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Abstract

A method for training a deep learning model configured for virtual screening of molecules for micro ribonucleic acid (miRNA) drug discovery includes creating a training dataset including a plurality of assay datasets. The method also includes training the deep learning model to learn a plurality of tasks; performing, using the deep learning model, inference for the respective task associated with at least one miRNA assay dataset; and evaluating respective performance metrics associated with the respective predictions for each of the plurality of tasks. The method further includes selecting a set of the plurality of assay datasets for training; and training the deep learning model to learn a set of the plurality of tasks using the set of the plurality of assay datasets. The trained deep learning model is configured to predict molecules capable of affecting a target miRNA.

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