| Literature DB >> 14644141 |
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.Mesh:
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Year: 2003 PMID: 14644141 DOI: 10.1016/j.it.2003.10.006
Source DB: PubMed Journal: Trends Immunol ISSN: 1471-4906 Impact factor: 16.687