Statistical methods in molecular biology / edited by Heejung Bang [and others].

Format
Book
Language
English
Published/​Created
New York, NY ; Dordrecht : Humana Press, [2010], ©2010.
Description
xiii, 636 pages : illustrations ; 27 cm.

Availability

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    Details

    Subject(s)
    Series
    Bibliographic references
    Includes bibliographical references and index.
    Contents
    • Part I. Basic Statistics
    • 1. Experimental statistics for biological sciences / Heejung Bang and Marie Davidian
    • 2. Nonparametric methods for molecular biology / Knut M. Wittkowski and Tingting Song
    • 3. Basics of Bayesian methods / Sujit K. Ghosh
    • 4. The Bayesian t-test and beyond / Mithat Gönen
    • -- Part II. Designs and Methods for Molecular Biology
    • 5. Sample size and power calculation for molecular biology studies / Sin-Ho Jung
    • 6. Designs for linkage analysis and association studies of complex diseases / Yuehua Cui, Gengxin Li, Shaoyu Li, and Rongling Wu
    • 7. Introduction to epigenomics and epigenome-wide analysis / Melissa J. Fazzari and John M. Greally
    • 8. Exploration, visualization, and preprocessing of high-dimensional data / Zhijin Wu and Zhiqiang Wu
    • -- Part III . Statistical Methods for Microarray Data
    • 9. Introduction to the statistical analysis of two-color microarray data / Martina Bremer, Edward Himelblau, and Andreas Madlung
    • 10. Building networks with microarray data / Bradley M. Broom, Waree Rinsurongkawong, Lajos Pusztai, and Kim-Anh Do
    • -- Part IV. Advanced or Specialized Methods for Molecular Biology
    • 11. Support vector machines for classification: a statistical portrait / Yoonkyung Lee
    • 12. An Overview of clustering applied to molecular biology / Rebecca Nugent and Marina Meila
    • 13. Hidden Markov model and its applications in motif findings / Jing Wu and Jun Xie
    • 14. Dimension reduction for high-dimensional data / Lexin Li
    • 15. Introduction to the development and validation of predictive biomarker
    • models from high-throughput data sets / Xutao Deng and Fabien Campagne
    • 16. Multi-gene expression-based statistical approaches to predicting
    • patients' clinical outcomes and responses / Feng Cheng, Sang-Hoon Cho, and Jae K. Lee
    • 17. Two-stage testing strategies for genome-wide association studies
    • in family-based designs / Amy Murphy, Scott T. Weiss, and Christoph Lange
    • 18. Statistical methods for proteomics / Klaus Jung
    • -- Part V. Meta-Analysis for High-Dimensional Data
    • 19. Statistical methods for integrating multiple types of high-throughput data / Yang Xie and Chul Ahn
    • 20. A Bayesian hierarchical model for high-dimensional meta-analysis / Fei Liu
    • 21. Methods for combining multiple genome-wide linkage studies / Trecia A. Kippola and Stephanie A. Santorico
    • -- Part VI. Other Practical Information
    • 22. Improved reporting of statistical design and analysis: guidelines, education, and editorial policies / Madhu Mazumdar, Samprit Banerjee, and Heather L. Van Epps
    • 23. Stata companion / Jennifer Sousa Brennan
    ISBN
    • 9781607615781 (hbk.)
    • 1607615789 (hbk.)
    OCLC
    462919274
    RCP
    C - S
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