A linear control model for gene intervention in a genetic regulatory network

Shu Qin Zhang; Michael K. Ng; Wai Ki Ching; Tatsuya Akutsu

doi:10.1109/GRC.2005.1547303

A linear control model for gene intervention in a genetic regulatory network

Shu Qin Zhang^*, Michael K. Ng, Wai Ki Ching, Tatsuya Akutsu

^*Corresponding author for this work

Department of Mathematics

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

Abstract

In this paper, we propose a linear control model for gene intervention in a genetic regulatory network. At each time step, finite controls are allowed to drive the network states to some target states. The objective is to achieve a target state probability distribution with a minimal control cost The model can be formulated as a minimization problem with integer variables and continuous variables. Our experimental results show that the control model and the algorithm are efficient for gene intervention problems in genetic networks.

Original language	English
Title of host publication	2005 IEEE International Conference on Granular Computing
Editors	Xiaohua Hu, Qing Liu, Andrzej Skowron, Tsau Young Lin, Ronald R. Yager, Bo Zhang
Publisher	IEEE
Pages	354-358
Number of pages	5
ISBN (Print)	0780390172, 9780780390171
DOIs	https://doi.org/10.1109/GRC.2005.1547303
Publication status	Published - 25 Jul 2005
Event	2005 IEEE International Conference on Granular Computing - Beijing, China Duration: 25 Jul 2005 → 27 Jul 2005 https://ieeexplore.ieee.org/xpl/conhome/10381/proceeding

Publication series

Name	IEEE International Conference on Granular Computing
Publisher	IEEE

Conference

Conference	2005 IEEE International Conference on Granular Computing
Country/Territory	China
City	Beijing
Period	25/07/05 → 27/07/05
Internet address	https://ieeexplore.ieee.org/xpl/conhome/10381/proceeding

Scopus Subject Areas

General Engineering

User-Defined Keywords

Genetic regulatory network
Linear control
Minimization problem
Probabilistic boolean network

Access to Document

10.1109/GRC.2005.1547303

Cite this

Zhang, S. Q., Ng, M. K., Ching, W. K., & Akutsu, T. (2005). A linear control model for gene intervention in a genetic regulatory network. In X. Hu, Q. Liu, A. Skowron, T. Y. Lin, R. R. Yager, & B. Zhang (Eds.), 2005 IEEE International Conference on Granular Computing (pp. 354-358). (IEEE International Conference on Granular Computing). IEEE. https://doi.org/10.1109/GRC.2005.1547303

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title = "A linear control model for gene intervention in a genetic regulatory network",

abstract = "In this paper, we propose a linear control model for gene intervention in a genetic regulatory network. At each time step, finite controls are allowed to drive the network states to some target states. The objective is to achieve a target state probability distribution with a minimal control cost The model can be formulated as a minimization problem with integer variables and continuous variables. Our experimental results show that the control model and the algorithm are efficient for gene intervention problems in genetic networks.",

keywords = "Genetic regulatory network, Linear control, Minimization problem, Probabilistic boolean network",

author = "Zhang, {Shu Qin} and Ng, {Michael K.} and Ching, {Wai Ki} and Tatsuya Akutsu",

note = "Funding Information: The authors would like to thank the support in part by RGC Grant Nos. HKU 7126/02P, 7130/02P, 7046/03P, 7035/04P, and HKU CRCG Grant Nos. 10203919, 10203907, 10204437, 10203501. Publisher copyright: {\textcopyright} 2005 IEEE; 2005 IEEE International Conference on Granular Computing ; Conference date: 25-07-2005 Through 27-07-2005",

year = "2005",

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day = "25",

doi = "10.1109/GRC.2005.1547303",

language = "English",

isbn = "0780390172",

series = "IEEE International Conference on Granular Computing",

publisher = "IEEE",

pages = "354--358",

editor = "Xiaohua Hu and Qing Liu and Andrzej Skowron and Lin, {Tsau Young} and Yager, {Ronald R.} and Bo Zhang",

booktitle = "2005 IEEE International Conference on Granular Computing",

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url = "https://ieeexplore.ieee.org/xpl/conhome/10381/proceeding",

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Zhang, SQ, Ng, MK, Ching, WK & Akutsu, T 2005, A linear control model for gene intervention in a genetic regulatory network. in X Hu, Q Liu, A Skowron, TY Lin, RR Yager & B Zhang (eds), 2005 IEEE International Conference on Granular Computing. IEEE International Conference on Granular Computing, IEEE, pp. 354-358, 2005 IEEE International Conference on Granular Computing, Beijing, China, 25/07/05. https://doi.org/10.1109/GRC.2005.1547303

A linear control model for gene intervention in a genetic regulatory network. / Zhang, Shu Qin; Ng, Michael K.; Ching, Wai Ki et al.
2005 IEEE International Conference on Granular Computing. ed. / Xiaohua Hu; Qing Liu; Andrzej Skowron; Tsau Young Lin; Ronald R. Yager; Bo Zhang. IEEE, 2005. p. 354-358 (IEEE International Conference on Granular Computing).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

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T1 - A linear control model for gene intervention in a genetic regulatory network

AU - Zhang, Shu Qin

AU - Ng, Michael K.

AU - Ching, Wai Ki

AU - Akutsu, Tatsuya

N1 - Funding Information: The authors would like to thank the support in part by RGC Grant Nos. HKU 7126/02P, 7130/02P, 7046/03P, 7035/04P, and HKU CRCG Grant Nos. 10203919, 10203907, 10204437, 10203501. Publisher copyright: © 2005 IEEE

PY - 2005/7/25

Y1 - 2005/7/25

N2 - In this paper, we propose a linear control model for gene intervention in a genetic regulatory network. At each time step, finite controls are allowed to drive the network states to some target states. The objective is to achieve a target state probability distribution with a minimal control cost The model can be formulated as a minimization problem with integer variables and continuous variables. Our experimental results show that the control model and the algorithm are efficient for gene intervention problems in genetic networks.

AB - In this paper, we propose a linear control model for gene intervention in a genetic regulatory network. At each time step, finite controls are allowed to drive the network states to some target states. The objective is to achieve a target state probability distribution with a minimal control cost The model can be formulated as a minimization problem with integer variables and continuous variables. Our experimental results show that the control model and the algorithm are efficient for gene intervention problems in genetic networks.

KW - Genetic regulatory network

KW - Linear control

KW - Minimization problem

KW - Probabilistic boolean network

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A linear control model for gene intervention in a genetic regulatory network

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