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Showing 1 to 13 of 13 for “"stochastic simulation algorithm"”.
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Handling External Events Efficiently in Gillespie's Stochastic Simulation Algorithm
Gillespie's Stochastic Simulation Algorithm (SSA) provides an elegant simulation approach for simulating models composed of coupled chemical reactions. Although this approach can be used to describe a wide variety biological, chemical, and ecological systems, often systems have external behaviors …
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Analysis and Application of Haseltine and Rawlings's Hybrid Stochastic Simulation Algorithm
Stochastic effects in cellular systems are usually modeled and simulated with Gillespie's stochastic simulation algorithm (SSA), which follows the same theoretical derivation as the chemical master equation (CME), but the low efficiency of SSA limits its application to large chemical networks. To …
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A Gillespie-Type Algorithm for Particle Based Stochastic Model on Lattice
In this thesis, I propose a general stochastic simulation algorithm for particle based lattice model using the concepts of Gillespie's stochastic simulation algorithm, which was originally designed for well-stirred systems. I describe the details about this method and analyze its complexity …
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Investigation of the tau-leap method for stochastic simulation
The use of the relatively new tau-leap algorithm to model the kinematics of regulatory systems and other chemical processes inside the cell, is of great interest; however, the accuracy of the tau-leap algorithm is not known. We introduce a new method that enables us to establish the accuracy of the …
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Stochastic Simulation Methods for Biochemical Systems with Multi-state and Multi-scale Features
In this thesis we study stochastic modeling and simulation methods for biochemical systems. The thesis is focused on systems with multi-state and multi-scale features and divided into two parts. In the first part, we propose new algorithms that improve existing multi-state simulation methods. We …
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Stochastic Simulation Methods for Solving Systems with Multi-State Species
Gillespie's stochastic simulation algorithm (SSA) has been a conventional method for stochastic modeling and simulation of biochemical systems. However, its population-based scheme faces the challenge from multi-state situations in many biochemical models. To tackle this problem, Morton-Firth and …
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Computational Techniques for the Analysis of Large Scale Biological Systems
… computational, analytical, and high performance simulation techniques for biological problems, with applications to the yeast cell division cycle, and to the RNA-Sequencing of the yellow fever mosquito. Cell cycle system evolves stochastic effects when there are a small number of molecules react …
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Unraveling the intricacies of spatial organization of the ErbB receptors and downstream signaling pathways
… signaling. The coupled spatial non-spatial simulation algorithm, CSNSA is a tool that I took part in developing, which implements a spatial kinetic Monte Carlo for capturing receptor interactions on the cell membrane with Gillespies stochastic simulation algorithm, SSA, for temporal …
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Stochastic Modeling and Simulation of Multiscale Biochemical Systems
Numerous challenges arise in modeling and simulation as biochemical networks are discovered with increasing complexities and unknown mechanisms. With the improvement in experimental techniques, biologists are able to quantify genes and proteins and their dynamics in a single cell, which calls for …
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Binning for efficient stochastic particle simulations
Restriction data tranferred 2014-07-01T11:11:50-05:00 Original Data Group with Access UIUC Users [automated] Release Date: 2015-02-03 13:18:53 UTC Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system
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Multiscale simulation of heterophase polymerization : application to the synthesis of multicomponent colloidal polymer particles
… has been investigated using suitable numerical simulation techniques at their corresponding time and length scales. These methods, which include Molecular Dynamics (MD) simulation, Brownian Dynamics (BD) simulation and kinetic Monte Carlo (kMC) simulation, have been found to be very powerful and …
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On Efficient Algorithms for Stochastic Simulation of Biochemical Reaction Systems
… is formalized in a precise form by a model. A simulation algorithm will realize the dynamic interactions encoded in the model. The simulation can uncover biological implications and derive further predictive experiments. Several successful approaches with different levels of detail have been …
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Numerical Methods for the Chemical Master Equation
… underlying chemical kinetics, offers an accurate stochastic description of general chemical reaction systems on the mesoscopic scale. The chemical master equation is especially useful when formulating mathematical models of gene regulatory networks and protein-protein interaction networks, where …