Drug Repurposing Strategy Without An ‘Answer Book’ – Bio-IT World

June 7, 2022 | Scientists working in the information biology lab at Hokkaido University (Japan) have come up with a drug repurposing strategy combining machine learning, unsupervised clustering of gene expression, and two-stage prediction. Machine learning, as used here, differs from standard approaches where performance of the method is measured by “repeated partitioning of data to see [the] distribution of sensitivity and specificity of prediction using known data,” according to team member Toshinori Endo, Ph.D., professor of information science and technology. “We wanted to explore an alternative that is independent of [an] answer book.”

Typically, the “hidden assumption” is that training data has been used to teach a machine learning algorithm to predict the outcome the model was designed to predict, he says. But for unsupervised learning, determining the boundaries between classes of data can be a bit more complicated. “Lack of apparent criteria is normally the case for real…

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