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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 7
1983-1988

Identification of essential proteins based on centrality and modularity

Mao Yimina
Zhang Yumenga
Hu Jianb
a. School of Information Engineering, b. Dept. of Information Engineering, College of Applied Science, Jiangxi University of Science & Technolo-gy, Ganzhou Jiangxi 341000, China
DOI: 10.19734/j.issn.1001-3695.2019.01.0015

Abstract

Due to the noise in PPI network, as well as the poor identification accuracy of essential proteins, this paper proposed a method named UCM based on centrality and modularity to identify essential proteins. Firstly, this method integrated topological data and biological data to construct multi-attribute network to reduce the noise(the false positive and the false nega-tive) impact in the original PPI network. Secondly, according to the topological property and biological property of essential proteins, this paper developed a clustering algorithm to mine essential modules from multi-attribute network, which emphasized the importance of the essential proteins from multi-dimension in essential modules. Finally, based on centrality and modularity, it designed an EIS to improve the accuracy of predicting essential proteins by topological properties and biological properties. This paper applied UCM method to the DIP dataset for predicting essential proteins. Compared with other ten methods of predicting essential proteins, the experimental results show that this method can identify more essential proteins and have a better performance on predicting essential proteins.

Foundation Support

国家自然科学基金资助项目(41562019,41530640)
江西省自然基金资助项目(GJJ161566,20161BAB203093)
江西省教育厅科技项目(GJJ181504,GJJ151528)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.01.0015
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 7
Section: Algorithm Research & Explore
Pages: 1983-1988
Serial Number: 1001-3695(2020)07-013-1983-06

Publish History

[2020-07-05] Printed Article

Cite This Article

毛伊敏, 章宇盟, 胡健. 基于中心性和模块特性的关键蛋白质识别 [J]. 计算机应用研究, 2020, 37 (7): 1983-1988. (Mao Yimin, Zhang Yumeng, Hu Jian. Identification of essential proteins based on centrality and modularity [J]. Application Research of Computers, 2020, 37 (7): 1983-1988. )

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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