• Foreword. Preface. Acknowledgments. Contributors.
• Section I DATA COLLECTION, ANALYSIS, AND VISUALIZATION. 1 DEFINING BIOINFORMATICS AND STRUCTURAL BIOINFORMATICS (Russ B. Altman and Jonathan M. Dugan). 2 FUNDAMENTALS OF PROTEIN STRUCTURE (Eric D. Scheeff and J. Lynn Fink). 3 FUNDAMENTALS OF DNA AND RNA STRUCTURE (Stephen Neidle, Bohdan Schneider, and Helen M. Berman). 4 COMPUTATIONAL ASPECTS OF HIGH-THROUGHPUT CRYSTALLOGRAPHIC MACROMOLECULAR STRUCTURE DETERMINATION (Paul D. Adams, Ralf W. Grosse-Kunstleve, and Axel T. Brunger). 5 MACROMOLECULAR STRUCTURE DETERMINATION BY NMR SPECTROSCOPY (John L. Markley, Arash Bahrami, Hamid R. Eghbalnia, Francis C. Peterson, Robert C. Tyler, Eldon L. Ulrich, William M. Westler, and Brian F. Volkman). 6 ELECTRON MICROSCOPY IN THE CONTEXT OF STRUCTURAL SYSTEMS BIOLOGY (Niels Volkmann and Dorit Hanein). 7 STUDY OF PROTEIN THREE-DIMENSIONAL STRUCTURE AND DYNAMICS USING PEPTIDE AMIDE HYDROGEN/ DEUTERIUM EXCHANGE MASS SPECTROMETRY (DXMS) AND CHEMICAL CROSS-LINKING WITH MASS SPECTROMETRY TO CONSTRAIN MOLECULAR MODELING (Sheng Li, Dmitri Mouradov, Gordon King, Tong Liu, Ian Ross, Bostjan Kobe, Virgil L. Woods Jr, and Thomas Huber). 8 SEARCH AND SAMPLING IN STRUCTURAL BIOINFORMATICS (Ilan Samish). 9 MOLECULAR VISUALIZATION (Steven Bottomley and Erik Helmerhorst).
• Section II DATA REPRESENTATION AND DATABASES. 10 THE PDB FORMAT, mmCIF FORMATS, AND OTHER DATA FORMATS (John D. Westbrook and Paula M.D. Fitzgerald). 11 THE WORLDWIDE PROTEIN DATA BANK (Helen M. Berman, Kim Henrick, Haruki Nakamura, and John L. Markley). 12 THE NUCLEIC ACID DATABASE (Bohdan Schneider, Joanna de la Cruz, Zukang Feng, Li Chen, Shuchismita Dutta, Irina Persikova, John D. Westbrook, Huanwang Yang, Jasmine Young, Christine Zardecki, and Helen M. Berman). 13 OTHER STRUCTURE-BASED DATABASES (J. Lynn Fink, Helge Weissig, and Philip E. Bourne).
• Section III DATA INTEGRITY AND COMPARATIVE FEATURES. 14 STRUCTURAL QUALITY ASSURANCE (Roman A. Laskowski). 15 THE IMPACT OF LOCAL ACCURACY IN PROTEIN AND RNA STRUCTURES: VALIDATION AS AN ACTIVE TOOL (Jane S. Richardson and David C. Richardson). 16 STRUCTURE COMPARISON AND ALIGNMENT (Marc A. Marti-Renom, Emidio Capriotti, Ilya N. Shindyalov, and Philip E. Bourne). 17 PROTEIN STRUCTURE EVOLUTION AND THE SCOP DATABASE (Raghu P. R. Metpally and Boojala V. B. Reddy). 18 THE CATH DOMAIN STRUCTURE DATABASE (Frances M. G. Pearl, Alison Cuff, and Christine A. Orengo).
• Section IV STRUCTURAL AND FUNCTIONAL ASSIGNMENT. 19 SECONDARY STRUCTURE ASSIGNMENT (Claus A. Andersen and Burkhard Rost). 20 IDENTIFYING STRUCTURAL DOMAINS IN PROTEINS (Stella Veretnik, Jenny Gu, and Shoshana Wodak). 21 INFERRING PROTEIN FUNCTION FROM STRUCTURE (James D. Watson, Gail J. Bartlett, and Janet M. Thornton). 22 STRUCTURAL ANNOTATION OF GENOMES (Adam J. Reid, Corin Yeats, Jonathan Lees, and Christine A. Orengo). 23 EVOLUTION STUDIED USING PROTEIN STRUCTURE (Song Yang, Ruben Valas, and Philip E. Bourne).
• Section V MACROMOLECULAR INTERACTIONS. 24 ELECTROSTATIC INTERACTIONS (Nathan A. Baker and J. Andrew McCammon). 25 PREDICTION OF PROTEIN-NUCLEIC ACID INTERACTIONS (Timothy Robertson and Gabriele Varani). 26 PREDICTION OF PROTEIN-PROTEIN INTERACTIONS FROM EVOLUTIONARY INFORMATION (Alfonso Valencia and Florencio Pazos). 27 DOCKING METHODS, LIGAND DESIGN, AND VALIDATING DATA SETS IN THE STRUCTURAL GENOMICS ERA (Natasja Brooijmans).
• Section VI STRUCTURE PREDICTION. 28 CASP AND OTHER COMMUNITY-WIDE ASSESSMENTS TO ADVANCE THE FIELD OF STRUCTURE PREDICTION (Jenny Gu and Philip E. Bourne). 29 PREDICTION OF PROTEIN STRUCTURE IN 1D: SECONDARY STRUCTURE, MEMBRANE REGIONS, AND SOLVENT ACCESSIBILITY (Burkhard Rost). 30 HOMOLOGY MODELING (Hanka Venselaar, Elmar Krieger, and Gert Vriend). 31 FOLD RECOGNITION METHODS (Adam Godzik). 32 DE NOVO PROTEIN STRUCTURE PREDICTION: METHODS AND APPLICATION (Kevin Drew, Dylan Chivian, and Richard Bonneau). 33 RNA STRUCTURAL BIOINFORMATICS (Magdalena A. Jonikas, Alain Laederach, and Russ B. Altman).
• Section VII THERAPEUTIC DISCOVERY. 34 STRUCTURAL BIOINFORMATICS IN DRUG DISCOVERY (William R. Pitt, Al -cia Perez Higueruelo, and Colin R. Groom). 35 B-CELL EPITOPE PREDICTION (Julia V. Ponomarenko and Marc H.V. van Regenmortel).
• Section VIII FUTURE CHALLENGES. 36 METHODS TO CLASSIFY AND PREDICT THE STRUCTURE OF MEMBRANE PROTEINS (Marialuisa Pellegrini-Calace and Janet M. Thornton). 37 PROTEIN MOTION: SIMULATION (Ilan Samish, Jenny Gu, and Michael L. Klein). 38 THE SIGNIFICANCE AND IMPACTS OF PROTEIN DISORDER AND CONFORMATIONAL VARIANTS (Jenny Gu and Vincent J. Hilser). 39 PROTEIN DESIGNABILITY AND ENGINEERING (Nikolay V. Dokholyan). 40 STRUCTURAL GENOMICS OF PROTEIN SUPERFAMILIES (Stephen K. Burley, Steven C. Almo, Jeffrey B. Bonanno, Mark R. Chance, Spencer Emtage, Andras Fiser, Andrej Sali, J. Michael Sauder, and Subramanyam Swaminathan). INDEX.
• (source: Nielsen Book Data)

