N.Wells
Posts: 1836
Joined: Oct. 2005
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| Quote (GaryGaulin @ June 05 2015,17:51) | | Quote | A Computer Just Solved This 100-Year-Old Biology Problem
A new study argues that computers can independently invent scientific ideas—not just crunch numbers.
A silicon theorist
Simply put, Levin and Lobo's computer attempted to mimic real-life studies over and over again in an excruciatingly-detailed simulation. The machine would randomly guess how the worm's genes formed a regulatory network that allowed for this amazing regeneration, then let that genetic network take control in a simulation, and finally measure how close the results were to real experimental data. If its guesses were good (meaning the gene network made the simulated worm regenerate similarly to real-life experiments), then the machine slightly modified the random genetic network it had created, and tried again until its model was even better.
This may sound simplistic, but after three days of constant guessing, simulating, evaluating its guesses, and tweaking its tactics, the computer had invented a core genetic network that faithfully matched every one of the hundreds of experiments in its database. Essentially, it had explained what scientists had failed to—how the genes connect.
Levin and Lobo are quite adamant that what they programed their computer to do "is not just statistics or number-crunching," says Levin. Through trail and error, the computer invented an accurate model of the inner-workings of the flatworm. "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," he says. "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."
Hava Siegelmann, a computer scientist and biomedical engineer at the University of Massachusetts who was not involved in the research, applauds the the team's inventive work, and also agrees with Levin's claim that this is more than just 'statistics or number-crunching.'
http://www.popularmechanics.com/science....-theory
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No one has said that computer models cannot contribute to science. I have stressed YOURS does not, because ground-truthing is essential and you don't do that. Note the bit around your highlight: | Quote | | and finally measure how close the results were to real experimental data. If its guesses were good (meaning the gene network made the simulated worm regenerate similarly to real-life experiments), then the machine slightly modified the random genetic network it had created, and tried again until its model was even better. |
That's ground-truthing, spelled out just about perfectly.
Plus what Tony said about hippocampi.
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