16th Community Wide Experiment on the
Critical Assessment of Techniques for Protein Structure Prediction
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RNA Predictions Analysis : Group performance based on combined z-scores
Results Home Table Browser
  • Analysis on the models designated as "1"
  • Analysis on the models with the best scores
The final ranking was generated according to the formula: 0.3*Z-score(TM) + 0.3*Z-score(GDTTS) + 0.4*Z-score(LDDT).
    #     GR
    name		     GR
    code		     Targets Count     SUM Zscore
    (>0.0)		     Rank SUM Zscore
    (>0.0)		     AVG Zscore
    (>0.0)		     Rank AVG Zscore
    (>0.0)
1 Vfold 481 33 27.3168 1 0.8278 3
2 GuangzhouRNA-human 183 32 24.0427 2 0.7513 4
3 KiharaLab 294 34 23.9823 3 0.7054 7
4 Yang-Server 052 32 18.4999 4 0.5781 12
5 GeneSilico 338 34 18.0046 5 0.5295 14
6 elofsson 241 34 17.3175 6 0.5093 18
7 CSSB_experimental 286 34 16.9891 7 0.4997 22
8 Diff 033 32 16.8963 8 0.5280 15
9 AF3-server 304 34 16.5855 9 0.4878 25
10 RNAFOLDX 435 32 15.7111 10 0.4910 24
11 Bhattacharya 369 31 15.5553 11 0.5018 21
12 CoDock 262 24 15.2819 12 0.6367 9
13 GuangzhouRNA-meta 417 33 14.7437 13 0.4468 26
14 RNApolis 063 27 14.7266 14 0.5454 13
15 GromihaLab 272 29 14.7134 15 0.5074 19
16 BRIQX 238 27 14.0407 16 0.5200 16
17 LCBio 189 27 13.8765 17 0.5139 17
18 Zheng 462 34 13.3293 18 0.3920 31
19 NKRNA-s 028 34 12.7633 19 0.3754 34
20 Yang-Multimer 456 24 12.0773 20 0.5032 20
21 falcon2 208 31 11.9522 21 0.3856 32
22 MIEnsembles-Server 110 34 11.2678 22 0.3314 42
23 dNAfold 448 27 9.9307 23 0.3678 36
24 405 325 23 9.7991 24 0.4260 27
25 406 159 25 9.2046 25 0.3682 35
26 OpenComplex 167 33 8.6563 26 0.2623 44
27 OpenComplex_Server 450 32 7.6184 27 0.2381 45
28 GuangzhouRNA_AI 317 33 7.4756 28 0.2265 46
29 dfr 165 21 7.3641 29 0.3507 38
30 RNA_Dojo 006 24 7.0720 30 0.2947 43
31 nfRNA 307 17 5.9728 31 0.3513 37
32 B-LAB 231 32 5.5436 32 0.1732 48
33 Huang-HUST 091 13 4.9451 33 0.3804 33
34 LCDD-team 055 5 4.6393 34 0.9279 1
35 dMNAfold 143 11 4.3783 35 0.3980 30
36 ShanghaiTech-human 298 10 4.1120 36 0.4112 28
37 ShanghaiTech-server 423 10 4.1120 36 0.4112 28
38 SNU-CHEM-lig 408 5 3.0331 38 0.6066 10
39 SoutheRNA 156 33 2.8839 39 0.0874 54
40 kiharalab_server 267 28 2.6438 40 0.0944 52
41 comppharmunibas 020 3 2.5449 41 0.8483 2
42 OmniFold 400 4 2.3555 42 0.5889 11
43 FrederickFolding 276 3 2.1730 43 0.7243 6
44 mmagnus 403 4 1.9811 44 0.4953 23
45 GeneSilicoRNA-server 306 23 1.9702 45 0.0857 55
46 SimRNA-server 094 25 1.2376 46 0.0495 57
47 MULTICOM_ligand 207 5 0.8699 47 0.1740 47
48 KUMC 227 5 0.8491 48 0.1698 49
49 test001 202 1 0.7429 49 0.7429 5
50 Zheng-Multimer 147 1 0.6453 50 0.6453 8
51 isyslab-hust 235 33 0.5326 51 0.0161 59
52 PerezLab_Gators 358 13 0.3656 52 0.0281 58
53 MULTICOM_LLM 319 1 0.3396 53 0.3396 39
54 MULTICOM_AI 331 1 0.3396 53 0.3396 39
55 MULTICOM_GATE 425 1 0.3396 53 0.3396 39
56 MULTICOM 051 2 0.3396 53 0.1698 50
57 MULTICOM_human 345 2 0.3396 53 0.1698 50
58 SwRI 026 1 0.0920 58 0.0920 53
59 AIR 367 1 0.0696 59 0.0696 56
60 PocketTracer 464 5 0.0442 60 0.0088 61
61 UDMod 447 2 0.0222 61 0.0111 60
62 thermomaps 169 25 0.0000 62 0.0000 62
63 UNRES 261 19 0.0000 62 0.0000 62
64 Dokholyan 439 9 0.0000 62 0.0000 62
D1273  R1203  R1205  R1209  R1211  R1212  R1221s2  R1221s3  R1224s2  R1224s3  R1241  R1242  R1248  R1250  R1251  R1252  R1253v1  R1253v2  R1254  R1255  R1256  R1261  R1262  R1263  R1264  R1271  R1281  R1283v1  R1285  R1286  R1288  R1289  R1290  R1291  R1293  R1296 
The cummulative z-scores in this table are calculated according to the following procedure (example for the "first" models):
1. Calculate zscores 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 zscores 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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