LEADER 03519nam 2200589 450 001 9910797483903321 005 20230126213039.0 010 $a3-03734-569-1 035 $a(CKB)3710000000449498 035 $a(EBL)2127894 035 $a(SSID)ssj0001578153 035 $a(PQKBManifestationID)16254006 035 $a(PQKBTitleCode)TC0001578153 035 $a(PQKBWorkID)14860942 035 $a(PQKB)10780947 035 $a(MiAaPQ)EBC2127894 035 $a(Au-PeEL)EBL2127894 035 $a(CaPaEBR)ebr11079852 035 $a(OCoLC)918622870 035 $a(EXLCZ)993710000000449498 100 $a20150729h20152015 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt 182 $cc 183 $acr 200 00$aNeighborhood technologies $emedia and mathematics of dynamic networks /$fedited by Tobias Harks and Sebastian Vehlken 210 1$aZurich, Switzerland :$cDiaphanes,$d2015. 210 4$d©2015 215 $a1 online resource (233 p.) 300 $aDescription based upon print version of record. 311 $a3-03734-523-3 327 $aCover; Table of Contents; Acknowledgements; Neighborhood Technologies: An Introduction / Sebastian Vehlken, Tobias Harks; I. NEIGHBORHOOD EPISTEMOLOGIES; Neighborhoods in Mathematical Optimization and Algorithmic Game Theory / Martin Hoefer, Tobias Harks; Ghetto Blasts: Media Histories of Neighborhood Technologies between Segregation, Cooperation, and Craziness / Sebastian Vehlken; Neighborhoods in Traffic: How Computer Science Can Change the Laws of Physics / Sa?ndor P. Fekete; II. NEIGHBORHOD ARCHITECTURES; Neighborhood Design: Buckminster Fuller's Planning Tools and the City / Christina Vagt 327 $aDigitally-Driven Design and Architecture / Henriette BierIII. NEIGHBORHOOD SOCIETIES; Economics 2.0: The Natural Step towards a Self-Regulating, Participatory Market Society / Dirk Helbing; Neighborhoods and Social Security: An Agent-based Experiment on the Emergence of Common Goods / Manfred Fu?llsack; Towards a Media History of the Credit Card / Sebastian Giessmann; IV. NEIGHBORHOOD ACTIVITIES; Neighborhood Sounding: An Archaeology of Dynamic Media Networks 1960-1980 | 2010 / Shintaro Miyazaki 327 $aDigital Swarming and Affective Infrastructures: A New Materialist Approach to '4chan' / Carolin Wiedemann Choreographing the Swarm: Relational Bodies in Contemporary Performance / Gabriele Brandstetter; Authors 330 $aNeighborhood Technologies expands upon sociologist Thomas Schelling's well-known study of segregation in major American cities, using this classic work as the basis for a new way of researching social networks across many different disciplines. Up to now, research has focused on macro-level behaviors that, together, form rigid systems of neighborhood relations. But can neighborhoods conversely affect larger, global dynamics? What relationships can be found between micro- and macro- perspectives?To answer these and related questions, this volume introduces the concept of "neighborhood technology 606 $aSocial networks 606 $aNeighborhoods 606 $aSegregation 615 0$aSocial networks. 615 0$aNeighborhoods. 615 0$aSegregation. 676 $a302.4 702 $aHarks$b Tobias 702 $aVehlken$b Sebastian 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910797483903321 996 $aNeighborhood technologies$93799281 997 $aUNINA LEADER 05039nam 22007095 450 001 9910984692103321 005 20250228120737.0 010 $a9783031767180 010 $a3031767187 024 7 $a10.1007/978-3-031-76718-0 035 $a(CKB)37726270900041 035 $a(MiAaPQ)EBC31927423 035 $a(Au-PeEL)EBL31927423 035 $a(DE-He213)978-3-031-76718-0 035 $a(OCoLC)1505736705 035 $a(EXLCZ)9937726270900041 100 $a20250228d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputer-Aided and Machine Learning-Driven Drug Design $eFrom Theory to Applications /$fedited by Vinícius Gonçalves Maltarollo 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (761 pages) 225 1 $aComputer-Aided Drug Discovery and Design,$x2730-5465 ;$v3 311 08$a9783031767173 311 08$a3031767179 327 $aEchoes from the past, visions from the future: a journey into the Medicinal Chemistry and the Computational Drug Discovery -- Molecular Databases -- A Brief Introduction to Pharmacogenomics and Personalized Medicine in the Drug Design Context -- Machine Learning and Neural Networks Methods Applied to Drug Discovery -- Clustering of Small Molecules -- QSAR and Machine learning predictors -- Molecular docking: state-of-art scoring functions and search algorithms -- Drug Design in Motion: concepts and applications of classical Molecular Dynamics simulations -- Conformational sampling of proteins: methods for simulate protein plasticity and ensemble docking -- Free energy perturbation and free energy calculations ap-plied to drug design -- Ultra-large-scale Virtual Screening -- Experimental assays: chemical properties, biochemical and cellular assays, and in vivo evaluations -- Challenges faced in the development of computational methods for predicting pharmacokinetics behavior -- Exploring the Significance of Experimental and Computational Methods in Protein Structure Determination -- Molecular modeling strategies in drug design, development, and discovery targeting proteases -- Computational study of conformational changes in nuclear receptors upon ligand binding -- An Overview on Computational Methods Targeting the Endocannabinoid System -- Kinase Inhibitors and Computer-aided Drug Design Methods -- Prediction of Drug Metabolism with In Silico Models: A Case Study of Doping Detection. 330 $aThe computer-aided drug design research field comprises several different knowledge areas, and often, researchers are only familiar or experienced with a small fraction of them. Indeed, pharmaceutical industries and large academic groups rely on a broad range of professionals, including chemists, biologists, pharmacists, and computer scientists. In this sense, it is difficult to be an expert in every single CADD approach. Furthermore, there are well-established methods that are constantly revisited, and novel approaches are introduced, such as machine-learning based scoring functions for molecular docking. This book provides an organized update of the most commonly employed CADD techniques, as well as successful examples of actual applications to develop bioactive compounds/drug candidates. Also includes is a section of case studies that cover certain pharmacological/target classes, focusing on the applications of the previously described methods. This part will especially appeal to professionals who are not as interested in the theoretical aspects of CADD. This is an ideal book for students, researchers, and industry professionals in the fields of pharmacy, chemistry, biology, bioinformatics, computer sciences, and medicine who are seeking a go-to reference on drug design and medicinal chemistry. 410 0$aComputer-Aided Drug Discovery and Design,$x2730-5465 ;$v3 606 $aDrug delivery systems 606 $aMachine learning 606 $aDrugs$xDesign 606 $aArtificial intelligence 606 $aComputer simulation 606 $aDrug Delivery 606 $aMachine Learning 606 $aStructure-Based Drug Design 606 $aArtificial Intelligence 606 $aComputer Modelling 615 0$aDrug delivery systems. 615 0$aMachine learning. 615 0$aDrugs$xDesign. 615 0$aArtificial intelligence. 615 0$aComputer simulation. 615 14$aDrug Delivery. 615 24$aMachine Learning. 615 24$aStructure-Based Drug Design. 615 24$aArtificial Intelligence. 615 24$aComputer Modelling. 676 $a615.6 700 $aMaltarollo$b Vinícius Gonçalves$01790116 701 $aMaltarollo$01790117 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910984692103321 996 $aComputer-Aided and Machine Learning-Driven Drug Design$94326220 997 $aUNINA