Download or read book Space in Discrete Stochastic Simulation of Chemical Kinetics written by Sotiria Lampoudi and published by ProQuest. This book was released on 2008 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis is concerned with studying what happens when space must be taken into account in discrete stochastic simulation of chemical kinetics. The Stochastic Simulation Algorithm of Gillespie, which is the simulation technique of choice for mesoscopic stochastic chemical kinetics, is rigorously applicable to systems of point molecules which are well-stirred. The former condition means that the molecules must occupy volume negligible compared to the total volume of the system. The latter condition means that the distribution of the molecules' positions in space must be uniformly random.
Download or read book Stochastic Chemical Kinetics written by Péter Érdi and published by Springer. This book was released on 2014-05-06 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume reviews the theory and simulation methods of stochastic kinetics by integrating historical and recent perspectives, presents applications, mostly in the context of systems biology and also in combustion theory. In recent years, due to the development in experimental techniques, such as optical imaging, single cell analysis, and fluorescence spectroscopy, biochemical kinetic data inside single living cells have increasingly been available. The emergence of systems biology brought renaissance in the application of stochastic kinetic methods.
Download or read book Molecular Kinetics in Condensed Phases written by Ron Elber and published by John Wiley & Sons. This book was released on 2019-12-06 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to the theoretical and computational toolkits for the modern study of molecular kinetics in condensed phases Molecular Kinetics in Condensed Phases: Theory, Simulation and Analysis puts the focus on the theory, algorithms, simulations methods and analysis of molecular kinetics in condensed phases. The authors – noted experts on the topic – offer a detailed and thorough description of modern theories and simulation methods to model molecular events. They highlight the rigorous stochastic modelling of molecular processes and the use of mathematical models to reproduce experimental observations, such as rate coefficients, mean first passage times and transition path times. The book’s exploration of simulations examines atomically detailed modelling of molecules in action and the connections of these simulations to theory and experiment. The authors also explore the applications that range from simple intuitive examples of one- and two-dimensional systems to complex solvated macromolecules. This important book: Offers an introduction to the topic that combines theory, simulation and analysis Presents a guide written by authors that are well-known and highly regarded leaders in their fields Contains detailed examples and explanation of how to conduct computer simulations of kinetics. A detailed study of a two-dimensional system and of a solvated peptide are discussed. Discusses modern developments in the field and explains their connection to the more traditional concepts in chemical dynamics Written for students and academic researchers in the fields of chemical kinetics, chemistry, computational statistical mechanics, biophysics and computational biology, Molecular Kinetics in Condensed Phases is the authoritative guide to the theoretical and computational toolkits for the study of molecular kinetics in condensed phases.
Download or read book Stochastic Chemical Reaction Systems in Biology written by Hong Qian and published by Springer Nature. This book was released on 2021-10-18 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the analysis of stochastic dynamic models in biology and medicine. The main aim is to offer a coherent set of probabilistic techniques and mathematical tools which can be used for the simulation and analysis of various biological phenomena. These tools are illustrated on a number of examples. For each example, the biological background is described, and mathematical models are developed following a unified set of principles. These models are then analyzed and, finally, the biological implications of the mathematical results are interpreted. The biological topics covered include gene expression, biochemistry, cellular regulation, and cancer biology. The book will be accessible to graduate students who have a strong background in differential equations, the theory of nonlinear dynamical systems, Markovian stochastic processes, and both discrete and continuous state spaces, and who are familiar with the basic concepts of probability theory.
Download or read book Stochastic Modelling for Systems Biology written by Darren J. Wilkinson and published by CRC Press. This book was released on 2006-04-18 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although stochastic kinetic models are increasingly accepted as the best way to represent and simulate genetic and biochemical networks, most researchers in the field have limited knowledge of stochastic process theory. The stochastic processes formalism provides a beautiful, elegant, and coherent foundation for chemical kinetics and there is a wealth of associated theory every bit as powerful and elegant as that for conventional continuous deterministic models. The time is right for an introductory text written from this perspective. Stochastic Modelling for Systems Biology presents an accessible introduction to stochastic modelling using examples that are familiar to systems biology researchers. Focusing on computer simulation, the author examines the use of stochastic processes for modelling biological systems. He provides a comprehensive understanding of stochastic kinetic modelling of biological networks in the systems biology context. The text covers the latest simulation techniques and research material, such as parameter inference, and includes many examples and figures as well as software code in R for various applications. While emphasizing the necessary probabilistic and stochastic methods, the author takes a practical approach, rooting his theoretical development in discussions of the intended application. Written with self-study in mind, the book includes technical chapters that deal with the difficult problems of inference for stochastic kinetic models from experimental data. Providing enough background information to make the subject accessible to the non-specialist, the book integrates a fairly diverse literature into a single convenient and notationally consistent source.
