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)
1 009 XU-YING 36 3.8040 17 0.0614 41 21.6920 1 0.3499 40
2 005 JONES 21 17.3490 1 0.8261 3 19.9740 2 0.9511 3
3 061 YANG-ANSUEI 33 6.2650 10 0.0994 40 19.5420 3 0.3102 42
4 217 SIPPL-MANFRED 21 14.8420 2 0.7068 6 15.2050 4 0.7240 7
5 035 BAKER 18 13.9580 3 0.7754 4 15.1710 5 0.8428 4
6 074 STERNBERG 23 10.7470 4 0.4673 12 13.4700 6 0.5857 17
7 017 SJOLANDER-THOMAS 27 4.5390 14 0.1681 35 12.2490 7 0.4537 26
8 166 SB-FOLD 17 7.5980 9 0.4469 14 11.1170 8 0.6539 13
9 176 UNAGI 14 8.5820 7 0.6130 9 10.9280 9 0.7806 5
10 092 DUNBRACK 14 10.4540 5 0.5502 10 10.7780 10 0.5673 18
11 028 GODZIK 22 4.1440 16 0.1802 31 10.7590 11 0.4678 24
12 019 UCSC-COMPBIO 24 4.2270 15 0.1761 34 10.6590 12 0.4441 27
13 163 SKOL-ORT-KOL 10 8.6880 6 0.8688 2 10.1240 13 1.0124 2
14 212 BRYANT 13 4.8990 12 0.3768 16 9.0250 14 0.6942 10
15 136 BLUNDELL-TL 13 8.0510 8 0.6193 8 8.7850 15 0.6758 12
16 072 WEBER 30 -5.9980 74 -0.1999 59 7.5400 16 0.2513 51
17 045 TORDA 20 2.4210 25 0.1211 39 7.5300 17 0.3765 34
18 076 BASS-MICHAEL 29 -3.6090 67 -0.1244 50 7.2730 18 0.2508 52
19 105 MOULT-JOHN 18 4.6930 13 0.2607 26 6.9800 19 0.3878 33
20 022 SAMUDRALA-AB 13 2.3340 26 0.1795 32 6.9180 20 0.5322 21
21 096 OSGDJ 9 2.7550 21 0.3061 20 6.5040 21 0.7227 8
22 220 LUETHY-ROLAND 30 -4.8480 70 -0.1616 52 6.3810 22 0.2127 55
23 054 BATEMAN-ALEX 14 5.0250 11 0.3589 19 6.3640 23 0.4546 25
24 266 BYSTROFF-CHRIS 18 -0.6250 50 -0.0347 46 6.3220 24 0.3512 39
25 143 SOLOVYEV-VICTOR 13 3.6290 18 0.2792 22 6.2580 25 0.4814 22
26 185 SCHERAGA 8 -1.0600 54 -0.1325 51 5.7130 26 0.7141 9
27 168 EISENBERG 31 -8.1150 77 -0.2618 61 5.6500 27 0.1823 61
28 179 GMD-SCAI 10 3.0060 20 0.3006 21 5.4680 28 0.5468 20
29 190 KOLINSKOL 14 2.6320 24 0.1880 30 5.2570 29 0.3755 36
30 040 OLSZEWSKI 26 -2.4830 64 -0.0955 49 5.0770 30 0.1953 57
31 034 LEVITT 14 -2.5840 65 -0.1846 55 4.9580 31 0.3541 38
32 203 BOURNE 28 -8.4170 78 -0.3006 63 4.6240 32 0.1651 63
33 273 REVA-BORIS 28 -20.0450 82 -0.7159 78 4.5730 33 0.1633 64
34 033 ELOFSSON-ARNE 11 1.5720 32 0.1429 38 4.1410 34 0.3765 35
35 085 PARK-TEICHMANN 12 -4.9030 71 -0.3772 68 3.9560 35 0.3043 44
36 090 VALENCIA-ALFONSO 12 1.8850 28 0.1571 37 3.6490 36 0.3041 45
37 142 TAYLOR-WILLIE 9 1.4250 35 0.1583 36 3.5720 37 0.3969 30
38 008 LUND 13 -0.8230 53 -0.0633 47 3.3740 38 0.2595 50
39 162 COULSON 8 1.4210 36 0.1776 33 3.3520 39 0.4190 28
40 003 HUBBARD 8 -0.0340 43 -0.0043 43 3.3320 40 0.4165 29
41 060 LOMIZE 5 2.6780 23 0.5356 11 3.1690 41 0.6338 15
42 066 FISCHER-DANIEL 19 -3.2380 66 -0.1704 53 3.1440 42 0.1655 62
