An Invitation to Biomathematics

Essential for all biology and biomathematics courses, this textbook provides students with a fresh perspective of quantitative techniques in biology in a field where virtually any advance in the life sciences requires a sophisticated mathematical approach. An Invitation to Biomathematics, expertly written by a team of experienced educators, offers students a solid understanding of solving biological problems with mathematical applications. This text succeeds in enabling students to truly experience advancements made in biology through mathematical models by containing computer-based hands-on laboratory projects with emphasis on model development, model validation, and model refinement.

The supplementary work, Laboratory Manual of Biomathematics is available separately ISBN 0123740223, or as a set ISBN: 0123740290)

Provides a complete guide for development of quantification skills crucial for applying mathematical methods to biological problemsIncludes well-known examples from across disciplines in the life sciences including modern biomedical researchExplains how to use data sets or dynamical processes to build mathematical modelsOffers extensive illustrative materialsWritten in clear and easy-to-follow language without assuming a background in math or biologyA laboratory manual is available for hands-on, computer-assisted projects based on material covered in the text

1. Processes that Change with Time: Introduction to Dynamical Systems / 2. Complex Dynamics Emerging from Interacting Dynamical Systems / 3. Mathematics in Genetics / 4. Quantitative Genetics and Statistics / 5. Risk Analysis of Blood Glucose Data / 6. Predicting Septicemia in Neonates / 7. Cooperative Binding: How Your Blood Transports Oxygen / 8. Ligand Binding, Data Fitting, and Least-Squares Estimates of Model Parameters / 9. Endocrinology and Hormone Pulsatility / 10. Endocrine Network Modeling: Feedback Loops and Hormone Oscillations / 11. Detecting Rhythms in Confounded Data / 12. Using Microarrays to Study Gene Expression Patterns