Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
MTZ-Fachkongress

Antriebe und Energiesysteme von morgen


Austausch von Automobil- und Energiewirtschaft

Am 14./15. Mai geht es in Chemnitz um die Mobilitätswende durch Elektro- und Wasserstofffahrzeuge.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Enzymkinetik Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

13. Systembiologie in der Bioverfahrenstechnik

verfasst von : Ralf Takors

Erschienen in: Bioprozesstechnik

Verlag: Springer Berlin Heidelberg

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Zusammenfassung

Die Systembiologie ist eine Wissenschaft, die sich nach wie vor rasant entwickelt. Sie verfolgt den Ansatz, ein biologisches System holistisch, d. h. ganzheitlich zu betrachten und quantitativ zu beschreiben. Dabei steht die Interaktion der einzelnen Module (Moleküle, Zellen, Regulationsmechanismen oder Populationen) im Vordergrund der Untersuchungen. Folgerichtig setzen sich systembiologische Studien aus unterschiedlichsten Facetten der Forschungsthemen zusammen und adressieren vielfältige Themenfelder der Biologie und Medizin. Das nachfolgende Kapitel stellt nur einen kleinen Teilaspekt in den Vordergrund: nämlich die systembiologischen Aspekte in der Bioverfahrens- bzw. Bioprozesstechnik. Weitere Themenfelder werden in den Übersichten vorgestellt.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel Kultivierung von Säugetierzellen
Fußnoten
1
Zu beachten ist, dass 13C mit einer natürlichen Verbreitung von 1,13 % auch in „nicht“-markierten Substraten vorkommt.
 
