Corynebacterium glutamicum - JUWEL - Forschungszentrum Jülich

More documents

Recommendations

Info

Model 2.2 Model 2.2 is similar to model 2.1, with the following changes: instead of equation F.2: instead of equation F.3: rx,S1 = µmax,S1 · CS1 · CX Km,S1 + cS1 so equation F.6 can be omitted. instead of equation F.13 to F.15: rp = πmax,S1 · CS1 · CX Kp,S1 + CS1 Model 2.3 · KiP,rp KiP,rp + CP rx,S2 = rx,S2ext · · KiP,rxS1 KiP,rxS1 + CP (CS3int/CX − S3intmin,rp) KpS3int +(CS3int/CX − S3intmin,rp) Model 2.3 is similar to model 2.1, but with the following changes: instead of equation F.6: instead of equation F.14: Model 2.4 rx,S2int = µmax,S2int · CS2int · + kS1extra(rx,S1 − rx) Yp,s1 KiP,rxs2int KiP,rxs2int + CP πmax,S1 · CS1 · CX rp,S1 = CS1 + Kp,S1(1 + CS2int/CX Kirp,S2int ) + kS1extra(rx,S1 − rx) Yps1 Model 2.4 is similar to model 2.1, but with the following changes: instead of equation F.5: rx,S2ext = instead of equation F.6: µmax,S2ext · CS2ext · CX CS2ext + Km,S2ext(1 + CP /KiP,rxs2) rx,S2int = µmax,S2int · CS2int (F.17) (F.18) (F.19) (F.20) (F.21) (F.22) (F.23) 163
F. Models used in the Second Model Discriminating Experiment. instead of equation F.14: rp,S1 = instead of equation F.15: Model 2.5 πmax,S1 · CS1 · CX Kp,S1(1 + CS2int/CX Kirp,S2int )+CS1 rp,S3 = πmax,S3 · CX(CS3int/CX) Kp,S3 +(CS3int/CX) + kS1extra(rx,S1 − rx) Yp,s1 · CP KiP,rp + CP Model 2.5 is similar to model 2.3, with the following difference: instead of equation F.10: rS2int = −rx,S2ext − mS2int · (CS2int/CX − S2intmin) · rp/Yps1 Reduced model for the production experiment The reduced model is based on model 2.3, but with the following difference: instead of equation F.12: Parameter Estimates rS3int = −rx,S3ext (F.24) (F.25) (F.26) (F.27) The estimated model parameters are shown with the corresponding standard deviations, which were calculated in a similar way as the parameters shown in appendix E. 164
Page 1 and 2:
Lebenswissenschaften Life Sciences
Page 4 and 5:
Forschungszentrum Jülich GmbH Inst
Page 6:
’Therefore, mathematical modeling
Page 9 and 10:
Contents 3.4. Application: L-Valine
Page 11 and 12:
Contents 4
Page 13 and 14:
1. Introduction need for improved m
Page 15 and 16:
2. Theory In a batch process, all s
Page 17 and 18:
2. Theory 1997; Goncalves et al., 2
Page 19 and 20:
2. Theory For batch fermentations,
Page 21 and 22:
2. Theory with Yps being the yield
Page 23 and 24:
2. Theory Inhibition Some catalytic
Page 25 and 26:
2. Theory The method of least squar
Page 27 and 28:
2. Theory evaluation can be made by
Page 29 and 30:
2. Theory We define the measured or
Page 31 and 32:
2. Theory build in the model. An ob
Page 33 and 34:
2. Theory nations, the researcher i
Page 35 and 36:
2. Theory W = J · Covθ · J T (2.
Page 37 and 38:
2. Theory arg max ξ � m� m�
Page 39 and 40:
2. Theory with all measured values
Page 41 and 42:
2. Theory which can be estimated us
Page 43 and 44:
2. Theory One option to account for
Page 45 and 46:
2. Theory θ 2 $θ 2 0 area ≅ det
Page 47 and 48:
2. Theory designed using a paramete
Page 49 and 50:
2. Theory proteome14 (Hermann et al
Page 51 and 52:
2. Theory 44
Page 53 and 54:
3. Dynamic Modeling Framework itera
Page 55 and 56:
3. Dynamic Modeling Framework 3.3.
Page 57 and 58:
3. Dynamic Modeling Framework 3.3.3
Page 59 and 60:
3. Dynamic Modeling Framework 52 du
Page 61 and 62:
3. Dynamic Modeling Framework the c
Page 63 and 64:
3. Dynamic Modeling Framework For d
Page 65 and 66:
3. Dynamic Modeling Framework subse
Page 67 and 68:
3. Dynamic Modeling Framework 60
Page 69 and 70:
4. Simulative Comparison of Model D
Page 71 and 72:
Page 73 and 74:
Page 75 and 76:
Page 77 and 78:
Page 79 and 80:
Page 81 and 82:
Page 83 and 84:
Page 85 and 86:
Page 87 and 88:
Page 89 and 90:
Page 91 and 92:
Page 93 and 94:
Page 95 and 96:
5. L-Valine Production Process Deve
Page 97 and 98:
Page 99 and 100:
Page 101 and 102:
Page 103 and 104:
Page 105 and 106:
Page 107 and 108:
Page 109 and 110:
Page 111 and 112:
Page 113 and 114:
Page 115 and 116:
Page 117 and 118:
Page 119 and 120: 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 160 and 161: E. Models used in the First Model D
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 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
Page 206 and 207: 6FKULIWHQ GHV )RUVFKXQJV]HQWUXPV -
Page 208 and 209: 6FKULIWHQ GHV )RUVFKXQJV]HQWUXPV -
show all

Corynebacterium glutamicum - JUWEL - Forschungszentrum Jülich

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?