Genetic programming (another name for evolutionary systems) creates generations of computer programs "using the principles of Darwinian natural selection and biologically inspired operations. The operations include reproduction, crossover (sexual recombination), mutation, and architecture-altering operations patterned after gene duplication and gene deletion in nature."
– Genetic Programming, Inc.
The ability to sequence genomes quickly has provided scientists with reams of data, but understanding how evolution has shaped humans is still a difficult task.Credit: Guy Tear/Wellcome Coll./CC Pinpointing where and how the human genome is evolving can be like hunting for a needle in a haystack. Each person's genome contains three billion building blocks called nucleotides, and researchers must compile data from thousands of people to discover patterns that signal how genes have been shaped by evolutionary pressures. To find these patterns, a growing number of geneticists are turning to a form of machine learning called deep learning. Proponents of the approach say that deep-learning algorithms incorporate fewer explicit assumptions about what the genetic signatures of natural selection should look like than do conventional statistical methods.