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OPTIMAL HIGH THROUGHPUT SCREENING PRACTICAL EXPERIMENTAL DESIGN AND DATA ANALYSIS FOR GENOME SCALE RNAI RESEARCH (HB 2011)

OPTIMAL HIGH THROUGHPUT SCREENING PRACTICAL EXPERIMENTAL DESIGN AND DATA ANALYSIS FOR GENOME SCALE RNAI RESEARCH (HB 2011)

OPTIMAL HIGH THROUGHPUT SCREENING PRACTICAL EXPERIMENTAL DESIGN AND DATA
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OPTIMAL HIGH THROUGHPUT SCREENING PRACTICAL EXPERIMENTAL DESIGN AND DATA ANALYSIS FOR GENOME SCALE RNAI RESEARCH (HB 2011) Hardback - 2011 - 1st Edition

by ZHANG X.D

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USA Edition . New. Brand New! Fast Delivery US Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Details

  • Title OPTIMAL HIGH THROUGHPUT SCREENING PRACTICAL EXPERIMENTAL DESIGN AND DATA ANALYSIS FOR GENOME SCALE RNAI RESEARCH (HB 2011)
  • Author ZHANG X.D
  • Binding Hardback
  • Edition number 1st
  • Edition USA Edition
  • Condition New
  • Pages 232
  • Volumes 1
  • Language ENG
  • Publisher Cambridge University Press
  • Publication date 2011-02
  • Illustrated Yes
  • Bookseller's Inventory # CvS 9780521517713
  • ISBN 9780521517713 / 0521517710
  • Weight 1.34 lbs (0.61 kg)
  • Dimensions 10.24 x 7.17 x 0.67 in (26.01 x 18.21 x 1.70 cm)
  • Category Medical / Nursing
  • Library of Congress subjects Research Design, Experimental design
  • Library of Congress Catalogue Number 2010051114
  • Dewey Decimal Code 615.19
  • Quantity available 1

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Reader reviews for OPTIMAL HIGH THROUGHPUT SCREENING PRACTICAL EXPERIMENTAL DESIGN AND DATA ANALYSIS FOR GENOME SCALE RNAI RESEARCH (HB 2011)

From the publisher

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.
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