This book provides an introduction to two important aspects of modern bioch- istry, molecular biology, and biophysics: computer simulation and data analysis. My aim is to introduce the tools that will enable students to learn and use some f- damental methods to construct quantitative models of biological mechanisms, both deterministicandwithsomeelementsofrandomness;tolearnhowconceptsofpr- ability can help to understand important features of DNA sequences; and to apply a useful set of statistical methods to analysis of experimental data. The availability of very capable but inexpensive personal computers and software makes it possible to do such work at a much higher level, but in a much easier way, than ever before. TheExecutiveSummaryofthein?uential2003reportfromtheNationalAcademy of Sciences, ¿BIO 2010: Transforming Undergraduate Education for Future - search Biologists¿ [12], begins The interplay of the recombinant DNA, instrumentation, and digital revolutions has p- foundly transformed biological research. The con?uence of these three innovations has led to important discoveries, such as the mapping of the human genome. How biologists design, perform, and analyze experiments is changing swiftly. Biological concepts and models are becoming more quantitative, and biological research has become critically dependent on concepts and methods drawn from other scienti?c disciplines. The connections between the biological sciences and the physical sciences, mathematics, and computer science are rapidly becoming deeper and more extensive.

Covers many of the major quantitative topics in modern molecular and cell biology and biophysics

The Basics of R.- Calculating with R.- Plotting with R.- Functions and Programming.- Data and Packages.- Simulation of Biological Processes.- Equilibrium and Steady State Calculations.- Differential Equations and Reaction Kinetics.- Population Dynamics.- Diffusion and Transport.- Regulation and Control of Metabolism.- Models of Regulation.- Analyzing DNA and Protein Sequences.- Probability and Population Genetics.- DNA Sequence Analysis.- Statistical Analysis in Molecular and Cellular Biology.- Statistical Analysis of Data.- Microarrays.