Computational Immunology

Computational immunology, also known as immunoinformatics, is an area of study that deals with the structuring of massive volumes of raw immunological data using computational methods, allowing researchers to develop useful interpretations. Computational immunology (also known as systems immunology) is the study of immune system biology using bioinformatics methodologies, mathematical models, and statistical techniques. The immune system is made up of dozens of different cell types and hundreds of biochemical pathways and signals that cross each other. To forecast how the immune system will respond to a certain infection or immunisation, systems techniques can be employed. It can also assist in determining how to best develop an immunotherapy, such as if it will help to alleviate disease and what the potential negative effects might be. Furthermore, computational techniques are becoming increasingly important for deciphering the implications of the vast amounts of gene expression and epigenomics data collected from immune cells. The construction of complete, multiscale network models of massively interacting systems that fully describe the dynamics of the immune system with its effector and regulatory aspects is a primary goal of computational immunology.

• Models and Tools
• Methods and Applications
• Immunoinformatics
• Modeling
• Data Analytics