Here are 13 books that Systems Biology fans have personally recommended if you like
Systems Biology.
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Ever since I studied control theory as an undergrad chemical engineer, mathematical models of complex phenomena have fascinated me. Mathematical models have the uncanny ability to uncover key aspects of biological systems, whose complexity poses a great challenge for understanding. As a researcher in systems biology for over 15 years, I have enjoyed reading several books that explore the exciting interface between computation and biology, trying to capture the burgeoning literature on this rapidly advancing field. I hope you enjoy these books and will join these authors on an exciting journey into the cartography of molecular networks underlying every living cell, using a variety of mathematical models!
One of the earliest books on this subject, Uri Alon presents an engaging account of biological networks. Focussing on transcriptional networks, and their motifs, the book illustrates the nexus between network structures and functions. The second edition of the book launched a few years ago and has some updated content and new material on interesting functionalities such as fold change detection. Uri Alon is a very accomplished scientist, mentor, and a leader in the field of biological networks/systems biology.
Thorough and accessible, this book presents the design principles of biological systems, and highlights the recurring circuit elements that make up biological networks. It provides a simple mathematical framework which can be used to understand and even design biological circuits. The textavoids specialist terms, focusing instead on several well-studied biological systems that concisely demonstrate key principles.
An Introduction to Systems Biology: Design Principles of Biological Circuits builds a solid foundation for the intuitive understanding of general principles. It encourages the reader to ask why a system is designed in a particular way and then proceeds to answer with simplified models.
Ever since I studied control theory as an undergrad chemical engineer, mathematical models of complex phenomena have fascinated me. Mathematical models have the uncanny ability to uncover key aspects of biological systems, whose complexity poses a great challenge for understanding. As a researcher in systems biology for over 15 years, I have enjoyed reading several books that explore the exciting interface between computation and biology, trying to capture the burgeoning literature on this rapidly advancing field. I hope you enjoy these books and will join these authors on an exciting journey into the cartography of molecular networks underlying every living cell, using a variety of mathematical models!
One of the best broad-based textbooks covering a wide gamut of topics, and in-depth coverage of dynamic models. I like this book for a particularly engaging introduction to the practice of mathematical modelling, excellent catchy illustrations, and nice exercise problems/reading material at the end of each chapter. The book chooses to organise the methods by the type of network (gene systems, protein systems, metabolic systems, and so on). Voit is a very accomplished researcher in the area of dynamic systems modelling and is particularly known for his contributions to Biochemical Systems Theory.
A First Course in Systems Biology is a textbook designed for advanced undergraduate and graduate students. Its main focus is the development of computational models and their applications to diverse biological systems.
Because the biological sciences have become so complex that no individual can acquire complete knowledge in any given area of specialization, the education of future systems biologists must instead develop a student's ability to retrieve, reformat, merge, and interpret complex biological information.
This book provides the reader with the background and mastery of methods to execute standard systems biology tasks, understand the modern literature, and launch into specialized…
Ever since I studied control theory as an undergrad chemical engineer, mathematical models of complex phenomena have fascinated me. Mathematical models have the uncanny ability to uncover key aspects of biological systems, whose complexity poses a great challenge for understanding. As a researcher in systems biology for over 15 years, I have enjoyed reading several books that explore the exciting interface between computation and biology, trying to capture the burgeoning literature on this rapidly advancing field. I hope you enjoy these books and will join these authors on an exciting journey into the cartography of molecular networks underlying every living cell, using a variety of mathematical models!
Perhaps the most authoritative text on Networks, especially for the mathematically inclined. Spanning over 700 pages, this book covers the basics of different types of real-world networks, followed by a detailed run-down of network theory fundamentals, a variety of network models, and finally, their applications. Newman is a highly regarded computer scientist and has contributed several seminal papers to the field of networks.
The scientific study of networks, including computer networks, social networks, and biological networks, has received an enormous amount of interest in the last few years. The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyze network data on a large scale, and the development of a variety of new theoretical tools has allowed us to extract new knowledge from many different kinds of networks. The study of networks is broadly interdisciplinary and important developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social…
Ever since I studied control theory as an undergrad chemical engineer, mathematical models of complex phenomena have fascinated me. Mathematical models have the uncanny ability to uncover key aspects of biological systems, whose complexity poses a great challenge for understanding. As a researcher in systems biology for over 15 years, I have enjoyed reading several books that explore the exciting interface between computation and biology, trying to capture the burgeoning literature on this rapidly advancing field. I hope you enjoy these books and will join these authors on an exciting journey into the cartography of molecular networks underlying every living cell, using a variety of mathematical models!
