A seed expansion-based method to identify essential proteins by integrating protein–protein interaction sub-networks and multiple biological characteristics

Table 3 Effectiveness of each part of SESN

Datasets	Measures	\(rm\_sub\)	\(rm\_correction\)	Wmatrix	\(score\_initial\)	\(all\_subcellular\)	SESN
DIP	SN	0.5493	0.5304	0.5501	0.5484	0.5467	0.5656
	SP	0.8390	0.8334	0.8393	0.8388	0.8382	0.8439
	PPV	0.5035	0.4863	0.5043	0.5027	0.5012	0.5185
	NPV	0.8623	0.8565	0.8626	0.8620	0.8615	0.8673
	F	0.5254	0.5074	0.5262	0.5246	0.5230	0.5410
	ACC	0.7726	0.7640	0.7730	0.7722	0.7715	0.7801
BioGRID	SN	0.5658	0.5542	0.5658	0.5650	0.5775	0.5967
	SP	0.8354	0.8322	0.8354	0.8351	0.8385	0.8437
	PPV	0.4816	0.4716	0.4816	0.4809	0.4915	0.5078
	NPV	0.8768	0.8735	0.8768	0.8766	0.8801	0.8856
	F	0.5203	0.5096	0.5203	0.5195	0.5310	0.5486
	ACC	0.7780	0.7730	0.7780	0.7777	0.7830	0.7912
Fruitfly	SN	0.2819	0.2799	0.2657	0.2779	0.2941	0.2982
	SP	0.9123	0.9122	0.9112	0.9121	0.9132	0.9134
	PPV	0.1787	0.1774	0.1684	0.1761	0.1864	0.1889
	NPV	0.9495	0.9493	0.9483	0.9491	0.9503	0.9506
	F	0.2187	0.2172	0.2061	0.2155	0.2282	0.2313
	ACC	0.8724	0.8722	0.8704	0.8719	0.8740	0.8745

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