In collaboration with University of Washington, Seattle, USA we are analyzing transcriptomics data from experiments with vaccines against SIV (Simian Immunodeficiency Virus) in Rhesus macaques and build models of protection acquisition. We apply Monte Carlo techniques and simplification of Boolean expressions to develop machine learning models. We further analyze data from a variety of viral diseases to build background models for responses of the immune system. These developments lead to large computational tasks that exceed the resource available locally hence an application to UPPMAX.