P_UNSAT approach of attractor calculation for Boolean gene regulatory networks

被引：5

作者：

He, Qinbin ^{[1
]}

Xia, Zhile ^{[1
]}

Lin, Bin ^{[1
]}

机构：

[1] Taizhou Univ, Dept Math, Linhai 317000, Zhejiang, Peoples R China

来源：

JOURNAL OF THEORETICAL BIOLOGY | 2018年 / 447卷

关键词：

Boolean networks; Genetic regulatory networks; Attractor; CANCER; REDUCTION; STABILITY; DYNAMICS; PATHWAY; MODELS;

D O I：

10.1016/j.jtbi.2018.03.037

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Boolean network models provide an efficient way for studying gene regulatory networks. The main dynamics of a Boolean network is determined by its attractors. Attractor calculation plays a key role for analyzing Boolean gene regulatory networks. An approach of attractor calculation was proposed in this study, which combined the predecessor approach and the logic unsatisfiability approach to accelerate at tractor calculation. The proposed algorithm is effective to calculate all attractors for large-scale Boolean gene regulatory networks even the networks with a relatively large average degree. (C) 2018 Elsevier Ltd. All rights reserved.

引用

页码：171 / 177

页数：7

共 50 条

[21] Computing Minimal Boolean Models of Gene Regulatory Networks
Karlebach, Guy
Robinson, Peter N.
JOURNAL OF COMPUTATIONAL BIOLOGY, 2024, 31 (02) : 117 - 127
[22] An Optimal Boolean Approach for Computational Modeling of Gene Regulatory Networks from Temporal Gene Expression Profile
Razmi F.
Rowhanimanesh A.
Dideban A.
International Journal of Engineering, Transactions B: Applications, 2022, 35 (03): : 604 - 612
[23] Structural stability analysis of gene regulatory networks modeled by Boolean networks
Liang, Shuang
Zhao, Guodong
Li, Haitao
Ding, Xueying
MATHEMATICAL METHODS IN THE APPLIED SCIENCES, 2019, 42 (07) : 2221 - 2230
[24] An FVS-Based Approach to Attractor Detection in Asynchronous Random Boolean Networks
Giang Van Trinh
Akutsu, Tatsuya
Hiraishi, Kunihiko
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2022, 19 (02) : 806 - 818
[25] An ASP-based Approach for Attractor Enumeration in Synchronous and Asynchronous Boolean Networks
Khaled, Tarek
Benhamou, Belaid
ELECTRONIC PROCEEDINGS IN THEORETICAL COMPUTER SCIENCE, 2019, (306): : 295 - 301
[26] Integer Programming-Based Approach to Attractor Detection and Control of Boolean Networks
Akutsu, Tatsuya
Zhao, Yang
Hayashida, Morihiro
Tamura, Takeyuki
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2012, E95D (12): : 2960 - 2970
[27] Review and assessment of Boolean approaches for inference of gene regulatory networks
Pusnik, Ziga
Mraz, Miha
Zimic, Nikolaj
Moskon, Miha
HELIYON, 2022, 8 (08)
[28] On learning gene regulatory networks under the Boolean network model
Lähdesmäki, H
Shmulevich, I
Yli-Harja, O
MACHINE LEARNING, 2003, 52 (1-2) : 147 - 167
[29] On Learning Gene Regulatory Networks Under the Boolean Network Model
Harri Lähdesmäki
Ilya Shmulevich
Olli Yli-Harja
Machine Learning, 2003, 52 : 147 - 167
[30] Research on the Decomposition Method of Probabilistic Boolean Gene Regulatory Networks
Xu, Honglin
Wang, Shitong
2008 INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION, VOL III, PROCEEDINGS, 2008, : 342 - 346

← 1 2 3 4 5 →