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Author: Kim Sneppen
Publisher: Cambridge University Press
Published: 2014-10-02
Total Pages: 353
ISBN-13: 1107061903
DOWNLOAD EBOOK →An overview of current models of biological systems, reflecting the major advances that have been made over the past decade.
Author: Alan Garfinkel
Publisher: Springer
Published: 2017-09-06
Total Pages: 445
ISBN-13: 3319597310
DOWNLOAD EBOOK →This book develops the mathematical tools essential for students in the life sciences to describe interacting systems and predict their behavior. From predator-prey populations in an ecosystem, to hormone regulation within the body, the natural world abounds in dynamical systems that affect us profoundly. Complex feedback relations and counter-intuitive responses are common in nature; this book develops the quantitative skills needed to explore these interactions. Differential equations are the natural mathematical tool for quantifying change, and are the driving force throughout this book. The use of Euler’s method makes nonlinear examples tractable and accessible to a broad spectrum of early-stage undergraduates, thus providing a practical alternative to the procedural approach of a traditional Calculus curriculum. Tools are developed within numerous, relevant examples, with an emphasis on the construction, evaluation, and interpretation of mathematical models throughout. Encountering these concepts in context, students learn not only quantitative techniques, but how to bridge between biological and mathematical ways of thinking. Examples range broadly, exploring the dynamics of neurons and the immune system, through to population dynamics and the Google PageRank algorithm. Each scenario relies only on an interest in the natural world; no biological expertise is assumed of student or instructor. Building on a single prerequisite of Precalculus, the book suits a two-quarter sequence for first or second year undergraduates, and meets the mathematical requirements of medical school entry. The later material provides opportunities for more advanced students in both mathematics and life sciences to revisit theoretical knowledge in a rich, real-world framework. In all cases, the focus is clear: how does the math help us understand the science?
Author: Herbert A. Simon
Publisher: MIT Press
Published: 1996-10-08
Total Pages: 463
ISBN-13: 026269185X
DOWNLOAD EBOOK →In this candid and witty autobiography, Nobel laureate Herbert A. Simon looks at his distinguished and varied career, continually asking himself whether (and how) what he learned as a scientist helps to explain other aspects of his life. A brilliant polymath in an age of increasing specialization, Simon is one of those rare scholars whose work defines fields of inquiry. Crossing disciplinary lines in half a dozen fields, Simon's story encompasses an explosion in the information sciences, the transformation of psychology by the information-processing paradigm, and the use of computer simulation for modeling the behavior of highly complex systems. Simon's theory of bounded rationality led to a Nobel Prize in economics, and his work on building machines that think—based on the notion that human intelligence is the rule-governed manipulation of symbols—laid conceptual foundations for the new cognitive science. Subsequently, contrasting metaphors of the maze (Simon's view) and of the mind (neural nets) have dominated the artificial intelligence debate. There is also a warm account of his successful marriage and of an unconsummated love affair, letters to his children, columns, a short story, and political and personal intrigue in academe.
Author: Kim Sneppen
Publisher: Cambridge University Press
Published: 2014-10-02
Total Pages: 353
ISBN-13: 1316061655
DOWNLOAD EBOOK →Reflecting the major advances that have been made in the field over the past decade, this book provides an overview of current models of biological systems. The focus is on simple quantitative models, highlighting their role in enhancing our understanding of the strategies of gene regulation and dynamics of information transfer along signalling pathways, as well as in unravelling the interplay between function and evolution. The chapters are self-contained, each describing key methods for studying the quantitative aspects of life through the use of physical models. They focus, in particular, on connecting the dynamics of proteins and DNA with strategic decisions on the larger scale of a living cell, using E. coli and phage lambda as key examples. Encompassing fields such as quantitative molecular biology, systems biology and biophysics, this book will be a valuable tool for students from both biological and physical science backgrounds.
Author: Emanuel Derman
Publisher: Simon and Schuster
Published: 2011-10-25
Total Pages: 242
ISBN-13: 1439165017
DOWNLOAD EBOOK →Now in paperback, “a compelling, accessible, and provocative piece of work that forces us to question many of our assumptions” (Gillian Tett, author of Fool’s Gold). Quants, physicists working on Wall Street as quantitative analysts, have been widely blamed for triggering financial crises with their complex mathematical models. Their formulas were meant to allow Wall Street to prosper without risk. But in this penetrating insider’s look at the recent economic collapse, Emanuel Derman—former head quant at Goldman Sachs—explains the collision between mathematical modeling and economics and what makes financial models so dangerous. Though such models imitate the style of physics and employ the language of mathematics, theories in physics aim for a description of reality—but in finance, models can shoot only for a very limited approximation of reality. Derman uses his firsthand experience in financial theory and practice to explain the complicated tangles that have paralyzed the economy. Models.Behaving.Badly. exposes Wall Street’s love affair with models, and shows us why nobody will ever be able to write a model that can encapsulate human behavior.
