LEADER 04070nam 22007335 450 001 9910298635503321 005 20250609111713.0 010 $a3-319-17281-6 024 7 $a10.1007/978-3-319-17281-1 035 $a(CKB)3710000000394742 035 $a(EBL)2095477 035 $a(SSID)ssj0001500953 035 $a(PQKBManifestationID)11852694 035 $a(PQKBTitleCode)TC0001500953 035 $a(PQKBWorkID)11521242 035 $a(PQKB)11748361 035 $a(DE-He213)978-3-319-17281-1 035 $a(MiAaPQ)EBC2095477 035 $z(PPN)258863048 035 $a(PPN)185487033 035 $a(MiAaPQ)EBC3109709 035 $a(EXLCZ)993710000000394742 100 $a20150411d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 12$aA Primer on QSAR/QSPR Modeling $eFundamental Concepts /$fby Kunal Roy, Supratik Kar, Rudra Narayan Das 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (129 p.) 225 1 $aSpringerBriefs in Molecular Science,$x2191-5407 300 $aDescription based upon print version of record. 311 08$a3-319-17280-8 320 $aIncludes bibliographical references at the end of each chapters. 327 $aQSAR/QSPR Modeling: Introduction -- Statistical methods in QSAR/QSPR -- QSAR/QSPR Methods -- Newer directions in QSAR/QSPR. 330 $aThis brief goes back to basics and describes the Quantitative structure-activity/property relationships (QSARs/QSPRs) that represent predictive models derived from the application of statistical tools correlating biological activity (including therapeutic and toxic) and properties of chemicals (drugs/toxicants/environmental pollutants) with descriptors representative of molecular structure and/or properties. It explains how the sub-discipline of Cheminformatics is used for many applications such as risk assessment, toxicity prediction, property prediction and regulatory decisions apart from drug discovery and lead optimization. The authors also present, in basic terms, how QSARs and related chemometric tools are extensively involved in medicinal chemistry, environmental chemistry and agricultural chemistry for ranking of potential compounds and prioritizing experiments. At present, there is no standard or introductory publication available that introduces this important topic to students of chemistry and pharmacy. With this in mind, the authors have carefully compiled this brief in order to provide a thorough and painless introduction to the fundamental concepts of QSAR/QSPR modelling. The brief is aimed at novice readers. 410 0$aSpringerBriefs in Molecular Science,$x2191-5407 606 $aChemistry, Physical and theoretical 606 $aChemometrics 606 $aBioinformatics 606 $aComputational biology 606 $aTheoretical and Computational Chemistry$3https://scigraph.springernature.com/ontologies/product-market-codes/C25007 606 $aMath. Applications in Chemistry$3https://scigraph.springernature.com/ontologies/product-market-codes/C17004 606 $aComputer Appl. in Life Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/L17004 615 0$aChemistry, Physical and theoretical. 615 0$aChemometrics. 615 0$aBioinformatics. 615 0$aComputational biology. 615 14$aTheoretical and Computational Chemistry. 615 24$aMath. Applications in Chemistry. 615 24$aComputer Appl. in Life Sciences. 676 $a543.0072 700 $aRoy$b Kunal$4aut$4http://id.loc.gov/vocabulary/relators/aut$0929716 702 $aKar$b Supratik$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aDas$b Rudra Narayan$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910298635503321 996 $aA Primer on QSAR$92089754 997 $aUNINA