Evidence map›Paper›PMID 34103008›Full record

ArticleBMC genomics2021

Protein functional module identification method combining topological features and gene expression data.

Zihao Zhao, Wenjun Xu, Aiwen Chen, Yueyue Han, Shengrong Xia, ChuLei Xiang, Chao Wang, Jun Jiao, Hui Wang, Xiaohui Yuan and 1 more

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Article in BMC genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Zihao Zhao *School of Computer and Information, Anhui Agricultural University, Hefei, Anhui, 230036, China.
Wenjun Xu *School of Computer and Information, Anhui Agricultural University, Hefei, Anhui, 230036, China.
Aiwen ChenSchool of Computer and Information, Anhui Agricultural University, Hefei, Anhui, 230036, China.
Yueyue HanSchool of Computer and Information, Anhui Agricultural University, Hefei, Anhui, 230036, China.
Shengrong XiaSchool of Computer and Information, Anhui Agricultural University, Hefei, Anhui, 230036, China.
ChuLei XiangSchool of Computer and Information, Anhui Agricultural University, Hefei, Anhui, 230036, China.
Chao WangSchool of Computer and Information, Anhui Agricultural University, Hefei, Anhui, 230036, China.
Jun JiaoSchool of Computer and Information, Anhui Agricultural University, Hefei, Anhui, 230036, China.
Hui WangSchool of Computer and Information, Anhui Agricultural University, Hefei, Anhui, 230036, China.
Xiaohui YuanDepartment of Computer Science and Engineering, University of North Texas, Denton, TX, 76203, United States.
Lichuan GuSchool of Computer and Information, Anhui Agricultural University, Hefei, Anhui, 230036, China. glc@ahau.edu.cn.

Funding

2019 Anhui University collaborative innovation project GXXT-2019-013Anhui Foundation for Science and Technology Major Project 16030701092, 18030901034, 201904e01020006Hefei Major Research Project of Key Technology J2018G14Key Laboratory of Agricultural Electronic Commerce, Ministry of Agriculture of China AEC2018003, AEC2018006National Natural Science Foundation of China 31771679, 31671589
6 · The paper itself

Abstract

backgroundThe study of protein complexes and protein functional modules has become an important method to further understand the mechanism and organization of life activities. The clustering algorithms used to analyze the information contained in protein-protein interaction network are effective ways to explore the characteristics of protein functional modules.

resultsThis paper conducts an intensive study on the problems of low recognition efficiency and noise in the overlapping structure of protein functional modules, based on topological characteristics of PPI network. Developing a protein function module recognition method ECTG based on Topological Features and Gene expression data for Protein Complex Identification.

conclusionsThe algorithm can effectively remove the noise data reflected by calculating the topological structure characteristic values in the PPI network through the similarity of gene expression patterns, and also properly use the information hidden in the gene expression data. The experimental results show that the ECTG algorithm can detect protein functional modules better.

Indexed as

Protein Interaction MappingProtein Interaction MapsAlgorithmsCluster AnalysisGene ExpressionProteinsProteinsEvolutionary clusteringGene expression dataProtein complexesTopological features

Identifiers

PMID34103008
PMCPMC8185953

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