This volume investigates whether the integration of theoretical modeling and experimental data can accelerate the understanding of complex immune system phenomena. Alan S. Perelson, a prominent researcher in theoretical biology, compiles the proceedings from a 1987 workshop co-sponsored by the Santa Fe Institute and Los Alamos National Laboratory. The text argues that interdisciplinary collaboration between mathematicians and experimentalists is necessary to resolve ambiguities in immunological research. By applying quantitative frameworks to biological systems, the contributors aim to refine existing paradigms regarding immune function and disease progression.

Experts recognize this text as a foundational record of early efforts to apply rigorous mathematical modeling to immunological problems. Researchers frequently note that while the data reflects the state of the field in 1987, the methodological approaches remain relevant for those studying the history of computational biology.