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Table 1 Classification results

From: FISH Amyloid – a new method for finding amyloidogenic segments in proteins based on site specific co-occurence of aminoacids

Training set (horizontal)

TG

Waltz

AmylHex

Tested set (vertical)

   
 

sliding window of length 5

 

TG

0.75 | 0.62

0.82 | 0.21

0.77 | 0.42

Waltz

0.62 | 0.60

0.69 | 0.60

0.59 | 0.51

AmylHex

0.69 | 0.60

0.84 | 0.31

0.81 | 0.47

 

sliding window of length 6

 

TG

0.76 | 0.57

0.77 | 0.30

0.78 | 0.44

Waltz

0.54 | 0.45

0.69 | 0.61

0.61 | 0.43

AmylHex

0.48 | 0.57

0.82 | 0.25

0.79 | 0.47

  1. AUC ROC of the classification results with two window lengths. To test if a classification pattern is observable in the negative datasets, the training and testing procedures were also applied on negative datasets (POSITIVE | NEGATIVE); the positive datasets are in bold. Training dataset is defined horizontally; testing dataset – vertically. Random classification (or no pattern in a dataset) would obtain 0.5 and an ideal classifier 1.