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Table 4.13 Homology detection success rate (%) for mainly beta proteins at the superfamily level
on three benchmarks SCOP20, SCOP40 and SCOP80
SCOP20
SCOP40
SCOP80
Top1
Top5
Top10
Top1
Top5
Top10
Top1
Top5
Top10
Hmmscan
29.1
29.4
29.4
34.7
35.1
35.1
43.7
44.0
44.1
FFAS
43.6
49.9
51.9
48.2
52.4
53.5
43.7
46.3
47.2
HHsearch
48.2
54.6
56.9
52.0
56.9
59.1
47.7
51.8
53.7
HHblits
47.5
52.1
53.7
51.4
54.8
56.6
52.9
54.6
57.8
MRFalign
55.4
61.7
65.9
57.3
63.5
66.8
54.2
59.7
64.2
Table 4.14 Homology detection success rate (%) for mainly beta proteins at the fold level on
three benchmarks SCOP20, SCOP40 and SCOP80
SCOP20
SCOP40
SCOP80
Top1
Top5
Top10
Top1
Top5
Top10
Top1
Top5
Top10
Hmmscan
6.9
7.6
7.6
8.0
8.6
8.6
7.0
7.4
7.4
FFAS
22.7
30.1
31.8
15.2
20.4
21.7
11.8
15.3
16.1
HHsearch
24.4
34.7
38.8
26.8
37.7
41.6
19.1
26.8
29.5
HHblits
24.1
33.3
34.8
26.9
35.3
37.1
24.7
34.1
35.5
MRFalign
37.4
55.0
61.4
42.5
51.0
54.6
36.4
48.0
55.9
4.6 Contribution of Edge Alignment Potential
and Mutual Information
To evaluate the contribution of the edge alignment potential, we calculate the
alignment recall improvement resulting from using the edge alignment potential on
two benchmarks Set3.6K and Set2.6K. As shown in Tables
4.15
and
4.16
, the edge
alignment potential can improve alignment recall by 3.4 and 3.7 %, respectively.
When mutual information is used to measure residue co-evolution, alignment recall
can be further improved by 1.1 and 1.9 % on these two sets, respectively. Mutual
Table 4.15 Contribution of the edge alignment potential and mutual information (MI), measured
by alignment recall improvement on two benchmarks Set3.6K and Set2.6K
Set3.6K
Set2.6K
Exact match
(%)
4-offset
(%)
Exact match
(%)
4-offset
(%)
Only node potential
44.7
48.6
68.6
71.8
Node + edge potential, no
MI
48.1
52.2
72.3
75.2
Node + edge potential with
MI
49.2
53.5
74.2
77.8
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