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Jenny Gu, PhD, is Assistant Professor at the Skaggs School of Pharmacy and Pharmaceutical Sciences University of California, San Diego. This is her first book.
Philip E. Bourne, PhD, is professor in the Department of Pharmacology at the University of California, San Diego, and Director of Integrated Biosciences at the San Diego Supercomputer Center. He is past president of the International Society for Computational Biology (ISCB). He is author of over 125 peer-reviewed scientific papers and four previous books.
Foreword | p. xi |
Preface | p. xv |
Acknowledgments | p. xix |
Contributors | p. xxi |
Data Collection, Analysis, and Visualization | p. 1 |
Defining Bioinformatics and Structural Bioinformatics | p. 3 |
Fundamentals of Protein Structure | p. 15 |
Fundamentals of DNA and RNA Structure | p. 41 |
Computational Aspects of High-Throughput Crystallographic Macromolecular Structure Determination | p. 77 |
Macromolecular Structure Determination by NMR Spectroscopy | p. 93 |
Electron Microscopy in the Context of Structural Systems Biology | p. 143 |
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 | p. 171 |
Search and Sampling in Structural Bioinformatics | p. 207 |
Molecular Visualization | p. 237 |
Data Representation and Databases | p. 269 |
The PDB Format, mmCIF Formats, and Other Data Formats | p. 271 |
The Worldwide Protein Data Bank | p. 293 |
The Nucleic Acid Database | p. 305 |
Other Structure-Based Databases | p. 321 |
Data Integrity and Comparative Features | p. 339 |
Structural Quality Assurance | p. 341 |
The Impact of Local Accuracy in Protein and RNA Structures: Validation as an Active Tool | p. 377 |
Structure Comparison and Alignment | p. 397 |
Protein Structure Evolution and the Scop Database | p. 419 |
The Cath Domain Structure Database | p. 433 |
Structural and Functional Assignment | p. 457 |
Secondary Structure Assignment | p. 459 |
Identifying Structural Domains in Proteins | p. 485 |
Inferring Protein Function from Structure | p. 515 |
Structural Annotation of Genomes | p. 539 |
Evolution Studied Using Protein Structure | p. 559 |
Macromolecular Interactions | p. 573 |
Electrostatic Interactions | p. 575 |
Prediction of Protein-Nucleic Acid Interactions | p. 593 |
Prediction of Protein-Protein Interactions from Evolutionary Information | p. 615 |
Docking Methods, Ligand Design, and Validating Data Sets in the Structural Genomics Era | p. 633 |
Structure Prediction | p. 663 |
Casp and Other Community-Wide Assessments to Advance the Field of Structure Prediction | p. 665 |
Prediction of Protein Structure in 1D: Secondary Structure, Membrane Regions, and Solvent Accessibility | p. 679 |
Homology Modeling | p. 715 |
Fold Recognition Methods | p. 733 |
De Novo Protein Structure Prediction: Methods and Application | p. 755 |
RNA Structural Bioinformatics | p. 791 |
Therapeutic Discovery | p. 807 |
Structural Bioinformatics in Drug Discovery | p. 809 |
B-Cell Epitope Prediction | p. 847 |
Future Challenges | p. 879 |
Methods to Classify and Predict the Structure of Membrane Proteins | p. 881 |
Protein Motion: Simulation | p. 907 |
The Significance and Impacts of Protein Disorder and Conformational Variants | p. 937 |
Protein Designability and Engineering | p. 961 |
Structural Genomics of Protein Superfamilies | p. 983 |
Index | p. 1019 |
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