A very useful reference on systems biology, a sort of handbook, that provides a lot of breadth on systems biology topics. A unique aspect of this book is a set of chapters, introducing basic biology, mathematical techniques, experimental techniques, and a somewhat elaborate collection of databases/tools. Also includes material on stochastic modelling of biochemical reaction systems.
This advanced textbook is tailored to the needs of introductory course in Systems Biology. It has a compagnion website (WWW.WILEY-VCH.DE/HOME/SYSTEMSBIOLOGY) with solutions to questions in the book and several additional extensive working models. The book is related to the very successful previous title 'Systems Biology in Practice' and has incorporated the feedback and suggestions from many lecturers worldwide. The book addresses biologists as well as engineers and computer scientists. The interdisciplinary team of acclaimed authors worked closely together to ensure a comprehensive coverage with no overlaps in a homogenous and compelling style.
Mathematics and chemistry were my strongest subjects at school, and I started programming computers when I was 16, but life seemed most important. Hence I studied biochemistry in university but moved into molecular biology with programming to assist the data analysis. My track record in successfully predicting new biology through computing led to a pharmaceutical company recruiting me to do bioinformatics for them. However, not content with studying genes and proteins, I pushed for bioinformatics to move up into metabolism, anatomy, and physiology. That’s when I discovered systems biology. My international reputation lies at this interface and includes discoveries in microbial physiology, botany, agriculture, animal biology, and antenatal diseases.
Of the various books available on this subject, I very much prefer this one because it makes it far easier to do systems biology.
First, it shows you how to view biological regulatory processes as a set of interacting components and their effect on each other. This alone can give clues to the behaviour of the system under different circumstances. However, it then goes on to show how these processes can be defined mathematically, which then enables us to get a quantitative view of what is going on.
When the predicted and observed numbers don’t match, we know that there is a gap in our knowledge and, hence, the place to discover new biology. Using this approach, I have.
... superb, beautifully written and organized work that takes an engineering approach to systems biology. Alon provides nicely written appendices to explain the basic mathematical and biological concepts clearly and succinctly without interfering with the main text. He starts with a mathematical description of transcriptional activation and then describes some basic transcription-network motifs (patterns) that can be combined to form larger networks. - Nature
[This text deserves] serious attention from any quantitative scientist who hopes to learn about modern biology ... It assumes no prior knowledge of or even interest in biology ... One final…
Mathematics and chemistry were my strongest subjects at school, and I started programming computers when I was 16, but life seemed most important. Hence I studied biochemistry in university but moved into molecular biology with programming to assist the data analysis. My track record in successfully predicting new biology through computing led to a pharmaceutical company recruiting me to do bioinformatics for them. However, not content with studying genes and proteins, I pushed for bioinformatics to move up into metabolism, anatomy, and physiology. That’s when I discovered systems biology. My international reputation lies at this interface and includes discoveries in microbial physiology, botany, agriculture, animal biology, and antenatal diseases.
This book has been a companion for almost three decades.
Any bona fide bioinformatician will write some program scripts if only to reformat data in new and useful ways. Perl is not the most efficient or widespread scripting language, but it has the advantage of being highly flexible. It offers many ways to write a program to carry out a given task, so even computationally naive programmers can generate effective code.
Even though I am no longer actively developing software, I still have occasions when it is quicker to script something in Perl than do battle with larger apps.
When it comes to learning Perl, programmers consider this book to be the undisputed bible. You not only learn every nuance of this language, you also get a unique perspective on the evolution of Perl and its future direction. The 4th edition has been thoroughly updated for version 5.14, with details on regular expressions, support for UNICODE, threads, and many other features. Many Perl books explain typeglobs, pseudohashes, and closures, but only this one shows the motivations behind these features and why they work the way they do. It's exactly what you'd expect from its prominent authors: Larry Wall is…
Mathematics and chemistry were my strongest subjects at school, and I started programming computers when I was 16, but life seemed most important. Hence I studied biochemistry in university but moved into molecular biology with programming to assist the data analysis. My track record in successfully predicting new biology through computing led to a pharmaceutical company recruiting me to do bioinformatics for them. However, not content with studying genes and proteins, I pushed for bioinformatics to move up into metabolism, anatomy, and physiology. That’s when I discovered systems biology. My international reputation lies at this interface and includes discoveries in microbial physiology, botany, agriculture, animal biology, and antenatal diseases.
