13th Community Wide Experiment on the
Critical Assessment of Techniques for Protein Structure Prediction
Menu
TS Analysis (refienement targets) : Group performance based on combined z-scores
Results Home Table Browser Estimate of Model Accuracy Results RR Assessment Results
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.
  GDT_TS based   Assessors' formula
    Models:
    • Analysis on the models designated as "1"
    • Analysis on the models with the best scores

    • Targets:
    • TBM easy
    • TBM hard
    • TBM/FM
    • FM
The ranking of the groups is based on the analysis of zscores for GDT_TS.
G356G086G425G156G390G117G102G344G460G174G068G312G190G217G433G004G270G208G112G457G358G328G431G195G281G492G329G197G288G359G196G122Sum(Zscore>0.0)051015202530G356G086G425G156G390G117G102G344G460G174G068G312G190G217G433G004G270G208G112G457G358G328G431G195G281G492G329G197G288G359G196G122Groups
    #     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)
1 356 FEIGLAB 29 30.4670 1 1.0506 1 31.4340 1 1.0839 1
2 086 BAKER 29 21.8224 2 0.7525 2 24.4866 2 0.8444 2
3 425 BAKER-AUTOREFINE 29 20.1455 3 0.6947 3 22.9743 3 0.7922 3
4 156 Seok-server 29 17.9070 4 0.6175 4 18.3973 4 0.6344 4
5 390 Bhattacharya 29 14.1785 5 0.4889 5 14.2819 5 0.4925 5
6 117 Jones-UCL 29 9.6293 9 0.3320 11 13.7515 6 0.4742 7
7 102 Bhattacharya-Server 29 13.1079 6 0.4520 7 13.4647 7 0.4643 8
8 344 Kiharalab 29 12.8538 8 0.4432 9 13.1466 8 0.4533 9
9 460 McGuffin 29 13.0312 7 0.4494 8 13.1346 9 0.4529 10
10 174 Zhang-Refinement 27 8.5455 12 0.4646 6 12.9981 10 0.4814 6
11 068 Seok 29 8.5765 11 0.2957 13 12.3752 11 0.4267 12
12 312 MUFold_server 27 1.5804 16 0.2067 15 12.0316 12 0.4456 11
13 190 DC_refine 29 8.2978 13 0.2861 14 11.4749 13 0.3957 14
14 217 Boniecki_pred 28 7.6000 14 0.3429 10 11.4674 14 0.4095 13
15 433 AIR 29 9.3973 10 0.3240 12 10.9292 15 0.3769 15
16 004 YASARA 28 2.0243 15 0.1437 16 8.5517 16 0.3054 16
17 270 Huang 29 -2.5068 17 -0.0864 17 7.0247 17 0.2422 18
18 208 KIAS-Gdansk 29 -10.4628 19 -0.3608 21 6.4424 18 0.2222 19
19 112 AWSEM 27 -9.8841 18 -0.2179 20 5.8188 19 0.2155 20
20 457 Wallner 19 -22.2482 22 -0.1183 19 5.2959 20 0.2787 17
21 358 Spider 25 -10.8361 20 -0.1134 18 4.9279 21 0.1971 22
22 328 Kiharalab_RF2 29 -14.6666 21 -0.5057 23 4.7511 22 0.1638 23
23 431 Laufer 29 -40.1360 27 -1.3840 30 3.0248 23 0.1043 25
24 195 Seminoles 26 -35.8216 25 -1.1470 28 2.4734 24 0.0951 26
25 281 SHORTLE 29 -32.2888 24 -1.1134 27 1.7359 25 0.0599 27
26 492 wf-BAKER-UNRES 25 -41.3130 28 -1.3325 29 0.9895 26 0.0396 28
27 329 D-Haven 5 -52.1912 30 -0.8382 24 0.9889 27 0.1978 21
28 197 MESHI 3 -53.5118 31 -0.5039 22 0.4882 28 0.1627 24
29 288 UNRES 29 -43.4930 29 -1.4998 31 0.4328 29 0.0149 29
30 359 3DCNN 23 -37.1851 26 -1.0950 25 0.0194 30 0.0008 30
31 196 Grudinin 29 -32.2670 23 -1.1127 26 0.0194 30 0.0007 31
32 122 Forbidden 1 -58.0000 32 -2.0000 32 0.0000 32 0.0000 32
Protein Structure Prediction Center
Sponsored by the US National Institute of General Medical Sciences (NIH/NIGMS)
Please address any questions or queries to: casp@predictioncenter.org
© 2007-2018, University of California, Davis