Communications of the ACM
AI Model Helps Discover Causes of Motor Neuron Disease
Said Michael Snyder at the Stanford School of Medicine, “By doing machine learning for genome analysis, we are discovering more hidden genes for human complex diseases such as MND, which will eventually power personalized treatment and intervention
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A new machine learning model developed by researchers at the U.K.'s University of Sheffield and the Stanford University School of Medicine identified 690 risk genes for motor neuron disease (MND).
The new genes identified by the tool, RefMap, resulted in a five-fold increase in discovered heritability.
Stanford's Sai Zhang explained, "RefMap identifies risk genes by integrating genetic and epigenetic data. It is a generic tool and we are applying it to more diseases in the lab."
One new MND gene, KANK1, was found to produce neurotoxicity in human neurons similar to that in the brains of patients and could be a new target for designing new drugs.
Said Stanford's Michael Snyder, "By doing machine learning for genome analysis, we are discovering more hidden genes for human complex diseases such as MND, which will eventually power personalized treatment and intervention."
From University of Sheffield (U.K.)
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