43 044 SALI-ANDREJ 8 3.1240 19 0.3905 15 3.1240 43 0.3905 32
44 108 FIDELIS 4 2.7190 22 0.6797 7 2.7190 44 0.6797 11
45 201 TATSUYA-AKUTSU 31 -17.5400 81 -0.5658 72 2.6410 45 0.0852 72
46 254 CHEN-KEASAR 4 1.4680 33 0.3670 17 2.5450 46 0.6362 14
47 224 FINKELSTEIN-ALEXEI 15 -10.0290 79 -0.6686 77 2.2090 47 0.1473 66
48 263 MOE-CCG 3 2.1850 27 0.7283 5 2.1850 48 0.7283 6
49 148 KOONIN 5 1.1730 38 0.2346 28 1.9830 49 0.3966 31
50 047 ROSE 3 1.3820 37 0.4607 13 1.8810 50 0.6270 16
51 262 DLAKIC-MENSUR 7 1.8530 29 0.2647 24 1.8530 51 0.2647 49
52 023 TIMMS-DAVE 6 -0.1550 45 -0.0258 45 1.8490 52 0.3082 43
53 155 SAMUDRALA-CM 6 1.5800 31 0.2633 25 1.7650 53 0.2942 46
54 100 PONDER-JAY 8 -1.5740 59 -0.1968 57 1.7420 54 0.2177 54
55 272 LEE-JUNG 11 -3.6670 68 -0.3334 66 1.6800 55 0.1527 65
56 182 NIH-CIT 9 -5.3360 72 -0.5929 74 1.6760 56 0.1862 60
57 233 VIETH 5 -0.3630 46 -0.0726 48 1.6370 57 0.3274 41
58 281 STRUCT-BIOINF 6 1.5950 30 0.2658 23 1.5950 58 0.2658 48
59 053 AVBELJ-FRANC 4 1.4590 34 0.3648 18 1.4590 59 0.3648 37
60 257 GREGORET-LYDIA 3 -0.5690 48 -0.1897 56 1.4310 60 0.4770 23
61 189 ABAGYAN-RUBEN 7 -0.0360 44 -0.0051 44 1.3290 61 0.1899 59
62 277 DEERFIELD 11 -6.2790 75 -0.5708 73 1.2470 62 0.1134 70
63 215 ZHU-JUN 9 -5.8160 73 -0.6462 75 1.2440 63 0.1382 67
64 222 RWCP 14 -4.6220 69 -0.3301 65 1.1640 64 0.0831 73
65 293 BOWER 1 1.1210 39 1.1210 1 1.1210 65 1.1210 1
66 173 FLAKE 2 0.3960 40 0.1980 29 1.0940 66 0.5470 19
67 147 BMERC 14 -14.1120 80 -1.0080 80 0.9640 67 0.0689 74
68 156 BENNER-COHEN 9 -1.8270 61 -0.1827 54 0.9130 68 0.0913 71
69 042 GODDARD 5 -1.5510 58 -0.3102 64 0.6250 69 0.1250 69
70 081 FLOHIL 3 -1.4250 56 -0.4750 69 0.5750 70 0.1917 58
71 084 DIFRANCESCO 10 -6.4890 76 -0.6489 76 0.5610 71 0.0561 76
72 026 FORSTER-MARK 2 -1.4490 57 -0.7245 79 0.5510 72 0.2755 47
73 195 WOLYNES-PETER 4 -2.2320 63 -0.5580 71 0.5250 73 0.1313 68
74 282 MIRNY-LEONID 2 -0.4310 47 -0.2155 60 0.4170 74 0.2085 56
75 093 BINDEWALD 4 -0.7870 52 -0.1968 57 0.2640 75 0.0660 75
76 232 FIDELIS-JOHANNES 1 0.2410 41 0.2410 27 0.2410 76 0.2410 53
77 249 CMD-WUSTL 2 -0.5760 49 -0.2880 62 0.0690 77 0.0345 77
78 191 COHEN-FRED 2 -0.6760 51 -0.3380 67 0.0350 78 0.0175 79
79 055 EGNER 1 0.0250 42 0.0250 42 0.0250 79 0.0250 78
80 129 GLAXOWELLCOME-BIOINF 4 -1.9360 62 -0.4840 70 0.0000 80 0.0000 80
81 268 FRESCO-HALITSKY-LESK-WINGO 1 -1.1240 55 -1.1240 81 0.0000 80 0.0000 80
82 291 HAEDENER 1 -1.7440 60 -1.7440 82 0.0000 80 0.0000 80
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.
Protein Structure Prediction Center
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