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List of contents
1. Introduction to Basic Concepts in Immunology 2. Overview of Mechanistic Modeling: Techniques, Approximations, and Assumptions 3. The Fundamentals of Statistical Data Analysis 4. Using Data to Guide Model Construction: Application of Principal Component Analysis and Related Methods in Immunology Research 5. An Introduction to Rule-based Modeling of Immune Receptor Signaling 6. Boolean Models in Immunology 7. From evolutionary computation to phenotypic spandrels: inverse problem for immune ligand recognition 8. Zen and the Art of Parameter Estimation in Systems Biology 9. Spatial Kinetics in Immunological Modeling 10. Analysis and modeling of single cell data 11. Quantifying lymphocyte receptor diversity 12. Antigen receptor diversification during immune responses 13. Quantitative Modeling of Mast Cell Signaling 14. Physical models in immune signaling 15. Population Dynamics of Host and Pathogens 16. Viral fitness landscapes: A physical sciences perspective 17. A wish-list for modeling immunological synapses
About the author
Jayajit Das, Ph.D., is Assistant Professor of Pediatrics at the Wexner Medical Center, The Ohio State University, and Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children’s Hospital, both in Columbus, Ohio. He obtained his Ph.D. in statistical physics from The Institute of Mathematical Sciences and Raman Research Institute, India. He was a postdoctoral research associate at Virginia Tech, University of California, Berkeley, and Massachusetts Institute of Technology, prior to joining OSU. He is a member of the American Physical Society, author of many published journal articles, and invited speaker at numerous international conferences.
Ciriyam Jayaprakash, Ph.D., is Professor in the Department of Physics at The Ohio State University in Columbus, Ohio. He earned his doctorate in physics from the University of Illinois at Urbana-Champaign, and was a postdoctoral associate at Cornell University as well as a visiting scientist at the IBM Watson Research Center prior to joining the faculty of OSU. He is the recipient of a prestigious Alfred P. Sloan Foundation Fellowship and NSF Presidential Young Investigator Award, and is an elected Fellow of the American Physical Society. His current research interests include modeling of viral antagonists and immune system response, stochastic effects in subcellular processes, and applications of nonlinear dynamics.
Summary
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.
