Relevant bibliographies by topics / Chemical Langevin equation

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Chemical Langevin equation'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Chemical Langevin equation"

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Gillespie, Daniel T. "The chemical Langevin equation." Journal of Chemical Physics 113, no. 1 (July 2000): 297–306. http://dx.doi.org/10.1063/1.481811.

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Schnoerr, David, Guido Sanguinetti, and Ramon Grima. "The complex chemical Langevin equation." Journal of Chemical Physics 141, no. 2 (July 14, 2014): 024103. http://dx.doi.org/10.1063/1.4885345.

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Li, Tao. "Chemical Langevin Equation for Complex Reactions." Journal of Physical Chemistry A 124, no. 5 (January 15, 2020): 810–16. http://dx.doi.org/10.1021/acs.jpca.9b10108.

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Ilie, Silvana, and Monjur Morshed. "Automatic Simulation of the Chemical Langevin Equation." Applied Mathematics 04, no. 01 (2013): 235–41. http://dx.doi.org/10.4236/am.2013.41a036.

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Zwanzig, Robert. "A Chemical Langevin Equation with Non-Gaussian Noise†." Journal of Physical Chemistry B 105, no. 28 (July 2001): 6472–73. http://dx.doi.org/10.1021/jp0034630.

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Ilie, Silvana, and Monjur Morshed. "Adaptive Time-Stepping Using Control Theory for the Chemical Langevin Equation." Journal of Applied Mathematics 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/567275.

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Stochastic modeling of biochemical systems has been the subject of intense research in recent years due to the large number of important applications of these systems. A critical stochastic model of well-stirred biochemical systems in the regime of relatively large molecular numbers, far from the thermodynamic limit, is the chemical Langevin equation. This model is represented as a system of stochastic differential equations, with multiplicative and noncommutative noise. Often biochemical systems in applications evolve on multiple time-scales; examples include slow transcription and fast dimer
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Ilie, Silvana, and Alexandra Teslya. "An adaptive stepsize method for the chemical Langevin equation." Journal of Chemical Physics 136, no. 18 (May 14, 2012): 184101. http://dx.doi.org/10.1063/1.4711143.

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Mu, Wei-Hua, Zhong-Can Ou-Yang, and Xiao-Qing Li. "From Chemical Langevin Equations to Fokker—Planck Equation: Application of Hodge Decomposition and Klein—Kramers Equation." Communications in Theoretical Physics 55, no. 4 (April 2011): 602–4. http://dx.doi.org/10.1088/0253-6102/55/4/15.

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Ghosh, Atiyo, Andre Leier, and Tatiana T. Marquez-Lago. "The Spatial Chemical Langevin Equation and Reaction Diffusion Master Equations: moments and qualitative solutions." Theoretical Biology and Medical Modelling 12, no. 1 (2015): 5. http://dx.doi.org/10.1186/s12976-015-0001-6.

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Khanin, Raya, and Desmond J. Higham. "Chemical Master Equation and Langevin regimes for a gene transcription model." Theoretical Computer Science 408, no. 1 (November 2008): 31–40. http://dx.doi.org/10.1016/j.tcs.2008.07.007.

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Dissertations / Theses on the topic "Chemical Langevin equation"

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Mélykúti, Bence. "Theoretical advances in the modelling and interrogation of biochemical reaction systems : alternative formulations of the chemical Langevin equation and optimal experiment design for model discrimination." Thesis, University of Oxford, 2010. http://ora.ox.ac.uk/objects/uuid:d368c04c-b611-41b2-8866-cde16b283b0d.

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This thesis is concerned with methodologies for the accurate quantitative modelling of molecular biological systems. The first part is devoted to the chemical Langevin equation (CLE), a stochastic differential equation driven by a multidimensional Wiener process. The CLE is an approximation to the standard discrete Markov jump process model of chemical reaction kinetics. It is valid in the regime where molecular populations are abundant enough to assume their concentrations change continuously, but stochastic fluctuations still play a major role. We observe that the CLE is not a single equatio
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Xie, Zhi. "Modelling genetic regulatory networks: a new model for circadian rhythms in Drosophila and investigation of genetic noise in a viral infection process." Phd thesis, Lincoln University. Agriculture and Life Sciences Division, 2007. http://theses.lincoln.ac.nz/public/adt-NZLIU20070712.144258/.

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In spite of remarkable progress in molecular biology, our understanding of the dynamics and functions of intra- and inter-cellular biological networks has been hampered by their complexity. Kinetics modelling, an important type of mathematical modelling, provides a rigorous and reliable way to reveal the complexity of biological networks. In this thesis, two genetic regulatory networks have been investigated via kinetic models. In the first part of the study, a model is developed to represent the transcriptional regulatory network essential for the circadian rhythms in Drosophila. The model
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Derivaux, Jean-Francois. "Stochastic thermodynamics of transport phenomena and reactive systems: an extended local equilibrium approach." Doctoral thesis, Universite Libre de Bruxelles, 2020. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/308809.

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Avec les progrès de la technologie, il est désormais devenu possible de manipuler des faibles quantités d’objets nanométriques, voire des objets uniques. Observer une réaction chimique de quelques centaines de molécules sur des catalyseurs, étudier le travail exercé lors du déploiement d’un brin d’ADN unique ou mesurer la chaleur émise par un unique électron dans un circuit électrique constituent aujourd’hui des actes expérimentaux courants. Cependant, à cette échelle, le caractère aléatoire des processus physiques étudiés se fait plus fortement ressentir. Développer une théorie thermodynamiqu
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Dana, Saswati. "Computational Studies Of Uncertainty In Intra-Cellular Biochemical Reaction Systems." Thesis, 2011. http://etd.iisc.ernet.in/handle/2005/2069.

