LEADER 02463nam 2200577 a 450 001 9911020015903321 005 20250204110758.0 010 $a9783527665471 010 $a3527665471 010 $a9781299158511 010 $a129915851X 010 $a9783527665440 010 $a3527665447 010 $a9783527665457 010 $a3527665455 035 $a(OCoLC)881385141 035 $a(MiFhGG)GVRL8FLF 035 $a(CKB)2670000000328191 035 $a(MiAaPQ)EBC1120854 035 $a(MiFhGG)9783527665457 035 $a(Perlego)1002731 035 $a(EXLCZ)992670000000328191 100 $a20130225d2013 uy 0 101 0 $aeng 135 $aurun|---uuuua 181 $ctxt 182 $cc 183 $acr 200 00$aStatistical diagnostics for cancer $eanalyzing high-dimensional data /$fedited by Frank Emmert-Streib and Matthias Dehmer 210 $aWeinheim $cWiley-Blackwell$d2013 215 $a1 online resource (xx, 292 pages) $cillustrations (some color) 225 0$aQuantitative and network biology ;$vv. 3 300 $aDescription based upon print version of record. 311 08$a9783527332625 311 08$a3527332626 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 ;$vv. 3. 606 $aCancer$xDiagnosis 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 $a9911020015903321 996 $aStatistical diagnostics for cancer$94416118 997 $aUNINA