Use of BONSAI decision trees for the identification of potential MHC class I peptide epitope motifs.

摘要: Recognition of short peptides 8 to 10 mer bound MHC class I molecules by cytotoxic T lymphocytes forms the basis cellular immunity. While sequence motifs necessary for binding intracellular have been well studied, little is known about that may cause preferential affinity cell receptor and/or recognition and response cells. Here we demonstrate computational learning systems can be useful elucidate affect activation. Knowledge activation could targeted vaccine design or immunotherapy. With BONSAI algorithm, using a database previously reported had positive negative responses, were able identify motif rules explain 70% responses 84% responses.