SaeGraphDTI: drug–target interaction prediction based on sequence attribute extraction and graph neural network

SaeGraphDTI: drug–target interaction prediction based on sequence attribute extraction and graph neural network

Abstract Background Accurately identifying drug–target interactions (DTI) can greatly shorten the drug development cycle and reduce the cost of drug development. In current deep learning-based DTI prediction models, the extraction of drug and target features is a key step to improve model performanc...

Full description

Saved in:
Bibliographic Details
Main Authors: Qiaosheng Zhang, Zhenyu Sun, Zhaoman Zhong, Huihui Yang, Yalong Wei, Junjie Xu
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Bioinformatics
Subjects:
Drug–target interaction prediction
Sequence attribute extraction
Graph neural network
Deep learning
Online Access:https://doi.org/10.1186/s12859-025-06195-0
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1186/s12859-025-06195-0

Similar Items