A group of computer scientists from the University of Maryland programmed a computer to randomly predict how a worm's genes formed a regulatory network capable of regeneration, which experts would evaluate afterwards through simulation.
Researcher Michael Levin said that solving how flatworms regenerate, through AI, is not just statistics or number-crunching.
"The invention of models to explain what nature is doing is the most creative thing scientists do. This is the heart and soul of the scientific enterprise. None of us could have come up with this model; we (as a field) have failed to do so after over a century of effort," he said.
It is important to note, however, that even if the computer only took three days to create the worm model, it took the scientists several years to put together the program.
Researchers are opening up the use of the worm model to create other scientific models and theories in different areas, including cancer research. But, they said, in order to transfer the computer's abilities to other areas, massive databases of scientific experiments would need to be prepared in order to have enough raw material for discoveries to be made.
The study by Daniel Lobo and Michael Levin, Inferring Regulatory Networks from Experimental Morphological Phenotypes, was published on Thursday (4 June) in the journal PLOS.