Humana Bioinformatics: Volume II: Structure, Function, and Applications: 1526 (Methods in Molecular Biology, 1526)

Preface... Table of Contents... Contributing Authors...Part I Structure, Function, Pathways and Networks1. 3D Computational Modeling of Proteins Using Sparse Paramagnetic NMR DataKala Bharath Pilla, Gottfried Otting, and Thomas Huber2. Inferring Function from HomologyTom C. Giles and Richard D. Emes3. Inferring Functional Relationships from Conservation of Gene OrderGabriel Moreno-Hagelsieb4. Structural and Functional Annotation of Long Non-Coding RNAsMartin A. Smith and John S. Mattick5. Construction of Functional Gene Networks Using Phylogenetic ProfilesJunha Shin and Insuk Lee6. Inferring Genome-Wide Interaction NetworksGökmen Altay and Onur Mendi7. Integrating Heterogeneous Datasets for Cancer Module IdentificationA.K.M. Azad8. Metabolic Pathway MiningJan M. Czarnecki and Adrian J. ShepherdPart II Applications9. Analysis of Genome-Wide Association DataAllan F. McRae10. Adjusting for Familial Relatedness in the Analysis of GWAS DataRussell Thomson and Rebekah McWhirter11. Analysis of Quantitative Trait LociDavid L. Duffy12. High-Dimensional Profiling for Computational DiagnosisClaudio Lottaz, Wolfram Gronwald, Rainer Spang, and Julia C. Engelmann 13. Molecular Similarity Concepts for Informatics ApplicationsJürgen Bajorath14. Compound Data Mining for Drug DiscoveryJürgen Bajorath15. Studying Antibody Repertoires with Next-Generation SequencingWilliam D. Lees and Adrian J. Shepherd16. Using the QAPgrid Visualization Approach for Biomarker Identification of Cell-Specific Transcriptomic SignaturesChloe Warren, Mario Inostroza-Ponta, and Pablo Moscato17. Computer-Aided Breast Cancer Diagnosis with Optimal Feature Sets: Reduction Rules and Optimization TechniquesLuke Mathieson, Alexandre Mendes, John Marsden, Jeffrey Pond, and Pablo MoscatoPart III Computational Methods18. Inference Method for Developing Mathematical Models of Cell Signaling Pathways Using Proteomic DatasetsTianhai Tian and Jiangning Song19. ClusteringGeoffrey J. McLachlan, Richard W. Bean and Shu-Kay Ng20. Parameterized Algorithmics for Finding Exact Solutions of NP-Hard Biological ProblemsFalk Hüffner, Christian Komusiewicz, Rolf Niedermeier, and Sebastian Wernicke21. Information Visualization for Biological DataTobias Czauderna and Falk Schreiber Review “The book is as an excellent starting point for a wide audience including undergraduates, graduates and established researchers alike. The amount of detail presented for each methodological approach, coupled with extensive examples, facilitate not only the understanding of the topic but also the bridging between the various tasks associated with the mining of big (high throughput) biological datasets.” (Irina Ioana Mohorianu, zbMATH, Vol. 1384.92002, 2018) From the Back Cover This second edition provides updated and expanded chapters covering a broad sampling of useful and current methods in the rapidly developing and expanding field of bioinformatics. Bioinformatics, Volume II: Structure, Function, and Applications, Second Edition is comprised of three sections: Structure, Function, Pathways and Networks; Applications; and Computational Methods. The first section examines methodologies for understanding biological molecules as systems of interacting elements. The Applications section covers numerous applications of bioinformatics, focusing on analysis of genome-wide association data, computational diagnostic, and drug discovery. The final section describes four broadly applicable computational methods that are important to this field. These are: modeling and inference, clustering, parameterized algorithmics, and visualization. As a volume in the highly successful Methods in Molecular Biology series, chapters feature the kind of detail and expert implementation advice to ensure positive results.Comprehensive and practical, Bioinformatics, Volume II: Structure, Function, and Applications is an essential resource for graduate students, early career researchers, a