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A Novel Collaborative Filtering Model-Based Method for Identifying Essential Proteins

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成果类型:
期刊论文
作者:
Zhu, Xianyou;He, Xin;Kuang, Linai;Chen, Zhiping;Lancine, Camara
通讯作者:
He, X.;Zhu, X.
作者机构:
College of Computer Science and Technology, Hengyang Normal University, China
Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, China
College of Computer, Xiangtan University, China
College of Computer Engineering and Applied Mathematics, Changsha University, China
The Social Sciences and Management University of Bamako, Mali
通讯机构:
[Zhu, X.; He, X.] C
College of Computer Science and Technology, China
College of Computer, China
语种:
英文
关键词:
collaborative filtering model;data integration;essential proteins;PDI network;prediction model
期刊:
Frontiers in Genetics
ISSN:
1664-8021
年:
2021
卷:
12
页码:
763153
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), and the Science and Technology Plan Project of Hunan Province (2016TP1020). The Hunan Province Science and Technology Project Funds (2018TP1036), 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:
Considering that traditional biological experiments are expensive and time consuming, it is important to develop effective computational models to infer potential essential proteins. In this manuscript, a novel collaborative filtering model-based method called CFMM was proposed, in which, an updated protein–domain interaction (PDI) network was constructed first by applying collaborative filtering algorithm on the original PDI network, and then, through integrating topological features of PDI networks with biological features of proteins, a cal...

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