Please use this identifier to cite or link to this item:
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 |
Show full item record
Files in This Item:
There are no files associated with this item.
SCOPUSTM
Citations
32
checked on May 13, 2022
WEB OF SCIENCETM
Citations
28
checked on May 13, 2022
Page view(s)
141
checked on May 12, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.