Statistical methods in molecular biology
By: edited by Heejung Bang ... [et al.].
Series: Springer protocols; Methods in molecular biology -- 620; Springer protocols; Methods in molecular biology (Clifton, N.J.) -- v. 620.
Publisher: Humana Press
Published: 2010
Place of publication: New York
Language: eng
Number of pages: 636
ISBN-13: 9781607615781; 9781607615804
Subjects: Statistical methods; Molecular Biology; Molecular biology; Molekularbiologie; Methods; Statistics as Topic; Laboratory Manuals; Statistik
Notes: Includes bibliographical references and index.
Table of contents: title: Part I. Basic statistics; title: 1. Experimental statistics for biological sciences / Heejung Bang and Marie Davidian; title: 2. Nonparametric methods for molecular biology / Knut M. Wittkowski and Tingting Song; title: 3. Basics of Bayesian methods / Sujit K. Ghosh; title: 4. The Bayesian t-test and beyond / Mithat Gönen; title: Part II. Designs and methods for molecular biology; title: 5. Sample size and power calculation for molecular biology studies / Sin-Ho Jung; title: 6. Designs for linkage analysis and association studies of complex diseases / Yuehua Cui ... [et al.]; title: 7. Introduction to epigenomics and epigenome-wide analysis / Melissa J. Fazzari and John M. Greally; title: 8. Exploration, visualization, and preprocessing of high-dimensional data / Zhijin Wu and Zhiqiang Wu; title: Part III. Statistical methods for microarray data; title: 9. Introduction to the statistical analysis of two-color microarray data / Martina Bremer, Edward Himelblau, and Andreas Madlung; title: 10. Building networks with microarray data / Bradley M. Broom ... [et al.]; title: Part IV. Advanced or specialized methods for molecular biology; title: 11. Support vector machines for classification: a statistical portrait / Yoonkyung Lee; title: 12. An overview of clustering applied to molecular biology / Rebecca Nugent and Marina Meila; title: 13. Hidden Markov model and its applications in motif findings / Jing Wu and Jun Xie; title: 14. Dimension reduction for high-dimensional data / Lexin Li; title: 15. Introduction to the development and validation of predictive biomarker models from high-throughput data sets / Xutao Deng and Fabien Campagne; title: 16. Multi-gene expression-based statistical approaches to predicting patients' clinical outcomes and responses / Feng Cheng, Sang-Hoon Cho, and Jae K. Lee; title: 17. Two-stage testing strategies for genome-wide association studies in family-based designs / Amy Murphy, Scott T. Weiss, and Christoph Lange; title: 18. Statistical methods for proteomics / Klaus Jung; title: Part V. Meta-analysis for high-dimensional data; title: 19. Statistical methods for integrating multiple types of high-throughput data / Yang Xie and Chul Ahn; title: 20. A Bayesian hierarchical model for high-dimensional meta-analysis / Fei Liu; title: 21. Methods for combining multiple genome-wide linkage studies / Trecia A. Kippola and Stephanie A. Santorico; title: Part VI. Other practical information; title: 22. Improved reporting of statistical design and analysis: guidelines, education, and editorial policies / Madhu Mazumdar, Samprit Banerjee, and Heather L. Van Epps; title: 23. Stata companion / Jennifer Sousa Brennan.