15th Community Wide Experiment on the
Critical Assessment of Techniques for Protein Structure Prediction
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TS Analysis : Z-score based relative group performance
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  GDT_TS   Assessors' formulae

    Models:

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

    Groups:

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

    Formula and Domains:

    • CASP15 formula for ALL domains:
           1/6*(GDT_HA + reLLG_lddt + ASE) + 1/16*(LDDT + CAD_aa + SG + SC_error) + 1/12*(MolProbity + BB_error + DipDiff)

      •  
    • CASP12 formula for TBM domains: GDT_HA + (SphereGrinder + LDDT + CAD_aa)/3 + ASE
    • CASP12 formula for FM + TBM/FM domains: GDT_TS + QCS + 0.1*Molprobity
    • CASP12 formula for FM domains: GDT_TS + QCS + 0.1*Molprobity
    #     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)
1 278 PEZYFoldings 107 28.2448 2 0.3014 2 70.8310 1 0.6620 1
2 162 UM-TBM 109 33.4626 1 0.3070 1 68.5623 2 0.6290 3
3 229 Yang-Server 108 20.0022 4 0.2037 4 61.2772 3 0.5674 4
4 074 DFolding 109 25.8625 3 0.2373 3 61.0695 4 0.5603 5
5 439 Yang 108 16.2255 5 0.1688 5 59.0136 5 0.5464 6
6 180 McGuffin 109 2.6214 19 0.0240 31 49.7262 6 0.4562 10
7 367 MULTICOM 109 2.3021 21 0.0211 33 48.8284 7 0.4480 12
8 475 MULTICOM_refine 109 13.6109 6 0.1249 9 48.8258 8 0.4479 14
9 185 BAKER 109 4.3748 11 0.0401 22 47.9903 9 0.4403 15
10 003 MULTICOM_human 109 2.4662 20 0.0226 32 47.9002 10 0.4395 16
11 158 MULTICOM_deep 109 9.8068 8 0.0900 14 46.2544 11 0.4244 22
12 086 MULTICOM_qa 109 9.4572 9 0.0868 15 46.2344 12 0.4242 23
13 120 MULTICOM_egnn 109 11.9136 7 0.1093 12 45.7611 13 0.4198 26
14 035 Manifold-E 109 -5.7186 34 -0.0525 54 45.1978 14 0.4147 27
15 119 Kiharalab 109 -0.9270 25 -0.0085 43 45.1273 15 0.4140 28
16 360 MUFold_H 109 4.2297 12 0.0388 23 44.2540 16 0.4060 29
17 446 ColabFold 109 4.9637 10 0.0455 21 44.0177 17 0.4038 30
18 461 colabfold_human 109 2.9425 18 0.0270 30 43.2644 18 0.3969 32
19 037 Wallner 109 4.0416 14 0.0371 26 43.1163 19 0.3956 35
20 204 Asclepius 108 -1.5361 26 0.0043 35 43.0518 20 0.3986 31
21 008 bench 108 3.7085 16 0.0529 19 42.8291 21 0.3966 34
22 248 Manifold 109 -6.4946 39 -0.0596 56 42.8201 22 0.3928 36
23 288 DFolding-server 109 4.0592 13 0.0372 24 41.9520 23 0.3849 38
24 320 Elofsson 92 -23.6888 59 0.1121 11 41.7392 24 0.4537 11
25 298 MUFold 109 3.8458 15 0.0353 27 40.9513 25 0.3757 40
26 166 RaptorX 109 2.9560 17 0.0271 29 40.5804 26 0.3723 42
27 092 Agemo_mix 109 -4.2573 32 -0.0391 53 40.4984 27 0.3715 43
28 225 ShanghaiTech 109 -11.8306 47 -0.1085 66 40.1253 28 0.3681 46
29 125 UltraFold_Server 109 1.0805 22 0.0099 34 40.0715 29 0.3676 47
30 054 UltraFold 107 -3.9657 30 0.0003 37 39.7243 30 0.3713 44
31 208 B11L 102 -10.2095 44 0.0372 25 38.2788 31 0.3753 41
32 188 GuijunLab-DeepDA 109 -0.4924 23 -0.0045 39 38.2400 32 0.3508 54
33 399 BeijingAIProtein 103 -12.5932 49 -0.0058 40 38.0237 33 0.3692 45
34 398 ChaePred 107 -5.5144 33 -0.0142 44 37.9319 34 0.3545 50
35 466 Shennong 105 -2.8649 28 0.0489 20 37.3845 35 0.3560 48
36 462 MultiFOLD 109 -12.1034 48 -0.1110 67 36.6712 36 0.3364 56
37 098 GuijunLab-Assembly 109 -2.6529 27 -0.0243 48 36.4567 37 0.3345 57