"Structural Bioinformatics" 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. 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. Offering detailed coverage for practitioners while remaining accessible to the novice, "Structural Bioinformatics, Second Edition" is a valuable resource and an excellent textbook for a range of readers in the bioinformatics and advanced biology fields. Praise for the previous edition: 'This book is a gold mine of fundamental and practical information in an area not previously well represented in book form' - "Biochemistry and Molecular Education". '...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 - "BAMBED". '...a useful and timely summary of a rapidly expanding field' - "Nature Structural Biology". '...a terrific job in this timely creation of a compilation of articles that appropriately addresses this issue' - "Briefings in Bioinformatics".
(source: Nielsen Book Data)

• Preface
• Chapter 1. Historical introduction and overview
• Chapter 2. Collecting and storing sequences in the laboratory
• Chapter 3. Alignment of pairs of sequences
• Chapter 4. Introduction to probability and statistical analysis of sequence alignments
• Chapter 5. Multiple sequence alignment
• Chapter 6. Sequence database searching for similar sequences
• Chapter 7. Phylogenetic prediction
• Chapter 8. Prediction of RNA secondary structure
• Chapter 9. Gene prediction and regulation
• Chapter 10. Protein classification and structure prediction
• Chapter 11. Genome analysis
• Chapter 12. Bioinformatics programming using Perl and Perl modules
• Chapter 13. Analysis of microarrays.
• (source: Nielsen Book Data)

As more species' genomes are sequenced, computational analysis of these data has become increasingly important. The second, entirely updated edition of this widely praised textbook provides a comprehensive and critical examination of the computational methods needed for analyzing DNA, RNA, and protein data, as well as genomes. The book has been rewritten to make it more accessible to a wider audience, including advanced undergraduate and graduate students. New features include chapter guides and explanatory information panels and glossary terms. New chapters in this second edition cover statistical analysis of sequence alignments, computer programming for bioinformatics, and data management and mining. Practically oriented problems at the ends of chapters enhance the value of the book as a teaching resource. The book also serves as an essential reference for professionals in molecular biology, pharmaceutical, and genome laboratories.
(source: Nielsen Book Data)
This second edition of Bioinformatics: Sequence and Genome Analysis provides a comprehensive overview and critical examination of the computational methods needed for analyzing DNA, RNA, and protein data as well as entire genomes. The book has been completey revised, redesigned for increased accessibility and to further aid learning, and updated with three completely new chapters. It is now more student-friendly than ever and will build on the adoption success of the first edition.
(source: Nielsen Book Data)

