Skip to main content

Table 1 Parameter relationships resulting in correlations as good as those found in Zinzen et al. from 100,000 tested parameters

From: Thermodynamic modeling of transcription: sensitivity analysis differentiates biological mechanism from mathematical model-induced effects

Set(s)

all correct

DT wrong

TT wrong

SS wrong

DT and TT wrong

DT and SS wrong

TT and SS wrong

all wrong

total

1

57 (39%)

6 (4%)

43 (29%)

20 (14%)

0 (0%)

2 (1%)

18 (12%)

0 (0%)

146

2

49 (28%)

32 (18%)

45 (26%)

16 (9%)

8 (5%)

9 (5%)

13 (7%)

2 (1%)

174

3 and 9

59 (38%)

10 (6%)

47 (31%)

13 (8%)

1 (1%)

5 (3%)

19 (12%)

0 (0%)

154

4 and 7

48 (39%)

1 (1%)

44 (36%)

17 (14%)

0 (0%)

0 (0%)

13 (11%)

0 (0%)

123

5, 6, and 8

37 (35%)

2 (2%)

34 (32%)

17 (16%)

0 (0%)

0 (0%)

15 (14%)

0 (0%)

105

10

13 (11%)

4 (3%)

17 (15%)

29 (25%)

8 (7%)

12 (10%)

21 (18%)

13 (11%)

117

11

36 (24%)

1 (1%)

30 (20%)

37 (25%)

0 (0%)

8 (5%)

36 (24%)

0 (0%)

148

12

36 (28%)

3 (2%)

16 (13%)

38 (30%)

0 (0%)

3 (2%)

32 (25%)

0 (0%)

128

  1. From those parameter sets with a Pearson correlation coefficient greater than 0.981 (last column) the relationships highlighted by Zinzen et al. are observed in the largest proportion, although still less than 40% of the time. The first column lists the sets of enhancer structures used to calculate the Pearson correlation coefficient for each random set of parameter values. The numbering of the enhancer structure sets is consistent with Table S2 of the Zinzen et al. study. Columns 2-9 list the number of parameter sets that fall into each relationship category, compared to those relationships stated in Zinzen et al., DTr > DTv, TTr > TTv, and SSr < SSv, and the corresponding percentage, rounded to the nearest percent, of the parameter sets tested that fall into each category.