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.
I am a professor of physics, passionate about researching physics and inspiring non-scientists to enjoy learning about physics. My research addresses how to use quantum physics to accelerate the development of quantum information science including quantum computing, quantum communications, and quantum measurement. My current projects are in developing quantum satellite communications, increasing the precision of telescopes, and constructing a quantum version of the Internet—the Quantum Internet. These topics revolve around quantum optics—the study of how light interacts with matter. I originated the idea of a National Quantum Initiative and lobbied the U.S. Congress to pass it into law, resulting in large investments in the new, exciting field of quantum technology.
Now we are getting to the modern era, where physics meets computing in ways never dreamed of by the founders of quantum physics. Seth Lloyd is a professor at MIT and one of the first to prove that quantum theory admits the possibility of building computers on wholly quantum foundations. He is also one of the most creative and engaging writers on the subject. His main message is that information is the basis of all things physical. From quantum bits or qubits to cosmology, this book has it all, and is written in a highly accessible way. Not a single equation can be found.
The universe is made of bits of information and it has been known for more than a century that every piece of the the universe - every electron, atom and molecule - registers these bits and that information. It is only in the last years, however, with the discovery and development of quantum computers, that scientists have gained a fundamental understanding of just how that information is registered and processed.
Building on recent breakthroughs in quantum computation, Seth Lloyd shows how the universe itself is a giant computer. Every atom and elementary particle stores…
I am fascinated with the relationship between our individual behaviors and the social structures and institutions in which we live—and how these influence each over time. I think this sort of understanding is important if we want to consider the kind of world we want to live in, and how we might get there from where we are. I take insights from many disciplines, from physics and biology to the cognitive and social sciences, from philosophy and art to mathematics and engineering. I am currently a professor of cognitive and information sciences at the University of California, Merced, and an external professor at the Santa Fe Institute.
Peter Turchin has gotten famous recently for predicting the US political upheaval of 2020 way back in 2012.
This book represents the first landmark of Turchin’s attempt to understand the ebbs and flows of history using dynamical models. The book’s centerpiece is a formalization of a theory about how empires rise and fall, first conceived by the 14th century (!) Arab scholar Ibn Khaldun.
The book inspired me to replicate the computational model it presents, and it was remarkably illuminating to watch empires grow, fight, and collapse on my computer screen.
Many historical processes are dynamic. Populations grow and decline. Empires expand and collapse. Religions spread and wither. Natural scientists have made great strides in understanding dynamical processes in the physical and biological worlds using a synthetic approach that combines mathematical modeling with statistical analyses. Taking up the problem of territorial dynamics--why some polities at certain times expand and at other times contract--this book shows that a similar research program can advance our understanding of dynamical processes in history. Peter Turchin develops hypotheses from a wide range of social, political, economic, and demographic factors: geopolitics, factors affecting collective solidarity, dynamics of…
Having a master's degree in chemical engineering, I wasn't destined to work in the area of quantitative finance… the reason why I professionally moved to this discipline aren't worth exposing, but as a matter of fact, I've been quickly fascinated by this science, and encountered some of my favorites, such as maths and statistics, as used in the traditional activity of an engineer. And I had many opportunities of combining the knowledge and practice of financial markets with pragmatism, typically of the engineer’s education, i.e. oriented toward problem solving. In addition, I've always loved teaching, and writing books on financial markets & instruments, hence the importance I'm giving to pedagogy in professional books.
The valuation of options has been the subject of numerous studies, papers, and books.
The originality of this one is that it is collecting the resulting formulae to be used in practice, and for each of them, proposing related Excel spreadsheets, and VBA coding (also with a CD included). All types of options are covered, from “vanilla” to “exotics”, on every kind of underlyings (from traditional ones up to commodities and energy).
It also develops calculation methods for the options “greeks” and volatility. But the book is not only such a catalog of formulae, these are assorted by useful comments about the best way to apply them, and their validity limits. Not surprisingly, this book is qualified as the “bible” of options valuation.
Long-established as a definitive resource by Wall Street professionals, The Complete Guide to Option Pricing Formulas has been revised and updated to reflect the realities of today's options markets. The Second Edition contains a complete listing of virtually every pricing formula_all presented in an easy-to-use dictionary format, with expert author commentary and ready-to-use programming code.
The Second Edition of this classic guide now includes more than 60 new option models and formulas...extensive tables providing an overview of all formulas...new examples and applications...and an updated CD containing all pricing formulas, with VBA code and ready-to-use Excel spreadsheets.
