Inconsistent Sensitivity Analysis

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Tyler Nicholas Simmons

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Mar 14, 2024, 9:21:22 AMMar 14
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Hello everyone,

I have created a deterministic ODE model in COPASI. I have recently learned that every time I open COPASI and run the model, the sensitivity analysis provides me different results. Other tasks yield the same results no matter when I run it. Only the sensitivity analysis does not. A majority of the unscaled and scaled sensitivity analysis is consistent, but for certain species, the coefficients are always different. When looking at the summarized sensitivities, there is no consistency whatsoever, different every time. 

If anyone has encountered this problem or knows what's happening, please let me know.
Best,

Frank Bergmann

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Mar 14, 2024, 9:26:34 AMMar 14
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Hello Tyler, 

this will be difficult to answer without seeing the model. So the only thing i could guess at so far, would be numerical instabilities, resulting in slightly different unscaled values. And of course, once they are scaled with the parameter values, the difference might compound for the scaled sensitivities. 

best
Frank

Tyler Simmons

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Mar 14, 2024, 9:35:16 AMMar 14
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Thank you for this answer. I am still confused about the methodology behind this analysis. How would numerical instability result in different values every time. I get that they may be different and may compound when scaled, but how is the initial computations with the same equation and same parameters yielding different numbers each time?

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Tyler Simmons
Biophysics Graduate Student
University of Maryland
College Park, MD

Frank Bergmann

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Mar 14, 2024, 9:56:52 AMMar 14
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COPASI uses finite differences, to compute the sensitivities. For each cause a permutation is applied and the selected subtask run twice to compute the difference. To answer where the differences come from, we'd have to know more like what subtask was selected. How different are the results you observe? Are the differences on the sensitive parameters? What role do these parameter play in the model and the like. 

That's why I said, that so far we can only guess. 

best
Frank

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