14th 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:
All targets
Regular targets
Extended time-frame 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
335
FEIG
44
33.8049
2
0.7683
2
35.2441
1
0.8010
1
2
013
FEIG-S
44
34.0920
1
0.7748
1
34.9871
2
0.7952
2
3
473
BAKER
44
24.8950
4
0.5658
4
32.0784
3
0.7291
3
4
323
DellaCorteLab
44
25.3405
3
0.5759
3
25.5121
4
0.5798
4
5
999
---STARTING-MODEL---
44
24.1972
5
0.5499
5
24.6528
5
0.5603
5
6
403
BAKER-experimental
44
5.8909
13
0.1339
19
23.7376
6
0.5395
7
7
236
DeepMUSICS
44
20.7449
6
0.4715
8
21.4627
7
0.4878
9
8
253
Bhattacharya
44
20.1427
7
0.4578
9
20.9159
8
0.4754
10
9
149
Bhattacharya-Server
44
19.8619
8
0.4514
10
20.6578
9
0.4695
11
10
071
Kiharalab
44
9.4455
12
0.2147
18
18.5737
10
0.4221
13
11
100
AIR
44
16.6137
9
0.3776
12
17.9345
11
0.4076
15
12
294
JLU_Comp_Struct_Bio
31
-9.1224
20
0.5444
6
16.9672
12
0.5473
6
13
360
UNRES
42
11.3944
11
0.3665
14
16.7867
13
0.3997
16
14
220
McGuffin
37
1.5324
14
0.4198
11
16.4612
14
0.4449
12
15
470
PerillaGroup
44
12.5141
10
0.2844
16
15.7922
15
0.3589
19
16
070
Seok-server
37
-0.1070
15
0.3755
13
15.2839
16
0.4131
14
17
075
MULTICOM-CLUSTER
30
-13.5244
22
0.4825
7
14.7872
17
0.4929
8
18
349
Spider
36
-4.6798
17
0.3145
15
14.3063
18
0.3974
17
19
394
Kiharalab_Refine
44
-1.8841
16
-0.0428
22
13.8675
19
0.3152
20
20
193
Seok
37
-4.7458
18
0.2501
17
13.4154
20
0.3626
18
21
341
Risoluto
44
-14.6968
23
-0.3340
24
13.1957
21
0.2999
21
22
003
SHORTLE
44
-41.0634
29
-0.9333
31
12.8364
22
0.2917
22
23
233
Frustration_Refine
40
-6.7100
19
0.0323
21
9.2749
23
0.2319
25
24
270
Beta
34
-35.4810
27
-0.4553
25
8.7382
24
0.2570
23
25
423
Seminoles
41
-31.8470
26
-0.6304
26
8.5760
25
0.2092
26
26
018
UNRES-template
44
-11.7077
21
-0.2661
23
7.8377
26
0.1781
27
27
434
GLoSA
32
-22.4822
24
0.0474
20
7.7991
27
0.2437
24
28
340
Pharmulator
44
-30.7712
25
-0.6993
28
7.4497
28
0.1693
28
29
081
MUFOLD
44
-36.5884
28
-0.8316
29
5.0600
29
0.1150
30
30
291
Protein-blacksmith
44
-61.1672
32
-1.3902
34
2.4783
30
0.0563
31
31
304
Jones-UCL
19
-62.4972
33
-0.6577
27
2.3957
31
0.1261
29
32
192
AILON
44
-44.4560
30
-1.0104
32
2.1867
32
0.0497
32
33
131
PerezLab_Gators
33
-77.6181
34
-1.6854
36
0.8554
33
0.0259
33
34
389
AWSEM_PCA
43
-49.6340
31
-1.1078
33
0.4910
34
0.0114
35
35
352
laufer_ros
26
-79.2883
35
-1.6649
35
0.4400
35
0.0169
34
36
080
FOLDYNE
6
-81.5350
36
-0.9225
30
0.0037
36
0.0006
36
37
342
CUTSP
7
-86.1473
37
-1.7353
37
0.0000
37
0.0000
37
Protein Structure Prediction Center
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US National Institute of General Medical Sciences (NIH/NIGMS)
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