This text for a one-semester junior or senior undergraduate course explains basic mathematical techniques underlying some of the core algorithms in structural bioinformatics, presenting bioinformatics topics and problems within a scientific methodology that integrates empirical observations, mathematical modeling of natural processes, and the science of calculating predictions and mathematical objects based on mathematical models. Coverage progresses from RNA structure, data sources and formats, and dynamic programming through algorithms and topics representative of structural bioinformatics, such as protein sequence alignment, coordinate transformations, and machine learning. About 60 exercises, across ten chapters, are included, along with color and b&w illustrations. About 50 pages of appendixes review basics of vector spaces, linear algebra, theorems and proofs, and vector derivatives. Prerequisites include linear algebra, calculus, computer programming, introductory algorithms and an introductory course in bioinformatics. Information on the author is not given. Annotation ©2010 Book News, Inc., Portland, OR (booknews.com)