Enhancement of conformational B-cell epitope prediction using CluSMOTE.

ABSTRACT:

Background

A conformational B-cell epitope is one of the main components of vaccine design. It contains separate segments in its sequence, which are spatially close in the antigen chain. The availability of Ag-Ab complex data on the Protein Data Bank allows for the development predictive methods. Several epitope prediction models also have been developed, including learning-based methods. However, the performance of the model is still not optimum. The main problem in learning-based prediction models is class imbalance.

Methods

This study proposes CluSMOTE, which is a combination of a cluster-based undersampling method and Synthetic Minority Oversampling Technique. The approach is used to generate other sample data to ensure that the dataset of the conformational epitope is b

SUBMITTER: Solihah B 

PROVIDER: S-EPMC7924438 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature