DGPDHGCN: A Heterogeneous Graph Convolutional Network Method for Predicting Drug-Disease Associations

Haoran Zhu, Tong Yu, Ling Ge*, Jianjia Wang*

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

Abstract

Drug repositioning is a crucial aspect of biomedical research, and predicting drug-disease associations (DDAs) is a critical step in this process. With the development of deep learning and neural network technologies, Graph Convolutional Networks (GCNs) have achieved significant performances in this research field. Although existing DDAs models have made substantial progress, there is still need for improvement in sufficiently utilizing and integrating information from multiple biological entities. In this study, we propose a Drug-Gene-Protein-Disease Heterogeneous Graph Convolutional Network (DGPDHGCN) model for drug-disease association prediction. First, we construct a heterogeneous network from multiple data sources and establish meta-paths based on the topological information of biological entities. Then, the DGPDHGCN model learns representations of drugs and diseases from similarity and association data of those entities. Finally, we define a score function to quantify the associations between drugs and diseases. Through extensive experiments, we demonstrate that DGPDHGCN outperforms baseline models in DDAs prediction tasks in terms of metrics such as AUPR, F1-score, precision, and recall. The source code and experimental datasets can be found in https://github.com/Saxon0918/DGPDHGCN

Original languageEnglish
Title of host publicationProceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024
EditorsMario Cannataro, Huiru Zheng, Lin Gao, Jianlin Cheng, Joao Luis de Miranda, Ester Zumpano, Xiaohua Hu, Young-Rae Cho, Taesung Park
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1397-1402
Number of pages6
ISBN (Electronic)9798350386226
DOIs
Publication statusPublished - 2024
Event2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024 - Lisbon, Portugal
Duration: 3 Dec 20246 Dec 2024

Publication series

NameProceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

Conference

Conference2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024
Country/TerritoryPortugal
CityLisbon
Period3/12/246/12/24

Keywords

  • drug repositioning
  • drug-disease association
  • graph convolutional network
  • heterogeneous network

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