000			02730nam a22003618i 4500
001			CR9780511973888
003			UkCbUP
005			20200124160302.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			101011s2011||||enk o ||1 0|eng|d
020			_a9780511973888 (ebook)
020			_z9780521517713 (hardback)
020			_z9780521734448 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aRS419.5 _b.Z43 2011
082	0	0	_a615/.19 _222
100	1		_aZhang, Xiaohua Douglas, _d1966- _eauthor.
245	1	0	_aOptimal high-throughput screening : _bpractical experimental design and data analysis for genome-scale RNAi research / _cXiaohua Douglas Zhang, Merck Research Laboratories.
264		1	_aCambridge : _bCambridge University Press, _c2011.
300			_a1 online resource (xviii, 203 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
505	8		_aMachine generated contents note: 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.
520			_aThis 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.
650		0	_aHigh throughput screening (Drug development)
650		0	_aSmall interfering RNA.
650		0	_aExperimental design.
776	0	8	_iPrint version: _z9780521517713
856	4	0	_uhttps://doi.org/10.1017/CBO9780511973888
999			_c520465 _d520463