Includes bibliographical references and index.

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 ... [et al.] -- 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 ... [et al.] -- 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.