16th Community Wide Experiment on the
Critical Assessment of Techniques for Protein Structure Prediction
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Multimer 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

Assessor's Ranking formula: 0.3*[0.3*Zscore(GDT_TS) + 0.3*Zscore(TM) + 0.4*Zscore(LDDT)] + 0.7*[Zscore(ICS)/3 + Zscore(IPS)/3 + Zscore(iLDDT)/3]
    #     GR
    name		     GR
    code		      Targets
     Count		     SUM Zscore
    (>0.0)		     Rank SUM
    Zscore (>0.0)		     AVG Zscore
    (>0.0)		     Rank AVG 
    Zscore  (>0.0)		     SUM Zscore
    (>-2.0)		     Rank SUM 
    Zscore  (>-2.0)		     AVG Zscore
    (>-2.0)		     Rank AVG 
    Zscore  (>-2.0)
1 Vfold 481 11 8.0056 1 0.6671 1 2.4320 3 0.2211 5
2 CoDock 262 11 7.9009 2 0.6584 2 5.1666 1 0.4697 1
3 KiharaLab 294 11 7.8003 3 0.6500 3 4.3953 2 0.3996 2
4 GuangzhouRNA-human 183 10 6.8880 4 0.6262 4 1.5638 5 0.3564 4
5 LCBio 189 10 6.5269 5 0.5934 5 1.7743 4 0.3774 3
6 CSSB_experimental 286 11 5.2851 6 0.4404 11 1.2712 6 0.1156 12
7 NKRNA-s 028 11 5.0599 7 0.4217 14 0.8619 7 0.0784 13
8 AF3-server 304 10 4.5224 8 0.4522 9 -0.1363 9 0.1864 8
9 Zheng 462 11 4.2783 9 0.3565 15 0.0957 8 0.0087 15
10 Yang-Server 052 10 3.3127 10 0.3012 17 -4.5288 13 -0.2529 23
11 falcon2 208 9 3.2138 11 0.3214 16 -6.0657 14 -0.2295 21
12 elofsson 241 11 3.1740 12 0.2645 19 -1.1286 10 -0.1026 18
13 GuangzhouRNA-meta 417 10 2.7434 13 0.2494 20 -3.3325 12 -0.1333 19
14 MIEnsembles-Server 110 11 2.1103 14 0.1759 24 -2.7116 11 -0.2465 22
15 Bhattacharya 369 4 1.7007 15 0.4252 13 -13.5210 21 0.1198 11
16 isyslab-hust 235 3 1.4978 16 0.4993 6 -15.5206 22 0.1598 9
17 GuangzhouRNA_AI 317 6 1.4134 17 0.2356 21 -11.8115 19 -0.3019 24
18 dNAfold 448 2 1.3737 18 0.4579 7 -17.5976 28 0.2012 6
19 dMNAfold 143 2 1.3737 18 0.4579 7 -17.5976 28 0.2012 6
20 406 159 3 1.3391 20 0.4464 10 -15.7708 25 0.0764 14
21 405 325 3 1.2787 21 0.4262 12 -15.5942 23 0.1353 10
22 Huang-HUST 091 5 1.1486 22 0.1914 23 -12.9302 20 -0.1860 20
23 GromihaLab 272 8 1.1310 23 0.1257 27 -9.5815 17 -0.4477 28
24 Diff 033 3 0.9013 24 0.3004 18 -16.1954 26 -0.0651 16
25 SoutheRNA 156 9 0.8689 25 0.0869 30 -9.2715 16 -0.5857 29
26 kiharalab_server 267 4 0.8243 26 0.1649 26 -17.1484 27 -0.7871 32
27 OpenComplex 167 8 0.7942 27 0.0882 29 -8.8635 15 -0.3579 26
28 OpenComplex_Server 450 7 0.7526 28 0.0941 28 -10.4250 18 -0.3464 25
29 GeneSilico 338 4 0.6762 29 0.1691 25 -15.6261 24 -0.4065 27
30 B-LAB 231 3 0.2275 30 0.0758 31 -17.9134 30 -0.6378 30
31 RNApolis 063 1 0.2009 31 0.2009 22 -20.0709 32 -0.0709 17
32 RNAFOLDX 435 2 0.0509 32 0.0255 32 -19.5629 31 -0.7814 31
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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