doing something … ...

By analyzing thousands of genetic risk variants, a new algorithm may be able to predict your risk of developing chronic kidney disease decades before onset.

Genetic algorithms evaluate potential solutions by evolving them over many generations and keeping the ones which work best each time.