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With an increased popularity for systems-based approaches in biology, a wide spectrum of techniques has been applied to the simulation and analysis of biochemical systems which involves uncertainty and stochasticity. It is particularly concerned with modelling and analysis of metabolic pathways, regulatory and signal transduction networks for understanding intra-cellular pathway behaviour. Typically, parameter estimation in ordinary differential equations(ODEs) models is used for this purpose when there is large number of molecules involved in the reaction system. However this approach is corr
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Books on the topic "Chemical Langevin equation"

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Coffey, William T., Yu P. Kalmykov, and J. T. Waldron. The Langevin Equation: With Applications to Stochastic Problems in Physics, Chemistry and Electrical Engineering (World Scientific Series in Contemporary Chemical Physics Vol. 14) - Second Edition. 2nd ed. World Scientific Publishing Company, 2004.

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Henriksen, Niels Engholm, and Flemming Yssing Hansen. Dynamic Solvent Effects: Kramers Theory and Beyond. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198805014.003.0011.

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This chapter discusses dynamical solvent effects on the rate constants for chemical reactions in solution. The effect is described by stochastic dynamics, where the influence of the solvent on the reaction dynamics is included by describing the motion along the reaction coordinate as Brownian motion. Two theoretical approaches are discussed: Kramers theory with a constant time-independent solvent friction coefficient and Grote–Hynes theory, a generalization of Kramers theory, based on the generalized Langevin equation with a time-dependent solvent friction coefficient. The expressions for the
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Book chapters on the topic "Chemical Langevin equation"

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Goychuk, Igor. "Viscoelastic Subdiffusion: Generalized Langevin Equation Approach." In Advances in Chemical Physics, 187–253. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118197714.ch5.

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Cooke, Jennie. "A Fractional Langevin Equation Approach to Diffusion Magnetic Resonance Imaging." In Advances in Chemical Physics, 279–378. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118135242.ch5.

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Giordano, M., P. Grigolini, D. Leporini, and P. Marin. "Slow Motion EPR Spectra in Terms of a Generalized Langevin Equation." In Advances in Chemical Physics, 321–88. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2007. http://dx.doi.org/10.1002/9780470142868.ch8.

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Coffey, W. T., Yu P. Kalmykov, and E. S. Massawe. "The Effective Eigenvalue Method and Its Application to Stochastic Problems in Conjunction with the Nonlinear Langevin Equation." In Advances in Chemical Physics, 667–792. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2007. http://dx.doi.org/10.1002/9780470141441.ch10.

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Adelman, S. A. "Generalized Langevin Equations and Many-Body Problems in Chemical Dynamics." In Advances in Chemical Physics, 143–253. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2007. http://dx.doi.org/10.1002/9780470142639.ch2.

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Murray, Richard M. "Stochastic Modeling and Analysis." In Biomolecular Feedback Systems. Princeton University Press, 2014. http://dx.doi.org/10.23943/princeton/9780691161532.003.0004.

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This chapter explores stochastic behavior in biomolecular systems. It does so by first building on the preliminary discussion of stochastic modeling laid out in Chapter 2. The chapter reviews methods for modeling stochastic processes, including the chemical master equation (CME), the chemical Langevin equation (CLE), and the Fokker–Planck equation (FPE). Given a stochastic description, the chapter then analyzes the behavior of the system using a collection of stochastic simulation and analysis tools. This chapter makes use of a variety of topics in stochastic processes; readers should have a good working knowledge of basic probability and some exposure to simple stochastic processes.
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Merkt, FrÉdÉric. "Molecular-physics aspects of cold chemistry." In Current Trends in Atomic Physics, 82–141. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198837190.003.0003.

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Molecular-physics aspects of cold chemistry are introduced with the example of few-electron molecules. After a brief overview of general aspects of molecular physics, the solution of the molecular Schrödinger equation is presented based on the Born-Oppenheimer approximation and the subsequent evaluation of adiabatic, nonadiabatic, relativistic and radiative (QED) corrections. Low-temperature chemical phenomena are introduced with the example of ion-molecule reactions, using the classical Langevin model for barrier-free exothermic reactions as reference. Then, methods to generate cold few-electron molecules by supersonic-beam-deceleration methods such as Stark, Zeeman, and Rydberg-Stark decelerations are presented. Two astrophysically important reactions, the reaction between H2 and H2+ forming H3+ and H, a very fast reaction following Langevin-capture going over to quantum-Langevin capture at low temperature, and the radiative association reaction H+ + H forming H2+, a very slow reaction in which quantum effects (shape resonances) become important at low temperatures, are used to illustrate the concepts introduced.
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Conference papers on the topic "Chemical Langevin equation"

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Altinkaya, Mustafa A., and Ercan E. Kuruoglu. "Modeling enzymatic reactions via chemical Langevin-Levy equation." In 2012 20th Signal Processing and Communications Applications Conference (SIU). IEEE, 2012. http://dx.doi.org/10.1109/siu.2012.6204746.

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Contou-Carrere, M. N., and P. Daoutidis. "Decoupling of fast and slow variables in chemical Langevin equations with fast and slow reactions." In 2006 American Control Conference. IEEE, 2006. http://dx.doi.org/10.1109/acc.2006.1655396.

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