Communications of the ACM
Machine Learning Lets Scientists Reverse-Engineer Cellular Control Networks
The Stampede supercomputer at the Texas Advanced Computing Center is helping researchers from Tufts University and the University of Maryland, Baltimore County create tadpoles with pigmentation never before seen in nature.
Credit: Daniel Lobo, Maria Lobikin, Michael Levin
Researchers from Tufts University and University of Maryland, Baltimore County are using the Texas Advanced Computing Center's Stampede supercomputer to create tadpoles with pigmentation never before seen in nature.
The researchers used machine learning to uncover the cellular control networks that determine how organisms develop, and to design methods to disrupt them.
This study could pave the way for computationally-designed cancer treatments and regenerative medicine.
"In the end, the value of machine-learning platforms is in whether they can get us to new capabilities, whether for regenerative medicine or other therapeutic approaches," says Tufts University professor Michael Levin.
The researchers used Stampede to run billions of simulations in order to model the cellular network and the means of altering it. The team found its artificial intelligence-derived model could be used to discover a treatment that would break the normal concordance among cells.
From Texas Advanced Computing Center
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