Skip to main content

Table 1 The best predictive model and gene signature for discrimination of metal from non-metal toxicants

From: Development of predicitve models to distinguish metals from non-metal toxicants, and individual metal from one another

No. of probe sets Cross validation error Prediction error (D2 to D1) Probe set ID
D2 C
1 8 8 9 A_44_P915194(FAM174B)
5 4 5 8 + A_42_P546708(KHDRBS3), A_44_P1034910(RTN2), A_42_P537091(FAM12B), A_43_P11261(AHNAK2)
7 3 4 5 + A_44_P593735(TC632928), A_42_P829301(SLC1A5)
8 3 3 4 + A_44_P427814(IGH-6)
10 2 3 2 + A_42_P537051(FAM70B), A_44_P1005988(CDIG2)
14 0 1 1 + A_43_P11561(ARNT), A_44_P1011716(ADORA2B),
A_43_P11444(S100G), A_44_P608892(TC596871)
15 0 0 0 + A_43_P11861(DIO3)
16 0 1 1 + A_44_P175654
18 2 1 1 + A_44_P1040207, A_44_P426107
25 2 2 1 + A_43_P21000, A_44_P299835,A_44_P1040926
A_44_P751206
A_44_P961496
A_44_P471440
A_43_P21816