Table 3.

Benchmark datasets collected from existing literatures for DDI events prediction tasks

Task	Dataset name	Drugs	DDIs	Types	Drug-related information	Data resource
Multi-class	Dm_c179	572	74,528	65	Chemical substructure, Target, Pathway, Enzyme	DrugBank, KEGG
	Dm_c252	–	172,426	81	SMILES	Ryu et al.80
	Dm_c381	1,697	190,728	86	Chemical structure	Ryu et al.80
	Dm_c482	1,704	191,400	86	SMILES	DrugBank
	Dm_c583	1,258	323,539	100	Substructure, Target, Enzyme	DrugBank
	Dm_c684	1,935	589,827	2	Chemical structure	DrugBank
	Dm_c781	1,013	114,204	71	Chemical structure	Ryu et al.80, Lin et al.83
Multi-label	Dm_l152	–	99,002	200	SMILES	TWOSIDES
	Dm_l285	10,533	1,195,972	39	–	OGB-biokg78
	Dm_l381	751	53,888	200	Chemical structure	TWOSIDES,83
	Dm_l480	1,861	192,284	86	SMILES	DrugBank
	Dm_l585	3,797	1,236,361	2	–	DrugBank
	Dm_l685	1,925	56,983	2	–	KEGG
	Dm_l786	1,918	30,979	100	–	TWOSIDES
	Dm_l887	1,597	188,258	106	SMILES, Gene: 22,032 GO terms: 29,692	DrugBank, BioGrid88,89,90
	Dm_l981	1,314	103,938	200	Chemical structure	TWOSIDES
	Dm_l1091	1,317	198,697	86	Protein, Substructure Fingerprint	DrugBank, PubChem

Note: ‘Task’ represents prediction task, ‘Drugs’ represents the number of drugs in the dataset, ‘DDIs’ represents the numbers of drug-drug interactions, and ‘Types’ indicates the number of DDI types, ‘Drug-related information’ represents other types of data, ‘Data resource’ represents the source of the data, ‘-’ represents no clear explanation in the original literature. There are a total of 2,322 drugs in 52.