Here are 50 books that A First Course in Systems Biology fans have personally recommended if you like
A First Course in 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!
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!
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.
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…
I’m a scientist at the University of Cambridge who’s worked on
environmental research topics such as jet streams and the Antarctic
ozone hole. I’ve also worked on solar physics and musical acoustics.
And other branches of science have always interested me. Toward the
end of my career, I became fascinated by cutting-edge issues in
biological evolution and natural selection. Evolution is far
richer and more complex than you’d think from its popular description
in terms of ‘selfish genes’. The complexities are central to
understanding deep connections between the sciences, the arts, and
human nature in general, and the profound differences between human
intelligence and artificial intelligence.
This short and lucid book by an eminent molecular biologist shows
how our DNA and its genes do not act as a blueprint that dictates
everything, as assumed by selfish-gene theory.
Rather, there’s a
fascinating ‘systems biology’ of the DNA and its surrounding
biomolecular ‘circuits’, which act like electronic circuits in many
ways. Different parts influence each other. So there are influences
on the DNA as well as from the DNA. Noble likens the DNA to a
musical recording, which can influence our mood but not dictate it.
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 am a psychiatrist and public health doctor, non-fiction writer, and lay and medical editor. For over 12 years, I have taught non-fiction writing for a general audience at Columbia medical and public health schools to physicians, neuroscientists, epidemiologists, psychologists, and other professionals. I have published 14 books and over 500 written articles and videos. I love to write and help others write...well.
I loved this book because it demonstrates we can write about any subject we have a passion for: bowling, the bassoon, the Canary Islands, UFOs, opium, truffles, cats and dogs, evil and good, or cells!
Thomas starts his book by marveling about cells. Vivid imagination, not labor, carries him to subjects like insects, music, language, computers, and medicine. After all, they are interconnected, like we are.
Which means I need only start with one subject* that stirs my wonder or worry and holds meaning for me. I don’t need to hunt for something to write about, it is right in front of my eyes.
*BTW, the author of my book choice #1, Bill Zinsser, covered war, theatre, baseball, music, nonfiction writing, and memoirs. Note to self: One subject will do.
Elegant, suggestive, and clarifying, Lewis Thomas's profoundly humane vision explores the world around us and examines the complex interdependence of all things. Extending beyond the usual limitations of biological science and into a vast and wondrous world of hidden relationships, this provocative book explores in personal, poetic essays to topics such as computers, germs, language, music, death, insects, and medicine. Lewis Thomas writes, "Once you have become permanently startled, as I am, by the realization that we are a social species, you tend to keep an eye out for the pieces of evidence that this is, by and large, good…
I have long been fascinated by how very complicated things can arise from comparatively simple ones, because it seems counterintuitive that this is even possible. This led me to lead a life in science, researching how a whole human body can come from a simple egg, and trying to apply what we learn to make new body parts for those who need them. Though much of my professional reading consists of detailed research papers, I have always relied on books to make me think and to show me the big picture. I write books myself, to share with others some of the amazing things that science lets us discover.
This is the best scientific novel I have ever read. The story is fiction (not 'science fiction' in the sense of fantasy, but a story that could easily take place in the real world right now), but its portrayal of how science is done, by a bunch of completely believable characters, is really true-to-life. It's a great way for young people considering a research career to taste what they are really like, and a great way for everyone to ask why we do science the way we do, while enjoying a well-paced multi-layer story, that is written with real wit. [Declaration for transparency: I know the author as a scientific collaborator, but this is nothing to do with my recommendation of her fiction].
Sexism, Secrets and Science: Cat Zero by Jennifer Rohn
Scientist Artie Marshall is perpetually underfunded, relegated to a damp basement, and besieged on all sides by sexist colleagues. Added to that, she is immersed in a messy divorce. But she’s never been happier, studying an obscure cat virus that nobody else in the world seems to have heard of – or cares about.
Everything changes when local cats start dropping dead and Artie’s arcane little research problem becomes worryingly relevant. Matters get worse when people start getting infected too.
Working with her right-hand man Mark, her vet friends and her…
I am Professor of Philosophy of Science at the University of Bristol. I am interested in most areas of contemporary philosophy, in particular the interplay between philosophy and the natural and social sciences. Much of my recent work has focused on evolutionary biology, a science that is replete with implications for traditional philosophical debates about human nature, knowledge, and our place in the world.
This book is an engaging treatment of philosophical issues in biology, with a strong though not exclusive focus on evolution. Written by two leading practitioners, the book continues to be an excellent entry point into the subject despite being more than 20 years old. For any reader of my own book who wants more detail, Sterelny and Griffiths’ text is ideal. Chock full of real-life examples, the book offers an excellent model of how philosophy can engage with biology. Topics discussed include function and adaptation, reductionism, levels of selection, the “selfish gene” theory, and more.
Is the history of life a series of accidents or a drama scripted by selfish genes? Is there an "essential" human nature, determined at birth or in a distant evolutionary past? What should we conserve-species, ecosystems, or something else?
Informed answers to questions like these, critical to our understanding of ourselves and the world around us, require both a knowledge of biology and a philosophical framework within which to make sense of its findings. In this accessible introduction to philosophy of biology, Kim Sterelny and Paul E. Griffiths present both the science and the philosophical context necessary for a critical…
I studied statistics and data science for years before anyone ever suggested to me that these topics might have an ethical dimension, or that my numerical tools were products of human beings with motivations specific to their time and place. I’ve since written about the history and philosophy of mathematical probability and statistics, and I’ve come to understand just how important that historical background is and how critically important it is that the next generation of data scientists understand where these ideas come from and their potential to do harm. I hope anyone who reads these books avoids getting blinkered by the ideas that data = objectivity and that science is morally neutral.
People need less Dawkins in their lives and more Lewontin, whose thought-provoking, accessible writing about evolutionary biology stands in fierce opposition to the trend toward genetic determinism that seems to be the rage nowadays. We are not simply our genes, Lewontin says, because the effects DNA has on our lives are mediated by social and environmental factors, many of which we can influence. While it’s nominally about biology, I also read this as a critique of causal inference, generally. What we consider a “cause” reveals our ideological commitments to certain aspects of the world being maintained, and we should be careful what causal lessons we draw from data.
Following in the fashion of Stephen Jay Gould and Peter Medawar, one of the world's leading scientists examines how "pure science" is in fact shaped and guided by social and political needs and assumptions.
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