Table 3.

Integrating AMP-Detector to evaluate unknown peptide sequences obtained from non-annotated databases or de novo-generated peptides using generative learning methods.

Activity	# Discovered from Peptide Atlas	# Generated Using Trained VAE	# Generated Using Positive Examples	# Generated Used Negative Examples
Antibacterial	403,367	336	63,709	58,826
Anti-Gram (+)	83,271	147	34,468	31,960
Antifungal	406,191	554	37,147	37,976
Blood–brain barrier penetrating	1,259,618	38	12,384	11,277
Antiparasitic	133,555	563	2887	2077
Anti-inflamatory	2,999,776	1	27	27
Cell-penetrating	698,536	58	12,468	14,066
Anti mammalian cell	81,701	93	16,360	14,611
Anuran defense	593,692	40	4729	4554
Anti-methicillin-resistant S. aureus	29,964	114	12,984	12,774
Cell–cell communication	129,651	2	13,237	13,475
Antioxidative	290,289	75	5307	4821
Antiangiogenic	292,815	34	37,954	33,980
Antiviral	2,582,176	29	24,987	24,178
Quorum sensing	2,088,671	17	16,477	15,624
Antimicrobial	305,496	640	49,497	45,325
Antimalarial	259,169	311	35,862	34,647
Anti-Gram (−)	152,568	232	37,009	33,168
Drug delivery vehicle	113,0481	60	14,147	15,857
Antidiabetic	3,344,580	1	4571	4518
Neuropeptide	2,499,312	1	20,188	19,898