<i>Structural Bioinformatics</i> was the first major effort to show the application of the principles and basic knowledge of the larger field of bioinformatics to questions focusing on macromolecular structure, such as the prediction of protein structure and how proteins carry out cellular functions, and how the application of bioinformatics to these life science issues can improve healthcare by accelerating drug discovery and development. Designed primarily as a reference, the first edition nevertheless saw widespread use as a textbook in graduate and undergraduate university courses dealing with the theories and associated algorithms, resources, and tools used in the analysis, prediction, and theoretical underpinnings of DNA, RNA, and proteins.<p>This new edition contains not only thorough updates of the advances in structural bioinformatics since publication of the first edition, but also features eleven new chapters dealing with frontier areas of high scientific impact, including: sampling and search techniques; use of mass spectrometry; genome functional annotation; and much more.<p>Offering detailed coverage for practitioners while remaining accessible to the novice, <i>Structural Bioinformatics, Second Edition</i> is a valuable resource and an excellent textbook for a range of readers in the bioinformatics and advanced biology fields.<p><b>Praise for the previous edition:</b><p>"This book is a gold mine of fundamental and practical information in an area not previously well represented in book form."<br><b><i>—Biochemistry and Molecular Education</i></b><p>"... destined to become a classic reference work for workers at all levels in structural bioinformatics...recommended with great enthusiasm for educators, researchers, and graduate students."<br><b><i>—BAMBED</i></b><p>"...a useful and timely summary of a rapidly expanding field."<br><b><i>—Nature Structural Biology</i></b><p>"...a terrific job in this timely creation of a compilation of articles that appropriately addresses this issue."<br><b><i>—Briefings in Bioinformatics</i></b>