Saying just the right words in just the right way can cause a box of electronics to behave however you want it to behave… that’s an idea that has captivated me ever since I first played around with a computer at Radio Shack back in 1979. I’m always on the lookout for compelling ways to convey the topic to people who are open-minded, but maybe turned off by things that are overly technical. I teach computer science and study artificial intelligence as a way of expanding what we can get computers to do on our behalf.
I always find myself applying algorithmic thinking in my everyday life—it affects the way I put away dishes, navigate to the store, and organize my to-do lists. And I think others could benefit from that mindset.
So, when I read this book, my reaction was "Yes! That's what I want people to know. I just wish I could have said it that well!" The authors (who I know, but didn't know they wrote a book together), did a fantastic job of selecting algorithms with deep human connections. Really! And they explain them just right, without getting too mathematical but while still hitting the key ideas with clarity and accuracy. Fantastic!
A fascinating exploration of how computer algorithms can be applied to our everyday lives.
In this dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show us how the simple, precise algorithms used by computers can also untangle very human questions. Modern life is constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? The authors explain how to have better hunches and when to leave things to chance, how to deal…
I am fascinated with the relationship between our individual behaviors and the social structures and institutions in which we live—and how these influence each over time. I think this sort of understanding is important if we want to consider the kind of world we want to live in, and how we might get there from where we are. I take insights from many disciplines, from physics and biology to the cognitive and social sciences, from philosophy and art to mathematics and engineering. I am currently a professor of cognitive and information sciences at the University of California, Merced, and an external professor at the Santa Fe Institute.
I have always been fascinated by how people join and leave groups.
What are the benefits of joining a particular group? Which group should I join? What happens if someone wants to join a group, but its current members don’t want them to? I once thought such questions were merely qualitative, and when I was a graduate student I thought I’d be the first to tackle them quantitatively.
I was humbled when I stumbled upon this book, written years earlier, in which two behavioral ecologists review game theoretic models that address questions of just this sort, starting simple, and building up models of increasing nuance and complexity. I think anyone interested in the dynamics of group formation in humans or other animals should read this book.
Although there is extensive literature in the field of behavioral ecology that attempts to explain foraging of individuals, social foraging--the ways in which animals search and compete for food in groups--has been relatively neglected. This book redresses that situation by providing both a synthesis of the existing literature and a new theory of social foraging. Giraldeau and Caraco develop models informed by game theory that offer a new framework for analysis. Social Foraging Theory contains the most comprehensive theoretical approach to its subject, coupled with quantitative methods that will underpin future work in the field. The new models and approaches…
Once upon a time, I was a computer science researcher, working in the research labs of companies like Microsoft and Hewlett-Packard. Later I started teaching computer science to college students and writing books about algorithms. I love computers and I love algorithms. Most of all, I love explaining algorithms to other people. In fact, one of my most important missions in life is to advance the public understanding of computer science and algorithms. So if you read any of the books on my list, you’ll bring me one step closer to achieving my mission. Go ahead, read one now!
In a world full of buzzwords about the latest AI algorithms, Leslie Valiant is one of the few authors who can shrug off the hype and deliver something truly profound. Valiant is a Turing Award winner whose work has changed the face of computational learning theory. His ideas show how algorithms can arise naturally, as part of evolution. (He calls them ecorithms.) These ideas are stunningly original. I admire Valiant’s no-nonsense prose style immensely—it’s such a pleasure to read something where the ideas and explanations are simultaneously so clear and so deep that they provide their own star power.
From a leading computer scientist, a unifying theory that will revolutionize our understanding of how life evolves and learns.How does life prosper in a complex and erratic world? While we know that nature follows patterns,such as the law of gravity,our everyday lives are beyond what known science can predict. We nevertheless muddle through even in the absence of theories of how to act. But how do we do it?In Probably Approximately Correct , computer scientist Leslie Valiant presents a masterful synthesis of learning and evolution to show how both individually and collectively we not only survive, but prosper in a…
Having a master's degree in chemical engineering, I wasn't destined to work in the area of quantitative finance… the reason why I professionally moved to this discipline aren't worth exposing, but as a matter of fact, I've been quickly fascinated by this science, and encountered some of my favorites, such as maths and statistics, as used in the traditional activity of an engineer. And I had many opportunities of combining the knowledge and practice of financial markets with pragmatism, typically of the engineer’s education, i.e. oriented toward problem solving. In addition, I've always loved teaching, and writing books on financial markets & instruments, hence the importance I'm giving to pedagogy in professional books.
