AUTHOR=Su Wenxia , Qian Xiaojun , Yang Keli , Ding Hui , Huang Chengbing , Zhang Zhaoyue 

TITLE=Recognition of outer membrane proteins using multiple feature fusion

JOURNAL=Frontiers in Genetics

VOLUME=14

YEAR=2023

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2023.1211020

DOI=10.3389/fgene.2023.1211020

ISSN=1664-8021

ABSTRACT=<p><bold>Introduction:</bold> Outer membrane proteins are crucial in maintaining the structural stability and permeability of the outer membrane. Outer membrane proteins exhibit several functions such as antigenicity and strong immunogenicity, which have potential applications in clinical diagnosis and disease prevention. However, wet experiments for studying OMPs are time and capital-intensive, thereby necessitating the use of computational methods for their identification.</p><p><bold>Methods:</bold> In this study, we developed a computational model to predict outer membrane proteins. The non-redundant dataset consists of a positive set of 208 outer membrane proteins and a negative set of 876 non-outer membrane proteins. In this study, we employed the pseudo amino acid composition method to extract feature vectors and subsequently utilized the support vector machine for prediction.</p><p><bold>Results and Discussion:</bold> In the Jackknife cross-validation, the overall accuracy and the area under receiver operating characteristic curve were observed to be 93.19% and 0.966, respectively. These results demonstrate that our model can produce accurate predictions, and could serve as a valuable guide for experimental research on outer membrane proteins.</p>