The question aims to investigate the extent to which transfer learning enhances the prediction capabilities of computational models in the domain of drug-target binding affinity. By utilizing pre-existing knowledge and leveraging patterns learned from prior data, transfer learning can potentially overcome data limitations and improve the accuracy of predictions for new drug-target interactions.
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