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Table 2 Parameters values with noisy data (one experiment)

From: Identification of regulatory structure and kinetic parameters of biochemical networks via mixed-integer dynamic optimization

  

10%

  
 

Profile 1

Profile 2

Profile 3

Profile 4

f 13

-0.14

-0.27

-0.84

-0.79

f 21

0.26

0.47

0.4

0.29

f 32

0.44

1

0.64

0.41

f 41

0.04

0

0.9

1

f 53

0

0.26

0.42

0.12

f 54

-0.06

0.04

0.1

-0.12

f 64

0.13

0.07

1

1

Residual

1.88

1.67

1.68

2.29

  

5%

  
 

Profile 5

Profile 6

Profile 7

Profile 8

f 13

-0.282

-0.532

-0.631

-0.893

f 21

0.56

0.618

0.306

0.6

f 32

1

1

0.436

1

f 41

0

0.092

0.761

0.742

f 53

0.368

0.639

0.273

0.298

f 54

0.127

0.244

0.021

0.279

f 64

0.064

0.158

1

1

Residual

0.4128

0.4203

0.5706

0.4482

  

1%

  
 

Profile 9

Profile 10

Profile 11

Profile 12

f 13

-0.881

-0.427

-0.859

-0.71

f 21

0.571

0.523

0.5

0.414

f 32

0.885

0.809

0.758

0.608

f 41

0.587

0.078

0.661

0.656

f 53

0.479

0.467

0.507

0.402

f 54

0.2

0.176

0.197

0.136

f 64

1

0.162

1

1

Residual

0.0207

0.0163

0.0167

0.0227

  

0.5%

  
 

Profile 13

Profile 14

Profile 15

Profile 16

f 13

-0.845

-0.744

-0.843

-0.765

f 21

0.535

0.472

0.496

0.453

f 32

0.816

0.714

0.749

0.673

f 41

0.556

0.492

0.647

0.643

f 53

0.492

0.439

0.497

0.443

f 54

0.201

0.167

0.196

0.164

f 64

0.916

0.816

1

1

Residual

0.0052

0.0041

0.0042

0.0057

  1. We solved a total of 100 problems, each corresponding to a different replication, generated randomly see Additional file 1: Table S1). The table shows the 16 cases for which the residual error is low.