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Monitoring the genetic regulation process with a nonlinear software sensor | | V. Ibarra-Junquera
; L.A. Torres
; H.C. Rosu
; J. Collado-Vides
; | | Date: |
30 Sep 2004 | | Subject: | Quantitative Methods; Molecular Networks | q-bio.QM q-bio.MN | | Abstract: | The software sensor technique that occurs in the nonlinear automatic control theory and is in standard usage in chemical systems is applied to a simple genetic regulation process based on the Hill nonlinear regulation function. The software sensor (also called observer) combines an analytical differential-equation-based model with partial measurement of the system in order to estimate the non-measured state variables. For the illustration of this procedure, we employ a model recently adapted from Goodwin (1963) by De Jong (2002) in which one plays with the dynamics of the concentrations of mRNA a, a given protein A, and metabolite K. Using the data from metabolite K and the simple software sensor instead of the directly measured concentrations of mRNA a and protein A, it is possible to rebuild the latter concentrations despite the uncertainties in the steepness parameter of the Hill regulation function | | Source: | arXiv, q-bio.QM/0409036 | | Services: | Forum | Review | PDF | Favorites | |
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