Customer Reviews

An Introduction to Systems Biology: Design Principles of Biological Circuits (Chapman & Hall/CRC Mathematical & Computational Biology)

5 star:		(18)
4 star:		(0)
3 star:		(0)
2 star:		(0)
1 star:		(4)

 

 

This is a great book for learning about how biology works. I've been wanting to learn a bit more about biology, and I've read many of the popularized science books on the subject. Most serious biology books require a pretty good understanding of organic chemistry. (At first that didn't seem like a problem, after all organic chemistry is just regular chemistry with a bunch of carbon atoms lying around, but the jargon gets so dense that you lose track of what's going on.) This book offers an entirely different perspective on biology that is much more accessible to someone with a general interest in science.

This book looks at biology from the perspective of how genes and proteins interact at a network level, rather than a chemical level. It's a lot like learning electronics -- you can understand a lot about a transistor without knowing how semiconductors work. After explaining the operation of some of the most common network "motifs" the author talks about why those motifs were favored by evolution, in particular what makes them robust and how can they act to minimize errors. The book leaves you with the very interesting question of what characteristics might be different between an engineered system and an evolved one?

The language of the book is very clear, this is a technical book you could easily read for fun. The math is simple, just a little calculus, and if you don't care about the math you can just look at the diagrams.

I'm a Ph.D. student in biophysics. This is the best treatment of systems biology that I've encountered. It treats both the math and the biology with clarity, rigor, and respect. It simplifies without dumbing down. It's beautifully written. If you doubt that systems biology is a real scientific discipline, this book will change your mind.

A superb intro to the field. The math is moderate and helpful. Network concepts and their ties to examples and theory are clearly and succinctly presented. This is a textbook but reads easily like a book. Covers key elements while connecting them by at least mention to up-to-date further research. The basics and the grandeur of systems biology. I am trying to remember now anything on the negative side and cannot.

This is a great book! It manages to convey the new ideas of systems biology with clarity and without sacrificing scientific rigor.
Whether you're a biologist, physicist or engineer this book will be perfect for you as it encompasses the many disciplines that make up systems biology.
Many universities (including Harvard) are using this book as their textbook for introductory courses to systems biology. This is a testament to its clearness and thoroughness. There are also excellent homework type problems at the end of each chapter, and a solution manual is available from the author for class instructors.
As a graduate student of systems biology I found this book very useful and I highly recommend it!

Important:
Disregard the 4 reviews that give this book a low rating! I wonder if they are related, as they all are from July 09, and argue the exact same thing: that the modeling of biology described in the book is not representative of biology. This is a philosophical argument that by no means reduces the importance, relevance and scientific depth of this book. Discussions as to what is systems biology should not be conducted using Amazon book reviews.

There are a number a books on systems biology out there and the majority seem hastily put together during the past couple of years just to ride the wave of the systems biology buzz of late (IMO: in reality biology has always been about systems, and using mathematical/computational models to study biological systems is nothing new, it has been going on for about 50 years or perhaps more). A significant fraction of the books I've seen are just a compilation or random subjects and application examples of dubious educational relevance, often ill explained, and rarely developed to the point of being useful as a guide. Strangely enough, I am often left with the odd feeling that the authors of these books actually forgot to talk about the "systems" aspect and the big picture.

Alon's book is different because it is about concepts; It is about how we can study the dialog between the different layers of complexity that constitute a biological system. A number of approaches are beautifully presented in simple terms. Most of the topics covered use very simple math, which often is not even essential to get the point. Alon approaches biology from a more engineering-oriented mindset, not a bad approach considering that organisms and their cells evolved to solve problems not all that different from what engineers deal with. The specifics of nature's solutions are clearly different, but the underlying principles are often uncannily similar. This is a fact, that although not explicitly stated in the book,I think pervades Alon thinking here. One of the things that I liked the most about this book, is that Uri Alon not only focuses on the techniques themselves, but he also take a deep look into the kind of insight we can get out of them.

This is not a biology book, is a book about how to think about biological systems. The book is mostly focused on physiological systems (as opposed to population-level or ecological issues) and therefore the examples are heavily biased towards biophysical problems such as regulation of gene expression -very simplified-, intracellular signaling cascades, etc.

By force, the treatment is not complete (it's an introduction after all) and leaves out many important approaches currently used for analyzing biological systems that most would categorize under the umbrella of systems biology. But what it covers it covers well, the examples are well chosen, and the analysis insightful, and this is why in my opinion, this book is way above other book in the area.

I highly recommend this book to anyone who is planning on getting into gene-regulation and/or any area that involves signaling, regardless of their background. If you have never seen this material before, this book could be a wonderful eye-opener.


