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3296535 Aerni, Sarah; Sirota, Marina:
A Bioinformatics Guide for Molecular Biologists
  Preis:   € 69,50

Einband: Hardcover
Auflage: 1.Auflage
Verlag: Cold Spring Harbor Laboratory Press New York
Erscheinungsdatum: 2014
Seiten: 328 pp
Abbildungen: Illus ( 64 4C.26 B&W ) index

ISBN-10: 1-936113-22-8   
ISBN-13: 9781936113224

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Weitere Fachbücher aus dem Fachgebiet:
Bioinformatik | Genetik | Molekularbiologie | 
Informatics can vastly assist progress in research and development in cell and molecular biology and biomedicine. However, many investigators are either unaware of the ways in which informatics can improve their research or find it inaccessible due to a feeling of “informatics anxiety.” This sense of apprehension results from improper communication of the principles behind these approaches and of the value of the many tools available. In fact, many researchers are inherently distrustful of these tools. A more complete understanding of bioinformatics offered in A Bioinformatics Guide for Molecular Biologists will allow the reader to become comfortable with these techniques, encouraging their use—thus helping to make sense of the vast accumulation of data. To make these concepts more accessible, the editors approach the field of bioinformatics from the viewpoint of a molecular biologist, (1) arming the biologist with a basic understanding of the fundamental concepts in the field, (2) presenting approaches for using the tools from the standpoint of the data for which they are created, and (3) showing how the field of informatics is quickly adapting to the advancements in biology and biomedical technologies. All concepts are paired with recommendations for the appropriate programming environment and tools best suited to solve the particular problem at hand. It is a must-read for those interested in learning informatics techniques required for successful research and development in the laboratory.
Preface Section 1: Introduction and Overview1 Introduction to Computational Approaches for Biology and MedicineSarah J. Aerni and Marina Sirota Section 2: Fundamental Concepts2 Introduction to Computer ScienceEugene Davydov and Olga Russakovsky3 Probability and StatisticsAlexander A. Morgan and Linda Miller4 Machine LearningMarc A. Schaub and Chuong B. Do Section 3: Techniques for Analyzing Your Data5 Image AnalysisMarina Sirota, Sarah J. Aerni, Tiffany Liu, and Guanglei Xiong6 Expression DataDavid Ruau7 A Gentle Introduction to Genome-Wide Association StudiesChuong B. Do, Marc A. Schaub, Marina Sirota, and Karen Lee8 Next-Generation Sequencing TechnologiesJesse Rodriguez and George Asimenos9 ProteomicsAmit Kaushal and Tiffany J. Chen Section 4: Augmenting Your Data10 Knowledge Base-Driven Pathway AnalysisPurvesh Khatri11 Learning Biomolecular Pathways from DataKaren Sachs and Gabriela K. Fragiadakis12 Meta-Analysis and Data Integration of Gene Expression ExperimentsChirag J. Patel and Andrew H. Beck13 Natural Language Processing: Informatics Techniques and ResourcesBethany Percha and Wei-Nchih LeeIndex

Genetics and Genome Science; Biotechnology; Laboratory Manuals/Handbooks
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