Literatur
[1]
Aiba S, Matsuoka M (1979) Identification of metabolic model: Citrate production from glucose by Candida lipolytica. Biotechnol Bioeng 21:1373‒1386
[2]
Antoniewicz MR, Kelleher JK, Stephanopoulos G (2007) Elementary metabolite units (EMU): A novel framework for modeling isotopic distributions. Metab Eng 9:68‒86PubMed
[3]
Antoniewicz MR, Kraynie DF, Laffend LA, Gonzalez-Lergier J, Kelleher JK, Stephanopoulos G (2007) Metabolic flux analysis in a nonstationary system: Fed-batch fermentation of a high yielding strain of E. coli producing 1,3-propanediol. Metab Eng 9:277‒292PubMedPubMedCentral
[4]
Avery SV (2006) Microbial cell individuality and the underlying sources of heterogeneity. Nature Rev 4:577–587
[5]
Bailey JE (1991) Towards a science of metabolic engineering. Science 252:1668‒1674PubMed
[6]
Bailey JE (1999) Lessons from metabolic engineering for functional genomics and drug discovery. Nat Biotechnol 17:616–618PubMed
[7]
Beckwith JR (1967) Regulation of the lac operon. Recent studies on the regulation of lactose metabolism in Escherichia coli support the operon model. Science 156:597‒604PubMed
[8]
Blank LM, Kuepfer L, Sauer U (2005) Large-scale 13C-flux analysis reveals mechanistic principles of metabolic network robustness to null mutations in yeast. Genome Biol 6:R49PubMedPubMedCentral
[9]
Blum JJ, Stein RB. (1982) On the analysis of metabolic networks. In: Goldberger RF (Hrsg) Biological regulation and development, Plenum Press, New York, S 99‒124
[10]
Bonarius HPJ, Schmidt G, Tramper J (1997) Flux analysis of underdetermined metabolic systems: The quest of missing constraints. Trends Biotechnol 15:308‒314
[11]
Bordel S, Nielsen J (2010) Identification of flux control in metabolic networks using non-equilibrium thermodynamics. MetabEng 12:369–377
[12]
Buchholz J, Graf M, Freund A, Busche J, Kalinowski J, Blombach B, Takors R (2014) CO2/HCO3− perturbations of simulated large scale gradients in a scale-down device cause fast transcriptional responses in Corynebacterium glutamicum. Appl Microbiol Biotechnol 98(29):8563–8572PubMed
[13]
Burgard AP, Phakya P, Maranas CD (2003) OptKnock, a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization. Biotechnol Bioeng 84:647‒657PubMed
[14]
Burns JA, Cornish-Bowden A, Groen AK, Heinrich R, Kacser H, Porteous JW, Rapoport SM, Rapoport TA, Stucki JW, Tager JM, Wanders RJA, Westerhoff HV (1985) Control analysis of metabolic systems. Trends Biochem Sci 10:16
[15]
Bylund F, Collet E, Enfors SO, Larsson G (1998) Substrate gradient formation in the large-scale bioreactor lowers cell yield and increases by-product formation, Bioproc Eng 18:171–180
[16]
Cameron DC, Tong T-T (1993) Cellular and metabolic engineering. Appl Biochem Biotechnol 38:105‒140PubMed
[17]
Caspeta L, Nielsen J (2013) Towards systems metabolic engineering of Aspergillus and Pichia species for the production of chemicals and biofuels. Biotechnol J 8:534–544.PubMed
[18]
Chance B, Garfinkel D, Higgins J, Hess B (1960) Metabolic control mechanisms. J Biol Chem 235:2426‒2439PubMed
[19]
Christensen B, Nielsen J (1999) Metabolic network analysis – a powerful tool in metabolic engineering. Adv Biochem Eng Biotechnol 66:209‒231
[20]
Christensen B, Nielsen J (1999) Isotopomer analysis using CG-MS. Metab Eng 1:282‒290PubMed
[21]
de Graaf AA (2000) Metabolic analysis of Zymomonas mobilis. In: Schügerl K, Belgardt KH (Hrsg) Bioreaction Engineering, Modelling and Control, Springer Verlag, New York
[22]
Delvigne F, Brognaux A, Gorret N, Neubauer P, Delafosse A, Collignon ML, Toye D, Crine M, Boxus M, Thonart P (2011) Characterization of the response of GFP microbial biosensors sensitive to substrate limitation in scale-down bioreactors. Biochem Eng J 55:131–139
