International Conference on Computer and Knowledge Engineering

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Home / 14th International Conference on Computer and Knowledge Engineering

Virus-Antiviral Prediction Using Machine and Deep Learning Methods

Authors :

Shayan Majidifar¹ Fatemeh Nasiri² Mohsen Hooshmand³

1- Institute for Advanced Studies in Basic Sciences (IASBS) 2- Institute for Advanced Studies in Basic Sciences (IASBS) 3- Assistant Professor

Keywords :

Drug repurposing،Machine learning،Virus،Antiviral،Deep learning،Dataset

Abstract :

Prediction of new virus-antiviral associations is significant in the treatment of virus diseases. This work proposes a prediction framework for finding new associations among the virus diseases and approved antivirals. To do this, we have generated a new virus-antiviral dataset. Additionally, we propose a prediction framework using random forest, SVM, XGBoost, and a deep learning model. The results are promising and XGBoost outperforms all other methods in the prediction of virus-antiviral associations.

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