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Trends Immunol. 2003 Dec;24(12):667-74.

Towards in silico prediction of immunogenic epitopes.

Author information

1
Edward Jenner Institute for Vaccine Research, Compton, RG20 7NN, Berkshire, UK. darren.flower@jenner.ac.uk

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.

PMID:
14644141
[Indexed for MEDLINE]

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