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An Iterative Method for Predicting Essential Proteins Based on Multifeature Fusion and Linear Neighborhood Similarity

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成果类型:
期刊论文
作者:
Zhu, Xianyou;Zhu, Yaocan*;Tan, Yihong;Chen, Zhiping;Wang, Lei*
通讯作者:
Zhu, Yaocan;Wang, Lei
作者机构:
[Zhu, Xianyou; Chen, Zhiping] Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang, Peoples R China.
[Chen, Zhiping; Wang, Lei; Zhu, Yaocan; Tan, Yihong] Changsha Univ, Coll Comp Engn & Appl Math, Changsha, Peoples R China.
通讯机构:
[Zhu, YC; Wang, L] C
Changsha Univ, Coll Comp Engn & Appl Math, Changsha, Peoples R China.
语种:
英文
关键词:
Key protein;entropy;Linear neighborhood similarity;Iterative method;Multi-feature fusion
期刊:
FRONTIERS IN AGING NEUROSCIENCE
ISSN:
1663-4365
年:
2022
卷:
13
页码:
799500
基金类别:
This research is partly sponsored by the Research Foundation of Education Bureau of Hunan Province (No. 20B080), the Natural Science Foundation of Hunan Province (No. 2019JJ70010), the Hunan Provincial Natural Science Foundation of China (2020JJ4152), the Science and Technology Plan Project of Hunan Province (2016TP1020), the Hunan Province Science and Technology Project Funds (2018TP1036), and the National Scientific Research Foundation of Hunan Province Education Commission (18B367).
机构署名:
本校为第一机构
院系归属:
计算机科学与技术学院
摘要:
Growing evidence have demonstrated that many biological processes are inseparable from the participation of key proteins. In this paper, a novel iterative method called linear neighborhood similarity-based protein multifeatures fusion (LNSPF) is proposed to identify potential key proteins based on multifeature fusion. In LNSPF, an original protein-protein interaction (PPI) network will be constructed first based on known protein-protein interaction data downloaded from benchmark databases, based on which, topological features will be further ex...

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