Physical Models of Living Systems - 2nd Edition by Philip Nelson (Paperback)

About the Book

Award-winning prof brings you from first-year classes to the frontiers of inference from data, systems and synthetic biology, cellular control networks, epidemic modeling, and superresolution and cryo-electron microscopy imaging.

Book Synopsis

Award-winning prof brings you from first-year classes to the frontiers of systems and synthetic biology, epidemic modeling, and imaging. Physical Models of Living Systems is a university textbook that integrates those cutting-edge topics with classic results in statistical inference, control theory, biophysical chemistry and mechanobiology, immunology, and neuroscience, as well as guiding you to create your own stochastic simulations. Instead of offering a huge pile of facts, the discovery-style exposition frequently asks you to reflect on "How could anything like that happen at all?" and then shows how scientists have incrementally peeled back the layers of mystery surrounding these beautiful mechanisms. Working through this book will give you an appreciation for how science has advanced in the past, and the skills and frameworks needed to push forward in the future.

Intended for intermediate-level undergraduates in any science or engineering major, the only prerequisite for this course is first-year physics. Supplementary sections make the book also suitable as the basis of a graduate-level course. This low-cost second edition expands the first one with four new chapters as well as adding add many clarifications and updates. Dozens of exercises are included at all levels of complexity, many involving computer work. Throughout, the goal is for you to gain the fluency needed to derive every result for yourself.

Along the way, you will acquire several research skills that are often not addressed in traditional courses:

Basic modeling skills, including dimensional analysis, identification of variables, and ODE formulation;

Probabilistic modeling skills, including stochastic simulation;

Data analysis methods, including maximum likelihood and Bayesian methods;

Computer programming using a general-purpose platform like MATLAB or Python, with short codes written from scratch;

Dynamical systems, particularly feedback control, with phase portrait methods.

All of these basic skills, which are relevant to nearly any field of science or engineering, are presented in the context of case studies from living systems, including:

Virus dynamics;

Bacterial genetics and evolution of drug resistance;

Statistical inference;

Superresolution microscopy and cryo-electron microscopy;

Stochastic simulation, for example of gene expression;

Synthetic biology;

Epidemic modeling;

Naturally evolved cellular control circuits, including homeostasis, genetic switches, and the mitotic clock;

Excitable media.

Review Quotes

For first edition:

"Particularly compelling for its smooth integration of biological experiments, physical models, and computational exercises. Readers who complete the text will be well equipped with the computational and mathematical skills needed for a quantitative understanding of a range of biological systems.... Thanks to Nelson's skillful writing and the excellent accompanying online resources, this book will appeal to a broad audience and teach even a beginner how to solve problems numerically." -- Eva-Maria Collins, Physics Today 2015 vol. 68 (12) pp. 56-58.

"There is growing interest in quantitative biology and biological physics, driven in part by the rising popularity of synthetic biology and systems biology. However, the development of educational materials has not kept pace with this emerging interest. Phil Nelson's marvelous new book nicely fills this gap and will serve as a fantastic resource for the field.... The writing style is clear and accessible, and the examples and homework problems have been carefully designed and presented to enable students to become proficient in key concepts and principles at the interface of physics and molecular biology.... Students and professors alike will love this book." --James J. Collins, Biological Engineering, MIT

What students are most stunned and amazed by is how a handful of basic mathematical concepts (e.g., Poisson statistics, Bayes rules) can be used to understand myriad problems at many levels. Nelson's book communicates these key concepts in a very engaging way. Choice of topic, strong thematic unity, and lucidness are its major strengths." -- Aravinthan Samuel, Dept of Physics & Center for Brain Science, Harvard University

"I love the combination of real data along with the simplified mathematical modeling. This is exactly the kind of thoughtful back-and-forth between the real world and the modeling world that I try to inculcate in my own students." -- Ned Wingreen, Molecular Biology, Princeton University

"This text is beautifully written. It succeeds by presenting a clear and coherent point of view: It is essential to develop quantitative, testable models of biological phenomena and these models are based on the basic physical foundations of nature which are essential for understanding living systems and for developing the modern tools used to investigate their structure and dynamics." -- Alex Levine, Chemistry, UCLA

"Excellent conversational tone that Nelson has perfected over time... Excellent mixtures of physical and biological examples, with enough technical content that students can appreciate and understand the biology, but without the jargon and details that often prevent abstract concepts from being easily understood - Illustrations and problems for students are great." -- Megan Valentine, Mechanical Engineering, University of California at Santa Barbara