SVM-based prediction of linear B-cell epitopes using Bayes Feature Extraction

SVM-based prediction of linear B-cell epitopes using Bayes Feature Extraction

10.1186/1471-2164-11-S4-S21

Saved in:

Bibliographic Details
Main Authors:	Wee, L.J.K, Simarmata, D, Kam, Y.-W, Ng, L.F.P, Tong, J.C
Other Authors:	BIOCHEMISTRY
Format:	Article
Published:	2020
Subjects:	antigen epitope glutamine proline tryptophan peptide access to information accuracy amino acid composition article B lymphocyte Bayes theorem computer model epitope mapping Internet mathematical analysis prediction quality control receiver operating characteristic sequence analysis support vector machine algorithm chemistry computer simulation immunology predictive value Benchmark datasets Data sets Experimental approaches High variability In-silico Prediction algorithms Prediction model SVM classifiers Test sets Web servers Algorithms Bioinformatics Classification (of information) Feature extraction Forecasting Mathematical models Polypeptides Proteins Support vector machines Antigens Bayes Theorem Benchmarking Computer Simulation Epitopes, B-Lymphocyte Peptides Predictive Value of Tests
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/181652
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	10.1186/1471-2164-11-S4-S21