Graph regularized non-negative matrix factorization with $$L_{2,1}$$ L 2 , 1 norm regularization terms for drug–target interactions prediction

Graph regularized non-negative matrix factorization with $$L_{2,1}$$ L 2 , 1 norm regularization terms for drug–target interactions prediction

Abstract Background Identifying drug–target interactions (DTIs) plays a key role in drug development. Traditional wet experiments to identify DTIs are costly and time consuming. Effective computational methods to predict DTIs are useful to speed up the process of drug discovery. A variety of non-neg...

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Bibliographic Details
Main Authors: Junjun Zhang, Minzhu Xie
Format: Article
Language:English
Published: BMC 2023-10-01
Series:BMC Bioinformatics
Subjects:
Drug–target interactions
$$L_{2,1}$$ L 2 , 1 norm
Inertial proximal alternating linearized minimization
Online Access:https://doi.org/10.1186/s12859-023-05496-6

Internet

https://doi.org/10.1186/s12859-023-05496-6

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