AUTHOR=Liu Songbo , Cui Chengmin , Chen Huipeng , Liu Tong 

TITLE=Ensemble Learning-Based Feature Selection for Phage Protein Prediction

JOURNAL=Frontiers in Microbiology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2022.932661

DOI=10.3389/fmicb.2022.932661

ISSN=1664-302X

ABSTRACT=Phage has high specificity for its host recognition. As a natural enemy of bacteria, it has been used to treat super bacteria for many times. Identifying phage proteins from the original sequence is very important for understanding the relationship between phage and host bacteria and developing new antimicrobial agents. However, the traditional experimental methods are expensive and time-consuming. Especially, the neural network needs a large number of accurate sample data. Therefore, we propose a feature selection method based on ensemble learning to classify phage proteins. In a data-driven way, effective features such as protein sequence characteristics, physicochemical features and spatial features are first selected. Then, an ensemble classification method is used to classify and predict a new sample based on the selected features. Experimental results which show better accuracies demonstrate the effectiveness of our method.