A new approach for determining SARS-CoV-2 epitopes using machine learning-based in silico methods

A new approach (SMOTE-RF-SVM) is proposed to identify SARS-CoV-2 epitopes that can be used in vaccine design. Epitope candidates that can be used in vaccine design were determined using machine learning-based in silico and bioinformatics tools. In the unbalanced dataset, generating artificial data with the SMOTE technique increased the model performance. Nonallergic, high antigen (antigen score ≥1.0) and nontoxic 11 possible epitopes candidates were proposed. The search space for vaccine studies was narrowed by SMOTE-RF-SVM.