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Statistical methods in molecular biology

Author: Heejung Bang
Publisher: New York : Humana Press, ©2010.
Series: Springer protocols (Series); Methods in molecular biology (Clifton, N.J.), v. 620.
Edition/Format:   Print book : EnglishView all editions and formats
Database:WorldCat
Summary:

This progressive book presents the basic principles of proper statistical analyses. It progresses to more advanced statistical methods in response to rapidly developing technologies and methodologies  Read more...

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Genre/Form: Laboratory Manuals
Aufsatzsammlung
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].

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"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. Read more...

 
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