Computational predictions for protein sequences of COVID-19 virus via machine learning algorithms.

ABSTRACT: The rapid spread of coronavirus disease (COVID-19) has become a worldwide pandemic and affected more than 15 million patients reported in 27 countries. Therefore, the computational biology carrying this virus that correlates with the human population urgently needs to be understood. In this paper, the classification of the human protein sequences of COVID-19, according to the country, is presented based on machine learning algorithms. The proposed model is based on distinguishing 9238 sequences using three stages, including data preprocessing, data labeling, and classification. In the first stage, data preprocessing's function converts the amino acids of COVID-19 protein sequences into eight groups of numbers based on the amino acids' volume and dipole. It is based on the conjoint triad (C

SUBMITTER: Afify HM 

PROVIDER: S-EPMC8295007 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature