LEADER 00684nam0 2200253 450 001 9910339459403321 005 20190930093326.0 010 $a978-88-921-1513-2 100 $a20190930d2019----km y0itay50 ba 101 0 $aita 102 $aIT 105 $ay 001yy 200 1 $aEnti religiosi/ecclesiastici e riforma del terzo settore$fMario Ferrante 205 $a2. ed. 210 $aTorino$cGiappichelli$d2019 215 $aIX, 189 p.$d25 cm 700 1$aFerrante,$bMario$036506 801 0$aIT$bUNINA$gREICAT$2UNIMARC 901 $aBK 912 $a9910339459403321 952 $aII MM 48$bE122$fDCEC 959 $aDCEC 996 $aEnti religiosi$91562108 997 $aUNINA LEADER 02769nam 2200673 450 001 9910139003203321 005 20200520144314.0 010 $a3-527-65600-6 010 $a3-527-65598-0 010 $a3-527-65601-4 035 $a(CKB)2550000001123453 035 $a(EBL)1420233 035 $a(OCoLC)862830262 035 $a(SSID)ssj0001155640 035 $a(PQKBManifestationID)11751495 035 $a(PQKBTitleCode)TC0001155640 035 $a(PQKBWorkID)11187820 035 $a(PQKB)11392294 035 $a(MiAaPQ)EBC1420233 035 $a(Au-PeEL)EBL1420233 035 $a(CaPaEBR)ebr10768955 035 $a(CaONFJC)MIL525170 035 $a(PPN)178873616 035 $a(EXLCZ)992550000001123453 100 $a20131011h20142014 uy| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aData mining in drug discovery /$fedited by Re?my D. Hoffmann, Arnaud Gohier, and Pavel Pospisil 210 1$aWeinheim :$cWiley-VCH,$d[2014] 210 4$dİ2014 215 $a1 online resource (347 p.) 225 1 $aMethods and principles in medicinal chemistry ;$vvol. 57 300 $aDescription based upon print version of record. 311 $a3-527-32984-6 311 $a1-299-93919-8 320 $aIncludes bibliographical references and index. 327 $apart one. Data sources -- part two. Analysis and enrichment -- part three. Applications to polypharmacology -- part four. system biology approaches. 330 $a Written for drug developers rather than computer scientists, this monograph adopts a systematic approach to mining scientifi c data sources, covering all key steps in rational drug discovery, from compound screening to lead compound selection and personalized medicine. Clearly divided into four sections, the first part discusses the different data sources available, both commercial and non-commercial, while the next section looks at the role and value of data mining in drug discovery. The third part compares the most common applications and strategies for polypharmacology, where data mining 410 0$aMethods and principles in medicinal chemistry ;$vv. 57. 606 $aDrug development$xComputer simulation 606 $aData mining 606 $aDrugs$xResearch 615 0$aDrug development$xComputer simulation. 615 0$aData mining. 615 0$aDrugs$xResearch. 676 $a615.102856312 701 $aHoffmann$b Re?my D$0968298 701 $aGohier$b Arnaud$0968299 701 $aPospisil$b Pavel$0968300 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910139003203321 996 $aData mining in drug discovery$92199261 997 $aUNINA LEADER 01457nas 2200457 a 450 001 996202295503316 005 20231101153739.0 011 $a1872-9436 035 $a(OCoLC)39061794 035 $a(CKB)954925471351 035 $a(CONSER) 2001242158 035 $a(DE-599)ZDB1479003-8 035 $a(EXLCZ)99954925471351 100 $a19980505a19789999 sy a 101 0 $aeng 135 $aur|||||||| 200 10$aMicroprocessors and microsystems$b[e-journal] 210 1$aGuilford, England :$cIPC Science and Technology Press,$dc1979- 210 21$a[Oxford, UK] :$cButterworth-Heinemann Ltd. 210 31$a[Amsterdam, Netherlands] :$cElsevier B.V. 300 $aRefereed/Peer-reviewed 311 $a0141-9331 517 $aMicroprocessors & Microsystems 517 1 $aMICPRO - Embedded software design 517 1 $aEmbedded software design 531 $aMICROPROCESS MICROSYST 531 $aMICROPROCESSORS MICROSYSTEMS 531 $aMICROPROCESS MICROSY 531 $aMICROPR MIC 531 0 $aMicroprocess. microsyst. 531 0 $aMicroprocess. microsyst. 531 $aMICROPROCESS. MICROSYST 606 $aMicroprocessors$vPeriodicals 606 $aMicroprocessors$2fast$3(OCoLC)fst01020008 608 $aPeriodicals.$2fast 615 0$aMicroprocessors 615 7$aMicroprocessors. 906 $aJOURNAL 912 $a996202295503316 996 $aMicroprocessors and microsystems$9792267 997 $aUNISA