Citation

Barman, Shohag and Al Farid, Fahmid and Gope, Hira Lal and Hafiz, Md. Ferdous and Khan, Niaz Ashraf and Ahmad, Sabbir and Mansor, Sarina (2024) LBF-MI: Limited Boolean Functions and Mutual Information to Infer a Gene Regulatory Network from Time-Series Gene Expression Data. Genes, 15 (12). p. 1530. ISSN 2073-4425

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Abstract

Background: In the realm of system biology, it is a challenging endeavor to infer a gene regulatory network from time-series gene expression data. Numerous Boolean network inference techniques have emerged for reconstructing a gene regulatory network from a time-series gene expression dataset. However, most of these techniques pose scalability concerns given their capability to consider only two to three regulatory genes over a specific target gene. Methods: To overcome this limitation, a novel inference method, LBF-MI, has been proposed in this research. This two-phase method utilizes limited Boolean functions and multivariate mutual information to reconstruct a Boolean gene regulatory network from time-series gene expression data. Initially, Boolean functions are applied to determine the optimum solutions. In case of failure, multivariate mutual information is applied to obtain the optimum solutions. Results: This research conducted a performance-comparison experiment between LBF-MI and three other methods: mutual information-based Boolean network inference, context likelihood relatedness, and relevance network. When examined on artificial as well as real-time-series gene expression data, the outcomes exhibited that the proposed LBF-MI method outperformed mutual information-based Boolean network inference, context likelihood relatedness, and relevance network on artificial datasets, and two real Escherichia coli datasets (E. coli gene regulatory network, and SOS response of E. coli regulatory network). Conclusions: LBF-MI’s superior performance in gene regulatory network inference enables researchers to uncover the regulatory mechanisms and cellular behaviors of various organisms.

Item Type:	Article
Uncontrolled Keywords:	Network inference; gene regulatory network; mutual information; Boolean functions
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	03 Jan 2025 03:15
Last Modified:	03 Jan 2025 03:15
URII:	http://shdl.mmu.edu.my/id/eprint/13258

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