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Identification of Helicobacter pylori Membrane Proteins Using Sequence-Based Features
- 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.
- Subjects :
- Support Vector Machine
Article Subject
Helicobacter pylori
Host Microbial Interactions
General Immunology and Microbiology
Applied Mathematics
Computer applications to medicine. Medical informatics
R858-859.7
Computational Biology
Membrane Proteins
General Medicine
bacterial infections and mycoses
General Biochemistry, Genetics and Molecular Biology
Bacterial Proteins
Modeling and Simulation
Humans
Amino Acid Sequence
Amino Acids
Databases, Protein
Research Article
Subjects
Details
- ISSN :
- 17486718 and 1748670X
- Volume :
- 2022
- Database :
- OpenAIRE
- Journal :
- Computational and Mathematical Methods in Medicine
- Accession number :
- edsair.doi.dedup.....2c819f9cb3cd1f518f645b57436eec8b