000 02215nam a22003618a 4500
001 CR9780511973888
003 UkCbUP
005 20180107143414.0
006 m|||||o||d||||||||
007 cr||||||||||||
008 101011s2011||||enk s ||1 0|eng|d
020 _a9780511973888 (ebook)
020 _z9780521517713 (hardback)
020 _z9780521734448 (paperback)
040 _aUkCbUP
_cUkCbUP
_erda
050 0 0 _aRS419.5
_b.Z43 2011
082 0 0 _a615/.19
_222
100 1 _aZhang, Xiaohua Douglas,
_eauthor.
245 1 0 _aOptimal High-Throughput Screening :
_bPractical Experimental Design and Data Analysis for Genome-Scale RNAi Research / [electronic resource]
_cXiaohua Douglas Zhang.
264 1 _aCambridge :
_bCambridge University Press,
_c2011.
300 _a1 online resource (232 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 09 Oct 2015).
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
650 0 _aRNA Interference
776 0 8 _iPrint version:
_z9780521517713
856 4 0 _uhttp://dx.doi.org/10.1017/CBO9780511973888
_zCambridge Books Online
999 _c236616
_d236616