[23]
Feist AM, Henry CS, Reed JL, Krummenacker M, Joyce AR, Karp P-D, Broadbelt LJ, Hatzimanikatis V, Palsson BO (2007) A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information. Mol Syst Biol 3:121PubMedPubMedCentral
[24]
Fell DA (1997) Metabolic control analysis: A survey of its theoretical and experimental development. Biochem J 286:313‒330
[25]
Ferenci T (2001) Hungry bacteria ‒ definition and properties of a nutritional state. Environ Microbiol 3(10):605‒611PubMed
[26]
Griffith JS (1968) Mathematics of cellular control processes. I. Negative feedback to one gene. J Theor Biol 20:202‒208PubMed
[27]
Griffith JS (1968) Mathematics of cellular control processes. II. Positive feedback to one gene. J Theor Biol 20:209‒216PubMed
[28]
Hatzimanikatis V, Bailey JE (1997) Effects of spatiotemporal variations on metabolic control: Approximate analysis using (log) linear kinetic models. Biotechnol Bioeng 1:75–87
[29]
Hatzimanikatis V, Emmerling M, Sauer U, Bailey JE (1998) Application of mathematical tools for metabolic design of microbial ethanol production. Biotechnol Bioeng 58:154–161PubMed
[30]
Hatzimanikatis V, Floudas CA, Bailey JE (1996) Analysis and design of metabolic reaction networks via mixed-integer linear optimization. AICHE J 42:1277–1292
[31]
Heinrich R, Rapoport TA (1974) A linear steady-state treatment of enzymatic chains. General properties, control and effector strength. Eur J Biochem 42:89‒95PubMed
[32]
Henry CS, Broadbelt LJ, Hatzimanikatis V (2007) Thermodynamics-based metabolic flux analysis. Biophys J 92(5):1792‒1805PubMed
[33]
Henson MA (2003) Dynamic modeling of microbial populations. Curr Opin Biotechnol 14:460–467PubMed
[34]
Hess B, Boiteux A (1968) Mechanism of glycolytic oscillation in yeast. I. Aerobic and anaerobic growth conditions for obtaining glycolytic oscillation. Hoppe-Seylers Z physiol Chem 349(11):1567‒1574PubMed
[35]
Hewitt C, Nebe-von Caron G, Axelsson B, McFarlane CM, Nienow AW (2003) Studies related to the scale-up of high-cell-density E.coli fed-batch fermentations using multiparameter flow cytometry: Effect of a changing microenvironment with respect to glucose and dissolved oxygen concentration. Biotechnol Bioeng 70(4):381–390
[36]
Ibarra RU, Edwards JS, Palsson BO (2002) Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth. Nature 420: 186‒189PubMed
[37]
Jandt U, Platas Barradas O, Pörtner R, Zeng AP (2014) Mammalian cell culture synchronization under physiological conditions and population dynamic simulation. Appl Microbiol Biotechnol 98:4311–4319PubMed
[38]
Junker BH (2004) Scale-up Methodologies for Escherichia coli and Yeast Fermentation Process. J BiosciBioeng 97(6):347–364
[39]
Kacser H, Burns, JA (1973) The control of flux. Symp Soc Exp Biol 27:37‒63
[40]
Käß F, Hariskos I, Michel A, Brandt H-J, Spann R, Junne S, Wiechert W, Neubauer P, Oldiges M (2013) Assessment of robustness against dissolved oxygen/substrate oscillations for C. glutamicum DM1933 in two-compartment bioreactor. Bioprocess Biosystems Eng 37(6):1–12. https://​doi.​org/​10.​1007/​s00449-013-1086-0 PubMed
[41]
[42]
Klipp E, Herwig R, Kowald A, Wierling C, Lehrach H (2005) Systems Biology in Practice. Wiley-VCH, Weinheim
[43]
[44]
Lapin A, Müller D, Reuss M (2004) Dynamic behavior of microbial populations in stirred bioreactors simulated with euler-lagrange methods: Travelling along the Lifeline of Single Cells. Ind Eng Chem Res 43:4647–4657
[45]
Lapin A, Schmid J, Reuss M (2006) Modeling the dynamics of E. coli populations in the three-dimensional turbulent field of a stirred-tank bioreactor – A structured – segregated approach. Chem Eng Sci 61:4783–4797