Note: I do not fully understand the reviewers that accuse the author's approach of being "too physical", claiming that no biologist thinks in these terms. On the one hand I see little or no physics in this book --perhaps some physical chemistry, or rather, some solutions from physical chemistry. As matter of fact the language used in this book is of common use among most of my bio-medical colleagues (I work in immune signaling) and in the conferences I attend. The thinking certainly is not foreign to my colleagues in pharmacology who, credit must be given, have been doing "systems thinking" of the kind described here well before the term became a catch-phrase (actually, even before computers!). If the comments refer to the use of chemical kinetics models (Michaelis-Menten or mass action for example) to represent processes operating inside living cells, then I think the reviewer didn't really get the point of the book, or at least some of it. Coarse grained models (lumping bunch of details into an equation for a conceptual entity often without a biochemical counterpart) could be sometimes enough to understand the fundamental principles underlying a biological process, principles that too much detailed data often obfuscate. Furthermore, I don't think Uri Alon, or anyone in their right mind for that matter, would take the model of chemotactic signaling for example as anything else than just a model that happens to capture the observations. The beauty is that such a simple model is enough to provide a sensible explanation of what's going on and be used to make predictions. That's what this book is about: using models and other tools to elucidate key principles with explanatory and predictive powers, in other words, understanding.

I have never seen a book, especially a science one, with such a bimodal response. IMO, the people with one star were trained as biologists. They present a valid viewpoint--I'll get back to that later.

When I first read this book at the end of my undergrad days, I was simply amazed. I never realized biology could be so fun, if we asked questions about robustness, optimality, design principles, etc. Now that I'm in this field in my day job (as a grad student), I realize this book does have some issues.

First, the book does make some strong claims, ie. the idea of inherent design principles. This is what most of the one-star reviews here are angry about. Alon doesn't really discuss the philosophy behind systems biology, but jumps straight to the physicists' view that the system is understandable and our job is to understand it.

Also, the book pretty much only covers work done by people in Leibler's lab. The works presented in the book are considered hallmarks in the field of systems biology, but people familiar with the field might be sad to see some areas not presented here.

Finally, it should be noted that the book doesn't really teach you that much. It does a wonderful job telling the story of the papers that it does discuss, but it hides away the details. Thus, you don't learn the biology of what's going on nor will you learn common mathematical techniques used in this field (eg, bifurcation analysis).

Nonetheless, I give this book five stars enthusiastically. This is the most enjoyable book I have read, and I highly recommend it to everyone who has any interest in this field. The problems included in the chapters are not bad for use in a class, although I recommend Strogatz's Nonliner Dynamics for a class focused on the modeling.

This is an excellent textbook for systems biology. I have used it two times. One is a short course of systems biology in the summer 2008 for some professors who are interested in systems biology from different departments and different universities in Hsinchu, with background in statistics, applied math, engineering and biology. They found this book very useful for their researches on systems biology. Another is as a textbook of computational biology for graduate course in EE department of National Tsing Hua University. My students and I have learned a bit more from this book. This book offers an entirely different perspective on biology, from gene circuits and network motifs to networks as well as from the robustness and demand rule for gene regulation to the optimal gene circuit design. They are all described with simple but precise mathematic equations. Further, the role of evolution in robustness design of different biological circuits and systems is also discussed with several famous biological examples. The language of the book is very clear and the math is very simple, with both the math and the biology beautifully written. Therefore, I strongly recommend this book to those interested in systems biology.

Uri Alon searches for the most recurrent connectivity patterns (motifs) found in natural networks and then analyze their dynamical properties in detail. Although simple, the consequences of having these motifs (and combinations of them) in gene regulatory networks are not always easy to grasp, and the author makes a good job clarifying their function. Despite some mathematical fluency is assumed, I think the simplicity of his language, added to the explanatory figures accompanying the text, makes it easy to read and understand. A must for 'Systems Biology' oriented people, and a good lecture for any student interested in the field.

I used this book as the text for a graduate course in computational systems biology in the spring semester 2009. This book is an excellent text. It presents a lot of insights of how components in biological systems may work together. At the end of the semester, students from biology as well as computer science wrote me emails saying they enjoyed the class. It was not because my teaching rather the rich contents of the book.

Biology is a scientific area with a long history. A large amount of knowledge has accumulated in understanding details of single components in biological systems. It is the time to open a new field in biology, the study of systems biology. Apparently, systems biology is interdisciplinary. Because of this, the insights presented in this book is very much useful. I happened to read a couple of recent articles (some of which were in PNAS). In these articles, the idea of motif was used to find networks that control developmental processes based upon data collected in experiments. I believe this book would become classic in systems biology, and very much hope the author would continue the work to produce new edition(s) in the future.

This book is a real treasure. I always recommend it to new students arriving at my lab. Not only does it give them a clear and elegant introduction to the field of "systems biology"; it actually inspires them to think in simple, yet quantitative, terms about living systems.