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CLC number: O223

On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

Crosschecked: 2019-11-15

Cited: 0

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Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Jin-feng Pan

https://orcid.org/0000-0001-8567-3121

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Frontiers of Information Technology & Electronic Engineering  2020 Vol.21 No.2 P.294-303

http://doi.org/10.1631/FITEE.1900411


Optimal one-bit perturbation in Boolean networks based on cascading aggregation


Author(s):  Jin-feng Pan, Min Meng

Affiliation(s):  School of Mathematics and Information Sciences, Weifang University, Weifang 261061, China; more

Corresponding email(s):   panjinfeng1989@163.com, mengminmath@gmail.com

Key Words:  Large-scale Boolean network, Attractor, Cascading aggregation, One-bit perturbation


Jin-feng Pan, Min Meng. Optimal one-bit perturbation in Boolean networks based on cascading aggregation[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(2): 294-303.

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author="Jin-feng Pan, Min Meng",
journal="Frontiers of Information Technology & Electronic Engineering",
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year="2020",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1900411"
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T1 - Optimal one-bit perturbation in Boolean networks based on cascading aggregation
A1 - Jin-feng Pan
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Abstract: 
We investigate the problem of finding optimal one-bit perturbation that maximizes the size of the basin of attractions (BOAs) of desired attractors and minimizes the size of the BOAs of undesired attractors for large-scale Boolean networks by cascading aggregation. First, via the aggregation, a necessary and sufficient condition is given to ensure the invariance of desired attractors after one-bit perturbation. Second, an algorithm is proposed to identify whether the one-bit perturbation will cause the emergence of new attractors or not. Next, the change of the size of BOAs after one-bit perturbation is provided in an algorithm. Finally, the efficiency of the proposed method is verified by a T-cell receptor network.

基于级联聚合算法下的布尔网络最优单点摄动

潘金凤1,孟敏2
1潍坊学院数学与信息科学学院,中国潍坊市,261061
2南洋理工大学电气与电子工程学院,新加坡,639798

摘要:研究级联聚合算法分割下的大型布尔网络最优单点摄动问题;最大化期望吸引子吸引域,同时最小化非期望吸引子吸引域。首先,通过级联聚合算法给出一个在单点摄动下保持期望吸引子不变的充要条件。其次,提出一个判定是否出现新吸引子的算法。然后,提出另一算法给出单点摄动下吸引子吸引域的大小变化。最后,将本文理论应用于寻找T细胞受体网络的最优单点摄动问题。

关键词:大型布尔网络;吸引子;级联聚合算法;单点摄动

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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