000801101 000__ 04890cam\a2200469Ii\4500 000801101 001__ 801101 000801101 005__ 20230306143616.0 000801101 006__ m\\\\\o\\d\\\\\\\\ 000801101 007__ cr\cn\nnnunnun 000801101 008__ 171011s2017\\\\sz\a\\\\ob\\\\001\0\eng\d 000801101 019__ $$a1005506739$$a1005968552 000801101 020__ $$a9783319626277$$q(electronic book) 000801101 020__ $$a3319626272$$q(electronic book) 000801101 020__ $$z9783319626260 000801101 020__ $$z3319626264 000801101 0247_ $$a10.1007/978-3-319-62627-7$$2doi 000801101 035__ $$aSP(OCoLC)on1005850974 000801101 035__ $$aSP(OCoLC)1005850974$$z(OCoLC)1005506739$$z(OCoLC)1005968552 000801101 040__ $$aYDX$$beng$$erda$$cYDX$$dN$T$$dEBLCP$$dGW5XE$$dN$T$$dOCLCF$$dFIE$$dUAB$$dNHM 000801101 049__ $$aISEA 000801101 050_4 $$aQH324.2$$b.S76 2017e 000801101 08204 $$a570.285$$223 000801101 08204 $$a510$$222 000801101 24500 $$aStochastic processes, multiscale modeling, and numerical methods for computational cellular biology /$$cDavid Holcman, editor. 000801101 264_1 $$aCham, Switzerland :$$bSpringer Nature,$$c[2017] 000801101 300__ $$a1 online resource (xiii, 377 pages) :$$bcolor illustrations 000801101 336__ $$atext$$btxt$$2rdacontent 000801101 337__ $$acomputer$$bc$$2rdamedia 000801101 338__ $$aonline resource$$bcr$$2rdacarrier 000801101 504__ $$aIncludes bibliographical references and index. 000801101 5052_ $$aPart I: Stochastic Chemical Reactions -- Test Models for Statistical Inference: Two-Dimensional Reaction Systems Displaying Limit Cycle Bifurcations and Bistability -- Importance Sampling for Metastable and Multiscale Dynamical Systems -- Multiscale Simulation of Stochastic Reaction-diffusion Networks -- Part II: Stochastic Numerical Approaches, Algorithms and Coarse-Grained Simulations -- Numerical Methods for Ergodic SDEs: When Stochastic Integration Meets Geometric Integration -- Stability and Strong Convergence for Spatial Stochastic Kinetics -- The T cells in an Ageing Virtual Mouse -- Part III: Analysis of Stochastic Dynamical Systems for Modeling Cell Biology -- Model reduction for Stochastic Reaction Systems -- ZI-closure Scheme: A Method to Solve and Study Stochastic Reaction Networks -- Deterministic and Stochastic Becker-Döring Equations: Past and Recent Mathematical Developments -- Coagulation-Fragmentation with a Finite Number of Particles: Models, Stochastic Analysis and Applications to Telomere Clustering and Viral Capsid Assembly -- A Review of Stochastic and Delay Simulation Approaches in both Time and Space in Computational Cell Biology -- Part IV: Diffusion Processes and Stochastic Modeling -- Recent Mathematical Models of Axonal Transport -- Stochastic Models for Evolving Cellular Populations of Mitochondria: Disease, Development, and Ageing -- Modeling and Stochastic Analysis of the Single Photon Response -- A Phenomenological Spatial Model for Macro-ecological Patterns in Species-rich Ecosystems. 000801101 506__ $$aAccess limited to authorized users. 000801101 520__ $$a"This book focuses on the modeling and mathematical analysis of stochastic dynamical systems along with their simulations. The collected chapters will review fundamental and current topics and approaches to dynamical systems in cellular biology. This text aims to develop improved mathematical and computational methods with which to study biological processes. At the scale of a single cell, stochasticity becomes important due to low copy numbers of biological molecules, such as mRNA and proteins that take part in biochemical reactions driving cellular processes. When trying to describe such biological processes, the traditional deterministic models are often inadequate, precisely because of these low copy numbers. This book presents stochastic models, which are necessary to account for small particle numbers and extrinsic noise sources. The complexity of these models depend upon whether the biochemical reactions are diffusion-limited or reaction-limited. In the former case, one needs to adopt the framework of stochastic reaction-diffusion models, while in the latter, one can describe the processes by adopting the framework of Markov jump processes and stochastic differential equations. Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology will appeal to graduate students and researchers in the fields of applied mathematics, biophysics, and cellular biology."--Provided by publisher. 000801101 588__ $$aOnline resource; title from digital title page (viewed November 20, 2017). 000801101 650_0 $$aComputational biology. 000801101 650_0 $$aStochastic processes. 000801101 7001_ $$aHolcman, David,$$eeditor. 000801101 77608 $$iPrint version:$$tStochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology.$$dSpringer Verlag 2017$$z9783319626260$$w(OCoLC)989966603$$w(DLC) 2017952704 000801101 852__ $$bebk 000801101 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-62627-7$$zOnline Access$$91397441.1 000801101 909CO $$ooai:library.usi.edu:801101$$pGLOBAL_SET 000801101 980__ $$aEBOOK 000801101 980__ $$aBIB 000801101 982__ $$aEbook 000801101 983__ $$aOnline 000801101 994__ $$a92$$bISE