Here are 8 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.
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 sociologist, and I study how technology shapes and is shaped by people. I love my job because I am endlessly fascinated by why people do the things they do, and how our cultures, traditions, and knowledge affect how we interact with technology in our daily lives. I picked these books because they all tell fascinating stories about how different communities of people have designed, used, or been affected by technological tools.
This is one of those books that you have to read either alone or among tolerant friends, because every few pages you’ll be moved to read some bit of it aloud to everyone around you. Alondra Nelson is a brilliant sociologist of science and technology, and this book tells the story of how genetic science and racial politics intersect, sometimes in surprising ways. I love how this book intertwines cultural and political history with clear-eyed analysis of genomics, genealogy, and the life sciences—it’s a great example of how to write about the human stakes of scientific research and innovation.
A Favorite Book of 2016, Wall Street Journal 2017 Hurston/Wright Legacy Award for Nonfiction (Finalist) 2017 Day of Common Learning Selection, Seattle Pacific University 2020 Diana Forsythe Prize (Honorable Mention) 2020 Best Books of the Year, Writers' Trust of Canada
The unexpected story of how genetic testing is affecting race in America We know DNA is a master key that unlocks medical and forensic secrets, but its genealogical life is both revelatory and endlessly fascinating. Tracing genealogy is now the second-most popular hobby amongst Americans, as well as the second-most visited online category. This billion-dollar industry has spawned popular television…
I’m the Science Director of the Science Museum Group, based at the Science Museum in London, and visiting professor at the Dunn School, University of Oxford, and Department of Chemistry, University College London. Every time I write a book I swear that it will be my last and yet I'm now working on my ninth, after earlier forays into the physics of Christmas and the love life of Albert Einstein. Working with Peter Coveney of UCL, we're exploring ideas about computation and complexity we tackled in our two earlier books, along with the revolutionary implications of creating digital twins of people from the colossal amount of patient data now flowing from labs worldwide.
This might not look like a big data book but, for me, the race to read the human genome marks the birth of big data in biology, in the form of a tsunami of DNA sequencing data. I edited Craig Venter’s A Life Decoded, the first genetic autobiography, which explored the implications of becoming the first person to gaze upon all six billion ‘letters’ of their own genetic code. While working on Craig’s extraordinary story I came across The Genome War and thought James Shreeve did a brilliant job in describing the drama, rivalry, and personalities in the race to sequence the very first human genomes between government-backed scientists and Celera, Craig’s company.
The long-awaited story of the science, the business, the politics, the intrigue behind the scenes of the most ferocious competition in the history of modern science—the race to map the human genome. On May 10, 1998, biologist Craig Venter, director of the Institute for Genomic Research, announced that he was forming a private company that within three years would unravel the complete genetic code of human life—seven years before the projected finish of the U.S. government’s Human Genome Project. Venter hoped that by decoding the genome ahead of schedule, he would speed up the pace of biomedical research and save…
I’m a professor of economic psychology at the London School of Economics with affiliations in developmental economics and data science. Before that, I was at Harvard in Human Evolutionary Biology. During my PhD, I took graduate courses in psychology, economics, evolutionary biology, and statistics. I have undergraduate degrees in engineering and in psychology and took courses in everything from economics and biology to philosophy and political science. As a child, I witnessed the civil war in Sri Lanka; a violent coup in Papua New Guinea; the end of apartheid in South Africa, living in neighboring Botswana; and London’s 7/7 bomb attacks. I’ve also lived in Australia, Canada, USA, and UK.
The new science of DNA reveals a lot about how we think about identity.
Humans are a migratory species and our stories are complicated. Ancient DNA don't always match people's stories about their ancestors. Rather than being in a place for thousands of years, sometimes we replaced those who were there before or only the males of the group.
Sometimes we completely replaced the group that was there before but the original group's culture persisted or even replaced the invading culture. The book complicates our understanding of indigeneity and belonging.
The past few years have witnessed a revolution in our ability to obtain DNA from ancient humans. This important new data has added to our knowledge from archaeology and anthropology, helped resolve long-existing controversies, challenged long-held views, and thrown up remarkable surprises.
The emerging picture is one of many waves of ancient human migrations, so that all populations living today are mixes of ancient ones, and often carry a genetic component from archaic humans. David Reich, whose team has been at the forefront of these discoveries, explains what genetics is telling us about ourselves and our complex and often surprising…
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