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Genre/Form: | Laboratory manuals Laboratory Manual Statistics Aufsatzsammlung Biostatistics Manuels de laboratoire Statistiques |
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Material Type: | Internet resource |
Document Type: | Book, Internet Resource |
All Authors / Contributors: |
Heejung Bang |
ISBN: | 9781607615781 1607615789 9781607615804 1607615800 |
OCLC Number: | 462919274 |
Description: | xiii, 636 pages : illustrations |
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 [and others] -- 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 [and others] -- 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. |
Series Title: | Springer protocols (Series); Methods in molecular biology (Clifton, N.J.), v. 620. |
Responsibility: | edited by Heejung Bang [and others]. |
Abstract:
Reviews
Publisher Synopsis
"Here is a comprehensive book that systematically covers both basic and advanced statistical topics in molecular biology, including parametric and nonparametric, and frequentist and Bayesian methods. I am highly impressed by the breadth and depth of the applications. I strongly recommend this book for both statisticians and biologists who need to communicate with each other in this exciting field of research." (Robert C. Elston, PhD., Director, Division of Genetic and Molecular Epidemiology, Case Western Reserve University)"An extraordinary exposition of the central topics of modern molecular biology, presented by practicing experts who weave together rigorous theory with practical techniques and illustrative examples." (George C. Newman, MD, PhD, Chairman, Neurosensory Sciences, Albert Einstein Medical Center)"I cannot think of anything we need now in translation research field more than more efficient cross talk between molecular biology and statistics. This book is just on target. It fills the gap." (Iman Osman, MB, BCh, MD, Director, Interdisciplinary Melanoma Cooperative Program, New York University Langone Medical Center) Read more...

