MetWAMer: eukaryotic translation initiation site prediction

BMC Bioinformatics

Table 5 Effect of parameter set indexing strategy on PFCWLLKR performance using non-TIS-containing data

k	Indexing strategy		TN	FP	Sn
3	modulating	edit	5,074	11,047	0.3147
		PWM	5,134	10,987	0.3185
		WAM	5,069	11,052	0.3144
	static	edit	6,170	9,951	0.3827
		PWM	6,279	9,842	0.3895
		WAM	6,119	10,002	0.3796
5	modulating	edit	4,537	11,584	0.2814
		PWM	4,484	11,637	0.2781
		WAM	4,262	11,859	0.2644
	static	edit	5,993	10,128	0.3718
		PWM	6,065	10,056	0.3762
		WAM	5,679	10,442	0.3523
10	modulating	edit	4,190	11,931	0.2599
		PWM	3,708	12,413	0.2300
		WAM	3,533	12,588	0.2192
	static	edit	6,345	9,776	0.3936
		PWM	5,537	10,584	0.3435
		WAM	5,199	10,922	0.3225

16,121 non-TIS-containing instances were used in five-fold cross-validation experiments, in which parameter sets were selected for putative TIS evaluation according to best cluster fit established by either the Hamming distance relative to cached medoids (edit), position weight matrix scores (PWM), or weight array matrix scores (WAM). Parameter indexing was tested under both modulating (cluster assignment for each site separately) and static (cluster assignment based on the leftmost ATG) approaches. k denotes the number of clusters considered. TN represents the number of instances for which the method (correctly) refused to predict a TIS, and FP the number for which some prediction was made, though always incorrect (see Figure 2). $S n = \frac{T N}{T N + F P}$ .

ISSN: 1471-2105