13th Community Wide Experiment on the
Critical Assessment of Techniques for Protein Structure Prediction
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TS Analysis (refienement targets) : Group performance based on combined z-scores
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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
.
#
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
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US National Institute of General Medical Sciences (NIH/NIGMS)
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