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Metabolite-disease interaction prediction based on logistic matrix factorization and local neighborhood constraints

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成果类型:
期刊论文
作者:
Zhao, Yongbiao;Ma, Yuanyuan;Zhang, Qilin
通讯作者:
Ma, YY
作者机构:
[Zhao, Yongbiao] Cent China Normal Univ, Natl Engn Res Ctr Elearning, Wuhan, Hubei, Peoples R China.
[Zhao, Yongbiao; Ma, Yuanyuan; Ma, YY; Zhang, Qilin] Hubei Univ Arts & Sci, Sch Comp Engn, Xiangyang, Hubei, Peoples R China.
通讯机构:
[Ma, YY ] H
Hubei Univ Arts & Sci, Sch Comp Engn, Xiangyang, Hubei, Peoples R China.
语种:
英文
关键词:
association prediction;logistic matrix factorization;metabolite-disease interaction;neighborhood regularization;vicus matrix
期刊:
FRONTIERS IN PSYCHIATRY
ISSN:
1664-0640
年:
2023
卷:
14
页码:
1149947
基金类别:
This work was supported by Hubei Superior and Distinctive Discipline Group of “New Energy Vehicle and Smart Transportation.”
机构署名:
本校为第一机构
院系归属:
国家数字化学习工程技术研究中心
摘要:
Background: Increasing evidence indicates that metabolites are closely related to human diseases. Identifying disease-related metabolites is especially important for the diagnosis and treatment of disease. Previous works have mainly focused on the global topological information of metabolite and disease similarity networks. However, the local tiny structure of metabolites and diseases may have been ignored, leading to insufficiency and inaccuracy in the latent metabolite-disease interaction mining. Methods: To solve the aforementioned problem, ...

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