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Bioinformatics methods in clinical research 1st Edition by Ewa Gubb, Rune Matthiesen ISBN 9781603271936 1603271937

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Bioinformatics methods in clinical research 1st Edition Ewa Gubb Digital Instant Download

Author(s): Ewa Gubb, Rune Matthiesen (auth.), Rune Matthiesen (eds.)
ISBN(s): 9781603271943, 1603271945
Edition: 1
File Details: PDF, 11.38 MB
Year: 2010
Language: english
SKU: EB-1301344 Category: Tags: , ,

Bioinformatics methods in clinical research 1st Edition by Ewa Gubb, Rune Matthiesen – Ebook PDF Instant Download/Delivery: 9781603271936,  1603271937
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Product details: 

ISBN 10:  1603271937

ISBN 13: 9781603271936

Author: Ewa Gubb, Rune Matthiesen

Covering the latest developments in clinical omics, this volume details the algorithms currently used in publicly available software tools. It looks at statistics, algorithms, automated data retrieval, and experimental consideration in the various omics areas., Integrated bioinformatics solutions have become increasingly valuable in past years, as technological advances have allowed researchers to consider the potential of omics for clinical diagnosis, prognosis, and therapeutic purposes, and as the costs of such techniques have begun to lessen. In Bioinformatics Methods in Clinical Research, experts examine the latest developments impacting clinical omics, and describe in great detail the algorithms that are currently used in publicly available software tools. Chapters discuss statistics, algorithms, automated methods of data retrieval, and experimental consideration in genomics, transcriptomics, proteomics, and metabolomics. Composed in the highly successful Methods in Molecular Biology(tm) series format, each chapter contains a brief introduction, provides practical examples illustrating methods, results, and conclusions from data mining strategies wherever possible, and includes a Notes section which shares tips on troubleshooting and avoiding known pitfalls. Informative and ground-breaking, Bioinformatics Methods in Clinical Research establishes a much-needed bridge between theory and practice, making it an indispensable resource for bioinformatics researchers., Integrated bioinformatics solutions have become increasingly valuable in past years, as technological advances have allowed researchers to consider the potential of omics for clinical diagnosis, prognosis, and therapeutic purposes, and as the costs of such techniques have begun to lessen. In Bioinformatics Methods in Clinical Research, experts examine the latest developments impacting clinical omics, and describe in great detail the algorithms that are currently used in publicly available software tools. Chapters discuss statistics, algorithms, automated methods of data retrieval, and experimental consideration in genomics, transcriptomics, proteomics, and metabolomics. Composed in the highly successful Methods in Molecular Biology(TM) series format, each chapter contains a brief introduction, provides practical examples illustrating methods, results, and conclusions from data mining strategies wherever possible, and includes a Notes section which shares tips on troubleshooting and avoiding known pitfalls. Informative and ground-breaking, Bioinformatics Methods in Clinical Research establishes a much-needed bridge between theory and practice, making it an indispensable resource for bioinformatics researchers.
 

Table of contents: 

  1. Omics

  2. Machine Learning: An Indispensable Tool in Bioinformatics

  3. SNP-PHAGE: High-Throughput SNP Discovery Pipeline

  4. R Classes and Methods for SNP Array Data

  5. Overview on Techniques in Cluster Analysis

  6. Nonalcoholic Steatohepatitis, Animal Models, and Biomarkers: What Is New?

  7. Biomarkers in Breast Cancer

  8. Genome-Wide Proximal Promoter Analysis and Interpretation

  9. Proteomics Facing the Combinatorial Problem

  10. Methods and Algorithms for Relative Quantitative Proteomics by Mass Spectrometry

  11. Feature Selection and Machine Learning with Mass Spectrometry Data

  12. Computational Methods for Analysis of Two-Dimensional Gels

  13. Mass Spectrometry in Epigenetic Research

  14. Computational Approaches to Metabolomics

  15. Algorithms and Methods for Correlating Experimental Results with Annotation Databases

  16. Analysis of Biological Processes and Diseases Using Text Mining Approaches

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Tags: Ewa Gubb, Rune Matthiesen, Bioinformatics methods, clinical research