Skip to main content

Table 2 Ensembles of feasible vectors generated with different schemes

From: Predicting network modules of cell cycle regulators using relative protein abundance statistics

Ensemble Scheme Ensemble Selection of Feasibility criteria # generations # S
# # size the initial DE used in selection per DE run DE runs (Range of
    population from step of DE    predictions)
    Ensemble 1     
1   3146 - Parameter vectors Ensemble generated - 30
     satisfy F C 1 in optimization [22]   
2 1 243 - Parameter vectors Ensemble extracted - 51
     satisfy F C 1 from 50,000   
      LHS samples   
3 2 7143 Randomly selected F C 1 400 1 6
    parameter vectors     
4 3 1893 V max (10) F C 1 400 1 41
5 4 1594 V max (10) F C 1 and F C 2 1600 1 64
6 4 1326 V max (10) F C 1 and F C 2 1600 1 69
7 5 3405 V max (123) F C 1 and F C 2 1600 1 94
8 5 3753 V max (123) F C 1 and F C 2 1600 1 80
9 6 2207 S max & V max (123) F C 1 and F C 2 1600 1 117
10 6 1842 S max & V max (123) F C 1 and F C 2 1600 1 95
11 7 3704 S max & V max (123) F C 1, F C 2, and F C 3 1600 1 112
12 7 3481 S max & V max (123) F C 1, F C 2, and F C 3 1600 1 133
13 8 4280 S max & V max (123) F C 1 and F C 3 1600 1 313
14 8 4550 S max & V max (123) F C 1 and F C 3 1600 1 367
15 7 15520 S max & V max (123) F C 1, F C 2, and F C 3 2200 4 293
16 8 15050 S max & V max (123) F C 1 and F C 3 2200 4 671
  1. Parameter ranges used for LHS are from Ensemble 1. Parameter vectors in all ensembles capture the phenotypes listed in Additional file 1: Table S7, while missing the phenotypes in Additional file 1: Table S8. S: The range of the phenotypic prediction vectors generated per ensemble (unique rows of the prediction matrix P). V max (10): Biased selection is used to expand the estimated volume spanned by the initial population with respect to the axes of the ten most critical parameters (Table 3). V max (123): Biased selection is used to expand the estimated volume spanned by the initial population with respect to the axes of 123 kinetic parameters. S max : Biased selection is used to enhance the initial population’s range of phenotypic predictions. The prediction ranges for all ensembles can be reproduced using Additional file 4 (simulation code), and Additional files 5, 6, 7, 8 and 9 (Ensembles 1 through 16)