Systems Immunology

An Introduction to Modeling Methods for Scientists

Jayajit Das, Ciriyam Jayaprakash, Jayajit Das, Ciriyam Jayaprakash

• Publisher: CRC Press
• Year: 2018
• Print ISBN: 9781498717403
• eBook ISBN: 9781351646147
• Edition: 1
• Topic: Physical Sciences
• Subtopic: Applied Mathematics

"Taken together, the body of information contained in this book provides readers with a bird's-eye view of different aspects of exciting work at the convergence of disciplines that will ultimately lead to a future where we understand how immunity is regulated, and how we can harness this knowledge toward practical ends that reduce human suffering. I commend the editors for putting this volume together."

–Arup K. Chakraborty, Robert T. Haslam Professor of Chemical Engineering, and Professor of Physics, Chemistry, and Biological Engineering, Massachusetts Institute of Technology, Cambridge, USA

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.

Readers from immunology, quantitative biology, and applied physics will benefit from the following:

• 
  
  

• Fundamental principles of computational immunology and modern quantitative methods for studying immune response at the single molecule, cellular, organism, and population levels.

• 
  
  

• An overview of basic concepts in modeling and data analysis.

• 
  
  

• Coverage of topics where mechanistic modeling has contributed substantially to current understanding.

• 
  
  

• Discussion of genetic diversity of the immune system, cell signaling in the immune system, immune response at the cell population scale, and ecology of host-pathogen interactions.

Table of contents

• Cover
• Half Title Page
• Series Page
• Title Page
• Copyright Page
• Dedication
• Contents
• Series preface
• Foreword
• Preface
• Editor
• Author
• Chapter 1 Introduction to basic concepts in immunology
• Chapter 2 Overview of mechanistic modelingTechniques, approximations, and assumptions
• Chapter 3 The fundamentals of statistical data analysis
• Chapter 4 Using data to guide model constructionApplication of principal component analysis and related methods in immunology research
• Chapter 5 An introduction to rule-based modeling of immune receptor signaling
• Chapter 6 Boolean models in immunology
• Chapter 7 From evolutionary computation to phenotypic spandrelsInverse problem for immune ligand recognition
• Chapter 8 Zen and the art of parameter estimation in systems biology
• Chapter 9 Spatial kinetics in immunological modeling
• Chapter 10 Analysis and modeling of single cell data
• Chapter 11 Quantifying lymphocyte receptor diversity
• Chapter 12 Antigen receptor diversification during immune responses
• Chapter 13 Quantitative modeling of mast cell signaling
• Chapter 14 Physical models in immune signaling
• Chapter 15 Modeling and inference of cell population dynamics
• Chapter 16 Population dynamics of host and pathogens
• Chapter 17 Viral fitness landscapesA physical sciences perspective
• Chapter 18 A wish-list for modeling immunological synapses
• Index