CASP1 - CASP9
(* results recalculated with new /updated structure comparison programs in 2019)
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TS Analysis : Z-score based relative group performance

    Models:

    • Ranking on the models designated as "1"
    • Ranking on best models

    Groups:

    • All groups on 'all groups' targets
    • Server groups on 'all groups' + 'server only' targets

    Formula and Domains:

      The ranking of groups is based on the analysis of zscores for GDT_TS.
    • easy (TBM)
    • medium (TBM/FM)
    • hard (FM)
 
 
  #   GR
  code 		   GR
  name		   Domains   
  Count		   SUM Zscore   
  (>-2.0)		   Rank SUM Zscore   
  (>-2.0)		   AVG Zscore   
  (>-2.0)		   Rank AVG Zscore   
  (>-2.0)		   SUM Zscore   
  (>0.0)		   Rank SUM Zscore   
  (>0.0)		   AVG Zscore   
  (>0.0)		   Rank AVG Zscore   
  (>0.0)
1 380 QUARK 147 99.6350 1 0.6778 1 101.5800 1 0.6910 1
2 428 ZHANG-SERVER 147 95.7310 2 0.6512 2 97.8470 2 0.6656 2
3 453 HHPREDA 147 54.8710 9 0.3733 10 79.4080 3 0.5402 6
4 449 HHPREDB 147 54.8710 9 0.3733 10 79.4080 3 0.5402 6
5 346 HHPREDC 147 53.2710 11 0.3624 12 78.2040 5 0.5320 8
6 286 RAPTORX 129 73.4590 3 0.5694 3 75.2140 6 0.5831 3
7 002 MULTICOM-CLUSTER 147 66.4220 6 0.4519 6 75.1530 7 0.5112 10
8 077 RAPTORX-MSA 129 72.4860 4 0.5619 4 74.9120 8 0.5807 4
9 321 BAKER-ROSETTASERVER 145 51.7850 12 0.3571 13 73.1220 9 0.5043 11
10 119 MULTICOM-REFINE 147 56.3430 8 0.3833 9 71.7220 10 0.4879 12
11 276 RAPTORX-BOOST 129 69.9110 5 0.5419 5 71.7210 11 0.5560 5
12 215 MULTICOM-NOVEL 147 59.1490 7 0.4024 7 69.0350 12 0.4696 13
13 174 PHYRE2 147 51.3280 14 0.3492 14 63.3550 13 0.4310 15
14 080 MULTICOM-CONSTRUCT 147 36.6280 16 0.2492 16 61.2840 14 0.4169 16
15 457 CHUNK-TASSER 134 51.3810 13 0.3834 8 60.0240 15 0.4479 14
16 253 PRO-SP3-TASSER 143 46.3620 15 0.3242 15 57.9560 16 0.4053 17
17 236 GWS 145 -28.3380 54 -0.1954 50 55.3610 17 0.3818 18
18 452 SEOK-SERVER 147 -31.1510 56 -0.2119 52 54.2210 18 0.3689 20
19 127 FAMSD 147 35.2150 17 0.2396 17 53.8810 19 0.3665 21
20 166 ZHOU-SPARKS-X 147 29.9500 18 0.2037 19 53.5100 20 0.3640 23
21 103 SAM-T08-SERVER 140 29.8670 19 0.2133 18 50.9840 21 0.3642 22
22 208 PCONSD 147 21.4840 24 0.1461 25 50.5140 22 0.3436 24
23 481 MUFOLD-SERVER 133 23.4740 22 0.1765 22 49.7620 23 0.3742 19
24 056 PCONSM 143 29.1330 20 0.2037 20 48.9340 24 0.3422 25
25 291 PRDOS2 145 19.5270 26 0.1347 26 45.5920 25 0.3144 27
26 047 BIOSERF 147 7.4960 33 0.0510 34 45.2970 26 0.3081 28
27 275 INTFOLD-TS 147 12.9400 29 0.0880 32 44.4180 27 0.3022 30
28 165 GSMETASERVER 137 21.5680 23 0.1574 24 43.5380 28 0.3178 26
29 273 PCOMB 142 5.6590 34 0.0399 36 43.3140 29 0.3050 29
30 319 PCONS 139 26.4810 21 0.1905 21 41.2160 30 0.2965 32
31 307 CHUO-FAMS 147 16.3370 27 0.1111 28 41.1900 31 0.2802 34
32 142 CLEF-SERVER 147 13.8110 28 0.0940 31 40.3530 32 0.2745 35
33 213 CIRCLE 134 21.1220 25 0.1576 23 39.8180 33 0.2971 31
34 302 FALCON-SWIFT 147 11.7660 31 0.0800 33 39.6770 34 0.2699 36
35 028 PROFILECRF 147 -1.6850 39 -0.0115 38 38.6290 35 0.2628 40
36 001 PROQ2 141 -19.4080 50 -0.1376 48 37.3460 36 0.2649 38
37 476 FFAS03N 141 -5.3790 43 -0.0381 41 37.1060 37 0.2632 39
38 435 MIDWAYFOLDINGSERVER 139 -7.4380 45 -0.0535 43 36.8470 38 0.2651 37
