The building of conceptual models is an inherent part of our interaction with the world, and the foundation of scientific investigation. Scientists often perform the processes of modelling subconsciously, unaware of the scope and significance of this activity, and the techniques available to assist in the description and testing of their ideas. Mathematics has three important contributions to make in biological modelling: (1) it provides unambiguous languages for expressing relationships at both qualitative and quantitative levels of observation; (2) it allows effective analysis and prediction of model behaviour, and can thereby organize experimental effort productively; (3) it offers rigorous methods of testing hypotheses by comparing models with experimental data; by providing a means of objectively excluding unsuitable concepts, the development of ideas is given a sound experimental basis. Many modern mathematical techniques can be exploited only with the aid of computers. These machines not only provide increased speed and accuracy in determining the consequences of model assumptions, but also greatly extend the range of problems which can be explored. The impact of computers in the biological sciences has been widespread and revolutionary, and will continue to be so.

First multi-year cumulation covers six years: 1965-70.

A concise guide to mathematical modeling and analysis of pharmacokinetic data, this book contains valuable methods for maximizing the information obtained from given data. It is an ideal resource for scientists, scholars, and advanced students.

Introduces the concepts, methods and techniques of model formulation, identification, and validation as applicable to metabolic and endocrine processes. Shows how modeling can be used to provide a concise description of complex dynamic processes, to test hypotheses concerning physiological and biochemical structure, and to estimate physiological quantities (parameters) that otherwise would not be directly accessible to measurement. Includes numerous examples and case studies.

This book presents the proceedings from the International Conference held in Halifax, NS in July 1997. Funded by The Fields Institute and Le Centre de Recherches Mathématiques, the conference was held in honor of the retirement of Professors Lynn Erbe and Herb I. Freedman (University of Alberta). Featured topics include ordinary, partial, functional, and stochastic differential equations and their applications to biology, epidemiology, neurobiology, physiology and other related areas. The 41 papers included in this volume represent the recent work of leading researchers over a wide range of subjects, including bifurcation theory, chaos, stability theory, boundary value problems, persistence theory, neural networks, disease transmission, population dynamics, pattern formation and more. The text would be suitable for a graduate or advanced undergraduate course study in mathematical biology. Features: An overview of current developments in differential equations and mathematical biology. Authoritative contributions from over 60 leading worldwide researchers. Original, refereed contributions.