Heterogeneous network drug-target interaction prediction model based on graph wavelet transform and multi-level contrastive learning

Heterogeneous network drug-target interaction prediction model based on graph wavelet transform and multi-level contrastive learning

Abstract Reliable prediction of drug–target interaction (DTI) is essential for accelerating drug discovery, yet remains hindered by data imbalance, limited interpretability, and neglect of protein dynamics. Here, we present GHCDTI, a heterogeneous graph neural framework designed to overcome these ch...

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Bibliographic Details
Main Authors: Wenfeng Dai, Yanhong Wang, Shuai Yan, Qingzhi Yu, Xiang Cheng
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Heterogeneous networks
Graph wavelet transform
Heterogeneous graph convolutional network
Contrastive learning
Attention mechanism
Online Access:https://doi.org/10.1038/s41598-025-16098-y
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https://doi.org/10.1038/s41598-025-16098-y

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