Download or read book Statistical Thermodynamics and Stochastic Kinetics written by Yiannis N. Kaznessis and published by Cambridge University Press. This book was released on 2011-12-01 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting the key principles of thermodynamics from a microscopic point of view, this book provides engineers with the knowledge they need to apply thermodynamics and solve engineering challenges at the molecular level. It clearly explains the concepts of entropy and free energy, emphasizing key ideas used in equilibrium applications, whilst stochastic processes, such as stochastic reaction kinetics, are also covered. It provides a classical microscopic interpretation of thermodynamic properties, which is key for engineers, rather than focusing on more esoteric concepts of statistical mechanics and quantum mechanics. Coverage of molecular dynamics and Monte Carlo simulations as natural extensions of the theoretical treatment of statistical thermodynamics is also included, teaching readers how to use computer simulations and thus enabling them to understand and engineer the microcosm. Featuring many worked examples and over 100 end-of-chapter exercises, it is ideal for use in the classroom as well as for self-study.
Download or read book Stochastic Dynamics in Computational Biology written by Stefanie Winkelmann and published by Springer Nature. This book was released on 2021-01-04 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to provide a well-structured and coherent overview of existing mathematical modeling approaches for biochemical reaction systems, investigating relations between both the conventional models and several types of deterministic-stochastic hybrid model recombinations. Another main objective is to illustrate and compare diverse numerical simulation schemes and their computational effort. Unlike related works, this book presents a broad scope in its applications, from offering a detailed introduction to hybrid approaches for the case of multiple population scales to discussing the setting of time-scale separation resulting from widely varying firing rates of reaction channels. Additionally, it also addresses modeling approaches for non well-mixed reaction-diffusion dynamics, including deterministic and stochastic PDEs and spatiotemporal master equations. Finally, by translating and incorporating complex theory to a level accessible to non-mathematicians, this book effectively bridges the gap between mathematical research in computational biology and its practical use in biological, biochemical, and biomedical systems.
Download or read book Stochastic Approach to Chemical Kinetics written by Donald Allan McQuarrie and published by . This book was released on 1968 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Reaction Rate Theory and Rare Events written by Baron Peters and published by Elsevier. This book was released on 2017-03-22 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reaction Rate Theory and Rare Events bridges the historical gap between these subjects because the increasingly multidisciplinary nature of scientific research often requires an understanding of both reaction rate theory and the theory of other rare events. The book discusses collision theory, transition state theory, RRKM theory, catalysis, diffusion limited kinetics, mean first passage times, Kramers theory, Grote-Hynes theory, transition path theory, non-adiabatic reactions, electron transfer, and topics from reaction network analysis. It is an essential reference for students, professors and scientists who use reaction rate theory or the theory of rare events. In addition, the book discusses transition state search algorithms, tunneling corrections, transmission coefficients, microkinetic models, kinetic Monte Carlo, transition path sampling, and importance sampling methods. The unified treatment in this book explains why chemical reactions and other rare events, while having many common theoretical foundations, often require very different computational modeling strategies. - Offers an integrated approach to all simulation theories and reaction network analysis, a unique approach not found elsewhere - Gives algorithms in pseudocode for using molecular simulation and computational chemistry methods in studies of rare events - Uses graphics and explicit examples to explain concepts - Includes problem sets developed and tested in a course range from pen-and-paper theoretical problems, to computational exercises
Download or read book Mathematical Models of Chemical Reactions written by Peter Erdi and published by . This book was released on 1989 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chemical kinetics may be considered as a prototype of nonlinear science, since the velocities of a reaction are generally nonlinear functions of the quantities of reactants. Although an actual chemical process is spatially extensive and involves very large numbers of constituent particles and a considerable number of intermediate transition compounds, the behavior--equilibria, periodicity, or chaos--may be described by the stoichiometric equations for a relatively small number of reactants. The macroscopic description of the kinetics can be deterministic, by a low-order system of nonlinear ordinary differential equations with polynomial right-hand sides, or stochastic, in terms of Markov jump processes. This volume surveys the mathematical models of chemical kinetics--their algebraic structure, mass action deterministic models, continuous time, discrete state stochastic models, and spatial effects mediated by diffusion. Further, the metalanguage of chemical kinetics is used to describe behavior in systems of interacting components, in neurochemistry, population biology, and ecology.
Download or read book Computational Methods in Systems Biology written by Muffy Calder and published by Springer Science & Business Media. This book was released on 2007-09-05 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the International Conference on Computational Methods in Systems Biology, CMSB 2007, held in Edinburgh, Scotland, September 2007. The 16 revised full papers presented present a variety of techniques from computer science, such as language design, concurrency theory, software engineering, and formal methods, for biologists, physicists, and mathematicians interested in the systems-level understanding of cellular processes.
