Skip to main content

Table 1 Extracted features for different sets (CC, RS1, RS2 and BMDB), methods and feature size

From: Annotation-based feature extraction from sets of SBML models

5 Features Method 2 Method 4
  CC RS1 RS2 BMDB CC RS1 RS2 NFKB
  33285 24870 24870 24870 22563 22563 26816 24870
  33302 33302 33302 33302 33608 26082 33695 26082
ChEBI 33304 33304 33304 33304 33694 33241 47019 33241
  35701 33582 33582 33582 37096 33695 61120 33695
  36357 36357 36357 36357 37787 61120 63367 61120
avg depth 5.4 4.2 4.4 4.2 7.2 5.6 8.2 5.4
  8152 3674 3674 3674 22411 3674 3674 3674
  9987 8152 5575 8152 30163 5575 9987 5575
GO 44699 9987 8152 9987 51726 6810 22607 9987
  65007 44699 9987 44699 65009 9987 43170 43170
  71840 51234 44699 65007 71822 43170 71822 71822
avg depth 2 1.8 1.8 1.8 4.4 2.2 3.6 2.6
  003 064 231 003 009 009 009 003
  236 231 245 064 231 064 167 009
SBO 374 240 247 231 252 176 240 064
  375 241 291 236 336 252   167
  545 545 545 545     240
avg depth 2.4 2.4 2.4 2 4 4.3 3.5 3
15 Features Method 2 Method 4
  CC RS1 RS2 BMDB CC RS1 RS2 BMDB
  16646 18059 18059 18059 22563 22563 24875 24835
  24651 24835 24835 24835 33608 24835 25107 24870
  25367 24870 24870 24870 33694 25741 26816 26082
  25699 25367 25367 25367 37096 26082 33252 33241
  25741 25806 26082 26082 37787 33241 33620 33259
  26082 26082 33259 33241   33252 33636 33636
  33241 26835 33304 33259   33259 33695 33695
ChEBI 33839 33241 33581 33285   33608 35155 35155
  35701 33259 33674 33304   33695 35569 35569
  36358 33285 33839 33674   35701 47019 35701
  36606 33674 35701 33839   61120 61120 47019
  51143 33694 37577 35701   63367 63161 61120
  63161 35701 50906 50906   64709 63367 63161
  63299 51143 51143 51143     63367
  64709 64709 64709 64709     64709
avg depth 5.9 5.3 4.8 4.8 7.2 5.4 7.0 6.3
  3674 3674 3674 3674 216 3674 3674 3674
  5575 5575 5575 5575 4693 5575 5834 5575
  6807 6807 6807 8152 5575 6810 6826 9987
  9056 9056 9056 9987 22411 9987 8943 43170
  9058 9058 9058 32501 30163 16088 9987 71822
  40007 44237 32501 32502 32268 43170 22607  
  44237 44238 44237 40007 45750 45750 43170  
GO 44238 44699 44238 44699 51726   71822  
  44699 44710 44699 48511 65009    
  50896 48511 44710 50896 71822    
  51234 50896 50896 51234     
  65007 51234 51234 51704     
  71704 65007 65007 65007     
  71840 71704 71704 71840     
   71840 71840      
avg depth 2.3 2.3 1.9 1.8 4.1 2.1 3.0 2.6
  009 064 016 003 009 009 009 003
  177 177 017 064 231 064 167 009
  179 179 046 241 252 176 240 064
  180 180 153 245 336 252   167
  181 182 156 247     240
  182 185 231 253     
  205 205 241 285     
SBO 245 241 245 290     
  253 247 247 291     
  290 250 253 374     
  291 253 290 375     
  308 285 291 405     
  342 290 308 409     
  360 377 360 412     
  374 545 380 545     
avg depth 4.6 4.5 3.7 3.3 4 4.3 3.5 3
  1. The upper table shows a maximum of five features, the bottom table 15 features, respectively. IDs are shortened (e.g. SBO:0000064 is represented by 064) and ordered ascending. The average depth (avg) of features per ontology is emphasized for the test sets.