Optimal High-Throughput Screening
Practical Experimental Design and Data Analysis for Genome-Scale RNAi Research
$36.99 (P)
- Author: Xiaohua Douglas Zhang, Merck Research Laboratories, Pennsylvania
- Date Published: February 2011
- availability: Available
- format: Paperback
- isbn: 9780521734448
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This concise, self-contained, and cohesive book focuses on commonly used and recently developed methods for designing and analyzing high-throughput screening (HTS) experiments from a statistically sound basis. Combining ideas from biology, computing, and statistics, the author explains experimental designs and analytic methods that are amenable to rigorous analysis and interpretation of RNAi HTS experiments. The opening chapters are carefully presented to be accessible both to biologists with training only in basic statistics and to computational scientists and statisticians with basic biological knowledge. Biologists will see how new experiment designs and rudimentary data-handling strategies for RNAi HTS experiments can improve their results, whereas analysts will learn how to apply recently developed statistical methods to interpret HTS experiments.
Read more- A concise, self-contained and cohesive book for designing, analyzing and interpreting RNAi HTS experiments
- Suitable for biologists, statisticians and bioinformaticians
- Elaborates newly developed analytic methods with a statistically sound basis
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×Product details
- Date Published: February 2011
- format: Paperback
- isbn: 9780521734448
- length: 224 pages
- dimensions: 254 x 177 x 13 mm
- weight: 0.43kg
- contains: 47 b/w illus. 23 tables
- availability: Available
Table of Contents
Part I. RNAi HTS and Data Analysis:
1. Introduction to genome-scale RNAi research
2. Experimental designs
3. Data display and normalization
4. Quality control in genome-scale RNAi screens
5. Hit selection in genome-scale RNAi screens without replicates
6. Hit selection in genome-scale RNAi screens with replicates
Part II. Methodological Development for Analyzing RNAi HTS Screens:
7. Statistical methods for group comparison
8. Statistical methods for assessing the size of siRNA effects.
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