[46]
Lara AR, Galindo E, Ramirez OT, Palomares LA (2006) Living with heterogeneities in bioreactors. Mol Biotechnol 34:355‒381PubMed
[47]
Lee SY (2009) Systems Biology and Biotechnology of Escherichia coli. Springer Science+Business Media B.V., Berlin
[48]
Lee SY, Mattanovich D, Villaverde A (2013) Systems metabolic engineering, industrial biotechnology and microbial cell factories. Microb Cell Fact 11:156.
[49]
Leighty RW Antoniewicz MR (2011) Dynamic metabolic flux analysis (DMFA): a framework for determining fluxes at metabolic non-steady-state. Metab Eng 13(6):745–55PubMed
[50]
Lencastre Fernandes R, Nierychlo M, Pedersen AE, Puentes Tellez PE, Dutta A, Calquist M, Bolic A, Schäpper D, Brunetti AC, Helmark S, Heins A-L, Jensen AD, Nopens I, Rottwit K, Szita N, van Alsas JD, Nielsen PH, Martinussen J, Sorensen SJ, Lantz AE, Gernaey KV (2011) Experimental methods and modeling techniques for description of cell population heterogeneity. Biotechnol Adv 29:575–599PubMed
[51]
Liebermeister W, Klipp E (2006) Bringing metabolic networks to life: convenience rate law and thermodynamic constraints. Theor Biol Med Model 3:41PubMedPubMedCentral
[52]
Lieder S, Nikel PI, de Lorenzo V, Takors R (2015) Genome reduction boosts heterologous gene expression in Pseudomonas putida. Microb Cell Fac 14:23.
[53]
[54]
Magnus JB, Hollwedel D Oldiges M, Takors R (2006) Monitoring and modelling of the reaction dynamics in the valine/leucine synthesis pathway in Corynebacterium glutamicum. Biotechnol Prog 22(4):1071‒1083PubMed
[55]
Makinoshima H, Nishimura A, Ishihama A (2002) Fractionation of Escherichia coli cell populations at different stages during growth transition to stationary phase. Mol Micro 43:269–279
[56]
Malloy CR, Sherry AD, Jeffrey FMH (1988) Evaluation of carbon flux and substrate selection through alternate pathways involving the citric asset cycle of the heart by 13C MMR spectroscopy. J Biol Chem 263:6964‒6971PubMed
[57]
Marx A, de Graaf AA, Wiechert W, Eggeling L, Sahm H (1996) Determination of the fluxes in central metabolism of Corynebacterium by NMR spectroscopy combined with metabolite balancing. Biotechnol Bioeng 49:111‒129PubMed
[58]
Müller S, Harms H, Bley T (2010) Origin and analysis of microbial population heterogeneity in bioprocesses. Curr Opin Biotechnol 21(1):100–113PubMed
[59]
Mustafi N, Gruenberger A, Mahr R, Helfrich S, Nöh K, Blombach B, Kohlheyer D, Frunzke J (2014) Application of a genetically encoded biosensor for live cell imaging of L-valine production in pyruvate dehydrogenase complex-deficient Corynebacterium glutamicum strains. PlosOne 9(1):e85731PubMedPubMedCentral
[60]
Neubauer P, Junne S (2010) Scale-down simulators for metabolic analysis of large-scale bioprocesses. Cur Opin Biotechnol 21:114–121
[61]
Neubauer P, Cruz N, Glauche F, Junne S, Knepper A, Raven M (2013) Consistent development of bioprocesses from microliter cultures to the industrial scale. Eng Life Sci 13:224–238
[62]
Nielsen J (1997) Metabolic control analysis of biochemical pathways based on a thermokinetic description of reaction rates. Biochem J 321:133‒138PubMedPubMedCentral
[63]
Nielsen J, Villadsen J, Liden G (2003) Bioreaction Engineering Principles. Kluwer Academic/Plenum Publishers, New York
[64]
Nöh K, Grönke K, Luo B, Takors R, Oldiges M, Wiechert W (2007) Metabolic flux analysis at ultra short time scale: isotopically non-stationary 13C labeling experiments. J Biotechnol 129(2):249‒267PubMed
[65]
Onsager L (1931) Reciprocal relations in irreversible processes I. Physical Rev 37:405‒426
[66]
Palsson BO (2006) Systems Biology – Properties of reconstructed networks. University Press, Cambridge