39 366 JIANG_THREADER 147 -40.5840 59 -0.2761 55 36.6110 39 0.2491 44
40 218 3D-JIGSAW_V4 124 11.8510 30 0.0956 30 35.9370 40 0.2898 33
41 207 ATOME2_CBS 138 -16.5270 48 -0.1198 47 35.7960 41 0.2594 41
42 345 PRECORS 140 -12.9310 47 -0.0924 46 35.6180 42 0.2544 43
43 214 DISTILL 147 -1.3980 38 -0.0095 37 34.7150 43 0.2362 48
44 471 FFAS03 135 -5.0010 42 -0.0370 40 33.0020 44 0.2445 45
45 409 MUSTER 147 -3.1210 41 -0.0212 39 32.5940 45 0.2217 49
46 063 JIANG_ASSEMBLY 147 -74.2530 67 -0.5051 62 32.3550 46 0.2201 50
47 171 FFAS03SS 136 -19.1630 49 -0.1409 49 29.1750 47 0.2145 51
48 420 FFAS03A 137 -11.8500 46 -0.0865 45 29.1710 48 0.2129 52
49 129 MUSICS_SERVER 141 -73.1480 66 -0.5188 63 28.1960 49 0.2000 54
50 117 3D-JIGSAW_V4-5 105 11.5080 32 0.1096 29 26.9300 50 0.2565 42
51 026 LOOPP_AUSTIN 130 -6.4160 44 -0.0494 42 25.3500 51 0.1950 55
52 018 WOLFSON-SERV 145 -41.0210 60 -0.2829 57 25.2430 52 0.1741 58
53 436 PANTHER 116 -32.7740 57 -0.2825 56 23.9560 53 0.2065 53
54 245 PROTAGORAS 122 -29.3430 55 -0.2405 54 23.2900 54 0.1909 56
55 296 PROQ 125 -24.4440 52 -0.1956 51 22.2570 55 0.1781 57
56 314 LMUSERVER 130 -37.8120 58 -0.2909 58 21.8020 56 0.1677 59
57 285 SAM-T02-SERVER 127 -27.9750 53 -0.2203 53 19.8420 57 0.1562 60
58 244 SAM-T06-SERVER 137 -45.7010 61 -0.3336 59 18.9310 58 0.1382 61
59 304 MA-OPUS-SERVER 147 -71.7840 65 -0.4883 61 17.9880 59 0.1224 62
60 055 MUFOLD-MD 131 -153.0040 71 -1.1680 67 15.1770 60 0.1159 63
61 074 M4T_2009 61 2.6070 36 0.0427 35 14.4580 61 0.2370 47
62 396 FUGUE_KM 131 -46.2250 62 -0.3529 60 13.8860 62 0.1060 65
63 328 PUSHCHINO 113 -62.0520 64 -0.5491 64 12.8980 63 0.1141 64
64 075 RAPTORX-FM 21 2.7700 35 0.1319 27 10.7560 64 0.5122 9
65 248 MUSICS-2S 115 -85.8190 68 -0.7463 65 9.6000 65 0.0835 67
66 355 LENSERVER 126 -171.8300 72 -1.3637 70 8.9300 66 0.0709 68
67 228 YASARA 76 -95.2890 69 -1.2538 68 8.0470 67 0.1059 66
68 350 RBO-PROTEUS 143 -185.1040 76 -1.2944 69 6.9590 68 0.0487 69
69 173 PCONSR 142 -243.3900 78 -1.7140 76 5.4000 69 0.0380 70
70 102 BILAB-ENABLE 147 -273.0030 79 -1.8572 77 4.1970 70 0.0286 71
71 257 STAT-PROTEUS 127 -183.2610 75 -1.4430 72 3.5600 71 0.0280 72
72 250 REHTNAP 110 -108.2760 70 -0.9843 66 2.3200 72 0.0211 73
73 184 SMARTFOLD 8 -0.4970 37 -0.0621 44 1.8990 73 0.2374 46
74 289 YANG_KDD 125 -179.2350 74 -1.4339 71 1.5720 74 0.0126 74
75 229 BHAGEERATH 147 -233.2000 77 -1.5864 73 1.5420 75 0.0105 76
76 014 PLATO 110 -178.3440 73 -1.6213 75 1.2520 76 0.0114 75
77 444 SCHENK-TORDA-SERVER 31 -50.0850 63 -1.6156 74 0.0000 77 0.0000 77
78 362 FORTMANN_SERVER 11 -21.2450 51 -1.9314 78 0.0000 77 0.0000 77
79 180 PHAISTOSSERVER 1 -2.0000 40 -2.0000 79 0.0000 77 0.0000 77
The cummulative z-scores in this table are calculated according to the following procedure (example for the "first" models):
1. Calculate z-scores from the raw scores for all "first" models (corresponding values from the main result table);
2. Remove outliers - models with zscores below the tolerance threshold (set to -2.0);
3. Recalculate z-scores on the reduced dataset;
4. Assign z-scores below the penalty threshold (either -2.0 or 0.0) to the value of this threshold.
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