Machine learning algorithms excel at finding complex patterns within big data, so researchers often use them to make predictions. Researchers are pushing the technology beyond finding correlations to help uncover hidden cause-effect relationships and drive scientific discoveries. At the University of South Florida, researchers are integrating machine learning techniques into their work studying proteins. One of their challenges has been a lack of methods to identify cause-effect relationships in data obtained from molecular dynamics simulations.
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