38 169 GuijunLab-Human 107 -6.2358 36 -0.0209 46 36.2609 38 0.3389 55
39 131 Kiharalab_Server 109 -10.1914 43 -0.0935 62 36.0746 39 0.3310 58
40 383 server_124 109 -6.7143 40 -0.0616 57 35.8061 40 0.3285 60
41 282 GuijunLab-Threader 109 -4.1330 31 -0.0379 51 35.6270 41 0.3269 63
42 342 hFold_human 109 -0.8240 24 -0.0076 42 35.1927 42 0.3229 65
43 443 BAKER-SERVER 109 -14.2912 52 -0.1311 72 35.1349 43 0.3223 67
44 353 hFold 106 -5.7866 35 0.0020 36 35.0783 44 0.3309 59
45 270 NBIS-AF2-standard 109 -2.8881 29 -0.0265 49 34.6335 45 0.3177 68
46 151 IntFOLD7 109 -20.4751 57 -0.1878 78 34.4688 46 0.3162 69
47 354 hks1988 109 -6.4477 38 -0.0592 55 34.4345 47 0.3159 70
48 477 DMP 96 -36.1319 64 -0.1055 65 34.0681 48 0.3549 49
49 245 FoldEver 109 -9.9724 42 -0.0915 61 33.8486 49 0.3105 72
50 481 GuijunLab-Meta 107 -6.2794 37 -0.0213 47 33.6273 50 0.3143 71
51 269 AP_1 109 -14.1961 51 -0.1302 71 33.5073 51 0.3074 74
52 261 server_122 109 -10.4840 45 -0.0962 63 33.4822 52 0.3072 75
53 441 OpenFold 108 -19.6548 55 -0.1635 75 33.2518 53 0.3079 73
54 264 server_125 109 -10.9894 46 -0.1008 64 33.0675 54 0.3034 78
55 433 OpenFold-SingleSeq 108 -19.8857 56 -0.1656 76 32.9778 55 0.3054 77
56 018 server_123 109 -13.1209 50 -0.1204 69 32.9353 56 0.3022 79
57 385 FoldEver-Hybrid 101 -22.2976 58 -0.0624 58 32.9350 57 0.3261 64
58 403 server_126 109 -8.4517 41 -0.0775 59 32.8951 58 0.3018 80
59 494 Venclovas 74 -78.8584 71 -0.1197 68 32.2406 59 0.4357 18
60 450 ManiFold-serv 109 -14.4926 53 -0.1330 73 30.3083 60 0.2781 82
61 187 TRFold 108 -27.0165 60 -0.2316 83 29.4315 61 0.2725 83
62 089 GuijunLab-RocketX 108 -15.7410 54 -0.1272 70 29.3099 62 0.2714 84
63 423 trComplex 108 -28.1287 61 -0.2419 85 29.2205 63 0.2706 85
64 215 XRC_VU 80 -61.0768 68 -0.0385 52 26.1843 64 0.3273 61
65 133 ShanghaiTech-TS-SER 105 -32.4376 62 -0.2327 84 26.0202 65 0.2478 90
66 434 Coqualia 104 -35.7053 63 -0.2472 87 24.0265 66 0.2310 92
67 275 Bhattacharya 109 -49.9268 67 -0.4580 94 23.1218 67 0.2121 94
68 374 Zheng 45 -121.1419 81 0.1524 6 22.9098 68 0.5091 7
69 165 FTBiot0119 109 -76.4316 69 -0.7012 101 22.8312 69 0.2095 96
70 097 Graphen_Medical 73 -82.3454 72 -0.1417 74 22.4165 70 0.3071 76
71 227 GinobiFold 106 -43.2247 66 -0.3512 92 22.2223 71 0.2096 95
72 011 GinobiFold-SER 105 -36.4549 65 -0.2710 90 21.8518 72 0.2081 97
73 455 Seder2022easy 106 -83.5517 73 -0.7316 103 21.8495 73 0.2061 98
74 390 NBIS-AF2-multimer 50 -114.7135 80 0.0657 17 21.2860 74 0.4257 20
75 239 Yang-Multimer 45 -122.2089 82 0.1287 8 21.2429 75 0.4721 9
76 067 ESM-single-sequence 93 -77.8559 70 -0.4931 95 20.0903 76 0.2160 93
77 071 RaptorX-Multimer 45 -128.2922 85 -0.0065 41 19.6842 77 0.4374 17
78 348 Takeda-Shitaka_Lab 45 -124.3999 84 0.0800 16 19.1241 78 0.4250 21
79 216 Seder2022hard 94 -96.8854 77 -0.7115 102 19.0334 79 0.2025 99
80 147 SHT 96 -86.0486 74 -0.6255 99 18.2032 80 0.1896 102
81 150 Grudinin 44 -130.8786 87 -0.0200 45 16.7652 81 0.3810 39
82 478 Agemo 109 -90.3782 76 -0.8292 105 16.1139 82 0.1478 106
83 073 DFolding-refine 106 -89.0381 75 -0.7834 104 14.5185 83 0.1370 108
84 140 EMBER3D 92 -132.7949 88 -1.0739 113 13.8847 84 0.1509 105
85 444 CoDock 47 -135.5668 89 -0.2461 86 12.3283 85 0.2623 87
