Output format

DESCRIPTION

Example of output is found below. The output is divided into the folowinng sections:



EXAMPLE OUTPUT

Description of training data

Length of motif: 9
Number of training data: 200
Threshold for counting example as positive: 0.500000

Prediction method.

Neural network
Number of input units: 180
Number of hidden units: 2
Number of bins used for balancing training: 2
Doing 5 fold cross validation

Cross validation number 1
Output from the neural network program (HOW)
Maximal test set correlation coefficent sum = 0.323400 in epoch 255
Maximal test set pearson correlation coefficent sum = 0.329300 in epoch 300
minimal per example squared error = 0.039100 in epoch 299

Cross validation number 2
Output from the neural network program (HOW)
Maximal test set correlation coefficent sum = 0.397700 in epoch 239
Maximal test set pearson correlation coefficent sum = 0.514800 in epoch 299
minimal per example squared error = 0.017400 in epoch 299

Cross validation number 3
Output from the neural network program (HOW)
Maximal test set correlation coefficent sum = 0.285700 in epoch 256
Maximal test set pearson correlation coefficent sum = 0.441000 in epoch 300
minimal per example squared error = 0.027800 in epoch 272

Cross validation number 4
Output from the neural network program (HOW)
Maximal test set correlation coefficent sum = 0.369800 in epoch 282
Maximal test set pearson correlation coefficent sum = 0.561800 in epoch 225
minimal per example squared error = 0.021600 in epoch 300

Cross validation number 5
Output from the neural network program (HOW)
Maximal test set correlation coefficent sum = 0.315100 in epoch 208
Maximal test set pearson correlation coefficent sum = 0.546600 in epoch 261
minimal per example squared error = 0.021800 in epoch 272

Parameters for prediction method

Prediction data

Number of evaluation data: 66
Predicting using a neural network
Using all networks

Evaluation of predictions

Pearson coefficient for N= 66 data: 0.53066
Aroc value: 0.77124

Predictions 



Number Sequence Assignment Prediction
1      ILYQVPFSV    0.853    0.696
2      VVMGTLVAL    0.589    0.542
3      ILDEAYVMA    0.494    0.608
4      KILSVFFLA    0.851    0.526
5      HLYQGCQVV    0.539    0.558
6      YLDLALMSV    0.843    0.689
7      ALAKAAAAA    0.563    0.499
8      MALLRLPLV    0.634    0.555
9      FLLTRILTI    0.803    0.586
10     ILSSLGLPV    0.638    0.533
11     RMYGVLPWI    0.689    0.621
12     ALPYWNFAT    0.323    0.575
13     YLEPGPVTV    0.647    0.665
14     FLPWHRLFL    0.564    0.556
15     LLPSLFLLL    0.554    0.516
16     MLQDMAILT    0.527    0.542
17     LVSLLTFMI    0.301    0.423
18     GLMTAVYLV    0.798    0.592
19     ILTVILGVL    0.451    0.473
20     GLYSSTVPV    0.697    0.620
21     SLYFGGICV    0.782    0.500
22     GLYYLTTEV    0.719    0.595
23     ALYGALLLA    0.818    0.669
24     IMPGQEAGL    0.614    0.580
25     WLSLLVPFV    0.822    0.560
26     YLVAYQATV    0.639    0.645
27     RLMIGTAAA    0.499    0.525
28     WLDQVPFSV    0.774    0.657
29     AAAKAAAAV    0.446    0.450
30     KTWGQYWQV    0.778    0.575
31     VIHAFQYVI    0.343    0.407
32     GLLGWSPQA    0.793    0.585
33     YMLDLQPET    0.654    0.599
34     HLAVIGALL    0.571    0.449
35     MLLAVLYCL    0.463    0.614
36     MMWYWGPSL    0.770    0.552
37     FVNHDFTVV    0.473    0.479
38     FLLRWEQEI    0.700    0.563
39     IIDQVPFSV    0.659    0.646
40     QVMSLHNLV    0.367    0.435
41     SVYVDAKLV    0.572    0.456
42     RLLDDTPEV    0.578    0.605
43     IAATYNFAV    0.581    0.515
44     YLVSFGVWI    0.941    0.520
45     ILLLCLIFL    0.541    0.569
46     AIAKAAAAV    0.399    0.474
47     LLLCLIFLL    0.699    0.530
48     GLQDCTMLV    0.710    0.578
49     ALAKAAAAL    0.470    0.492
50     MLGNAPSVV    0.499    0.561
51     FTDQVPFSV    0.619    0.652
52     YLAPGPVTA    0.794    0.649
53     GLLGNVSTV    0.706    0.586
54     GTLGIVCPI    0.503    0.531
55     YLEPGPVTI    0.614    0.633
56     LLFLGVVFL    0.638    0.542
57     SLAGFVRML    0.565    0.528
58     GLYLSQIAV    0.578    0.578
59     WTDQVPFSV    0.392    0.611
60     RLTEELNTI    0.374    0.499
61     KLTPLCVTL    0.572    0.586
62     YLYPGPVTA    0.739    0.695
63     TVLRFVPPL    0.599    0.506
64     ILSPFMPLL    0.648    0.584
65     FVWLHYYSV    0.749    0.573
66     ILDQVPFSV    0.635    0.677