The constant and rapid increasing of computing power has favored the diffusion of computational methods into immunology, giving the birth to computational immunology. Computational immunology, known also as immunological bioinformatics or immunoinformatics, is a modern research area that embraces data-driven computational and mathematical approaches able to model and describe the dynamics of cellular and molecular entities of the immune system, its disorders, and infections. Nowadays, immunoinformatics is dedicated to methods and tool developments for the analyses of omic-type data in immunology and knowledge inference using simulation, statistical inference, and machine learning algorithms. These fields are complementary key drivers of data-driven basic and translational immunology research for the benefit of human and animal health. 

The Workshop will focus on the application of computer methods and computational models, at any level of description (e.g., microscopic/intracellular, mesoscopic/intercellular, macroscopic/tissue or organs), for the modeling of the Immune system function, along with their application in understanding the pathogenesis of specific diseases (e.g., infectious diseases, cancers, hypersensitivities, autoimmune disorders).