Here are 10 books that Networks fans have personally recommended if you like
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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!
An outstanding and authoritative reference on metabolic networks. Discusses all the mathematical foundations of constraint-based methods, followed by detailed discussions of various constraint-based modelling methods. Despite the age, this remains a thorough and excellent account of constraint-based modelling. A revised second edition of this book presents a more detailed overview of metabolic networks in different organisms and is up-to-date with several advances in the field. Palsson is one of the leaders in the field of systems biology and metabolic networks, and his lab is home to many of the most important constraint-based modelling methods, such as flux balance analysis.
Recent technological advances have enabled comprehensive determination of the molecular composition of living cells. The chemical interactions between many of these molecules are known, giving rise to genome-scale reconstructed biochemical reaction networks underlying cellular functions. Mathematical descriptions of the totality of these chemical interactions lead to genome-scale models that allow the computation of physiological functions. Reflecting these recent developments, this textbook explains how such quantitative and computable genotype-phenotype relationships are built using a genome-wide basis of information about the gene portfolio of a target organism. It describes how biological knowledge is assembled to reconstruct biochemical reaction networks, the formulation of…
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.
As Iago says in Shakespeare’s Othello, “I am nothing if not critical,” and regardless of what he meant, it applies to me - my intelligence works best at scrutinizing things for their significance. I studied science, worked in the financial sector, read fiction, watched cinema, and developed a sense of the interconnectedness of things. If the connections existed, I thought, there could be no one way of approaching anything; all intellectual paths were valid and the only criterion of value was that it must be intelligent. My book tries to stick to this since a writer may hold any opinions, but he or she must show intelligence.
My adult life can be characterized as a quest to make sense of the larger ecosystem around me, chiefly society, politics, and culture, within a single framework since knowledge is power; knowing and relating is what makes me strong.
I was stunned by the connections that Wallerstein makes across so many disciplines, and how his book empowered me in interactions with the culturally educated and politically knowledgeable.
In World-Systems Analysis, Immanuel Wallerstein provides a concise and accessible introduction to the comprehensive approach that he pioneered thirty years ago to understanding the history and development of the modern world. Since Wallerstein first developed world-systems analysis, it has become a widely utilized methodology within the historical social sciences and a common point of reference in discussions of globalization. Now, for the first time in one volume, Wallerstein offers a succinct summary of world-systems analysis and a clear outline of the modern world-system, describing the structures of knowledge upon which it is based, its mechanisms, and its future.
I have read the future studies literature for decades. A few years ago an alumnus suggested that my university should create a course about the future. My dean encouraged me to look into it. On reading Bishop and Hines, Teaching About the Future, I was struck by the maturity of the field, the strength of their program that they describe, and the fact that they bemoan the lack of a book that could introduce newcomers to the field. I decided that I could write such a book, combining the latest research in the field with my own understandings of interdisciplinarity, world history, economics, and political activism.
The book addresses a dozen key challenges in our collective future.
Though the chapters are uneven in quality, I found that the book had many good ideas on how to address these challenges. The editors encourage broad community consultations regarding our futures, systems analysis of how challenges interact, and policy experimentation.
We are running out of water, robots will take our jobs, we are eating ourselves to an early death, old age pension and health systems are bankrupting governments, and an immigration crisis is unravelling the European integration project. A growing number of nightmares, perfect storms, and global catastrophes create fear of the future. One response is technocratic optimism - we'll invent our way out of these impending crises. Or we'll simply ignore them as politically too hot to handle, too uncomfortable for experts - denied until crisis hits. History is littered with late lessons from early warnings. Cynicism is an…
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…
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 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.
I have enjoyed mathematics and writing since I’ve been a kid, not only enjoying doing research in mathematics but assisting others to appreciate and enjoy mathematics. Along the way, I’ve gained an interest in the history of mathematics and the mathematicians who created mathematics. Perhaps most important, my primary goal has been to show others how enjoyable mathematics can be. Mathematics has given me the marvelous opportunity to meet and work with other mathematicians who have a similar passion for mathematics.
Robin Wilson, the famous mathematical historian and storyteller with a great sense of humor, along with his co-authors, tell the story of how one particular area of mathematics (graph theory, my favorite area) got its start in the 18th and 19th centuries in Europe, found its way across the Atlantic to America, and what effect Americans had on this area of mathematics. It also tells the fascinating story of how and where more advanced mathematics became part of America.
How a new mathematical field grew and matured in America
Graph Theory in America focuses on the development of graph theory in North America from 1876 to 1976. At the beginning of this period, James Joseph Sylvester, perhaps the finest mathematician in the English-speaking world, took up his appointment as the first professor of mathematics at the Johns Hopkins University, where his inaugural lecture outlined connections between graph theory, algebra, and chemistry-shortly after, he introduced the word graph in our modern sense. A hundred years later, in 1976, graph theory witnessed the solution of the long-standing four color problem by…
