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!
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An Introduction to Computational Systems Biology: Systems-Level Modelling of Cellular Networks
This book delivers a comprehensive and insightful account of applying mathematical modelling approaches to very large biological systems and networks—a fundamental aspect of computational systems biology. The book covers key modelling paradigms in detail, while at the same time retaining a simplicity that will appeal to those from less quantitative fields. The book adopts a hands-on approach to modelling, covering a broad spectrum of paradigms, from static networks to dynamic models and constraint-based models. Every chapter includes thoughtful exercises to test and enable understanding of concepts.
The book has a rich companion website featuring lecture videos, codes, supplementary exercises, further reading, and appendices. Much like the field itself, the book is highly multi-disciplinary and will appeal to biologists, engineers, computer scientists, mathematicians, and others.
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.
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…
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…
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…
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.
I have spent my entire professional life quietly patrolling the frontiers of understanding human consciousness. I was an early adopter in the burgeoning field of biofeedback, then neurofeedback and neuroscience, plus theory and practices of humanistic and transpersonal psychology, plus steeping myself in systems theory as a context for all these other fields of focus. I hold a MS in psychology from San Francisco State University and a PhD from Saybrook Institute. I live in Mount Shasta CA with Molly, my life partner for over 60 years. We have two sons and two grandchildren.
In this thoroughly researched and exquisitely crafted treatise, Jim Brown synthesizes the newest understandings in neuroscience, developmental psychology, and dynamical systems theory for educators and others committed to nurturing human development.
He explains complex concepts in down-to-earth terms, suggesting how these understandings can transform education to engender optimal learning and intelligence. He explores the nature of consciousness, intelligence, and mind.
Brown then offers a model of optimal human learning through lifelong brain development within a supportive culture--drawing on the work of Piaget, Erickson, Maslow, Kohlberg, and Steiner--and how that work is being vastly expanded by neuroscience and dynamical systems thinking.
Mindleap: A Fresh View of Education Empowered by Neuroscience and Systems Thinking
In this thoroughly-researched and exquisitely crafted treatise, Jim Brown synthesizes the newest understandings in neuroscience, developmental psychology, and dynamical systems theory for educators and others committed to nurturing human development. He explains complex concepts in down-to-earth terms, suggesting how these understandings can transform education to truly engender optimal learning and intelligence. He explores the nature of consciousness, intelligence, and mind. Brown then offers a model of optimal human learning through life-long brain development within a supportive culture--drawing on the work of Piaget, Erickson, Maslow, Kohlberg, and Steiner--and how that work is being vastly expanded by neuroscience and dynamical systems thinking.
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