LEADER 01274nam--2200433---450- 001 990000531450203316 005 20050927160756.0 010 $a88-16-43310-8 035 $a0053145 035 $aUSA010053145 035 $a(ALEPH)000053145USA01 035 $a0053145 100 $a20010629d1998----km-y0itay0103----ba 101 $aita 102 $aIT 105 $a||||||||001yy 200 1 $aMeister Eckhart e la mistica renana$fAlain De Libera 210 $aMilano$cISTeM$cJaca book$d1998 215 $a123 p.$d21 cm 225 2 $aEreditą medievale$v10 300 $aTraduzione di Aldo Granata 410 $12001$aEreditą medievale$v10 606 0 $aEckhart 606 0 $aTauler, Johann 606 0 $aSuso Heinrich 676 $a230.092 700 1$aLIBERA,$bAlain : de$0473041 801 0$aIT$bsalbc$gISBD 912 $a990000531450203316 951 $aII.2. 3679 (XI A 41)$b140852 LM$cXI A 959 $aBK 969 $aUMA 979 $aPATTY$b90$c20010629$lUSA01$h0932 979 $aPATTY$b90$c20010629$lUSA01$h0937 979 $c20020403$lUSA01$h1702 979 $aPATRY$b90$c20040406$lUSA01$h1637 979 $aCOPAT4$b90$c20050927$lUSA01$h1607 996 $aMeister Eckhart e la mistica renana$9886256 997 $aUNISA LEADER 03030nam 22006135 450 001 9910806198703321 005 20250510004749.0 010 $a3-031-52057-2 024 7 $a10.1007/978-3-031-52057-0 035 $a(CKB)30097997700041 035 $a(MiAaPQ)EBC31090050 035 $a(Au-PeEL)EBL31090050 035 $a(DE-He213)978-3-031-52057-0 035 $a(EXLCZ)9930097997700041 100 $a20240125d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aq-RASAR $eA Path to Predictive Cheminformatics /$fby Kunal Roy, Arkaprava Banerjee 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (99 pages) 225 1 $aSpringerBriefs in Molecular Science,$x2191-5415 311 08$a9783031520563 320 $aIncludes bibliographical references. 327 $aChemical Information and Molecular Similarity -- Read-across and Quantitative Structure-activity Relationships (QSAR) for Making Predictions and Data Gap-Filling -- Quantitative Read-Across (q-RA) and Quantitative Read-Across Structure-Activity Relationships (q-RASAR) ? Genesis and Model Development -- Tools, Applications, and Case Studies (q-RA and q-RASAR) -- Future Prospects. 330 $aThis brief offers an introduction to the fascinating new field of quantitative read-across structure-activity relationships (q-RASAR) as a cheminformatics modeling approach in the background of quantitative structure-activity relationships (QSAR) and read-across (RA) as data gap-filling methods. It discusses the genesis and model development of q-RASAR models demonstrating practical examples. It also showcases successful case studies on the application of q-RASAR modeling in medicinal chemistry, predictive toxicology, and materials sciences. The book also includes the tools used for q-RASAR model development for new users. It is a valuable resource for researchers and students interested in grasping the development algorithm of q-RASAR models and their application within specific research domains. 410 0$aSpringerBriefs in Molecular Science,$x2191-5415 606 $aChemistry$xData processing 606 $aQuantum theory 606 $aComputer simulation 606 $aMolecules$xModels 606 $aComputational Chemistry 606 $aQuantum Simulations 606 $aMolecular Modelling 615 0$aChemistry$xData processing. 615 0$aQuantum theory. 615 0$aComputer simulation. 615 0$aMolecules$xModels. 615 14$aComputational Chemistry. 615 24$aQuantum Simulations. 615 24$aMolecular Modelling. 676 $a542.85 700 $aRoy$b Kunal$f1971-$0929716 702 $aBanerjee$b Arkaprava 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910806198703321 996 $aQ-RASAR$93907888 997 $aUNINA