Functional classification of proteins based on projection of amino acid sequences: application for prediction of protein kinase substrates

Sobolev, Boris; Filimonov, Dmitry; Lagunin, Alexey; Zakharov, Alexey; Koborova, Olga; Kel, Alexander; Poroikov, Vladimir

doi:10.1186/1471-2105-11-313

Table 2 IAP values obtained by LOO CV for the training set

From: Functional classification of proteins based on projection of amino acid sequences: application for prediction of protein kinase substrates

Kinase type	Number of substrates	Frame values
		10	15	20	25	30	35	40	45
ABL1	32	0.652	0.665	0.672	0.661	0.675	0.685	0.683	0.664
ATM	30	0.787	0.780	0.786	0.779	0.785	0.781	0.782	0.786
AURORA_A	12	0.747	0.732	0.743	0.792	0.784	0.773	0.769	0.744
AURORA_B	14	0.857	0.840	0.819	0.858	0.871	0.879	0.871	0.876
CAM_II_group	40	0.689	0.708	0.699	0.707	0.680	0.692	0.693	0.703
CAM_KII_alpha	21	0.616	0.592	0.591	0.531	0.532	0.528	0.519	0.529
CDK1	69	0.640	0.645	0.641	0.648	0.656	0.657	0.662	0.658
CDK2	28	0.767	0.747	0.754	0.761	0.753	0.748	0.730	0.725
CDKgroup	47	0.693	0.715	0.702	0.682	0.664	0.663	0.667	0.670
CK1alpha	11	0.578	0.553	0.575	0.609	0.625	0.642	0.594	0.560
CK1group	18	0.642	0.644	0.639	0.637	0.627	0.630	0.660	0.662
CK2group	122	0.745	0.740	0.735	0.746	0.742	0.737	0.742	0.748
DNA_PK	11	0.492	0.506	0.458	0.508	0.529	0.563	0.537	0.545
EGFR	27	0.840	0.843	0.883	0.861	0.893	0.887	0.891	0.888
ERK2	71	0.714	0.700	0.695	0.697	0.698	0.700	0.696	0.702
ERK1	61	0.655	0.639	0.634	0.632	0.632	0.631	0.622	0.634
FYN	25	0.687	0.697	0.695	0.696	0.651	0.627	0.619	0.632
GSK3beta	26	0.654	0.661	0.690	0.688	0.706	0.718	0.716	0.725
GSKgroup	20	0.650	0.640	0.664	0.616	0.589	0.592	0.557	0.566
INS_R	13	0.709	0.641	0.643	0.685	0.668	0.632	0.623	0.569
JNK1	20	0.762	0.773	0.754	0.766	0.783	0.770	0.777	0.779
JNK2	10	0.672	0.631	0.605	0.653	0.632	0.599	0.638	0.655
LCK	29	0.813	0.820	0.831	0.824	0.826	0.834	0.838	0.835
LKB1	16	0.996	0.995	0.994	0.994	0.993	0.989	0.990	0.991
LYN	26	0.751	0.771	0.743	0.722	0.705	0.706	0.711	0.712
MAPKAPK2	17	0.618	0.637	0.629	0.641	0.571	0.542	0.511	0.522
MAPKgroup	36	0.677	0.664	0.676	0.676	0.666	0.668	0.665	0.669
PAK1	21	0.500	0.517	0.570	0.573	0.569	0.575	0.576	0.541
PDK-1	24	0.957	0.958	0.956	0.957	0.955	0.948	0.949	0.950
PKAalpha	22	0.367	0.356	0.356	0.409	0.388	0.424	0.420	0.398
PKAgroup	206	0.658	0.660	0.669	0.668	0.672	0.648	0.646	0.648
PKBgroup	63	0.663	0.676	0.661	0.655	0.640	0.630	0.637	0.637
PKCalpha	81	0.663	0.653	0.656	0.643	0.646	0.649	0.656	0.653
PKCbeta	10	0.294	0.376	0.350	0.364	0.415	0.475	0.481	0.427
PKCdelta	17	0.418	0.472	0.449	0.490	0.489	0.463	0.479	0.493
PKCgroup	145	0.733	0.744	0.754	0.757	0.756	0.724	0.724	0.725
PKCzeta	11	0.643	0.626	0.668	0.701	0.736	0.746	0.743	0.733
PKGgroup	10	0.492	0.505	0.553	0.551	0.594	0.606	0.587	0.548
PLK1	18	0.678	0.628	0.670	0.718	0.731	0.721	0.688	0.704
ROCKgroup	12	0.828	0.852	0.862	0.856	0.866	0.872	0.880	0.889
RSKgroup	18	0.592	0.592	0.618	0.658	0.645	0.626	0.620	0.640
SGKgroup	11	0.738	0.749	0.699	0.695	0.699	0.699	0.699	0.683
SRC	92	0.731	0.732	0.740	0.742	0.742	0.738	0.746	0.745
SYK	21	0.741	0.729	0.752	0.766	0.775	0.764	0.744	0.750
P38alpha	24	0.726	0.720	0.723	0.737	0.741	0.728	0.705	0.717
Average		0.678	0.678	0.681	0.689	0.689	0.687	0.683	0.681

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ISSN: 1471-2105

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