An efficient finite-difference strategy for sensitivity analysis of stochastic models of biochemical systems

Biosystems ◽  
2017 ◽  
Vol 151 ◽  
pp. 43-52 ◽  
Author(s):  
Monjur Morshed ◽  
Brian Ingalls ◽  
Silvana Ilie
2021 ◽  
Author(s):  
Samaneh Gholami

Modeling and simulation of biochemical systems are some of the important research areas in the rapid rise of Systems Biology. Often biochemical kinetic models represent cellular processes as systems of chemical reactions. The dynamics of these systems is typically described by using stochastic models. We introduce a method for an accurate sensitivity analysis of continuous such models of well-stirred biochemical systems. Sensitivity analysis plays a central role in the study of biochemical systems, being an important tool in their model construction, investigation and validation. In particular, it enables the identification of the key reaction rate parameters and it gives insight on how to effectively reduce the system while maintaining its overall behavior. The efficiency and accuracy of the method discussed are tested on several examples of practical interest.


2021 ◽  
Author(s):  
Samaneh Gholami

Modeling and simulation of biochemical systems are some of the important research areas in the rapid rise of Systems Biology. Often biochemical kinetic models represent cellular processes as systems of chemical reactions. The dynamics of these systems is typically described by using stochastic models. We introduce a method for an accurate sensitivity analysis of continuous such models of well-stirred biochemical systems. Sensitivity analysis plays a central role in the study of biochemical systems, being an important tool in their model construction, investigation and validation. In particular, it enables the identification of the key reaction rate parameters and it gives insight on how to effectively reduce the system while maintaining its overall behavior. The efficiency and accuracy of the method discussed are tested on several examples of practical interest.


2013 ◽  
Vol 104 (5) ◽  
pp. 1142-1150 ◽  
Author(s):  
Young-Seon Lee ◽  
Ona Z. Liu ◽  
Hyun Seok Hwang ◽  
Bjorn C. Knollmann ◽  
Eric A. Sobie

Author(s):  
Eben C. Cobb ◽  
Tsu-Chien Cheu ◽  
Jay Hoffman

This paper presents a design methodology to determine the optimal circumferential placement of cylindrical probes upstream of a turbine stage for reduced excitation forces. The potential flow forcing function generated by the probes is characterized by means of a Fourier analysis. A finite difference formulation is used to evaluate the sensitivity of the forcing function to the probe positions. An optimization scheme, based on the linear programming method, uses the sensitivity analysis results to reposition the probes such that the Fourier amplitudes of critical excitation orders are reduced. The results for an example design situation are presented.


2019 ◽  
Vol 109 (6) ◽  
pp. 2305-2324 ◽  
Author(s):  
Amin Esmaeilzadeh ◽  
Dariush Motazedian

Abstract We used a finite‐difference modeling method to investigate the sensitivity of the ground‐motion simulation results to the main input parameters, including the source model, regional path properties, and local site conditions. We used a spectral frequency range of 0.1–1 Hz for the Kinburn bedrock topographic basin, Ottawa, Canada, for the Ladysmith earthquake (Mw 4.7). Some findings are known facts; however, the unique geophysical conditions in the Ottawa area, such as the high contrast between the shear‐wave velocities of the bedrock and the shear‐wave velocity of the soil, were the reason for a comprehensive sensitivity analysis. Using a Gaussian source function with a short half‐duration increased the peak ground velocities (PGVs) and the amplitude of the velocity Fourier spectrum. Relaxation times and relaxation coefficients for the viscoelastic simulation significantly increased the amplitude of later arrivals at the soil site, which, consequently, led to an increase in PGV, the amplitude of the pseudospectral acceleration (PSA) ratio, and the velocity Fourier spectrum for a small earthquake. Employing a small soil Q model damped a significant amount of energy of the waves in the basin; thus, PGV, the PSA of soil to rock ratios, and the velocity Fourier spectrum were dependent on the soil Q model. Also, using a high‐velocity contrast between soil and rock increased PGVs and the amplitude of the PSA of the soil to rock ratios, whereas the frequency content of the waves shifted toward lower frequencies. Using a finite‐fault source model for a scenario large earthquake (Mw 7) significantly reduced the PGV values relative to a point‐source model. Using nonlinear‐viscoelastic simulation for a large earthquake (Mw 7) reduced the amplitude of the later arrivals and the amplitude of the PSA of the soil to rock ratios, and shifted the frequency content of waves toward lower frequency.


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