Bioinformatics: Volume II: Structure, Function, and Applications (Paperback)

Preface... Table of Contents... Contributing Authors... Part I Structure, Function, Pathways and Networks 1. 3D Computational Modeling of Proteins Using Sparse Paramagnetic NMR Data Kala Bharath Pilla, Gottfried Otting, and Thomas Huber 2. Inferring Function from Homology Tom C. Giles and Richard D. Emes 3. Inferring Functional Relationships from Conservation of Gene Order Gabriel Moreno-Hagelsieb 4. Structural and Functional Annotation of Long Non-Coding RNAs Martin A. Smith and John S. Mattick 5. Construction of Functional Gene Networks Using Phylogenetic Profiles Junha Shin and Insuk Lee 6. Inferring Genome-Wide Interaction Networks Gokmen Altay and Onur Mendi 7. Integrating Heterogeneous Datasets for Cancer Module Identification A.K.M. Azad 8. Metabolic Pathway Mining Jan M. Czarnecki and Adrian J. Shepherd Part II Applications 9. Analysis of Genome-Wide Association Data Allan F. McRae 10. Adjusting for Familial Relatedness in the Analysis of GWAS Data Russell Thomson and Rebekah McWhirter 11. Analysis of Quantitative Trait Loci David L. Duffy 12. High-Dimensional Profiling for Computational Diagnosis Claudio Lottaz, Wolfram Gronwald, Rainer Spang, and Julia C. Engelmann 13. Molecular Similarity Concepts for Informatics Applications Jurgen Bajorath 14. Compound Data Mining for Drug Discovery Jurgen Bajorath 15. Studying Antibody Repertoires with Next-Generation Sequencing William D. Lees and Adrian J. Shepherd 16. Using the QAPgrid Visualization Approach for Biomarker Identification of Cell-Specific Transcriptomic Signatures Chloe Warren, Mario Inostroza-Ponta, and Pablo Moscato 17. Computer-Aided Breast Cancer Diagnosis with Optimal Feature Sets: Reduction Rules and Optimization Techniques Luke Mathieson, Alexandre Mendes, John Marsden, Jeffrey Pond, and Pablo Moscato Part III Computational Methods 18. Inference Method for Developing Mathematical Models of Cell Signaling Pathways Using Proteomic Datasets Tianhai Tian and Jiangning Song 19. Clustering Geoffrey J. McLachlan, Richard W. Bean and Shu-Kay Ng 20. Parameterized Algorithmics for Finding Exact Solutions of NP-Hard Biological Problems Falk Huffner, Christian Komusiewicz, Rolf Niedermeier, and Sebastian Wernicke 21. Information Visualization for Biological Data Tobias Czauderna and Falk Schreiber