Princeton Series in Theoretical and Computational Biology
()
About this series
The formulation, analysis, and re-evaluation of mathematical models in population biology has become a valuable source of insight to mathematicians and biologists alike. This book presents an overview and selected sample of these results and ideas, organized by biological theme rather than mathematical concept, with an emphasis on helping the reader develop appropriate modeling skills through use of well-chosen and varied examples.
Part I starts with unstructured single species population models, particularly in the framework of continuous time models, then adding the most rudimentary stage structure with variable stage duration. The theme of stage structure in an age-dependent context is developed in Part II, covering demographic concepts, such as life expectation and variance of life length, and their dynamic consequences. In Part III, the author considers the dynamic interplay of host and parasite populations, i.e., the epidemics and endemics of infectious diseases. The theme of stage structure continues here in the analysis of different stages of infection and of age-structure that is instrumental in optimizing vaccination strategies.
Each section concludes with exercises, some with solutions, and suggestions for further study. The level of mathematics is relatively modest; a "toolbox" provides a summary of required results in differential equations, integration, and integral equations. In addition, a selection of Maple worksheets is provided.
The book provides an authoritative tour through a dazzling ensemble of topics and is both an ideal introduction to the subject and reference for researchers.
Titles in the series (7)
- Analysis of Evolutionary Processes: The Adaptive Dynamics Approach and Its Applications
3
Quantitative approaches to evolutionary biology traditionally consider evolutionary change in isolation from an important pressure in natural selection: the demography of coevolving populations. In Analysis of Evolutionary Processes, Fabio Dercole and Sergio Rinaldi have written the first comprehensive book on Adaptive Dynamics (AD), a quantitative modeling approach that explicitly links evolutionary changes to demographic ones. The book shows how the so-called AD canonical equation can answer questions of paramount interest in biology, engineering, and the social sciences, especially economics. After introducing the basics of evolutionary processes and classifying available modeling approaches, Dercole and Rinaldi give a detailed presentation of the derivation of the AD canonical equation, an ordinary differential equation that focuses on evolutionary processes driven by rare and small innovations. The authors then look at important features of evolutionary dynamics as viewed through the lens of AD. They present their discovery of the first chaotic evolutionary attractor, which calls into question the common view that coevolution produces exquisitely harmonious adaptations between species. And, opening up potential new lines of research by providing the first application of AD to economics, they show how AD can explain the emergence of technological variety. Analysis of Evolutionary Processes will interest anyone looking for a self-contained treatment of AD for self-study or teaching, including graduate students and researchers in mathematical and theoretical biology, applied mathematics, and theoretical economics.
- Individual-based Modeling and Ecology
2
Individual-based models are an exciting and widely used new tool for ecology. These computational models allow scientists to explore the mechanisms through which population and ecosystem ecology arises from how individuals interact with each other and their environment. This book provides the first in-depth treatment of individual-based modeling and its use to develop theoretical understanding of how ecological systems work, an approach the authors call "individual-based ecology.? Grimm and Railsback start with a general primer on modeling: how to design models that are as simple as possible while still allowing specific problems to be solved, and how to move efficiently through a cycle of pattern-oriented model design, implementation, and analysis. Next, they address the problems of theory and conceptual framework for individual-based ecology: What is "theory"? That is, how do we develop reusable models of how system dynamics arise from characteristics of individuals? What conceptual framework do we use when the classical differential equation framework no longer applies? An extensive review illustrates the ecological problems that have been addressed with individual-based models. The authors then identify how the mechanics of building and using individual-based models differ from those of traditional science, and provide guidance on formulating, programming, and analyzing models. This book will be helpful to ecologists interested in modeling, and to other scientists interested in agent-based modeling.
