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Covers many of the major quantitative topics in modern molecular and cell biology and biophysics
Presents both standard and cutting-edge topics such as regulation of metabolism and development
Treats both computer simulation and statistics
Takes a computational approach that most students find more appealing than analytical mathematics
Uses the powerful, open-source, cross-platform computer language R
This book provides an introduction, suitable for advanced undergraduates and beginning graduate students, to two important aspects of molecular biology and biophysics: computer simulation and data analysis. It introduces tools to enable readers to learn and use fundamental methods for constructing quantitative models of biological mechanisms, both deterministic and with some elements of randomness, including complex reaction equilibria and kinetics, population models, and regulation of metabolism and development; to understand how concepts of probability can help in explaining important features of DNA sequences; and to apply a useful set of statistical methods to analysis of experimental data from spectroscopic, genomic, and proteomic sources.
These quantitative tools are implemented using the free, open source software program R. R provides an excellent environment for general numerical and statistical computing and graphics, with capabilities similar to Matlab®. Since R is increasingly used in bioinformatics applications such as the BioConductor project, it can serve students as their basic quantitative, statistical, and graphics tool as they develop their careers
Content Level »Research
Keywords »Biophysics computing - Data analysis in molecular biology - Markov chain - Microarray - Quantitative biology - R programming language - Simulation - Statistical computing graphics - bioinformatics - biology - biophysics - genetics - systems biology quantitative models - transcription - using GNU S