Organism-Specific training improves performance of linear B-Cell epitope prediction.

ABSTRACT: In silico identification of linear B-cell epitopes represents an important step in the development of diagnostic tests and vaccine candidates, by providing potential high-probability targets for experimental investigation. Current predictive tools were developed under a generalist approach, training models with heterogeneous data sets to develop predictors that can be deployed for a wide variety of pathogens. However, continuous advances in processing power and the increasing amount of epitope data for a broad range of pathogens indicate that training organism or taxon-specific models may become a feasible alternative, with unexplored potential gains in predictive performance. This paper shows how organism-specific training of epitope prediction models can yield substantial performance gai

SUBMITTER: Ashford J 

PROVIDER: S-EPMC8665745 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature