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https://doi.org/10.1016/j.biosystems.2006.12.005
| Title: | A Markovian approach to the control of genetic regulatory networks | Authors: | Chen, P.C.Y. Chen, J.W. |
Keywords: | Genetic networks Heuristic Markov chains Minimum-cost control |
Issue Date: | Sep-2007 | Citation: | Chen, P.C.Y., Chen, J.W. (2007-09). A Markovian approach to the control of genetic regulatory networks. BioSystems 90 (2) : 535-545. ScholarBank@NUS Repository. https://doi.org/10.1016/j.biosystems.2006.12.005 | Abstract: | This paper presents an approach for controlling gene networks based on a Markov chain model, where the state of a gene network is represented as a probability distribution, while state transitions are considered to be probabilistic. An algorithm is proposed to determine a sequence of control actions that drives (without state feedback) the state of a given network to within a desired state set with a prescribed minimum or maximum probability. A heuristic is proposed and shown to improve the efficiency of the algorithm for a class of genetic networks. © 2007 Elsevier Ireland Ltd. All rights reserved. | Source Title: | BioSystems | URI: | http://scholarbank.nus.edu.sg/handle/10635/54331 | ISSN: | 03032647 | DOI: | 10.1016/j.biosystems.2006.12.005 |
| Appears in Collections: | Staff Publications |
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