On the transient and steady-state estimates of interval genetic regulatory networks
On the transient and steady-state estimates of interval genetic regulatory networks
This paper is concerned with the transient and steady-state estimates of a class of genetic regulatory networks (GRNs). Some sufficient conditions, which do not only present the transient estimate but also provide the estimates of decay rate and decay coefficient of the GRN with interval parameter uncertainties (interval GRN), are established by means of linear matrix inequality (LMI) and Lyapunov-Krasovskii functional. Moreover, the steady-state estimate of the proposed GRN model is also investigated. Furthermore, it is well known that gene regulation is an intrinsically noisy process due to intracellular and extracellular noise perturbations and environmental fluctuations. Then, by utilizing stochastic differential equation theory, the obtained results are extended to the case with noise perturbations due to natural random fluctuations. All the conditions are expressed within the framework of LMIs, which can easily be computed by using standard numerical software. A three-gene network is provided to illustrate the effectiveness of the theoretical results.
336-349
Li, Ping
84293437-7ab4-4c22-b68b-937bfc57ee15
Lam, James
3eea3836-efda-430c-9ad4-ae4f3d4b8c4a
Shu, Zhan
ea5dc18c-d375-4db0-bbcc-dd0229f3a1cb
April 2010
Li, Ping
84293437-7ab4-4c22-b68b-937bfc57ee15
Lam, James
3eea3836-efda-430c-9ad4-ae4f3d4b8c4a
Shu, Zhan
ea5dc18c-d375-4db0-bbcc-dd0229f3a1cb
Li, Ping, Lam, James and Shu, Zhan
(2010)
On the transient and steady-state estimates of interval genetic regulatory networks.
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 40 (2), .
(doi:10.1109/TSMCB.2009.2022402).
Abstract
This paper is concerned with the transient and steady-state estimates of a class of genetic regulatory networks (GRNs). Some sufficient conditions, which do not only present the transient estimate but also provide the estimates of decay rate and decay coefficient of the GRN with interval parameter uncertainties (interval GRN), are established by means of linear matrix inequality (LMI) and Lyapunov-Krasovskii functional. Moreover, the steady-state estimate of the proposed GRN model is also investigated. Furthermore, it is well known that gene regulation is an intrinsically noisy process due to intracellular and extracellular noise perturbations and environmental fluctuations. Then, by utilizing stochastic differential equation theory, the obtained results are extended to the case with noise perturbations due to natural random fluctuations. All the conditions are expressed within the framework of LMIs, which can easily be computed by using standard numerical software. A three-gene network is provided to illustrate the effectiveness of the theoretical results.
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Published date: April 2010
Organisations:
Mechatronics
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Local EPrints ID: 199711
URI: http://eprints.soton.ac.uk/id/eprint/199711
ISSN: 1083-4419
PURE UUID: d2327f84-b60f-4381-8ed2-8a57f3763b32
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Date deposited: 19 Oct 2011 14:37
Last modified: 14 Mar 2024 04:16
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Author:
Ping Li
Author:
James Lam
Author:
Zhan Shu
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