The current ability to sequence the genomes of virulent microorganisms at low cost, now allows in-silico screenings to detect the most promising candidate proteins to develop vaccines and diagnostics. However, there is still limited knowledge on what molecular and sequence features differentiates a pathogen's protein targeted by the immune system from other proteins of the pathogen. In this project, we propose to approach that problem by exploiting the vast amount of immunological data centralized in the Immune Epitope Database, as well as data produced by high-throughput screening technologies, such as peptide and protein microarrays. Using these data, we plan to investigate if there are biases in the representation of functional classes or structural properties of the proteins targeted by the humoral immune system, and its coupling with the T-cell immune response. We have applied a similar strategy before for Chagas disease and here we propose to extend the analysis to a large number of prokaryotic and eukaryotic pathogens.