01735nam 2200445z- 450 9910346957503321202102121000076187(CKB)4920000000100947(oapen)https://directory.doabooks.org/handle/20.500.12854/57070(oapen)doab57070(EXLCZ)99492000000010094720202102d2018 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierProcess Simulation of Technical Precipitation Processes - The Influence of MixingKIT Scientific Publishing20181 online resource (XXIII, 209 p. p.)3-7315-0735-8 This work develops and shows up methods to tackle multi-scale challenges in particle formation during precipitation crystallization. Firstly, molecular, micro- and meso-scale interactions in confined impinging jet mixers are investigated and simulatively predicted. Secondly, to build up on developed methods, macroscale as present for instance in stirred tank reactors is added to the considerations.Biotechnologybicssccomputational fluid dynamicsFällungFluiddynamikmixingpopulation balancePopulationsbilanzprecipitationsimulationSimulationVermischungBiotechnologyMetzger Lukasauth1287620BOOK9910346957503321Process Simulation of Technical Precipitation Processes - The Influence of Mixing3020221UNINA03999nam 22007934a 450 991097366190332120251116214758.00-262-25706-81-282-09679-697866120967921-4237-7254-7(CKB)1000000000461545(EBL)3338535(SSID)ssj0000254896(PQKBManifestationID)11191653(PQKBTitleCode)TC0000254896(PQKBWorkID)10209040(PQKB)10290000(StDuBDS)EDZ0000130826(CaBNVSL)mat06267344(IDAMS)0b000064818b4332(IEEE)6267344(OCoLC)68816342(OCoLC)182530572(OCoLC)473746717(OCoLC)648224453(OCoLC)655188713(OCoLC)704103076(OCoLC)888573911(OCoLC)961526465(OCoLC)962598445(OCoLC)988420642(OCoLC)992036296(OCoLC)1037506181(OCoLC)1037911808(OCoLC)1038673673(OCoLC)1083558586(OCoLC-P)68816342(MaCbMITP)6604(Au-PeEL)EBL3338535(CaPaEBR)ebr10173591(CaONFJC)MIL209679(OCoLC)815776335(MiAaPQ)EBC3338535(PPN)261608673(EXLCZ)99100000000046154520051017d2006 uy 0engur|n|---|||||txtccrSystem modeling in cell biology from concepts to nuts and bolts /edited by Zoltan Szallasi, Jorg Stelling, Vipul Periwal1st ed.Cambridge, Mass. MIT Pressc20061 online resource (465 p.)"A Bradford book."0-262-19548-8 Includes bibliographical references (p. [385]-433) and index.Contents; Preface; I GENERAL CONCEPTS; 1 The Role of Modeling in Systems Biology; 2 Complexity and Robustness of Cellular Systems; 3 On Modules and Modularity; II MODELING APPROACHES; 4 Bayesian Inference of Biological Systems: The Logic of Biology; 5 Stoichiometric and Constraint-based Modeling; 6 Modeling Molecular Interaction Networks with Nonlinear Ordinary Differential Equations; 7 Qualitative Approaches to the Analysis of Genetic Regulatory Networks; 8 Stochastic Modeling of Intracellular Kinetics; 9 Kinetics in Spatially Extended Systems; III MODELS AND REALITY10 Biological Data Acquisition for System Level Modeling-An Exercise in the Art of Compromise11 Methods to Identify Cellular Architecture and Dynamics from Experimental Data; 12 Using Control Theory to Study Biology*; 13 Synthetic Gene Regulatory Systems; 14 Multilevel Modeling in Systems Biology: From Cells to Whole Organs; IV COMPUTATIONAL MODELING; 15 Computational Constraints on Modeling in Systems Biology; 16 Numerical Simulation for Biochemical Kinetics; 17 Software Infrastructure for Effective Communication and Reuse of Computational Models; A Software Tools for Biological ModelingReferencesContributors; IndexThis is an introduction and overview of system modelling in biology that is accessible to researchers from different fields including biology, computer science, mathematics, statistics physics, and biochemistry.System modeling in cellular biologyCytologyData processingCytologyMathematical modelsCytologyComputer simulationBiological systemsCytologyData processing.CytologyMathematical models.CytologyComputer simulation.Biological systems.571.601/1Szallasi Zoltan1892452Stelling Jörg1892453Periwal Vipul1892454MiAaPQMiAaPQMiAaPQBOOK9910973661903321System modeling in cell biology4538533UNINA