| A mixed clustering coefficient centrality for identifying essential proteins |
| Lu, Pengli; Yu, JingJuan
|
| 2020-04-20
|
| 发表期刊 | INTERNATIONAL JOURNAL OF MODERN PHYSICS B
(IF:0.863[JCR-2018],0.803[5-Year]) |
| ISSN | 0217-9792
|
| 卷号 | 34期号:10 |
| 摘要 | Essential protein plays a crucial role in the process of cell life. The identification of essential proteins not only promotes the development of drug target technology, but also contributes to the mechanism of biological evolution. There are plenty of scholars who pay attention to discover essential proteins according to the topological structure of protein network and biological information. The accuracy of protein recognition still demands to be improved. In this paper, we propose a method which integrates the clustering coefficient in protein complexes and topological properties to determine the essentiality of proteins. First, we give the definition of In-clustering coefficient (IC) to describe the properties of protein complexes. Then we propose a new method, complex edge and node clustering (CENC) coefficient, to identify essential proteins. Different Protein-Protein Interaction (PPI) networks of Saccharomyces cerevisiae, MIPS and DIP are used as experimental materials. Through some experiments of logistic regression model, the results show that the method of CENC can promote the ability of recognizing essential proteins by comparing with the existing methods DC, BC, EC, SC, LAC, NC and the recent UC method. |
| 关键词 | Protein interaction network
essential protein
protein complex
assessment method
|
| DOI | 10.1142/S0217979220500903
|
| 收录类别 | SCI
; SCIE
|
| 语种 | 英语
|
| 资助项目 | National Natural Science Foundation of China[11361033]
; Natural Science Foundation of Gansu Province[1212RJZA029]
|
| WOS研究方向 | Physics
|
| WOS类目 | Physics, Applied
; Physics, Condensed Matter
; Physics, Mathematical
|
| WOS记录号 | WOS:000531579300005
|
| 出版者 | WORLD SCIENTIFIC PUBL CO PTE LTD
|
| 来源库 | WOS
|
| 引用统计 | 正在获取...
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| 文献类型 | 期刊论文
|
| 条目标识符 | https://ir.lut.edu.cn/handle/2XXMBERH/64360
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| 专题 | 兰州理工大学
|
| 通讯作者 | Lu, Pengli |
| 作者单位 | Lanzhou Univ Technol, Sch Comp & Commun, Lanzhou 730050, Gansu, Peoples R China
|
| 第一作者单位 | 兰州理工大学
|
| 通讯作者单位 | 兰州理工大学
|
| 第一作者的第一单位 | 兰州理工大学
|
推荐引用方式
GB/T 7714 |
Lu, Pengli,Yu, JingJuan. A mixed clustering coefficient centrality for identifying essential proteins[J]. INTERNATIONAL JOURNAL OF MODERN PHYSICS B,2020,34(10).
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| APA |
Lu, Pengli,&Yu, JingJuan.(2020).A mixed clustering coefficient centrality for identifying essential proteins.INTERNATIONAL JOURNAL OF MODERN PHYSICS B,34(10).
|
| MLA |
Lu, Pengli,et al."A mixed clustering coefficient centrality for identifying essential proteins".INTERNATIONAL JOURNAL OF MODERN PHYSICS B 34.10(2020).
|
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