Statistical methods for stochastic biochemical kinetics
Stochastic gradients methods for statistical inference
... SGLD methods are poorly suited for general M -estimation problems in frequentist ...our methods and SGLD methods, is that we use averages of consecutive iterates, whereas SGLD does not use ...
167
Statistical methods for estimation of biochemical kinetic parameters
... provides the mechanistic rules for the back-calculation. In practise heterogeneous data sets may be available from different experiments which contain information about the transcription process and model parameters. ...
174
On the Stability of Stochastic Jump Kinetics
... As an argument in favor of this bottom-up approach one can note that, for evolutionary reasons, biochemical systems tend to operate close to critical points in phase-space where the efficiency is the highest. ...
24
Intrinsic Noise Analyzer: A Software Package for the Exploration of Stochastic Biochemical Kinetics Using the System Size Expansion
... accepted stochastic descriptions of biochemical dynamics under well-mixed conditions are given by the Chemical Master Equation and the Stochastic Simulation Algorithm, which are ...of ...
20
On the origins of approximations for stochastic chemical kinetics
... the stochastic equivalent of the equilibrium ...discrete stochastic formulation of chemical kinetics and arises due to the fact that exact simulation methods can advance only one reaction at a ...
16
Causal network inference using biochemical kinetics
... Two ongoing challenges in Bayesian computation relevant to CheMA include inference of model parameters and computation of marginal likelihoods for model selection. The second is an active area of research, with candidate ...
8
Causal network inference using biochemical kinetics
... Two ongoing challenges in Bayesian computation relevant to CheMA include inference of model parameters and computation of marginal likelihoods for model selection. The second is an active area of research, with candidate ...
7
Stochastic Modelling of Subcellular Biochemical Systems
... 1.3 Research objectives 5 not imply that CLE ignores the coupling like the LNA which has the same mean as the solution of the deterministic model. The merits of the 2MA compared to alternative approximations have been ...
103
Statistical methods to estimate the relative contribution of individual effective dose and stochastic models in toxicology
... increases. Suppose the exact data is collected for N = 1000 individuals, only up to 7 more individuals are needed for interval censored data to achieve the same precision for the three parameters (Table 2.7). Only 5 more ...
136
Milstein Scheme Applied to Stochastic Point Kinetics
... 1 Departamento de Ciencias Naturales, Universidad Surcolombiana, Av. Pastrana, Neiva, Huila, Colombia 2 Departamento de Física, Universidad del Valle, A.A 25360, Cali, Colombia Abstract: The Milstein’s iterative scheme ...
7
APPROXIMATION TO THE COVARIANCE MATRIX FOR STOCHASTIC POINT KINETICS
... point kinetics was first introduced using the SPCA (Stochastic Piecewise Constant Approximation) and MC (Monte Carlo) methods [1], in this publication there is a matrix formulation consisting of the ...
8
Efficient Parameter Inference for Stochastic Chemical Kinetics
... SSA, stochastic chemical kinetics requires an efficient estimation of reaction rates or parameters which is often needed in systems biology involves ...of biochemical networks from experimental data: ...
34
Hybrid framework for the simulation of stochastic chemical kinetics
... various biochemical processes, such as cell regulatory networks and enzyme ...Gillespie Stochastic Simulation Algorithm (SSA) [25] ...such methods to compute statistics of extinction times for ...
22
STOCHASTIC METHODS PARTI
... Probably the most famous set of RNG tests is the Marsaglia’s “Diehard” set. These Diehard tests are a battery of statistical tests for measuring the quality of a set of random numbers. They were developed over ...
10
Precise parameter synthesis for stochastic biochemical systems
... of stochastic reaction networks. The methods are applied to the problem of parameter exploration, ...of stochastic mass action kinetics, while we consider a stochastic Michaelis-Menten ...
36
Simplifying Stochastic Mathematical Models of Biochemical Systems
... Lumping techniques lead to loss of information about particular species or reactions and thus the physical in- terpretation of the elementary reactions is lost. They may be appropriate when only limited information is ...
9
Efficient simulation of stochastic chemical kinetics with the Stochastic Bulirsch-Stoer extrapolation method
... numerical methods and the exact solution (as com- puted by the SSA) as a function of the ...the methods tested the SBS appears to be the most robust and efficient, even though the TTTL has weak order two in ...
18
Statistical Sentence Condensation using Ambiguity Packing and Stochastic Disambiguation Methods for Lexical Functional Grammar
... A stochastic disambiguator using a maximum entropy model is trained on parsed and manu- ally disambiguated f-structures for pairs of sentences and their ...expressive stochastic disambiguation ...
8
Approximation and Model Reduction for the Stochastic Kinetics of Reaction Networks
... Outlook Using the results of this thesis, a number of ideas for future investigations suggest them- selves. The variational approach to moment closure of Chapter 3 appears to be very suitable for the development of ...
117
On Efficient Algorithms for Stochastic Simulation of Biochemical Reaction Systems
... We prove the correctness and experimentally show performance improvement of RRD over other compartment-based approaches in literature. Finally, we focus on performing a statistical analysis of the targeted event ...
172