- Theories of Population Variation in Genes and Genomes
4
This textbook provides an authoritative introduction to both classical and coalescent approaches to population genetics. Written for graduate students and advanced undergraduates by one of the world's leading authorities in the field, the book focuses on the theoretical background of population genetics, while emphasizing the close interplay between theory and empiricism. Traditional topics such as genetic and phenotypic variation, mutation, migration, and linkage are covered and advanced by contemporary coalescent theory, which describes the genealogy of genes in a population, ultimately connecting them to a single common ancestor. Effects of selection, particularly genomic effects, are discussed with reference to molecular genetic variation. The book is designed for students of population genetics, bioinformatics, evolutionary biology, molecular evolution, and theoretical biology--as well as biologists, molecular biologists, breeders, biomathematicians, and biostatisticians. Contains up-to-date treatment of key areas in classical and modern theoretical population genetics Provides in-depth coverage of coalescent theory Discusses genomic effects of selection Gives examples from empirical population genetics Incorporates figures, diagrams, and boxed features throughout Includes end-of-chapter exercises Speaks to a wide range of students in biology, bioinformatics, and biostatistics
- The Geographic Spread of Infectious Diseases: Models and Applications
5
The 1918-19 influenza epidemic killed more than fifty million people worldwide. The SARS epidemic of 2002-3, by comparison, killed fewer than a thousand. The success in containing the spread of SARS was due largely to the rapid global response of public health authorities, which was aided by insights resulting from mathematical models. Models enabled authorities to better understand how the disease spread and to assess the relative effectiveness of different control strategies. In this book, Lisa Sattenspiel and Alun Lloyd provide a comprehensive introduction to mathematical models in epidemiology and show how they can be used to predict and control the geographic spread of major infectious diseases. Key concepts in infectious disease modeling are explained, readers are guided from simple mathematical models to more complex ones, and the strengths and weaknesses of these models are explored. The book highlights the breadth of techniques available to modelers today, such as population-based and individual-based models, and covers specific applications as well. Sattenspiel and Lloyd examine the powerful mathematical models that health authorities have developed to understand the spatial distribution and geographic spread of influenza, measles, foot-and-mouth disease, and SARS. Analytic methods geographers use to study human infectious diseases and the dynamics of epidemics are also discussed. A must-read for students, researchers, and practitioners, no other book provides such an accessible introduction to this exciting and fast-evolving field.
- The Calculus of Selfishness
6
A pioneer in evolutionary game theory looks at selfishness and cooperation How does cooperation emerge among selfish individuals? When do people share resources, punish those they consider unfair, and engage in joint enterprises? These questions fascinate philosophers, biologists, and economists alike, for the "invisible hand" that should turn selfish efforts into public benefit is not always at work. The Calculus of Selfishness looks at social dilemmas where cooperative motivations are subverted and self-interest becomes self-defeating. Karl Sigmund, a pioneer in evolutionary game theory, uses simple and well-known game theory models to examine the foundations of collective action and the effects of reciprocity and reputation. Focusing on some of the best-known social and economic experiments, including games such as the Prisoner's Dilemma, Trust, Ultimatum, Snowdrift, and Public Good, Sigmund explores the conditions leading to cooperative strategies. His approach is based on evolutionary game dynamics, applied to deterministic and probabilistic models of economic interactions. Exploring basic strategic interactions among individuals guided by self-interest and caught in social traps, The Calculus of Selfishness analyzes to what extent one key facet of human nature—selfishness—can lead to cooperation.
- Mathematics in Population Biology
12
The formulation, analysis, and re-evaluation of mathematical models in population biology has become a valuable source of insight to mathematicians and biologists alike. This book presents an overview and selected sample of these results and ideas, organized by biological theme rather than mathematical concept, with an emphasis on helping the reader develop appropriate modeling skills through use of well-chosen and varied examples. Part I starts with unstructured single species population models, particularly in the framework of continuous time models, then adding the most rudimentary stage structure with variable stage duration. The theme of stage structure in an age-dependent context is developed in Part II, covering demographic concepts, such as life expectation and variance of life length, and their dynamic consequences. In Part III, the author considers the dynamic interplay of host and parasite populations, i.e., the epidemics and endemics of infectious diseases. The theme of stage structure continues here in the analysis of different stages of infection and of age-structure that is instrumental in optimizing vaccination strategies. Each section concludes with exercises, some with solutions, and suggestions for further study. The level of mathematics is relatively modest; a "toolbox" provides a summary of required results in differential equations, integration, and integral equations. In addition, a selection of Maple worksheets is provided. The book provides an authoritative tour through a dazzling ensemble of topics and is both an ideal introduction to the subject and reference for researchers.
