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100   $a20130225d2013      uy             0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 00$aStatistical diagnostics for cancer$b[electronic resource] $eanalyzing high-dimensional data /$fedited by Frank Emmert-Streib and Matthias Dehmer
210   $aWeinheim $cWiley-Blackwell$d2013
215   $a1 online resource (314 p.)
225 1 $aQuantitative and Network Biology       (VCH)
225  0$aQuantitative and network biology ;$vv. 3
300   $aDescription based upon print version of record.
311   $a3-527-33262-6 
320   $aIncludes bibliographical references and index.
327   $apt. 1. General overview -- pt. 2. Bayesian methods -- pt. 3. Network-based approaches -- pt. 4. Phenotype influence of DNA copy number aberrations.
330   $aThis ready reference discusses different methods for statistically analyzing and validating data created with high-throughput methods. As opposed to other titles, this book focusses on systems approaches, meaning that no single gene or protein forms the basis of the analysis but rather a more or less complex biological network. From a methodological point of view, the well balanced contributions describe a variety of modern supervised and unsupervised statistical methods applied to various large-scale datasets from genomics and genetics experiments. Furthermore, since the availability of suffi
410  0$aQuantitative and Network Biology       (VCH)
606   $aCancer$xDiagnosis
608   $aElectronic books.
615  0$aCancer$xDiagnosis.
676   $a616.994075
701   $aEmmert-Streib$b Frank$0867728
701   $aDehmer$b Matthias$f1968-$0860612
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910141464803321
996   $aStatistical diagnostics for cancer$92074315
997   $aUNINA