[67]
Patil KR, Rocha I, Förster J, Nielsen J (2005) Evolutionary programming as a platform for in silico metabolic engineering. BMC Bioinformatics 6:308PubMedPubMedCentral
[68]
Petersen S, de Graaf AA, Eggeling L, Möllmay M, Wiechert W, Sahm H (2000) In vivo quantification of parallel and bidirectional fluxes in the anaplerosis of Corynebacterium glutamicum. J Biol Chem 275: 35932‒35941PubMed
[69]
Pharkya P, Burgard AP, Maranas CD (2004) OptStrain: A computational framework for redesign of microbial production systems. Genome Res 14:2367–2376PubMedPubMedCentral
[70]
Pharkya P, Maranas CD (2006) An optimization framework for identifying reaction activation/inhibition or elimination candidates for overproduction in microbial systems. Metab Eng 8:1–13PubMed
[71]
Reder C (1988) Metabolic control theory: a structural approach. J Theor Biol 135:175‒201PubMed
[72]
Reuss M (2007) Marrying diverse partners – a mixed complementary approach for integrating bottom-up and top-down methods in Systems Biology. In: Systems biology: A grand challenge for europe, European Science Foundation. www.​esf.​org
[73]
[74]
Savageau MA (1976) Biochemical Systems Analysis: A Study of Function and Design in Molecular Biology. Addison-Wesley, Reading, MA
[75]
[76]
[77]
Schaub J, Mauch K, Reuss M (2008) Metabolic flux analysis in Escherichia coli by integrating isotopic dynamic and isotopic stationary C-13 labeling data. Biotechnol Bioeng 99:1170‒1185PubMed
[78]
Schmalzriedt S, Jenne M, Mauch K, Reuss M (2003) Integration of Physiology and Fluid Dynamics. Adv Biochem Eng 80:19–68
[79]
Schmidt K, Carlsen M, Nielsen J, Villadsen J (1997) Modeling isotopomer distribution in biochemical networks using isotopomer maping matrices. Biotechnol Bioeng 55:831‒840PubMed
[80]
Schmidt K, Nielsen J, Villadsen J (1999) Quantitative analysis of metabolic fluxes in E. coli using 2-dimensional NMR spectroscopy and complete isotopomer models. J Biotechnol 71:175‒189PubMed
[81]
[82]
Schuster S, Fell D, Dandekar T (1999) A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks. Nature Biotechnol 18:326‒332
[83]
Schweder T, Krüger E, Xu B, Jürgen B, Blomsten G, Enfor S-O, Hecker M (1999) Monitoring of genes that respond to process-related stress in large-scale bioprocesses. Biotechnol Bioeng 65:151‒159PubMed
[84]
Segre D, Vitkup D, Church GM (2002) Analysis of optimality in natural perturbed metabolic networks. Proc Natl Acad Sci USA 99:15112‒15117PubMed
[85]
Shimizu K (2009) Towards systematic metabolic engineering based on the analysis of metabolic regulation by integration of different levels of information. Biochem Eng J 46:235‒251
[86]
Shlomi T, Berkman O, Ruppin E (2005) Regulatory on/off minimization of metabolic flux changes after genetic perturbations. PNAS 102(21):7695–7700PubMed
[87]
Sonntag K, Eggeling L, de Graaf AA, Sahm H (1993) Flux partitioning in the split pathway of lysine synthesis in Corynebacterium glutamicum – quantification by 13H- and 1H-NMR spectroscopy. Eur J Biochem 213:1325‒1331PubMed
[88]
Stephanopoulos GN, Aristidou AA, Nielsen J (1998) Metabolic Engineering. Academic Press, San Diego
[89]
Szyperski T (1995) Biosynthetically directed fractional 13 C labelling of proteinogenic amino acids – an efficient analytical tool to investigate intermediary metabolism. Eur J Biochem 232:433‒448PubMed
[90]
Szyperski T (1998) 13C-NMR, MS and metabolic flux balancing in biotechnological research. Q Rev Biophys 31:41‒106PubMed
[91]
Takors R (2012) Scale-up of microbial processes: Impacts, tools and open questions. J Biotechnol 160:3–9PubMed
[92]
