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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 6
1728-1734

Binary cancer single-driver pathway identification model and algorithm

Zhang Yia,b
Lu Hea
a. School of Information Science & Engineering, b. Guangxi Key Laboratory of Embedded Technology & Intelligent Systems, Guilin University of Technology, Guilin Guangxi 541004, China
DOI: 10.19734/j.issn.1001-3695.2023.10.0497

Abstract

The researches on driver pathway identification in cancer rely on traditional biological experiments, which have the drawbacks of being time-consuming, labor-intensive and costly. This paper proposed a novel binary cancer driver pathway identification method called PEA-BLMWS(parental evolutionary algorithm-binary linear maximum weight sub-matrix). Firstly, it utilized the existing gene expression data to uncovered potential gene mutation data by comparing the differences in expression levels between normal and mutated genes. Secondly, it incorporated protein-protein interaction network data to construct an improved binary linear maximum weight sub-matrix model. Finally, it proposed a parental evolutionary algorithm to solve this matrix model. Experimental results on the GBM(glioblastoma) and OVCA(ovarian cancer) datasets show that compared to other advanced identification methods such as Dendrix, CCA-NMWS and CGP-NCM, the gene set identified by PEA-BLMWS has more genes enriched in known signaling pathways, and genes not enriched in signaling pathways are also closely related to the occurrence of cancer. Therefore, this identification method can serve as an effective tool for driving pathway identification.

Foundation Support

国家自然科学基金资助项目(62166014,62162019)
广西自然科学基金面上项目(2020GXNSFAA297255)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.10.0497
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 6
Section: Algorithm Research & Explore
Pages: 1728-1734
Serial Number: 1001-3695(2024)06-018-1728-07

Publish History

[2024-02-02] Accepted Paper
[2024-06-05] Printed Article

Cite This Article

张奕, 鲁贺. 一种二进制癌症单驱动通路识别模型和算法 [J]. 计算机应用研究, 2024, 41 (6): 1728-1734. (Zhang Yi, Lu He. Binary cancer single-driver pathway identification model and algorithm [J]. Application Research of Computers, 2024, 41 (6): 1728-1734. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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