Author: Sahotra Sarkar
Publisher: MIT Press
Published: 2007-01-26
Total Pages: 426
ISBN-13: 9780262264730
DOWNLOAD EBOOK →Despite the transformation in biological practice and theory brought about by discoveries in molecular biology, until recently philosophy of biology continued to focus on evolutionary biology. When the Human Genome Project got underway in the late 1980s and early 1990s, philosophers of biology—unlike historians and social scientists—had little to add to the debate. In this landmark collection of essays, Sahotra Sarkar broadens the scope of current discussions of the philosophy of biology, viewing molecular biology as a unifying perspective on life that complements that of evolutionary biology. His focus is on molecular biology, but the overriding question behind these papers is what molecular biology contributes to all traditional areas of biological research.Molecular biology—described with some foresight in a 1938 Rockefeller Foundation report as a branch of science in which "delicate modern techniques are being used to investigate ever more minute details"—and its modeling strategies apparently argue in favor of physical reductionism. Sarkar's first three chapters explore reductionism—defending it, but cautioning that reduction to molecular interactions is not necessarily a reduction to genetics (and does not support the claims of either heriditarianism or environmentalism). The next sections of the book discuss function, exploring how functional explanations pose a problem for reductionism; the informational interpretation of biology and how it interacts with reductionism; and the tension between the unifying framework of molecular biology and the received framework of evolutionary theory. The concluding chapter is an essay in the emerging field of developmental evolution, exploring what molecular biology may contribute to the transformation of evolutionary theory as evolutionary theory takes into account morphogenetic development.
Author: Jeffrey T. Barton
Publisher: John Wiley & Sons
Published: 2016-03-07
Total Pages: 182
ISBN-13: 1119040027
DOWNLOAD EBOOK →A solutions manual to accompany An Introduction to Discrete Mathematical Modeling with Microsoft® Office Excel® With a focus on mathematical models based on real and current data, Models for Life: An Introduction to Discrete Mathematical Modeling with Microsoft® Office Excel® guides readers in the solution of relevant, practical problems by introducing both mathematical and Excel techniques. The book begins with a step-by-step introduction to discrete dynamical systems, which are mathematical models that describe how a quantity changes from one point in time to the next. Readers are taken through the process, language, and notation required for the construction of such models as well as their implementation in Excel. The book examines single-compartment models in contexts such as population growth, personal finance, and body weight and provides an introduction to more advanced, multi-compartment models via applications in many areas, including military combat, infectious disease epidemics, and ranking methods. Models for Life: An Introduction to Discrete Mathematical Modeling with Microsoft® Office Excel® also features: A modular organization that, after the first chapter, allows readers to explore chapters in any order Numerous practical examples and exercises that enable readers to personalize the presented models by using their own data Carefully selected real-world applications that motivate the mathematical material such as predicting blood alcohol concentration, ranking sports teams, and tracking credit card debt References throughout the book to disciplinary research on which the presented models and model parameters are based in order to provide authenticity and resources for further study Relevant Excel concepts with step-by-step guidance, including screenshots to help readers better understand the presented material Both mathematical and graphical techniques for understanding concepts such as equilibrium values, fixed points, disease endemicity, maximum sustainable yield, and a drug’s therapeutic window A companion website that includes the referenced Excel spreadsheets, select solutions to homework problems, and an instructor’s manual with solutions to all homework problems, project ideas, and a test bank
Author: Valeri I. Agoshko
Publisher: EOLSS Publications
Published: 2009-10-10
Total Pages: 504
ISBN-13: 1848261292
DOWNLOAD EBOOK →Mathematical Models of Life Support Systems is a component of Encyclopedia of Mathematical Sciences in which is part of the global Encyclopedia of Life Support Systems (EOLSS), an integrated compendium of twenty one Encyclopedias. The Theme is organized into several topics which represent the main scientific areas of the theme: The first topic, Introduction to Mathematical Modeling discusses the foundations of mathematical modeling and computational experiments, which are formed to support new methodologies of scientific research. The succeeding topics are Mathematical Models in - Water Sciences; Climate; Environmental Pollution and Degradation; Energy Sciences; Food and Agricultural Sciences; Population; Immunology; Medical Sciences; and Control of Catastrophic Processes. These two volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers and NGOs.
Author: Evelyn Fox KELLER
Publisher: Harvard University Press
Published: 2009-06-30
Total Pages: 402
ISBN-13: 0674039440
DOWNLOAD EBOOK →What do biologists want? How will we know when we have 'made sense' of life? Explanations in the biological sciences are provisional and partial, judged by criteria as heterogenous as their subject matter. This text accounts for this diversity.
Author: Mevin B. Hooten
Publisher: CRC Press
Published: 2019-05-15
Total Pages: 591
ISBN-13: 0429513372
DOWNLOAD EBOOK →Bringing Bayesian Models to Life empowers the reader to extend, enhance, and implement statistical models for ecological and environmental data analysis. We open the black box and show the reader how to connect modern statistical models to computer algorithms. These algorithms allow the user to fit models that answer their scientific questions without needing to rely on automated Bayesian software. We show how to handcraft statistical models that are useful in ecological and environmental science including: linear and generalized linear models, spatial and time series models, occupancy and capture-recapture models, animal movement models, spatio-temporal models, and integrated population-models. Features: R code implementing algorithms to fit Bayesian models using real and simulated data examples. A comprehensive review of statistical models commonly used in ecological and environmental science. Overview of Bayesian computational methods such as importance sampling, MCMC, and HMC. Derivations of the necessary components to construct statistical algorithms from scratch. Bringing Bayesian Models to Life contains a comprehensive treatment of models and associated algorithms for fitting the models to data. We provide detailed and annotated R code in each chapter and apply it to fit each model we present to either real or simulated data for instructional purposes. Our code shows how to create every result and figure in the book so that readers can use and modify it for their own analyses. We provide all code and data in an organized set of directories available at the authors' websites.
