Computational Immunology: Deciphering the Immune System

Abstract: Immunoinformatics, also known as computational immunology, comprises databases and computational models that focus on analyses of the immunological data. The immune system is highly combinatorial and requires significant computational infrastructure in support of experimental work. Immunological data are scattered across general and specialist molecular biology databases. The future of immunological databases is in combination of enriched and highly annotated data warehouses that integrate specialist analysis tools with molecular and clinical data and allow for easy maintenance and updating.

Accurate computational models that simulate immune interactions are essential for the selection of key experiments and increasing the efficiency of immunological research. The predictive models use data available from the specialist databases and data warehouses. Models for prediction of T-cell epitopes have evolved from simple motifs to the sophisticated machine-learning based applications. The models of highest accuracy are those that are of higher complexity and those that are based on larger amounts of training data. The latest models can predict regions that contain high concentration of MHC-binding peptides, and thus represent best targets for vaccine development. Molecular models have been combined with the system-level model of immune responses for simulation of immunological experiments. Large-scale projects, such as ImmunoGrid enable natural-scale simulation of immune processes and enable applications such as optimization of immunisation schedules for cancer vaccines. The future of immunology is dependent on combining molecular, clinical, and informatics approaches which collectively speed-up the research and development in the field.

The critical overlap of advances in basic immunology, instrumentation for large-scale experimentation, and immunoinformatics are shaping the new field of immunomics – the study of the complete set of genes and products involved in the immune response and translation of the molecular data into improved clinical applications.