Laboratory experimentation in immunology, particularly
that related to antigen recognition and determination of specific
targets of immune response, has become a combinatorial challenge.
Understanding the mechanisms of immune recognition
and specificity and selection of immune response targets is
necessary before this information can be applied systematically to the design of vaccines and immunotherapeutics. We anticipate
that dynamic models of immune interactions that can
absorb the ever-increasing amount of data generated in the field
and self-improve with the accumulation of data and knowledge
will become standard methodology in immunology research.
Standardization and exploitation of the synergies of modelling
and experimental methods provide an efficient means for largescale
epitope screening. This study provides a first-level guideline
for cyclical refinement of computer models and their
integration with laboratory experiments.