id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_ho2ac3l4ivbnbkr2yq3m3ik4re	Binti Solihah	Enhancement of conformational B-cell epitope prediction using CluSMOTE	2020	17	.pdf	application/pdf	7766	918	63	This study proposes CluSMOTE, which is a combination of a clusterbased undersampling method and Synthetic Minority Oversampling Technique. than other methods in the general protein antigen, though comparable with SEPPA 3 Keywords Cluster-based undersampling, SMOTE, Class imbalance, Hybrid sampling, Hierarchical DBSCAN, Vaccine design methods, including the structure and sequence-based approaches. discarded the negative class data that overlap the positive in a specific cluster based on the In this research, the cluster-based undersampling method is combined with SMOTE to Conformational B-cell epitope prediction method The number of clusters is less than the positive class data. A dataset used for conformational epitope prediction contains the class imbalance problem. An epitope is a small part of the exposed antigen that creates class imbalance problems in the prediction of learning-based conformational epitopes. Prediction of residues in discontinuous B-cell epitopes using protein 3D structures. A new performance measure for class imbalance learning.	./cache/work_ho2ac3l4ivbnbkr2yq3m3ik4re.pdf	./txt/work_ho2ac3l4ivbnbkr2yq3m3ik4re.txt