`
GR code
GR name
Domains Count
SUM Zscore (>-2.0)
Rank SUM Zscore (>-2.0)
AVG Zscore (>-2.0)
Rank AVG Zscore (>-2.0)
AVG Zscore (>0.0)
Rank AVG Zscore (>0.0)
1
010
Jones
16
4.5680
1
0.2855
7
8.4780
1
0.5299
6
2
014
Matsuo
16
0.9150
6
0.0572
11
5.6180
2
0.3511
12
3
009
Hubbard
6
4.4110
2
0.7352
2
4.7380
3
0.7897
2
4
022
Sippl
12
-3.3590
26
-0.2799
14
4.3340
4
0.3612
10
5
026
Weber-Harrison
5
2.3000
3
0.4600
4
2.5840
5
0.5168
7
6
017
OML
3
0.3020
9
0.1007
9
2.3020
6
0.7673
3
7
020
Sali
3
1.7380
4
0.5793
3
2.1180
7
0.7060
4
8
007
Covell
1
1.4680
5
1.4680
1
1.4680
8
1.4680
1
9
001
Abagyan
6
-2.4580
24
-0.4097
17
1.2370
9
0.2062
13
10
016
Moult
3
0.8710
7
0.2903
6
1.1980
10
0.3993
9
11
024
Vinals
2
-0.6600
15
-0.3300
16
1.1840
11
0.5920
5
12
019
Pedersen
2
-0.6400
14
-0.3200
15
0.7070
12
0.3535
11
13
015
Mosenkis
1
0.4160
8
0.4160
5
0.4160
13
0.4160
8
14
025
Vriend
3
0.1840
11
0.0613
10
0.3930
14
0.1310
16
15
023
Vihinen
2
-0.1570
13
-0.0785
13
0.3350
15
0.1675
14
16
012
Koehl
3
-1.8730
21
-0.6243
19
0.3350
15
0.1117
18
17
003
BIOSYM
2
-0.9130
17
-0.4565
18
0.3000
17
0.1500
15
18
008
Galaktionov-Marshall
2
0.2600
10
0.1300
8
0.2600
18
0.1300
17
19
021
Saqi
1
0.0370
12
0.0370
12
0.0370
19
0.0370
19
20
005
Bryant
8
-5.2600
27
-0.6575
20
0.0000
20
0.0000
20
21
027
Wilmanns
3
-1.9970
22
-0.6657
21
0.0000
20
0.0000
20
22
006
Clarke
2
-1.3640
20
-0.6820
22
0.0000
20
0.0000
20
23
013
Lee
1
-0.7070
16
-0.7070
23
0.0000
20
0.0000
20
24
002
Barton
1
-1.0130
18
-1.0130
24
0.0000
20
0.0000
20
25
004
Bolger
3
-3.3140
25
-1.1047
25
0.0000
20
0.0000
20
26
018
Osguthorpe
1
-1.2790
19
-1.2790
26
0.0000
20
0.0000
20
27
011
Kobayashi
1
-2.0000
23
-2.0000
27
0.0000
20
0.0000
20
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.