Tang YJ, Martin HG, Myers S, Rodriguez S, Baidoo EE, Keasling JD (2009) Advances in analysis of microbial metabolic fluxes cia 13c isotopic labeling. Mass Spectrom Rev 28:362‒375PubMed
[93]
Umbarger HE, Brown B (1957) Threonine deamination in Escherichia coli. II. Evidence for two L-threonine deaminases. J Bacteriol 73:105‒112PubMedPubMedCentral
[94]
Vallino JJ, Stephanopoulos G (1993) Metabolic flux distribution in Corynbacterium glutamicum during growth and lysine overproduction. Biotechnol Bioeng 41:633‒646PubMed
[95]
Van Berlo RJ, de Ridder D, Daran JM, Daran-Lapujade PA, Teusink B, Reinders MJ (2011) Predicting metabolic fluxes using gene expression differences as constraints. IEEE/ACM Transactions on Computational Biology and Bioinformatics 8(1):206–216PubMed
[96]
van der Meer R, Westerhoff HV, van Dam K (1980) Linear relation between rate and thermodynamic force in enzyme-catalyzed reactions. Biochim Biophys Acta 591:488‒493PubMed
[97]
Varma A, Boesch BW, Palsson BO (1993) Stoichiometric interpretation of Escherichia coli glucose catabolism under various oxygenation rates. Appl Environ Microbiol 59:2465‒2473PubMedPubMedCentral
[98]
Varma A. Palsson BO (1994) Metabolic flux balancing: basic concepts, scientific and practical use. Bio/Technology 12:994‒998
[99]
Vaseghi S, Baumeister A, Rizzi M, Reuss M (1999) In vivo dynamics of the pentose phosphate pathway in Saccharomyces cerevisiae. Metab Eng 1:128‒140PubMed
[100]
Visser D, Heijnen JJ (2002) The mathematics of metabolic control analysis revisited. Metab Eng 4:114‒123PubMed
[101]
Visser D, Heijnen JJ (2003) Dynamic simulation and metabolic re-design of a branched pathway using linlog kinetics. Metab Eng 5:164‒176PubMed
[102]
Vrabel P, van der Lans RGJM, van der Schot FN, Luyben KChAM, Xu B, Enfor S-O (2001) CMA: integration o fluid dynamics and microbial kinetics in modeling of large-scale fermentations, Chem Eng J 84:463–474
[103]
Westerhoff HV, Palsson BO (2004) The evolution of molecular biology into systems biology. Nature Biotechnol 22(10):1249‒1252
[104]
Westerhoff HV, van Dam K (1987) Thermodynamics and control of biological free-energy transduction. Elsevier, Amsterdam
[105]
Wiechert W (2001) 13C Metabolic Flux Analysis. Metab Eng 3:195–206PubMed
[106]
Wiechert W. (2002) Modeling and simulation: tools for metabolic engineering. J Biotechnol 94:37‒63PubMed
[107]
Wiechert W, Möllney M, Isermann N, Wurzel M, de Graaf AA (1999) Bidirectional reaction steps in metabolic networks part III: Explicit solution and analysis of isotopomer labelling systems. Biotechnol Bioeng 66:69‒85PubMed
[108]
Wittmann C, Heinzle E. (2001) Application of MALDI-TOF MS to lysine-producing Corynebacterium clutamicum ‒ a novel approach for metabolic flux analysis. Eur J Biochem 268:2441‒2455PubMed
[109]
Woolston BM, Edgar S, Stephanolpoulos G (2013) Metabolic Engineering: Past and Future. Ann Rev Chem Biomol Eng 4:259–288
[110]
Wright BE, Kelly PJ (1981) Kinetic models of metabolism in intact cells, tissues and organisms. Curr Top Cell Regul 19:103‒158PubMed
[111]
Wu L, Wang W, van Winden WA, van Gulik WM, Heijnen JJ (2004) A new framework for the estimation of control parameters in metabolic pathways using lin-log kinetics. Eur J Biochem 271:3348‒3359PubMed
[112]
Zupke G, Stephanopoulos G (1994) Modeling of isotope distributions and intracellular fluxes in metabolic networks using atom mapping matrices. Biotechnol Prog 10:489–498
Metadaten
Titel
Systembiologie in der Bioverfahrenstechnik
verfasst von
Ralf Takors
Copyright-Jahr
2018
Verlag
Springer Berlin Heidelberg
Buch
Bioprozesstechnik

Print ISBN: 978-3-662-54041-1

Electronic ISBN: 978-3-662-54042-8

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-662-54042-8_13

Premium Partner

    Bildnachweise