UNDERSTANDING IMMUNOLOGY
1 Introduction to basic concepts in immunology 1 2 Overview of mechanistic modeling: Techniques, approximations, and assumptions 29 3 The fundamentals of statistical data analysis 41 4 Using data to guide model construction: Application of principal component analysis and related methods in immunology research 51 5 An introduction to rule-based modeling of immune receptor signaling 71 6 Boolean models in immunology 91 7 From evolutionary computation to phenotypic spandrels: Inverse problem for immune ligand recognition 103 8 Zen and the art of parameter estimation in systems biology 123 9 Spatial kinetics in immunological modeling 139 10 Analysis and modeling of single cell data 159 11 Quantifying lymphocyte receptor diversity 183 12 Antigen receptor diversification during immune responses 199 13 Quantitative modeling of mast cell signaling 213 14 Physical models in immune signaling 227 15 Modeling and inference of cell population dynamics 251 16 Population dynamics of host and pathogens 265 17 Viral fitness landscapes: A physical sciences perspective 279 18 A wish-list for modeling immunological synapses 299