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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Autors principals:	Jing Zhu, Chao Che, Hao Jiang, Jian Xu, Jiajun Yin, Zhaoqian Zhong
Format:	Artigo
Idioma:	Inglês
Publicat:	BMC 2024-01-01
Col·lecció:	BMC Bioinformatics
Matèries:	DDI prediction Molecular graph Sequence feature Substructure interactions Deep learning
Accés en línia:	https://doi.org/10.1186/s12859-024-05654-4
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