86 117 QUIC 103 -110.2350 79 -0.9537 109 11.2555 86 0.1093 111
87 276 PICNIC 102 -129.3268 86 -1.1307 115 10.7159 87 0.1051 112
88 314 Pierce 27 -169.8130 98 -0.2153 79 10.5512 88 0.3908 37
89 123 RostlabUeFOFold 82 -155.9174 92 -1.2429 118 9.2273 89 0.1125 110
90 493 Shen-CAPRI 34 -160.2618 94 -0.3018 91 8.4582 90 0.2488 89
91 091 UNRES 103 -105.8942 78 -0.9116 107 8.1109 91 0.0787 117
92 205 Zou 41 -160.8293 95 -0.6056 98 8.0372 92 0.1960 100
93 257 WL_team 93 -123.6216 83 -0.9852 112 8.0090 93 0.0861 116
94 370 wuqi 87 -143.2171 91 -1.1404 116 7.7618 94 0.0892 114
95 350 ClusPro 42 -174.4625 100 -0.9634 111 5.6107 95 0.1336 109
96 312 Fernandez-Recio 34 -181.0940 102 -0.9145 108 5.1969 96 0.1528 104
97 199 TB_model_prediction 13 -191.2786 109 0.0555 18 5.1589 97 0.3968 33
98 456 AIchemy_LIG2 13 -194.8586 113 -0.2199 81 4.5994 98 0.3538 51
99 325 AIchemy_LIG 13 -194.8586 113 -0.2199 81 4.5994 98 0.3538 51
100 347 AIchemy_LIG3 13 -194.8543 112 -0.2196 80 4.5960 100 0.3535 53
101 234 Panlab 109 -143.0865 90 -1.3127 120 4.3993 101 0.0404 120
102 304 Manifold-X 18 -189.7355 107 -0.4298 93 4.2898 102 0.2383 91
103 447 DELCLAB 97 -157.8925 93 -1.3803 121 3.8920 103 0.0401 121
104 291 Kozakov-Vajda 28 -188.8308 106 -0.9582 110 3.8780 104 0.1385 107
105 280 ACOMPMOD 78 -193.4552 111 -1.6853 129 3.7334 105 0.0479 119
106 064 SHORTLE 51 -174.8588 101 -1.1541 117 3.6861 106 0.0723 118
107 132 TensorLab 11 -198.8770 116 -0.2615 89 3.5494 107 0.3227 66
108 219 Pan_Server 104 -164.4871 96 -1.4855 125 2.9232 108 0.0281 127
109 046 Manifold-LC-E 15 -196.1421 115 -0.5428 97 2.8952 109 0.1930 101
110 338 Convex-PL 6 -206.2240 120 -0.0373 50 2.6877 110 0.4479 13
111 201 UTMB 6 -205.8203 119 0.0299 28 2.5274 111 0.4212 25
112 368 FALCON2 107 -182.3897 104 -1.6672 127 2.4164 112 0.0226 128
113 333 FALCON0 107 -182.1541 103 -1.6650 126 2.4086 113 0.0225 129
114 236 noxelis 5 -207.4929 123 0.1014 13 2.4028 114 0.4806 8
115 352 KORP-PL 8 -204.0169 118 -0.2521 88 2.3884 115 0.2985 81
116 427 MESHI_server 76 -172.4795 99 -1.4010 122 2.3765 116 0.0313 124
117 362 MESHI 70 -165.2689 97 -1.2467 119 2.1919 117 0.0313 123
118 472 ddquest 5 -207.4390 122 0.1122 10 2.1296 118 0.4259 19
119 460 Convex-PL-R 6 -207.0127 121 -0.1688 77 1.9614 119 0.3269 62
120 122 zax 8 -209.0193 124 -0.8774 106 1.4544 120 0.1818 103
121 052 Gonglab-THU 109 -190.9123 108 -1.7515 130 1.4451 121 0.0133 130
122 397 bio3d 2 -214.0009 129 -0.0005 38 1.2791 122 0.6396 2
123 412 MeilerLab 3 -211.5698 125 0.1434 7 1.2702 123 0.4234 24
124 315 Cerebra 109 -192.3969 110 -1.7651 131 1.0310 124 0.0095 131
125 498 Spider 33 -200.0590 117 -1.4563 123 0.9318 125 0.0282 126
126 014 FEIGLAB 3 -212.2364 126 -0.0788 60 0.7872 126 0.2624 86
127 212 BhageerathH-Pro 103 -185.0512 105 -1.6801 128 0.6974 127 0.0068 132
128 006 Sun_Tsinghua 22 -213.0850 127 -1.7766 132 0.6866 128 0.0312 125
129 285 PerezLab_Gators 3 -213.5777 128 -0.5259 96 0.2630 129 0.0877 115
130 488 CSRC_ICM 1 -217.1089 132 -1.1089 114 0.2540 130 0.2540 88
131 088 coco 2 -215.3389 130 -0.6695 100 0.2100 131 0.1050 113
132 366 GatorsML 3 -216.4563 131 -1.4854 124 0.1091 132 0.0364 122
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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