AUTHOR=Zhang Yanqin , Li Zhiyuan 

TITLE=RF_phage virion: Classification of phage virion proteins with a random forest model

JOURNAL=Frontiers in Genetics

VOLUME=13

YEAR=2023

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.1103783

DOI=10.3389/fgene.2022.1103783

ISSN=1664-8021

ABSTRACT=<p><bold>Introduction:</bold> Phages play essential roles in biological procession, and the virion proteins encoded by the phage genome constitute critical elements of the assembled phage particle.</p><p><bold>Methods:</bold> This study uses machine learning methods to classify phage virion proteins. We proposed a novel approach, RF_phage virion, for the effective classification of the virion and non-virion proteins. The model uses four protein sequence coding methods as features, and the random forest algorithm was employed to solve the classification problem.</p><p><bold>Results:</bold> The performance of the RF_phage virion model was analyzed by comparing the performance of this algorithm with that of classical machine learning methods. The proposed method achieved a specificity (Sp) of 93.37%%, sensitivity (Sn) of 90.30%, accuracy (Acc) of 91.84%, Matthews correlation coefficient (MCC) of .8371, and an F1 score of .9196.</p>