LEADER 03667nam 22006735 450 001 9911049094803321 005 20251231120419.0 010 $a3-031-81728-1 024 7 $a10.1007/978-3-031-81728-1 035 $a(CKB)44760970700041 035 $a(MiAaPQ)EBC32469245 035 $a(Au-PeEL)EBL32469245 035 $a(DE-He213)978-3-031-81728-1 035 $a(EXLCZ)9944760970700041 100 $a20251231d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSpringer Handbook of Chem- and Bioinformatics /$fedited by Jerzy Leszczynski 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (2767 pages) 225 1 $aSpringer Handbooks,$x2522-8706 311 08$a3-031-81727-3 327 $a1 Computational Biology and Biochemistry -- 2 Cheminformatics I: Ligand-Based Molecular Modeling -- 3 Cheminformatics II: Structure-Based Molecular Modeling and Drug Design -- 4 Bioinformatics -- 5 Machine Learning, Artificial intelligence, and Big Data. 330 $aThe Springer Handbook of Chem- and Bioinformatics provides an introduction as well as a detailed description of the application of various techniques used in chemo- and bioinformatics. It covers basic topics such as a discussion of computational techniques used in the predictions of structures, properties, and dynamics of small compounds, macromolecules, and their complexes. Diverse applications of Quantitative structure-activity relationships (QSAR) methods are also revealed. Various chapters offer specifics of current methodologies used by research labs in the pharmaceutical industry for drug design. Modern computational approaches taking advantage of searching big data, using artificial intelligence and machine learning are discussed, while the necessity of applying such advanced novel techniques for bio- and chemo-informatics is revealed. This handbook combines nicely together discussion and assessment of both closely related fields of modern informatics. It is a welcome addition to the university libraries, research institutes, as well as to basic textbook resources of individual researchers. The target audience includes students (both graduate and advanced undergraduate), university researchers, scientists working in private and governmental laboratories as well as a large group of developers from pharmaceutical and medical institutes and related industrial research centers. 410 0$aSpringer Handbooks,$x2522-8706 606 $aChemistry$xData processing 606 $aBioinformatics 606 $aCheminformatics 606 $aMolecules$xModels 606 $aMachine learning 606 $aComputational Chemistry 606 $aComputational and Systems Biology 606 $aCheminformatics 606 $aMolecular Modelling 606 $aMachine Learning 615 0$aChemistry$xData processing. 615 0$aBioinformatics. 615 0$aCheminformatics. 615 0$aMolecules$xModels. 615 0$aMachine learning. 615 14$aComputational Chemistry. 615 24$aComputational and Systems Biology. 615 24$aCheminformatics. 615 24$aMolecular Modelling. 615 24$aMachine Learning. 676 $a542.85 700 $aLeszczyn?ski$b Jerzy$00 701 $aNatanson$b Wojciech$0678125 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911049094803321 996 $aSpringer Handbook of Chem- and Bioinformatics$94533258 997 $aUNINA