In the vast array of quantitative finance relative to financial markets instruments and related risks, the case of credit or counterparty risk remains by far the most complex one, and thus, unsurprisingly, the least mastered by financial markets professionals.
A lot has been done, but a lot remains to be done: covering this is precisely the goal of this book. In a nutshell, the main obstacle to succeed in developing grounded and useful models of default prediction is due to the fact that a default is (fortunately) a rare event, in other words, with a (very) low probability of occurrence, and statistical tools are uncomfortable with very low probability levels. Hence the need of this book, to help the practitioner to go ahead in this matter.
The book reveals to traders how to consistently outperform credit benchmarks, how to hedge the credit risk premium, and how to overcome pension liability deficits. In addition, several successful trading strategies are presented including debt versus equities, Co-Co bond trading and a quantitative analysis of the municipal bond market. Chapters include: Credit Models, Past Present and Future Predicting Annual Default Rates and Implications for Market Prices Risk and Relative Value in the Municipal Bond Market Contingent Collateral Bonds Model for Sovereign Default and Relative Value Beating Credit Benchmarks Analyzing and Hedging Systemic Liquidity Risk Building on the best-selling first edition,…
Like many people, I am deeply troubled by the death and destruction from violent conflict. When I began my graduate work in economics at Cornell University, I was allowed to apply my economics learning to the problem of war. When I began teaching at Holy Cross College, my colleagues encouraged me to offer courses on the economics of war and peace. After many years of teaching, I compiled Principles of Conflict Economics (with John Carter) to serve as a textbook on economic aspects of conflict. I hope the book might encourage other economics professors and students to learn more about war and how to resolve conflicts nonviolently.
I appreciated how this book took on the challenge of applying advanced mathematical modeling and simulation techniques to gain new insights into the social evolution of norms and institutions in societies, which is a critical topic in many fields, including conflict and peace economics.
I learned much from the book’s coverage of selected conflict and peace topics such as riots, revolutions, the 2010 Arab Spring movement, and the social evolution of cooperation. I especially like how the mathematical models in the book are described intuitively using wonderfully imaginative diagrams.
In this way, both the mathematically and non-mathematically inclined can come away with a richer understanding of human behavior in dynamically changing social systems.
Models of Society and Complex Systems introduces readers to a variety of different mathematical tools used for modelling human behaviour and interactions, and the complex social dynamics that drive institutions, conflict, and coordination. What laws govern human affairs? How can we make sense of the complexity of societies and how do individual actions, characteristics, and beliefs interact? Social systems follow regularities which allow us to answer these questions using different mathematical approaches.
This book emphasises both theory and application. It systematically introduces mathematical approaches, such as evolutionary and spatial game theory, social network analysis, agent-based modelling, and chaos theory. It…
Economics isn't really a good starting point for financial market analysis for the simple reason that its models are wildly inaccurate. As behaviorial economists like Daniel Kahneman have been showing, irrationality and the inability to measure risk properly are a very big component of the investment and trading decisions. But statistical risk management is also sloppy when applied to human behavior because people are not objects that reliably behave the same way under similar circumstances. So when you read an economist about markets or an engineer about risk management, you're missing a lot of the story. In the end, technical analysis is fascinating because how and why humans behave is an enduring mystery.
The subtitle is The Untold Story of the Scientific Betting System that Beat the Casinos and Wall Street. This book is an easy-to-read narrative of the intersection of the grimy underbelly of betting--with high-minded math. It reminds you that trading is not conducted in a clean little bubble. Technical analysis can give you an edge, but trading is still engaging in battle with opposing forces; strategy and tactics can count as much as building an elegant technical system.
Your opponent on the trading battlefield will try to trick you, like a general in real warfare. He may keep selling and selling after you have bought, triggering a sell signal in your trading system. He is hunting for your sell signal. The mechanical response is to sell—your system says sell, and you should follow your system. To exit a position when the market goes against you is named a stop,…
In 1956, two Bell Labs scientists discovered the scientific formula for getting rich. One was mathematician Claude Shannon, neurotic father of our digital age, whose genius is ranked with Einstein's. The other was John L. Kelly Jr., a Texas-born, gun-toting physicist. Together they applied the science of information theory—the basis of computers and the Internet—to the problem of making as much money as possible, as fast as possible.
Shannon and MIT mathematician Edward O. Thorp took the "Kelly formula" to Las Vegas. It worked. They realized that there was even more money to be made in the stock market. Thorp…
