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Thirty years ago, biologists could get by with a rudimentary grasp of mathematics and modeling. Not so today. In seeking to answer fundamental questions about how biological …
This book explores important aspects of Markov and hidden Markov processes and the applications of these ideas to various problems in computational biology. The book starts from …
From controlling disease outbreaks to predicting heart attacks, dynamic models are increasingly crucial for understanding biological processes. Many universities are starting …
A pseudorandom generator is an easy-to-compute function that stretches a short random string into a much longer string that "e;looks"e; just like a random string to any …
Despite decades of developments in immunization and drug therapy, tuberculosis remains among the leading causes of human mortality, and no country has successfully eradicated the …
A concise guide to representing complex Earth systems using simple dynamic modelsMathematical Modeling of Earth's Dynamical Systems gives earth scientists the essential skills for …
Rabinowitz's classical global bifurcation theory, which concerns the study in-the-large of parameter-dependent families of nonlinear equations, uses topological methods that …
An inviting collection of fun, hands-on applications in mathematics and computingThis book provides a fun, hands-on approach to learning how mathematics and computing relate to the …
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook …
Quantitative approaches to evolutionary biology traditionally consider evolutionary change in isolation from an important pressure in natural selection: the demography of …