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Identification of Helicobacter pylori Membrane Proteins Using Sequence-Based Features

Authors :
Mujiexin Liu
Hui Chen
Dong Gao
Cai-Yi Ma
Zhao-Yue Zhang
Source :
Computational and Mathematical Methods in Medicine, Vol 2022 (2022), Computational and Mathematical Methods in Medicine
Publication Year :
2022
Publisher :
Hindawi Limited, 2022.

Abstract

Helicobacter pylori (H. pylori) is the most common risk factor for gastric cancer worldwide. The membrane proteins of the H. pylori are involved in bacterial adherence and play a vital role in the field of drug discovery. Thus, an accurate and cost-effective computational model is needed to predict the uncharacterized membrane proteins of H. pylori. In this study, a reliable benchmark dataset consisted of 114 membrane and 219 nonmembrane proteins was constructed based on UniProt. A support vector machine- (SVM-) based model was developed for discriminating H. pylori membrane proteins from nonmembrane proteins by using sequence information. Cross-validation showed that our method achieved good performance with an accuracy of 91.29%. It is anticipated that the proposed model will be useful for the annotation of H. pylori membrane proteins and the development of new anti-H. pylori agents.

Details

ISSN :
17486718 and 1748670X
Volume :
2022
Database :
OpenAIRE
Journal :
Computational and Mathematical Methods in Medicine
Accession number :
edsair.doi.dedup.....2c819f9cb3cd1f518f645b57436eec8b