Kinetic Theory of Granular Gases

topics covered. For example, one could use Fourier-transform techniques and Gaussian statistics to provide an alternative derivation for the significance of sequence-alignment scores from random-walk models. One could also use cumulant expansions or steepestdescent methods and the Cramer function in a discussion of the rare events that lead to nonuniform convergence of a sum of random variables to the central limit. The discussion of maximumlikelihood estimation might be simplified to introduce readers to estimation theory and its importance as a statistical tool. Introduction to Mathematical Methods in Bioinformatics is a strong description of the theory behind the standard methods of computational sequence analysis. The book serves as a springboard for considering current bioinformatics research problems— such as the analysis of gene chip data—whose solutions entail a mixture of mathematics, statistics, engineering, and physics. With some additional work on the reader’s or instructor’s part, the text may also serve as an introduction to computational biology in general. Michael W. Deem Rice University Houston, Texas Kinetic Theory of Granular Gases