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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.