Successful Prediction for Major Histocompatibility Complex (MHC) molecule epitopes is an essential step in designing Genetic Vaccines. Successful prediction of MHC class II epitopes is more difficult than MHC class I epitopes due to open binding groove at both ends in class II molecules, this structure leads to variable length for MHC II epitopes and complicating the task for detecting the core binding 9-mer. In this Book we presented a novel classification algorithm for predicting MHC Class II epitopes using Multiple Instance Learning technique. Separated Constructive Clustering Ensemble...

The study of artificial immune systems is a relatively new field that tries to exploit the mechanisms of the natural immune system (NIS) in order to develop problem-solving techniques. In this book, we have combined the artificial immune system with the genetic algorithms in one hybrid algorithm. The hybrid algorithm used for evolving a fuzzy rule system to solve the well known Wisconsin Breast Cancer Diagnosis problem (WBCD). The hybrid algorithm overcomes both the GAs and the AIS, so that it reached the classification ratio 97.36, by only one rule, in the earlier generations than the two...