ISBN-10:
0199230919
ISBN-13:
9780199230914
Pub. Date:
11/23/2009
Publisher:
Oxford University Press, USA
Applying Maths in the Chemical and Biomolecular Sciences: An Example-Based Approach

Applying Maths in the Chemical and Biomolecular Sciences: An Example-Based Approach

by Godfrey Beddard

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Overview

Applying Maths in the Chemical and Biomolecular Sciences uses an extensive array of examples to demonstrate how mathematics can be applied to chemical and biological systems. Integrating computer software to solve mathematical problems, the text addresses such issues as how vectors help us work out the conformation of DNA or proteins, how matrices help us tackle problems in quantum mechanics, and what differential equations have to do with molecular dynamics and the spread of disease.

An accompanying Online Resource Centre features additional resources for both lecturers and students, enhancing the value of the text as a teaching and learning tool. For lecturers, the website offers figures from the text in electronic format, solutions to half of the problems presented in the book, and a guide tailoring the book for users of Mathematica.

Suitable for both undergraduate and graduates, Applying Maths in the Chemical and Biomolecular Sciences is appropriate for mathematics classes that make applications to chemistry, biochemistry, and biophysical chemistry.

Product Details

ISBN-13: 9780199230914
Publisher: Oxford University Press, USA
Publication date: 11/23/2009
Edition description: New Edition
Pages: 816
Product dimensions: 8.30(w) x 11.60(h) x 1.60(d)

About the Author

Godfrey Beddard is Professor of Chemical Physics in the School of Chemistry, University of Leeds, where his research interests encompass femtosecond spectroscopy, electron and energy transfer, and protein folding and unfolding.

Table of Contents

1. Numbers, Basic Functions, and Algorithms
2. Complex Numbers
3. Differentiation
4. Integration
5. Vectors
6. Matrices and Determinants
7. Matrices in Quantum Mechanics
8. Summations, Series, and Expansion of Functions
9. Fourier Series and Transforms
10. Differential Equations
11. Numerical Methods
12. Monte-carlo Methods
13. Statistics and Data Analysis

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