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Structural identification of unate-like genetic network models from time-lapse protein concentration measurements

Porreca, Riccardo; Cinquemani, Eugenio; Lygeros, John; Ferrari-Trecate, Giancarlo (2010). Structural identification of unate-like genetic network models from time-lapse protein concentration measurements. In: 49th IEEE Conference on Decision and Control, Atlanta, GA, 15 December 2010 - 17 December 2010, 2529-34.

Abstract

We consider the problem of learning dynamical models of genetic regulatory networks from time-lapse measurements of gene expression. In our previous work [1], we described a method for the structural and parametric identification of ODE models that makes use of concurrent measurements of concentrations and synthesis rates of the gene products, and requires the knowledge of the noise statistics. In this paper we assume all these pieces of information are not simultaneously available. In particular we propose extensions of [1] that make the method applicable to protein concentration measurements only. We discuss the performance of the method on experimental data from the network IRMA, a benchmark synthetic network engineered in yeast Saccharomices cerevisiae.

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:Special Collections > SystemsX.ch
Special Collections > SystemsX.ch > Research, Technology and Development Projects > YeastX
Dewey Decimal Classification:570 Life sciences; biology
Scopus Subject Areas:Physical Sciences > Control and Systems Engineering
Physical Sciences > Modeling and Simulation
Physical Sciences > Control and Optimization
Language:English
Event End Date:17 December 2010
Deposited On:04 Jul 2013 09:35
Last Modified:24 Jan 2022 01:12
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1109/CDC.2010.5717922

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