Geometric Deep Learning Methods with Deep Chemistry for Drug Pair Interactions
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About this project
Obtained the Simplified molecular-input line-entry system(SMILES) component of each drug, performed feature extraction using autoencoders, and built a multi-class classifier that can predict the interaction class from a range of 86 different interaction classes. Obtained accuracy of 80% (bound to increase further with better computational resources)