PFRMAT SS
TARGET T0063
AUTHOR 1751-3146-3362
METHOD Using neural net fssp-12345-IDaa1-9-6-11-9-3-8-7-ehl-seeded3-trained.net
METHOD This is a 4-layer network, with 
METHOD	window	units
METHOD	    9	    6
METHOD	   11	    9
METHOD	    3	    8
METHOD	    7	    3 (1 EHL )
METHOD The input amino acid frequencies were determined from
METHOD alignment hypusine-trimmed-retrain.a2m.gz
METHOD with weighted counts, using HenikoffWeight(1 bits/column, 0.5)
METHOD The weighting was determined by the posterior distribution
METHOD after regularizing with recode3.20comp.
METHOD Counts were regularized to probabilities using
METHOD /projects/compbio/lib/recode3.20comp
METHOD Total sequence weight for alignment was 3.92612
METHOD
MODEL 1
M C 0.88
V C 0.80
L C 0.78
K C 0.79
W C 0.79
V C 0.66
M C 0.63
S C 0.64
T C 0.75
K C 0.79
Y C 0.73
V C 0.47
E C 0.46
A H 0.58
G H 0.70
E H 0.75
L H 0.63
K C 0.46
E C 0.74
G C 0.94
S C 0.80
Y E 0.89
V E 0.98
V E 0.99
I E 0.98
D E 0.84
G C 0.77
E C 0.93
P C 0.88
C C 0.50
R E 0.89
V E 0.98
V E 0.98
E E 0.98
I E 0.94
E E 0.82
K E 0.55
S C 0.68
K C 0.76
T C 0.83
G C 0.84
K C 0.73
H C 0.61
G C 0.61
S C 0.57
A E 0.58
K E 0.75
A E 0.81
R E 0.87
I E 0.88
V E 0.91
A E 0.92
V E 0.88
G E 0.83
V E 0.77
F E 0.57
D C 0.63
G C 0.82
G C 0.79
K C 0.54
R E 0.55
T E 0.61
L E 0.62
S E 0.50
L C 0.71
P C 0.86
V C 0.85
D C 0.83
A C 0.80
Q C 0.85
V C 0.70
E C 0.51
V C 0.56
P C 0.65
I C 0.43
I H 0.42
E C 0.49
K C 0.65
F C 0.71
T C 0.61
A E 0.47
Q E 0.76
I E 0.87
L E 0.85
S E 0.75
V E 0.50
S C 0.75
G C 0.90
D C 0.93
V C 0.66
I E 0.57
Q E 0.76
L E 0.83
M E 0.69
D C 0.55
M C 0.62
R C 0.71
D C 0.63
Y C 0.55
K C 0.47
T C 0.58
I C 0.58
E C 0.54
V C 0.72
P C 0.89
M C 0.56
K H 0.68
Y H 0.68
V H 0.67
E H 0.86
E H 0.93
E H 0.91
A H 0.88
K H 0.86
G H 0.79
R H 0.61
L C 0.50
A C 0.69
P C 0.77
G C 0.92
A C 0.88
E C 0.51
V E 0.69
E E 0.81
V E 0.78
W E 0.66
Q E 0.61
I E 0.43
L C 0.51
D C 0.69
R C 0.52
Y C 0.49
K C 0.43
I E 0.45
I E 0.51
R E 0.46
V C 0.60
K C 0.76
END