Read more from Karl Sigmund
Games of Life: Explorations in Ecology, Evolution and Behavior Rating: 4 out of 5 stars4/5
Related to Princeton Series in Theoretical and Computational Biology
Related ebooks
Flying Saucers Vs. the Earth #4 Rating: 0 out of 5 stars0 ratings20 Million Miles More Rating: 1 out of 5 stars1/5Blackbeard Legacy #0 Rating: 0 out of 5 stars0 ratingsTill Death Us Do Part Rating: 0 out of 5 stars0 ratingsPolitical Power: Portrait Gallery Rating: 0 out of 5 stars0 ratingsLazar & Jingles and Bunson in Holiday Gifts Rating: 0 out of 5 stars0 ratingsJeremiah's Path to Confirmation: And his Pocketbook of seven, nine plus three Rating: 0 out of 5 stars0 ratingsJourney to the Moon Rating: 0 out of 5 stars0 ratingsSpace Women Beyond the Stratosphere #2 Rating: 0 out of 5 stars0 ratingsVictoria's Secret Service: Nemesis Rising #2 Rating: 0 out of 5 stars0 ratingsPolitical Power: Michele Bachmann Rating: 0 out of 5 stars0 ratingsFAME: Lady Gaga: Giant-Sized Rating: 0 out of 5 stars0 ratingsDaily Dose Rating: 0 out of 5 stars0 ratingsJudo Girl: Silencer Rating: 0 out of 5 stars0 ratingsOn the Way Rating: 0 out of 5 stars0 ratingsSoma Rating: 0 out of 5 stars0 ratingsTrapped in the Tower Rating: 0 out of 5 stars0 ratingsPolitical Power: Ted Kennedy Rating: 0 out of 5 stars0 ratingsWhen Reindeer Learned to Fly Rating: 0 out of 5 stars0 ratingsI Rescued Two Dogs: Now Who Will Rescue Me? Rating: 0 out of 5 stars0 ratingsSpace Women Beyond the Stratosphere #3 Rating: 0 out of 5 stars0 ratingsAdventures with Oakie the Other Heroes Rating: 0 out of 5 stars0 ratingsThe Blue Meteor Rating: 0 out of 5 stars0 ratingsBlackbeard Legacy #2 Volume 1 Rating: 0 out of 5 stars0 ratingsA Caboodle of Cat Tales Rating: 0 out of 5 stars0 ratingsMy Alabaster Box...: Poetry, Prose, and Prayer Rating: 0 out of 5 stars0 ratingsPrimordia Rating: 0 out of 5 stars0 ratingsBlackbeard Legacy #2 Volume 2 Rating: 0 out of 5 stars0 ratingsLegend of Isis: The First Flight of Horus Rating: 0 out of 5 stars0 ratings
Data Modeling & Design For You
Supercharge Power BI: Power BI is Better When You Learn To Write DAX Rating: 5 out of 5 stars5/5Data Analytics for Beginners: Introduction to Data Analytics Rating: 4 out of 5 stars4/5The Secrets of ChatGPT Prompt Engineering for Non-Developers Rating: 5 out of 5 stars5/5Mastering Agile User Stories Rating: 4 out of 5 stars4/5Raspberry Pi :Raspberry Pi Guide On Python & Projects Programming In Easy Steps Rating: 3 out of 5 stars3/5The Esri Guide to GIS Analysis, Volume 3: Modeling Suitability, Movement, and Interaction Rating: 0 out of 5 stars0 ratingsData Visualization: a successful design process Rating: 4 out of 5 stars4/5Thinking in Algorithms: Strategic Thinking Skills, #2 Rating: 5 out of 5 stars5/5Minding the Machines: Building and Leading Data Science and Analytics Teams Rating: 0 out of 5 stars0 ratingsData Analytics with Python: Data Analytics in Python Using Pandas Rating: 3 out of 5 stars3/5Spreadsheets To Cubes (Advanced Data Analytics for Small Medium Business): Data Science Rating: 0 out of 5 stars0 ratingsMetaheuristics: From Design to Implementation Rating: 0 out of 5 stars0 ratingsLearn T-SQL Querying: A guide to developing efficient and elegant T-SQL code Rating: 0 out of 5 stars0 ratings150 Most Poweful Excel Shortcuts: Secrets of Saving Time with MS Excel Rating: 3 out of 5 stars3/5AutoCAD® Pocket Reference Rating: 0 out of 5 stars0 ratingsR: Data Analysis and Visualization Rating: 5 out of 5 stars5/5Bayesian Analysis with Python Rating: 5 out of 5 stars5/5Living in Data: A Citizen's Guide to a Better Information Future Rating: 4 out of 5 stars4/5Principles of Data Science Rating: 4 out of 5 stars4/5Data Visualization with D3.js Cookbook Rating: 0 out of 5 stars0 ratingsGraph Databases in Action: Examples in Gremlin Rating: 0 out of 5 stars0 ratingsQuality metrics for semantic interoperability in Health Informatics Rating: 0 out of 5 stars0 ratingsA Concise Guide to Object Orientated Programming Rating: 0 out of 5 stars0 ratingsThe Systems Thinker - Mental Models: The Systems Thinker Series, #3 Rating: 0 out of 5 stars0 ratingsThink Like a Data Scientist: Tackle the data science process step-by-step Rating: 0 out of 5 stars0 ratings
Related categories
Reviews for Princeton Series in Theoretical and Computational Biology
0 ratings0 reviews