Data mining techniques for the life sciences / edited by Oliviero Carugo, Frank Eisenhaber. — New York : Humana Press, c2010. – (58.17/M592/v.609)

Contents

    Contents
    
    Contributors
    SECTION I: DATABASES
    1. Nucleic Acid Sequence and Structure Databases
    2. Genomic Databases and Resources at the National Center for Biotechnology information
    3. Protein Sequence Databases
    4. Protein Structure Databases
    5. Protein Domain Architectures
    6. Thermodynamic Database for Proteins: Features and Applications
    7. Enzyme Databases
    8. Biomolecular Pathway Databases
    9. Databases of Protein-Protein Interactions aim Complexes
    SECTION II: DATA MINING TECHNIQUES
    10. Proximity Measures for cluster Analysis
    11. Clustering Criteria and Algorithms
    12. Neural Networks
    13. A User's Guide to Support Vector Machines
    14. Hidden Markov Models in Biology
    SECTION III: DATABASE ANNOTATIONS AND PREDICTIONS
    15. Integrated Tools for Biomolecular Sequence-Based Function Prediction as Exemplified by the ANNOTATOR Software Environment
    16. Computational Methods for Ab Initio and Comparative Gene Finding
    17. Sequence and Structure Analysis of Noncoding RNAs
    18. Conformational Disorder
    19. Protein Secondary Structure Prediction
    20. Analysis and Prediction of Protein Quaternary Structure
    21. Prediction of Posttranslational Modification of Proteins from Their Amino Acid Sequence 365
    22. Protein Crystallizability
    Subject Index