Towards in silico prediction of immunogenic epitopes

Flower, Darren R. (2003). Towards in silico prediction of immunogenic epitopes. Trends in Immunology, 24 (12), pp. 667-674.

Abstract

As torrents of new data now emerge from microbial genomics, bioinformatic prediction of immunogenic epitopes remains challenging but vital. In silico methods often produce paradoxically inconsistent results: good prediction rates on certain test sets but not others. The inherent complexity of immune presentation and recognition processes complicates epitope prediction. Two encouraging developments – data driven artificial intelligence sequence-based methods for epitope prediction and molecular modeling methods based on three-dimensional protein structures – offer hope for the future.

Publication DOI: https://doi.org/10.1016/j.it.2003.10.006
Divisions: Life & Health Sciences > Pharmacy
Life & Health Sciences
Published Date: 2003-12
Authors: Flower, Darren R. ( 0000-0002-8542-7067)

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