Peptide-based vaccines, in which small peptides derived from target proteins (epitopes) are used to provoke an immune reaction, have attracted considerable attention recently as a potential means both of treating infectious diseases and promoting the destruction of cancerous cells by a patient's own immune system. With the availability of large sequence databases and computers fast enough for rapid processing of large numbers of peptides, computer aided design of peptide-based vaccines has emerged as a promising approach to screening among billions of possible immune-active peptides to nd those likely to provoke an immune response to a particular cell type. In this paper, we describe the development of three novel classes of methods for the prediction of class I epitopes. Each one of the three classes of methods gives a speci c set of insights into the epitope prediction problem. We present a quadratic programming approach that can be trained on quantitative as well as qualitativ...
Liliana Florea, Bjarni V. Halldórsson, Oliv