For any given outcome in a complex biological system, there are numerous possible pathways that might have been involved; one of the tasks faced by an immunologist is to work back from a known immune response to determine the crucial parameters and processes.

Rustom Antia, Vitaly Ganusov and Rafi Ahmed (page 101) describe how mathematical models can help us to understand such complexity. One of the most important aspects of immunity, which accounts for the success of vaccination, is the ability to respond more rapidly and effectively to previously encountered pathogens (immune memory). Several theories have been put forward to explain how memory T cells are generated and sustained; by comparing mathematical models with experimental data, it is possible to focus on the most likely explanation.

On page 171, Michael Neuberger and colleagues stress the importance of considering all possible explanations for a particular outcome. They put forward an alternative hypothesis to explain the A·T mutations that occur during somatic hypermutation of immunoglobulin genes. Although these are generally thought to occur as a result of polymerase error, Neuberger suggests that, until this model is proven, it would be unwise not to at least consider other options.

To add to the complexity of understanding biological systems, it is also important to consider that known pathways and mediators might have more than one important function. For example, members of the interferon-regulatory factor (IRF) family were originally discovered as mediators of the effects of interferons, but they have now been shown to be involved in T-helper-cell differentiation. This can occur through effects on either antigen-presenting cells or T cells themselves, as described by Michael Lohoff and Tak Mak on page 125.