Systems Immunology

Systems immunology is a branch of systems biology that studies the interactions among the immune system's cellular and molecular networks using mathematical and computational tools. The immune system has been thoroughly studied in terms of its components and function using a "reductionist" approach, but the overall function of the immune system cannot be easily predicted by studying the characteristics of its isolated components because it is heavily reliant on interactions among these numerous constituents. It focuses on in silico rather than in vivo studies. Mathematical models that address the dynamics of both the innate and adaptive immune systems have been developed as a result of recent research in experimental and clinical immunology. The majority of the mathematical models were employed to simulate processes that could not be replicated in vivo. T cell activation, cancer-immune interactions, migration and death of various immune cells (e.g. T cells, B cells, and neutrophils), and how the immune system would respond to a vaccination or medicine without conducting a clinical trial are all examples of these processes.

• Statistical Modelling
• Machine Learning
• Engineering and Synthetic Immunology
• Combination of Top-Down and Bottom-Up Approaches to Study
• Evolutionary Systems Immunology
• Computational and Experimental Method