Corynebacterium glutamicum - JUWEL - Forschungszentrum Jülich

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E. Models used in the First Model Discriminating Experiment. Model Equations Model 1.1 Model 1.2 rx =min(rx,S1,rx,S2) (E.1) rx,S1 = µmax,S1 · CS1 · CX KmS1 + cS1 rx,S2 = µmax,S2 · CS2 · CX CS2 + KmS2 rS2 = − rx YXS2 rp = πmax · CS1 · CX Kp,S1 + CS1 · − mS1 · CX + µmin,S2 · CX Kirp,S2 Kirp,S2 + CS2 rS1 = − µmax,S1 · CS1 · CX − (KmS1 + CS1) · YXS1 rp + YPS1 rx,S1 − rx YXS1 Model 1.2 is similar to model 1.1, with the following changes: instead of equation E.5: rp = πmax · CS1 · CX Kp,S1 + CS1 instead of equation E.6: Model 1.3 · Kirp,S2 Kirp,S2 + CS2 +(rx,S1 − rx) · YPXS1xtra rS1 = − µmax,S1 · CS1 · CX − (KmS1 + CS1) · YXS1 πmax · CS1 · CX (Kp,S1 + CS1) · YPS1 Model 1.3 is similar to model 1.1, but with the following changes: (E.2) (E.3) (E.4) (E.5) (E.6) (E.7) (E.8) 153
E. Models used in the First Model Discriminating Experiment. instead of equation E.2: instead of equation E.5: rx,S1 = µmax,S1 · CS1 · CX KmS1 + cS1 rp = πmax · CS1 · CX Kp,S1 + CS1 furthermore, instead of E.6: Model 1.4 rS1 = − µmax,S1 · CS1 · CX · (KmS1 + CS1) · YXS1 · · Kirp,P Kirp,P + CP Kirx,P Kirx,P + CP Kirx,P Kirx,P + CP − mS1 · CX +(rx,S1 − rx) · YPXS1xtra − πmax · CS1 · CX (Kp,S1 + CS1) · YPS1 Model 1.4 is similar to model 1.1, but with the following changes: instead of equation E.2: instead of equation E.5: rx,S1 = µmax,S1 · CS1 · CX KmS1 + cS1 rp = πmax · CS1 · CX Kp,S1 + CS1 furthermore, instead of E.6: Model 1.5 rS1 = − µmax,S1 · CS1 · CX · (KmS1 + CS1) · YXS1 · · Kirx,P Kirx,P + CP Kirp,P Kirp,P + CP Kirx,P Kirx,P + CP · − mS1 · CX Kirp,S2 Kirp,S2 + CS2 − rp + YPS1 rx,S1 − rx YXS1 Model 1.5 is similar to model 1.4, with the following difference: instead of equation E.13: 154 rp = πmax · CS1 · CX Kp,S1 + CS1 instead of equation E.14: · Kirp,P Kirp,P + CP · Kirp,S2 Kirp,S2 + CS2 rS1 = − µmax,S1 · CS1 · CX · (KmS1 + CS1) · YXS1 (E.9) (E.10) (E.11) (E.12) (E.13) (E.14) +(rx,S1 − rx) · YPXS1xtra (E.15) Kirx,P Kirx,P + CP − rp YPS1 (E.16)
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Lebenswissenschaften Life Sciences
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Forschungszentrum Jülich GmbH Inst
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’Therefore, mathematical modeling
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Contents 3.4. Application: L-Valine
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Contents 4
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1. Introduction need for improved m
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2. Theory In a batch process, all s
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2. Theory 1997; Goncalves et al., 2
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2. Theory For batch fermentations,
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2. Theory with Yps being the yield
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2. Theory Inhibition Some catalytic
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2. Theory The method of least squar
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2. Theory evaluation can be made by
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2. Theory We define the measured or
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2. Theory build in the model. An ob
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2. Theory nations, the researcher i
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2. Theory W = J · Covθ · J T (2.
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2. Theory arg max ξ � m� m�
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2. Theory with all measured values
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2. Theory which can be estimated us
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2. Theory One option to account for
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2. Theory θ 2 $θ 2 0 area ≅ det
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2. Theory designed using a paramete
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2. Theory proteome14 (Hermann et al
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2. Theory 44
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3. Dynamic Modeling Framework itera
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3. Dynamic Modeling Framework 3.3.
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3. Dynamic Modeling Framework 3.3.3
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3. Dynamic Modeling Framework 52 du
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3. Dynamic Modeling Framework the c
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3. Dynamic Modeling Framework For d
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3. Dynamic Modeling Framework subse
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3. Dynamic Modeling Framework 60
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4. Simulative Comparison of Model D
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5. L-Valine Production Process Deve
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Page 109 and 110: 5. L-Valine Production Process Deve
Page 140 and 141: A. Nomenclature Table A.1.: Symbols
Page 142 and 143: Table A.1.: Symbols and Abbreviatio
Page 144 and 145: Table A.1.: Symbols and Abbreviatio
Page 146 and 147: B. Ratio between OD600 and Dry Weig
Page 148 and 149: C. The Influence of the Oxygen Supp
Page 150 and 151: The measurements of amino acids and
Page 152 and 153: kiv [mM] lac [mM] 15 10 5 0 0 10 20
Page 154 and 155: OTR, CTR 0.06 0.04 0.02 0 0 10 20 3
Page 156 and 157: DO properly at a low value in dynam
Page 158 and 159: D. Dilution for Measurement of Amin
Page 162 and 163: Model 1.6 Model 1.6 is similar to m
Page 164 and 165: Table E.1: Model Parameters of the
Page 166 and 167: Table E.2: Model Parameters of the
Page 168 and 169: 161
Page 170 and 171: Model 2.2 Model 2.2 is similar to m
Page 172 and 173: Table F.1.: Model Parameters of the
Page 174 and 175: Table F.2.: Estimated Lag-Times of
Page 176 and 177: Table F.3: Model Parameters of the
Page 178 and 179: Table F.4.: Estimated Lag-Times of
Page 180 and 181: G. Alternative Off-line Optimized P
Page 182 and 183: G.2. Overall Yield of Product on Su
Page 184 and 185: Summary Fast development of product
Page 186 and 187: Zusammenfassung Es ist wichtig, die
Page 188 and 189: Acknowledgements This thesis result
Page 190 and 191: Bibliography K. Akashi, H. Shibai,
Page 192 and 193: Bibliography A. Bodalo-Santoyo, J.L
Page 194 and 195: Bibliography A.J. Cooper, J.Z. Gino
Page 196 and 197: Bibliography A.G. Fredrickson, R.D.
Page 198 and 199: Bibliography W.G. Hunter and A.M. R
Page 200 and 201: Bibliography A.C. McHardy, A. Tauch
Page 202 and 203: Bibliography E. Radmacher, A. Vaits
Page 204 and 205: Bibliography K.J. Versyck, J.E. Cla
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Corynebacterium glutamicum - JUWEL - Forschungszentrum Jülich

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