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CT-SLEB is able to computationally adapt quickly to increasingly complex settings, which makes the method scalable to larger data sets in the future, as it can easily handle larger numbers of genetic ...

Model making. To develop their model, the researchers used a machine learning algorithm called an autoencoder, which automatically integrates gigantic swaths of data into a concise representation ...