Functional genomics--the deconstruction of the genome to determine the biological function of genes and gene interactions--is one of the most fruitful new areas of biology. The growing use of DNA microarrays allows researchers to assess the expression of tens of thousands of genes at a time. This quantitative change has led to qualitative progress in our ability to understand regulatory processes at the cellular level.This book provides a systematic introduction to the use of DNA microarrays as an investigative tool for functional genomics. The presentation is appropriate for readers from biology or bioinformatics. After presenting a framework for the design of microarray-driven functional genomics experiments, the book discusses the foundations for analyzing microarray data sets, genomic data-mining, the creation of standardized nomenclature and data models, clinical applications of functional genomics research, and the future of functional genomics.
(source: Nielsen Book Data)

• Foreword. Preface. Acknowledgments. Contributors. SECTION I: INTRODUCTION. Defining Bioinformatics and Structural Bioinformatics (R. Altman & J. Dugan). Fundamentals of Protein Structure (E. Scheeff & J. Fink). Fundamentals of DNA and RNA Structure (S. Neidle, et al.). Computational Aspects of High--Throughput Crystallographic Macromolecular Structure Determination (P. Adams, et al.). Macromolecular Structure Determination by NMR Spectroscopy (J. Markley, et al.). Electron Microscopy (N. Volkmann & D. Hanein). Molecular Visualization (J. Tate). SECTION II: DATA REPRESENTATION AND DATABASES. The PDB Format, mmCIF Formats, and Other Data Formats (J. Westbrook & P. Fitzgerald). The Protein Data Bank (The PDB Team). The Nucleic Acid Database (H. Berman, et al.). Other Structure--Based Databases (H. Weissig & P. Bourne). SECTION III: COMPARATIVE FEATURES. Protein Structure Evolution and the SCOP Database (B. Reddy & amp
• P. Bourne). The CATH Domain Structure Database (C. Orengo, et al.). Structural Quality Assurance (R. Laskowski). All--Atom Contacts: A New Approach to Structure Validation (J. Richardson). Structure Comparison and Alignment (P. Bourne & I. Shindyalov). SECTION IV: STRUCTURE AND FUNCTIONAL ASSIGNMENT. Secondary Structure Assignment (C. Andersen & B. Rost). Identifying Structural Domains in Proteins (L. Wernisch & S. Wodak). Inferring Protein Function from Structure (G. Bartlett, et al.). SECTION V: PROTEIN INTERACTIONS. Prediction of Protein--Protein Interactions from Evolutionary Information (A. Valencia & F. Pazos). Electrostatic Interactions (N. Baker & J. McCammon). SECTION VI: PROTEINS AS DRUG TARGETS. Principles and Methods of Docking and Ligand Design (J. Krumrine, et al.). Structural Bioinformatics in Drug Discovery (E. Fauman, et al.). SECTION VII: STRUCTURE PREDICTION. CASP and CAFASP Experiments and Their Findings (P. Bourne). Homology Modeling (E. Krieger, et al.). Fold Recognition Methods (A. Godzik). Ab Initio Methods (D. Chivian, et al.). Prediction in 1D: Secondary Structure, Membrane Helices, and Accessibility (B. Rost). SECTION VIII: THE FUTURE. Structural Genomics (S. Burley & J. Bonanno). Index.
• (source: Nielsen Book Data)

From the Foreword: "[A] must read for all of us committed to understanding the interplay of structure and function...[T]he individual chapters outline the suite of major basic life science questions, such as the status of efforts to predict protein structure and how proteins carry out cellular functions, and also the applied life science questions such as how structural bioinformatics can improve health care through accelerating drug discovery." This book provides a basic understanding of the theories, associated algorithms, resources, and tools used in structural bioinformatics. The reader emerges with the ability to make effective use of protein, DNA, RNA, carbohydrate, and complex structures to better understand biological function. Moreover, it draws a clear connection between structural studies and the rational design of new therapies.
(source: Nielsen Book Data)

• 1. Introduction
• 2. Pairwise sequence alignment
• 3. Multiple alignments
• 4. Hidden Markov models
• 5. Hidden Markov models applied to biological sequences
• 6. The Chomsky hierarchy of formal grammars
• 7. RNA and stochastic context-free grammars
• 8. Phylogenetic trees
• 9. Phylogeny and alignment
• Index.
• (source: Nielsen Book Data)

Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.
(source: Nielsen Book Data)