SSF-DDI: a deep learning method utilizing drug sequence and substructure features for drug–drug interaction prediction

SSF-DDI: a deep learning method utilizing drug sequence and substructure features for drug–drug interaction prediction

Abstract Background Drug–drug interactions (DDI) are prevalent in combination therapy, necessitating the importance of identifying and predicting potential DDI. While various artificial intelligence methods can predict and identify potential DDI, they often overlook the sequence information of drug...

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Bibliographic Details
Main Authors: Jing Zhu, Chao Che, Hao Jiang, Jian Xu, Jiajun Yin, Zhaoqian Zhong
Format: Article
Language:English
Published: BMC 2024-01-01
Series:BMC Bioinformatics
Subjects:
DDI prediction
Molecular graph
Sequence feature
Substructure interactions
Deep learning
Online Access:https://doi.org/10.1186/s12859-024-05654-4

Internet

https://doi.org/10.1186/s12859-024-05654-4

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