Table 7.

Performance comparison when each individual feature is used independently.

Features used	Sn	Sp	Acc	MCC	auROC
Monomer	87.27%	85.8%	86.53%	0.73	0.94
Dimer	87.3%	86.48%	86.8%	0.74	0.94
PhyChe	85.36%	86.27%	85.8%	0.72	0.93
PseAAC	85.47%	83.98%	85.22%	0.70	0.92
All four features	90.35%	94.62%	92.48%	0.85	0.98

Experiments have been performed on the benchmark dataset containing 880 samples in each class.

Bold denotes our proposed tool results.