Bioinformatics
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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…mehr

Produktbeschreibung
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, and others who are in the process of integrating new bioinformatics methods into their research.
  • Produktdetails
  • Methods in Molecular Biology Vol.1526
  • Verlag: Springer, Berlin; Springer New York; Humana Press
  • Artikelnr. des Verlages: 978-1-4939-6611-0
  • 2nd ed.
  • Erscheinungstermin: 29. November 2016
  • Englisch
  • Abmessung: 260mm x 183mm x 29mm
  • Gewicht: 1008g
  • ISBN-13: 9781493966110
  • ISBN-10: 1493966111
  • Artikelnr.: 45471246
Inhaltsangabe
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
Gökmen 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
Jürgen Bajorath

14. Compound Data Mining for Drug Discovery
Jürgen 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 JiangningSong

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 Hüffner, Christian Komusiewicz, Rolf Niedermeier, and Sebastian Wernicke

21. Information Visualization for Biological Data
Tobias Czauderna and Falk Schreiber
Rezensionen
"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)