The assessment of efficient representation of drug features using deep learning for drug repositioning

BMC Bioinformatics

Table 3 Comparison three different versions of our pipeline with Yang & Agarwal [40] and Lee [21] on 21 diseases

MONDO	Disease name	Yang & Agarwa1	Lee (Random forest)	Lee (N-Net)	Ours {s}	Ours {g, s}	Ours {s, p}
0000190	ventricular fibrillation	0.74	0.85	0.78	0.81	0.82	0.79
0001627	dementia	0.62	0.89	0.79	0.83	0.89	0.81
0002049	thrombocytopenia	0.50	0.67	0.72	0.95	0.95	0.94
0002243	hemorrhagic disease	0.59	0.69	0.67	0.97	1.00	0.96
0003620	peripheral nervous system disease	0.91	0.64	0.69	0.92	0.93	0.91
0004975	alzheimer disease	0.68	0.62	0.61	0.86	0.89	0.84
0004976	amyotrophic lateral sclerosis	0.58	0.73	0.59	0.96	0.98	0.95
0004979	asthma	0.53	0.73	0.68	0.73	0.85	0.69
0004981	atrial fibrillation	0.50	0.80	0.79	0.87	0.92	0.85
0004985	bipolar disorder	0.69	0.84	0.82	0.87	0.90	0.86
0005015	diabetes mellitus	0.66	0.79	0.71	0.92	0.89	0.91
0005027	epilepsy	0.62	0.75	0.70	0.81	0.87	0.79
0005041	glaucoma	0.60	0.85	0.58	0.90	0.93	0.89
0005059	leukemia	0.69	0.79	0.55	0.97	0.97	0.97
0005062	lymphoma	0.72	0.85	0.55	0.97	0.94	0.97
0005068	myocardial infarction	0.64	0.70	0.68	0.92	0.91	0.91
0005180	parkinson disease	0.70	0.74	0.69	0.81	0.86	0.78
0005275	lung disease	0.70	0.78	0.68	0.94	0.90	0.93
0005578	arthritis	0.67	0.73	0.52	0.91	0.92	0.90
0008114	obsessive-compulsive disorder	0.95	0.79	0.76	0.97	0.95	0.97
0011122	obesity	0.64	0.72	0.66	0.67	0.44	0.71

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