This book turns on its head what I was taught about what controls metabolite flow through a pathway. It covers highly remarkable discoveries concerning which steps control changes in metabolite levels: those at the end rather than the start of pathways. This is amazing because it explains why decades of effort by bioengineers to overproduce particular metabolites was unsuccessful.
In response to a request from such a project, I explained how to block the inhibitory regulation by the early pathway step but added that, according to metabolic control theory, this would leave the end-product levels unchanged. I was correct on both counts! When my group later provided results from using a systems biology approach, they achieved their production target levels.
Mathematics and chemistry were my strongest subjects at school, and I started programming computers when I was 16, but life seemed most important. Hence I studied biochemistry in university but moved into molecular biology with programming to assist the data analysis. My track record in successfully predicting new biology through computing led to a pharmaceutical company recruiting me to do bioinformatics for them. However, not content with studying genes and proteins, I pushed for bioinformatics to move up into metabolism, anatomy, and physiology. That’s when I discovered systems biology. My international reputation lies at this interface and includes discoveries in microbial physiology, botany, agriculture, animal biology, and antenatal diseases.
This is one of my most valued reference books, and I have referred to it many times.
With some explanatory text, it consists of a set of maps of biochemical pathways, differentiating between organism kingdoms, and includes how specific metabolites regulate the activity of particular enzymes. The pathways are very easy to find and easy to interpret. In contrast, the online equivalents can be difficult to interpret for a variety of reasons.
The book has the added advantage that it does not need a power supply or an internet connection and can be used in a far wider range of temperatures than computer hardware.
The pathways and networks underlying biological function
Now in its second edition, Biochemical Pathways continues to garner praise from students, instructors, and researchers for its clear, full-color illustrations of the pathways and networks that determine biological function.
Biochemical Pathways examines the biochemistry of bacteria, plants, and animals. It offers a quick overview of the metabolic sequences in biochemical pathways, the chemistry and enzymology of conversions, the regulation of turnover, the expression of genes, the immunological interactions, and the metabolic background of health disorders. A standard set of conventions is used in all illustrations, enabling readers to easily gather information and…
Mathematics and chemistry were my strongest subjects at school, and I started programming computers when I was 16, but life seemed most important. Hence I studied biochemistry in university but moved into molecular biology with programming to assist the data analysis. My track record in successfully predicting new biology through computing led to a pharmaceutical company recruiting me to do bioinformatics for them. However, not content with studying genes and proteins, I pushed for bioinformatics to move up into metabolism, anatomy, and physiology. That’s when I discovered systems biology. My international reputation lies at this interface and includes discoveries in microbial physiology, botany, agriculture, animal biology, and antenatal diseases.
This book vindicates my long-held view that biological objects do not act in isolation but interact with other things to make a living whole. It confirms my opinion that genes are not the master controllers of living things.
Furthermore, it showed me that systems occur at different physical scales (molecules, cells, organs, organisms, populations), that the systems at these scales influence each other, and that no scale is dominant. To understand biological/medical phenomena, including human consciousness, one must look at the (multi-scale) systems, not their individual components, in isolation.
Finally, I found it a lot of fun to read because it uses hypothetical stories to illustrate points. For example, silicon-based aliens visit Earth but fail to understand why certain things and people behave the way that they do.
What is Life? Decades of research have resulted in the full mapping of the human genome - three billion pairs of code whose functions are only now being understood. The gene's eye view of life, advocated by evolutionary biology, sees living bodies as mere vehicles for the replication of the genetic codes.
But for a physiologist, working with the living organism, the view is a very different one. Denis Noble is a world renowned physiologist, and sets out an alternative view to the question - one that becomes deeply significant in terms of the living, breathing organism. The genome is…
I started my career in neuroscience. I wanted to understand brains. That is still proving difficult, and somewhere along the way, I realized my real motivation was to build things, and I wound up working in AI. I love the elegance of mathematical models of the world. Even the simplest machine learning model has complex implications, and exploring them is a joy.
The best parts of this book really represent a gold standard in pedagogical clarity.
Although it’s now twenty years old, there is still much to learn from this rather unconventional book that covers the boundary between machine learning, information theory, and Bayesian methods. There are also odd tangents and curiosities, some of which work better than others but are never dull.
Just writing this review makes me want to go back to it and squeeze more out of it.
Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo…
