A graph regularized generalized matrix factorization model for predicting links in biomedical bipartite networks | Zendy

Zi-Chao Zhang | Zendy; Xiao-Fei Zhang | Zendy; Min Wu | Zendy; Le Ou-Yang | Zendy; XingMing Zhao | Zendy; Xiaoli Li | Zendy

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A graph regularized generalized matrix factorization model for predicting links in biomedical bipartite networks

Author(s) -

Zi-Chao Zhang,

Xiao-Fei Zhang,

Min Wu,

Le Ou-Yang,

XingMing Zhao,

Xiaoli Li

Publication year - 2020

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btaa157

Subject(s) - bipartite graph , factorization , computer science , graph , matrix decomposition , theoretical computer science , mathematics , algorithm , eigenvalues and eigenvectors , physics , quantum mechanics

Predicting potential links in biomedical bipartite networks can provide useful insights into the diagnosis and treatment of complex diseases and the discovery of novel drug targets. Computational methods have been proposed recently to predict potential links for various biomedical bipartite networks. However, existing methods are usually rely on the coverage of known links, which may encounter difficulties when dealing with new nodes without any known link information.

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