Includes bibliographical references and index.

Introduction to basic concepts in immunology / Roxana Khazen and Salvatore Valitutti -- Overview of mechanistic modeling: techniques, approximations, and assumptions / Steven M. Abel -- The fundamentals of statistical data analysis / William C.L. Stewart -- Using data to guide model construction: application of principal component analysis and related methods in immunology research / Kathryn Miller-Jensen -- An introduction to rule-based modeling of immune receptor signaling / John A.P. Sekar, James R. Faeder -- Boolean models in immunology / Reinhard Laubenbacher and Elena Dimitrova -- From evolutionary computation to phenotypic spandrels: inverse problem for immune ligand recognition / Paul François and Mathieu Hemery -- Zen and the art of parameter estimation in systems biology / Christopher R. Myers -- Spatial kinetics in immunological modeling / Daniel Coombs and Byron Goldstein -- Analysis and modeling of single cell data / Derya Altintan, Jascha Diemer, and Heinz Koeppl -- Quantifying lymphocyte receptor diversity / Thierry Mora and Aleksandra M. Walczak -- Antigen receptor diversification during immune responses / Miri Michaeli and Ramit Mehr -- Quantitative modeling of mast cell signaling / Lily A. Chylek, David A. Holowka, Barbara A. Baird, and William S. Hlavacek -- Physical models in immune signaling / Jayajit Das -- Population dynamics of host and pathogens / Amber M. Smith, Ruy M. Ribeiro, and Alan S. Perelson -- Viral fitness landscapes: a physical sciences perspective / Gregory R. Hart and Andrew L. Ferguson -- A wish-list for modeling immunological synapses / Michael L. Dustin.

"New experimental techniques in immunology have produced large and complex data sets that require quantitative modeling for analysis. This book provides a complete overview of computational immunology, from basic concepts to mathematical modeling at the single molecule, cellular, organism, and population levels. It showcases modern mechanistic models and their use in making predictions, designing experiments, and elucidating underlying biochemical processes. It begins with an introduction to data analysis, approximations, and assumptions used in model building. Core chapters address models and methods for studying immune responses, with fundamental concepts clearly defined"-- Provided by publisher.