LEADER 02435oam 2200505 450 001 9910830855103321 005 20190911112726.0 010 $a3-527-66547-1 010 $a1-299-15851-X 010 $a3-527-66544-7 010 $a3-527-66545-5 035 $a(OCoLC)881385141 035 $a(MiFhGG)GVRL8FLF 035 $a(EXLCZ)992670000000328191 100 $a20130605d2013 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 210 1$aWeinheim, Germany :$cWiley-Blackwell,$d2013. 215 $a1 online resource (xx, 292 pages) $cillustrations (some color) 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 ;$vv. 3. 606 $aCancer$xDiagnosis$xStatistical methods 606 $aCancer$xGenetic aspects$xStatistical methods 615 0$aCancer$xDiagnosis$xStatistical methods. 615 0$aCancer$xGenetic aspects$xStatistical methods. 676 $a616.994075 702 $aEmmert-Streib$b Frank 702 $aDehmer$b Matthias$f1968- 801 0$bMiFhGG 801 1$bMiFhGG 906 $aBOOK 912 $a9910830855103321 996 $aStatistical diagnostics for cancer$93986468 997 $aUNINA