The boundaries between simple and complicated, and complicated and complex system designations are fuzzy and debatable, even using quantitative measures of complexity. However, if you are a biomedical engineer, a biologist, physiologist, economist, politician, stock market speculator, or politician, you have encountered complex systems. Furthermore, your success depends on your ability to successfully interact with and manage a variety of complex systems. In order not to be blindsided by unexpected results, we need a systematic, comprehensive way of analyzing, modeling, and simulating complex systems to predict non-anticipated outcomes.
In its engaging first chapters, the book introduces complex systems, Campbell's Law, and the Law of Unintended Consequences, and mathematics necessary for conversations in complex systems. Subsequent chapters illustrate concepts via commonly studied biological mechanisms. The final chapters focus on higher-level complexity problems, and introduce complexity in economic systems.
Designed as a reference for biologists and biological engineers, Introduction to Complexity and Complex Systems lends itself to use in a classroom course to introduce advanced students studying biomedical engineering, biophysics, or physiology to complex systems. Engaging and illustrative, this book aids scientists and decision makers in managing biological complexity and complex systems.
Table of Contents
Introduction to Complexity and Complex Systems
Introduction to Complexity
Why Study Complex Systems?
Human Responses to Complexity
Complex Systems Engineering
Introduction to Large Linear Systems
Linearity, Causality & Stationarity
L TI System Tools Impulse Response, Frequency Response and Real Convolution
Systems Described by Large Sets of Linear ODEs
Stability of Linear Systems
Signal Flow Graphs and Mason's Rule
Introduction to Nonlinear Biochemical Systems and Biochemical Oscillators
Introduction Some General Properties of NonIinear Systems
All Living Systems Are Nonlinear
Parametric Regulation in Complex Biological Systems
Chaos, Stability and Limit Cycle Oscillations in Nonlinear Systems
Modularity, Redundancy, Degeneracy, Pleiotropy and Robustness in
Complex Biological Systems
Measures of Modularity
Modularity in Physiological Organ Systems
Modularity in Gene Regulation and Development
Network Motifs and Modularity
Redundancy, Degeneracy, Pleiotropy and Robustness
The Evolution of Biological Complexity; Invertebrate Immune Systems
Darwinian Evolution; a Brief Summary
Why Does a Rise in Complexity Accompany Biological Evolution?
Examples of Biological Complexity; Invertebrate Immune Systems
The Complex Adaptive and Innate Human Immune Systems
An Overview of the CAIS
A Summary of the Cells of the hIS
Innate Immune Systems
Autacoids Immunocytokines, Proteins and Glycoproteins Secreted by hIS Cells
Discussion How the hIS is Adaptive
Complexity in Quasispecies MicroRNAs
Quasispecies; Viral and Bacterial Evolutionary Models [see Kamp papers in NB3]
The Role of Micro-RNAs in the Regulation of Gene Expression and Disease
Introduction to Physiological Complexity Examples of Models of Some Complex Physiological Systems
Structure & Function Some Examples of Complex Physiological Regulatory Systems and their Models
Examples of When Complex Physiological Systems Fail
The Quest for Quantitative Measures of Complexity
Intuitive Measures of Complexity
Structural Complexity Measures
Informatic Complexity Measures
"Irreducible and Specified Complexity" in Living Systems
Introduction to Complexity in Economic Systems
Dealing with Complexity
Dorner's Approaches to Tackling Complex Problems
Frederic Vester's "Paper Computer"
The Sensitivity Model of Vester
Learning From Our Mistakes
Bibliography and References
Robert B. Northrop is Professor Emeritus and the former Program Director of the Biomedical Engineering Graduate Program at the University of Connecticut.