Predicting Antimalarial Activity in Natural Products Using Pretrained Bidirectional Encoder Representations from Transformers

Malaria is a threatening disease that has claimed many lives and has a high prevalence rate annually. Through the past decade, there have been many studies to uncover effective antimalarial compounds to combat this disease. Alongside chemically synthesized chemicals, a number of natural compounds ha...

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Veröffentlicht in:	Journal of chemical information and modeling 2022-11, Vol.62 (21), p.5050-5058
Hauptverfasser:	Nguyen-Vo, Thanh-Hoang, Trinh, Quang H., Nguyen, Loc, Do, Trang T. T., Chua, Matthew Chin Heng, Nguyen, Binh P.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Antimalarials - chemistry Antimalarials - pharmacology Biological Products - pharmacology Biomedical materials Coders Machine Learning Machine Learning and Deep Learning Malaria Natural products Prediction models Representations Support Vector Machine Support vector machines Transformers
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