Data needed to reproduce the results from the manuscript “Uncertainty Reduction in Biochemical Kinetic Models: Enforcing Desired Model Properties" by L. Miskovic, J. Beal, M. Moret, and V. Hatzimanikatis 1. Data generated with the ORACLE workflow that was used in the iSCHRUNK training: Classification label vectors for the three analyzed metabolic concentration cases: Reference case: class_vector_train_ref.mat Extreme1 case: class_vector_train_ex1.mat Extreme2 case: class_vector_train_ex2.mat Parameter sets used for training for the three analyzed metabolite concentration cases. As parameters, we used the degree of saturation of the enzyme active site, σA, which is constrained between 0 and 1. Reference case: training_set_ref.mat Extreme1 case: training_set_ex1.mat Extreme2 case: training_set_ex2.mat Flux control coefficients of the xylose uptake rate (XTR) with respect to the network enzymes for the three cases. For the statistics and the figures we have used the population with removed outliers. Reference case: ccXTR_ref.mat Extreme1 case: ccXTR_ex1.mat Extreme2 case: ccXTR_ex2.mat Thermodynamics-based Flux Analysis (TFA) models for the three cases: Reference case: tfa_ref.mat Extreme1 case: tfa_ex1.mat Extreme2 case: tfa_ex2.mat Parameter names identical for the three cases parameterNames.mat 2. Validation data generated with the ORACLE workflow with the parameters constrained using the information obtained with the iSCHRUNK (Figure 4). Flux control coefficients of the xylose uptake rate (XTR) with respect to the network enzymes for the three cases. For the statistics and the figures we have used the population with removed outliers. ccXTR_ValidNeg.mat Parameter sets used in validation validation_set_neg.mat 3. Validation data generated with the ORACLE workflow with the parameters constrained using the information obtained with the iSCHRUNK (Table 3). Negative control: Flux control coefficients of the xylose uptake rate (XTR) with respect to the network enzymes for the three cases. For the statistics and the figures we have used the population with removed outliers. Reference case: ccXTR_ValidRef_neg_agg.mat Extreme1 case: ccXTR_ValidEx1_neg_agg.mat Extreme2 case: ccXTR_ValidEx2_neg_agg.mat Parameter sets used for training for the three analyzed metabolite concentration cases. As parameters, we used the degree of saturation of the enzyme active site, σA, which is constrained between 0 and 1. Reference case: validation_set_ref_neg_agg.mat Extreme1 case: validation_set_ref_neg_agg.mat Extreme2 case: tvalidation_set_ref_neg_agg.mat Positive control: Flux control coefficients of the xylose uptake rate (XTR) with respect to the network enzymes for the three cases. For the statistics and the figures we have used the population with removed outliers. Reference case: ccXTR_ValidRef_pos_agg.mat Extreme1 case: ccXTR_ValidEx1_pos_agg.mat Extreme2 case: ccXTR_ValidEx2_pos_agg.mat Parameter sets used for training for the three analyzed metabolite concentration cases. As parameters, we used the degree of saturation of the enzyme active site, σA, which is constrained between 0 and 1. Reference case: validation_set_ref_pos_agg.mat Extreme1 case: validation_set_ex1_pos_agg.mat Extreme2 case: validation_set_ex2_pos_agg.mat 4. Reassignment study: validation data generated with the ORACLE workflow with the parameters constrained using the information obtained with the iSCHRUNK (Figure 6 and Table 4). Negative control: Flux control coefficients of the xylose uptake rate (XTR) with respect to the network enzymes. For the statistics and the figures we have used the population with removed outliers. Reference case: ccXTR_Valid_reassignment_neg.mat Parameter sets used for training for the three analyzed metabolite concentration cases. As parameters, we used the degree of saturation of the enzyme active site, σA, which is constrained between 0 and 1. Reference case: validation_set_neg_reassignment.mat Positive control: Flux control coefficients of the xylose uptake rate (XTR) with respect to the network enzymes. For the statistics and the figures we have used the population with removed outliers. Reference case: ccXTR_Valid_reassignment_pos.mat Parameter sets used for training for the three analyzed metabolite concentration cases. As parameters, we used the degree of saturation of the enzyme active site, σA, which is constrained between 0 and 1. Reference case: validation_set_pos_reassignment.mat

This work was supported by funding from the Ecole Polytechnique Fédérale de Lausanne (EPFL), the 2015/313 ERASysAPP RobustYeast Project funded through SystemsX.ch, the Swiss Initiative for Systems Biology evaluated by the Swiss National Science Foundation, and the Swiss National Science Foundation grant 315230_163423.