TABLE 1.

Summary of AMP prediction approaches using GDL methods.

Predictor’s name	Applied prediction method	Outperforms	Paper Reference
sAMPpred-GAT	Graph Attention Neural Networks (GAT)	amPEPpy, AMPfun, AMPEP, ADAM-HMM, Ampir, AMPScannerV2, AmpGram, Deep-AMPEP30a, CAMP-ANN	Yan et al (2022b)
AMPs-Net	GCN	AMPScanner, AI4AMPs, CAMPR3, AMPDiscover, AMPlify, AMPEPpy (RF)	Puentes et al (2022)
LABAMPsGCN	GCN and Chebyshev Spectral CNN	CAMP-SVM, iAMP-2L, AMPfun	Sun et al (2022)
ACP-GCN	GCN	Convolutional neural network, long short-term memory (outperforms for accuracy)	Rao et al (2020)