Author:
Zhao Zihao,Xu Wenjun,Chen Aiwen,Han Yueyue,Xia Shengrong,Xiang ChuLei,Wang Chao,Jiao Jun,Wang Hui,Yuan Xiaohui,Gu Lichuan
Abstract
Abstract
Background
The 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.
Results
This 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.
Conclusions
The 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.
Funder
National Natural Science Foundation of China
Hefei Major Research Project of Key Technology
Anhui Foundation for Science and Technology Major Project
Key Laboratory of Agricultural Electronic Commerce, Ministry of Agriculture of China
2019 Anhui University collaborative innovation project
Publisher
Springer Science and Business Media LLC
Cited by
1 articles.
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