In this paper a mathematical tool is presented, to estimate unknown variables of transcription networks, according to a set of measurements of the transcriptional activity of promoters. The approach is based on the use of the mathematical model of the network under investigation and on the state-reconstruction technique known as ‘state observer’, borrowed from the control theory. To this aim, besides the general case, the network motif of the Multi-Output Feed-Forward Loop (MO-FFL) will be investigated in details. Simulations show the effectiveness of the proposed approach in a wide range of possible critical frameworks, such as only one target gene measurements, non-smooth input perturbations, noisy measurements and model parameter uncertainties.

The state observer as a tool for the estimation of gene expression

CACACE F;
2012-01-01

Abstract

In this paper a mathematical tool is presented, to estimate unknown variables of transcription networks, according to a set of measurements of the transcriptional activity of promoters. The approach is based on the use of the mathematical model of the network under investigation and on the state-reconstruction technique known as ‘state observer’, borrowed from the control theory. To this aim, besides the general case, the network motif of the Multi-Output Feed-Forward Loop (MO-FFL) will be investigated in details. Simulations show the effectiveness of the proposed approach in a wide range of possible critical frameworks, such as only one target gene measurements, non-smooth input perturbations, noisy measurements and model parameter uncertainties.
State observer ; Nonlinear systems ; Systems biology
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12610/2657
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