Download or read book Stochasticity in Processes written by Peter Schuster and published by Springer. This book was released on 2016-10-14 with total page 728 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has developed over the past fifteen years from a modern course on stochastic chemical kinetics for graduate students in physics, chemistry and biology. The first part presents a systematic collection of the mathematical background material needed to understand probability, statistics, and stochastic processes as a prerequisite for the increasingly challenging practical applications in chemistry and the life sciences examined in the second part. Recent advances in the development of new techniques and in the resolution of conventional experiments at nano-scales have been tremendous: today molecular spectroscopy can provide insights into processes down to scales at which current theories at the interface of physics, chemistry and the life sciences cannot be successful without a firm grasp of randomness and its sources. Routinely measured data is now sufficiently accurate to allow the direct recording of fluctuations. As a result, the sampling of data and the modeling of relevant processes are doomed to produce artifacts in interpretation unless the observer has a solid background in the mathematics of limited reproducibility. The material covered is presented in a modular approach, allowing more advanced sections to be skipped if the reader is primarily interested in applications. At the same time, most derivations of analytical solutions for the selected examples are provided in full length to guide more advanced readers in their attempts to derive solutions on their own. The book employs uniform notation throughout, and a glossary has been added to define the most important notions discussed.
Download or read book Systems Analysis of Stochastic and Population Balance Models for Chemically Reacting Systems written by Eric Lynn Haseltine and published by . This book was released on 2005 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Chemical Kinetics Stochastic Processes and Irreversible Thermodynamics written by Moises Santillan and published by . This book was released on 2014-07-31 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Simple Brownian Diffusion written by Daniel Thomas Gillespie and published by OUP Oxford. This book was released on 2012-10-18 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brownian diffusion is the motion of one or more solute molecules in a sea of very many, much smaller solvent molecules. Its importance today owes mainly to cellular chemistry, since Brownian diffusion is one of the ways in which key reactant molecules move about inside a living cell. This book focuses on the four simplest models of Brownian diffusion: the classical Fickian model, the Einstein model, the discrete-stochastic (cell-jumping) model, and the Langevin model. The authors carefully develop the theories underlying these models, assess their relative advantages, and clarify their conditions of applicability. Special attention is given to the stochastic simulation of diffusion, and to showing how simulation can complement theory and experiment. Two self-contained tutorial chapters, one on the mathematics of random variables and the other on the mathematics of continuous Markov processes (stochastic differential equations), make the book accessible to researchers from a broad spectrum of technical backgrounds.
Download or read book Dynamics of Crowd minds written by Andrew Adamatzky and published by World Scientific. This book was released on 2005 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: - Includes easily accessible discrete models (cellular automata, artificial chemistry), a great number of informative illustrations, enlightening quotations, and an encyclopedic list of references.- Models and paradigms developed in the book can be applied to mathematical studies of affective collective intelligence, computational models of minds near the state of mental disorder, the design of massive-parallel prototypes of artificial consciousness, software implementations of affective cognition, and the design of hardware prototypes of emotional controllers.
Download or read book Stochastic Modelling for Systems Biology Third Edition written by Darren J. Wilkinson and published by CRC Press. This book was released on 2018-12-07 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the first edition of Stochastic Modelling for Systems Biology, there have been many interesting developments in the use of "likelihood-free" methods of Bayesian inference for complex stochastic models. Having been thoroughly updated to reflect this, this third edition covers everything necessary for a good appreciation of stochastic kinetic modelling of biological networks in the systems biology context. New methods and applications are included in the book, and the use of R for practical illustration of the algorithms has been greatly extended. There is a brand new chapter on spatially extended systems, and the statistical inference chapter has also been extended with new methods, including approximate Bayesian computation (ABC). Stochastic Modelling for Systems Biology, Third Edition is now supplemented by an additional software library, written in Scala, described in a new appendix to the book. New in the Third Edition New chapter on spatially extended systems, covering the spatial Gillespie algorithm for reaction diffusion master equation models in 1- and 2-d, along with fast approximations based on the spatial chemical Langevin equation Significantly expanded chapter on inference for stochastic kinetic models from data, covering ABC, including ABC-SMC Updated R package, including code relating to all of the new material New R package for parsing SBML models into simulatable stochastic Petri net models New open-source software library, written in Scala, replicating most of the functionality of the R packages in a fast, compiled, strongly typed, functional language Keeping with the spirit of earlier editions, all of the new theory is presented in a very informal and intuitive manner, keeping the text as accessible as possible to the widest possible readership. An effective introduction to the area of stochastic modelling in computational systems biology, this new edition adds additional detail and computational methods that will provide a stronger foundation for the development of more advanced courses in stochastic biological modelling.
