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Optimal Perturbations for the Identification of Stochastic Reaction Dynamics

Nandy, P. and Unger, M. and Zechner, C. and Koeppl, H. (2012):
Optimal Perturbations for the Identification of Stochastic Reaction Dynamics.
pp. 686-691, Elsevier, 16th IFAC Symposium on System Identification, [Conference or Workshop Item]

Abstract

Identification of stochastic reaction dynamics inside the cell is hampered by the low-dimensional readouts available with today's measurement technologies. Moreover, such processes are poorly excited by standard experimental protocols, making identification even more ill-posed. Recent technological advances provide means to design and apply complex extra-cellular stimuli. Based on an information-theoretic setting we present novel Monte Carlo sampling techniques to determine optimal temporal excitation profiles for such stochastic processes. We give a new result for the controlled birth-death process and provide a proof of principle by considering a simple model of regulated gene expression.

Item Type: Conference or Workshop Item
Erschienen: 2012
Creators: Nandy, P. and Unger, M. and Zechner, C. and Koeppl, H.
Title: Optimal Perturbations for the Identification of Stochastic Reaction Dynamics
Language: English
Abstract:

Identification of stochastic reaction dynamics inside the cell is hampered by the low-dimensional readouts available with today's measurement technologies. Moreover, such processes are poorly excited by standard experimental protocols, making identification even more ill-posed. Recent technological advances provide means to design and apply complex extra-cellular stimuli. Based on an information-theoretic setting we present novel Monte Carlo sampling techniques to determine optimal temporal excitation profiles for such stochastic processes. We give a new result for the controlled birth-death process and provide a proof of principle by considering a simple model of regulated gene expression.

Publisher: Elsevier
Divisions: 18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Bioinspired Communication Systems
18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications
Event Title: 16th IFAC Symposium on System Identification
Date Deposited: 04 Apr 2014 11:40
Official URL: http://www.ifac-papersonline.net/Detailed/54661.html
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