Predicting Drug-Disease Associations via Multi-Task Learning Based on Collective Matrix Factorization

Predicting Drug-Disease Associations via Multi-Task Learning Based on Collective Matrix Factorization

Identifying drug-disease associations is integral to drug development. Computationally prioritizing candidate drug-disease associations has attracted growing attention due to its contribution to reducing the cost of laboratory screening. Drug-disease associations involve different association types,...

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Bibliographic Details
Main Authors: Feng Huang, Yang Qiu, Qiaojun Li, Shichao Liu, Fuchuan Ni
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-04-01
Series:Frontiers in Bioengineering and Biotechnology
Subjects:
drug-disease association
predicting association type
similarity
collective matrix factorization
multi-task learning
Online Access:https://www.frontiersin.org/article/10.3389/fbioe.2020.00218/full

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