Staged heterogeneity learning to identify conformational B-cell epitopes from antigen sequences.

ABSTRACT:

Background

The broad heterogeneity of antigen-antibody interactions brings tremendous challenges to the design of a widely applicable learning algorithm to identify conformational B-cell epitopes. Besides the intrinsic heterogeneity introduced by diverse species, extra heterogeneity can also be introduced by various data sources, adding another layer of complexity and further confounding the research.

Results

This work proposed a staged heterogeneity learning method, which learns both characteristics and heterogeneity of data in a phased manner. The method was applied to identify antigenic residues of heterogenous conformational B-cell epitopes based on antigen sequences. In the first stage, the model learns the general epitope patterns of each kind of propensity from a larg

SUBMITTER: Ren J 

PROVIDER: S-EPMC5374683 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature