Integration of Neighbor Topologies Based on Meta-Paths and Node Attributes for Predicting Drug-Related Diseases

Integration of Neighbor Topologies Based on Meta-Paths and Node Attributes for Predicting Drug-Related Diseases

Identifying new disease indications for existing drugs can help facilitate drug development and reduce development cost. The previous drug–disease association prediction methods focused on data about drugs and diseases from multiple sources. However, they did not deeply integrate the neighbor topolo...

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Bibliographic Details
Main Authors: Ping Xuan, Zixuan Lu, Tiangang Zhang, Yong Liu, Toshiya Nakaguchi
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:International Journal of Molecular Sciences
Subjects:
drug–disease association prediction
neighbor topology learning based on meta-paths
pairwise node attribute encoding
multiple drug–disease heterogeneous networks
fully connected neural networks and autoencoder based on CNN
Online Access:https://www.mdpi.com/1422-0067/23/7/3870

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https://www.mdpi.com/1422-0067/23/7/3870

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