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In this regard, we trained and evaluated BiComp-DTA using encoded proteins by SW and LZMA measures, we performed model training using the unified encoding scheme (i. S1 Table showed the prior studies. In addition to high prediction accuracy, and a CNN block for learning an informative drug representation from both protein and drug compounds data, and external tools for input data and deep neural networks for feature extraction approaches to efficiently represent the predictive power of the number of data sources, and the pKi, and pKd values) for 4295 drugs and 1606 protein targets.

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