Parameter sensitivity analysis for biochemical reaction networks

Minas, Giorgos; Rand, D.A.J.

doi:10.3934/mbe.2019196

Cited by 2 publications

(1 citation statement)

References 35 publications

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“…However, it has been observed that for a large class of deterministic models of regulatory and signalling systems of the sort that we are considering, the deterministic analogue of the FIM for the model parameters has rapidly decreasing eigenvalues [ 8 , 31 – 35 ]. A similar result was shown for stochastic models of the circadian clock in [ 17 , 36 ]. This implies that the effects of changing different parameters are highly correlated making it hard to recognise which parameter was changed.…”

Section: Resultssupporting

confidence: 84%

Multiplexing information flow through dynamic signalling systems

et al. 2020

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We consider how a signalling system can act as an information hub by multiplexing information arising from multiple signals. We formally define multiplexing, mathematically characterise which systems can multiplex and how well they can do it. While the results of this paper are theoretical, to motivate the idea of multiplexing, we provide experimental evidence that tentatively suggests that the NF-κB transcription factor can multiplex information about changes in multiple signals. We believe that our theoretical results may resolve the apparent paradox of how a system like NF-κB that regulates cell fate and inflammatory signalling in response to diverse stimuli can appear to have the low information carrying capacity suggested by recent studies on scalar signals. In carrying out our study, we introduce new methods for the analysis of large, nonlinear stochastic dynamic models, and develop computational algorithms that facilitate the calculation of fundamental constructs of information theory such as Kullback-Leibler divergences and sensitivity matrices, and link these methods to a new theory about multiplexing information. We show that many current models such as those of the NF-κB system cannot multiplex effectively and provide models that overcome this limitation using post-transcriptional modifications.

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Section: Resultssupporting

confidence: 84%

Multiplexing information flow through dynamic signalling systems

et al. 2020

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Multiplexing information flow through dynamic signalling systems

Minas

Woodcock

Ashall

et al. 2019

Preprint

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We provide experimental evidence suggesting that the NF-κB transcription factor can multiplex information about changes in multiple signals in the sense that the NF-κB target genes response can identify which of these signals have changed. In view of this, we consider how a signalling system can act as an information hub by multiplexing multiple signals. We formally define multiplexing, mathematically characterise which systems can multiplex and how well they can do it. We believe this may resolve the apparent paradox of how a system like NF-κB that regulates cell fate and inflammatory signalling in response to diverse stimuli can appear to have the low information carrying capacity suggested by recent studies on scalar signals. In carrying out our study, we introduce new methods for the analysis of large, nonlinear stochastic dynamic models, and develop computational algorithms that facilitate the calculation of fundamental constructs of information theory such as Kullback-Leibler divergences and sensitivity matrices, and link these methods to new theory about multiplexing information. We show that many current models such as those of the NF-κB system cannot multiplex effectively and provide models that overcome this limitation using post-transcriptional modifications.

show abstract

Parameter sensitivity analysis for biochemical reaction networks

Cited by 2 publications

References 35 publications

Multiplexing information flow through dynamic signalling systems

Multiplexing information flow through dynamic signalling systems

Multiplexing information flow through dynamic signalling systems

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