Synopses & Reviews
Designed to address a lack of computer skills training in biological science education, this volume presents problem-centered instruction for using basic computer programming in biological research and data manipulation and presentation. Based on the Mac OsX operating system, and heavily centered on its Unix components, this guide presents an overview of the Unix command line, regular expressions, scripting and Python programming all aimed at speeding up or improving the quality of biological research. Additional chapters deal with graphical presentation of data and advanced topics such as network communications and interfacing with electronic devices. The work includes color illustrations and code examples and access to a companion website is provided. Haddock is a research biologist with the Monterey Bay Aquarium Research Institute and Dunn is professor of evolutionary biology at Brown University. Annotation ©2011 Book News, Inc., Portland, OR (booknews.com)
Mathematical modeling has long been essential in physics: for instance, it is well known that distance traveled by an object traveling at constant speed v is proportional to the time traveled t. This mathematical model can be expressed as an equation: d = vt. Since the time of Newton, physicists have been incredibly successful at using mathematics to describe the behavior of matter of all sizes, ranging from subatomic particles to galaxies. Mathematical modeling has in the last two decades become an incredibly powerful and essential tool in the biologistand#8217;s arsenal. The tremendous potential of mathematical and computational approaches in leading to fundamental insights on biological systems are inspiring many biologists to find beauty and clarity in models.The central question is to understand how a network of interactions between individual molecules can lead to large-scale results, such as the development of a fertilized egg into a complex organism. The human mind is not suited for making correct intuitive judgments about networks comprised of thousands of actors. Addressing questions of this complexity requires quantitative modeling. To date, few textbooks have been unable to address these complexities directly, which is why Dmitry A. Kondrashov developed Living Math--a volume that focuses specifically on mathematical modeling for life scientists, including in-depth study of single variables, relationships between two variables, chains of random variables, and variables that change over time.