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

10.1186/1471-2164-11-S4-S21

محفوظ في:

التفاصيل البيبلوغرافية
المؤلفون الرئيسيون:	Wee, L.J.K, Simarmata, D, Kam, Y.-W, Ng, L.F.P, Tong, J.C
مؤلفون آخرون:	BIOCHEMISTRY
التنسيق:	مقال
منشور في:	2020
الموضوعات:	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
الوصول للمادة أونلاين:	https://scholarbank.nus.edu.sg/handle/10635/181652
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
المؤسسة:	National University of Singapore

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