Immunoinformatics and its relevance to understanding human immune disease.

Immunology research is characterized by the production of increasingly vast amounts of data, fuelled by genomics and proteomics projects and large-scale screening of pathogen- and antigen-host interactions. The need to store, manage and analyze this rapidly growing resource of experimental, clinical and epidemiologic data has given rise to the field known as immunoinformatics. Immunoinformatics represents computational methods and resources that are used in the study of immune function. It lies at the intersection of experimental and computational sciences and encompasses domain-specific databases, computational models and strategies drawn from artificial intelligence. For example, computational or artificial intelligence models are increasingly being used to simulate and improve our understanding of immune system behavior, such as antigen processing and presentation, as well as for analysis of host and pathogen genomes. Systemic models focus on simulating the behavior of cells or whole organs and can be used for applications such as tracking the course of infection or optimization of immunization protocols. Immunomics, the large-scale screening of immune processes, which includes powerful immunoinformatic tools, offers great promise for future translation of basic immunology research advances into clinical practice. Immunoinformatics is central to the research fields of immunogenomics, immunoproteomics and computational vaccinology.