End-to-End Representation Learning for Chemical-Chemical Interaction Prediction

Chemical-chemical interaction (CCI) plays a major role in predicting candidate drugs, toxicities, therapeutic effects, and biological functions. CCI is typically inferred from a variety of information; however, CCI has yet not been predicted using a learning-based approach. In other drug analyses, d...

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Veröffentlicht in:	IEEE/ACM transactions on computational biology and bioinformatics 2019-09, Vol.16 (5), p.1436-1447
Hauptverfasser:	Kwon, Sunyoung, Yoon, Sungroh
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Biological effects Biology Chemical-chemical interaction Chemicals CNN commutative property Commutativity Computational Biology - methods Databases, Chemical Deep Learning Drug development Drug Interactions Drugs Feature extraction Generators Machine learning neural network Neural networks Organic chemistry Pharmaceutical Preparations - chemistry Pharmaceutical Preparations - metabolism Predictions Representations Siamese SMILES Toxicity
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