Dynamic Models in Biology / / John Guckenheimer, Stephen P. Ellner.

• Superior document: Title is part of eBook package: De Gruyter Princeton University Press eBook-Package Backlist 2000-2013
• VerfasserIn: Ellner, Stephen P.,; Guckenheimer, John,
• Place / Publishing House: Princeton, NJ : : Princeton University Press, , [2011]; ©2006
• Year of Publication: 2011
• Language: English
• Physical Description: 1 online resource (352 p.) :; 10 halftones. 90 line illus. 15 tables.
• Other title: Frontmatter --; Contents --; List of Figures --; List of Tables --; Preface --; 1. What Are Dynamic Models? --; 2. Matrix Models and Structured Population Dynamics --; 3. Membrane Channels and Action Potentials --; 4. Cellular Dynamics: Pathways of Gene Expression --; 5. Dynamical Systems --; 6. Differential Equation Models for Infectious Disease --; 7. Spatial Patterns in Biology --; 8. Agent-Based and Other Computational Models for Complex Systems --; 9. Building Dynamic Models --; Index
• Format: Mode of access: Internet via World Wide Web.
• ISBN: 9781400840960; 9783110442502
• DOI: 10.1515/9781400840960?locatt=mode:legacy
• Access: restricted access
• Hierarchical level: Monograph
• Statement of Responsibility: John Guckenheimer, Stephen P. Ellner.

From controlling disease outbreaks to predicting heart attacks, dynamic models are increasingly crucial for understanding biological processes. Many universities are starting undergraduate programs in computational biology to introduce students to this rapidly growing field. In Dynamic Models in Biology, the first text on dynamic models specifically written for undergraduate students in the biological sciences, ecologist Stephen Ellner and mathematician John Guckenheimer teach students how to understand, build, and use dynamic models in biology. Developed from a course taught by Ellner and Guckenheimer at Cornell University, the book is organized around biological applications, with mathematics and computing developed through case studies at the molecular, cellular, and population levels. The authors cover both simple analytic models--the sort usually found in mathematical biology texts--and the complex computational models now used by both biologists and mathematicians. Linked to a Web site with computer-lab materials and exercises, Dynamic Models in Biology is a major new introduction to dynamic models for students in the biological sciences, mathematics, and engineering.