W Wiechert

Summary

Affiliation: University of Siegen
Country: Germany

Publications

  1. ncbi Modeling and simulation: tools for metabolic engineering
    Wolfgang Wiechert
    Department of Simulation and Computer Science, Institute of Mechanical and Control Engineering, University of Siegen, Paul Bonatz Str 9 11, D 57068 Siegen, Germany
    J Biotechnol 94:37-63. 2002
  2. pmc Visualizing regulatory interactions in metabolic networks
    Stephan Noack
    Institute of Biotechnology 2, Research Centre Julich, Germany
    BMC Biol 5:46. 2007
  3. ncbi Metabolic isotopomer labeling systems. Part I: global dynamic behavior
    W Wiechert
    IMR, Department of Simulation, University of Siegen, Paul Bonatz Str 9 11, D 57068, Siegen, Germany
    Math Biosci 169:173-205. 2001
  4. ncbi 13C metabolic flux analysis
    W Wiechert
    Department of Simulation, IMR, University of Siegen, Paul Bonatz Strasse 9 11, D 57068 Siegen, Germany
    Metab Eng 3:195-206. 2001
  5. ncbi A universal framework for 13C metabolic flux analysis
    W Wiechert
    Department of Simulation, IMR, University of Siegen, Paul Bonatz Strasse 9 11, D 57068 Siegen, Germany
    Metab Eng 3:265-83. 2001
  6. ncbi From stationary to instationary metabolic flux analysis
    Wolfgang Wiechert
    Department of Simulation, Institute of Systems Engineering, University of Siegen, Paul Bonatz Strasse 9 11, 57068 Siegen, Germany
    Adv Biochem Eng Biotechnol 92:145-72. 2005
  7. ncbi Investigating the dynamic behavior of biochemical networks using model families
    Marc Daniel Haunschild
    Department of Simulation, University of Siegen, Paul Bonatz Strasse 9 11, D 57068 Siegen, Germany
    Bioinformatics 21:1617-25. 2005
  8. pmc The thermodynamic meaning of metabolic exchange fluxes
    Wolfgang Wiechert
    Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
    Biophys J 93:2255-64. 2007
  9. ncbi Bidirectional reaction steps in metabolic networks: III. Explicit solution and analysis of isotopomer labeling systems
    W Wiechert
    IMR, Department of Simulation, University of Siegen, Paul Bonatz Strasse 9 11, D 57068 Siegen, Germany
    Biotechnol Bioeng 66:69-85. 1999
  10. ncbi Visual exploration of isotope labeling networks in 3D
    P Droste
    Simulation Group, Institute of Systems Engineering, Faculty 11 12, University of Siegen, 57068 Siegen, Germany
    Bioprocess Biosyst Eng 31:227-39. 2008

Collaborators

Detail Information

Publications24

  1. ncbi Modeling and simulation: tools for metabolic engineering
    Wolfgang Wiechert
    Department of Simulation and Computer Science, Institute of Mechanical and Control Engineering, University of Siegen, Paul Bonatz Str 9 11, D 57068 Siegen, Germany
    J Biotechnol 94:37-63. 2002
    ....
  2. pmc Visualizing regulatory interactions in metabolic networks
    Stephan Noack
    Institute of Biotechnology 2, Research Centre Julich, Germany
    BMC Biol 5:46. 2007
    ..Here we focus on the representation of this type of information given by the strength of regulatory interactions between metabolite pools and reaction steps...
  3. ncbi Metabolic isotopomer labeling systems. Part I: global dynamic behavior
    W Wiechert
    IMR, Department of Simulation, University of Siegen, Paul Bonatz Str 9 11, D 57068, Siegen, Germany
    Math Biosci 169:173-205. 2001
    ..This cascade structure has considerable consequences for the development of efficient numerical algorithms for the solution of ILSs and thus for MFA...
  4. ncbi 13C metabolic flux analysis
    W Wiechert
    Department of Simulation, IMR, University of Siegen, Paul Bonatz Strasse 9 11, D 57068 Siegen, Germany
    Metab Eng 3:195-206. 2001
    ..This minireview summarizes these recent developments and sketches the major practical problems. An outlook to possible future developments concludes the text...
  5. ncbi A universal framework for 13C metabolic flux analysis
    W Wiechert
    Department of Simulation, IMR, University of Siegen, Paul Bonatz Strasse 9 11, D 57068 Siegen, Germany
    Metab Eng 3:265-83. 2001
    ..Finally, a specific experiment is evaluated and the various statistical methods used to analyze the results are briefly explained. The appendix gives some details about the software implementation and availability...
  6. ncbi From stationary to instationary metabolic flux analysis
    Wolfgang Wiechert
    Department of Simulation, Institute of Systems Engineering, University of Siegen, Paul Bonatz Strasse 9 11, 57068 Siegen, Germany
    Adv Biochem Eng Biotechnol 92:145-72. 2005
    ..This paper presents some recent developments in the field of instationary metabolic flux analysis and discusses some critical aspects and limitations using some simulation examples...
  7. ncbi Investigating the dynamic behavior of biochemical networks using model families
    Marc Daniel Haunschild
    Department of Simulation, University of Siegen, Paul Bonatz Strasse 9 11, D 57068 Siegen, Germany
    Bioinformatics 21:1617-25. 2005
    ..Powerful automatic methods are then required to assist the modeler in the organization and the evaluation of alternative models. Moreover, the structure and peculiarities of the data require dedicated tool support...
  8. pmc The thermodynamic meaning of metabolic exchange fluxes
    Wolfgang Wiechert
    Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
    Biophys J 93:2255-64. 2007
    ..This relation has far-reaching consequences for metabolic flux analysis, quantitative metabolomics, and network thermodynamics...
  9. ncbi Bidirectional reaction steps in metabolic networks: III. Explicit solution and analysis of isotopomer labeling systems
    W Wiechert
    IMR, Department of Simulation, University of Siegen, Paul Bonatz Strasse 9 11, D 57068 Siegen, Germany
    Biotechnol Bioeng 66:69-85. 1999
    ..Finally, some illustrative examples are examined to show that an information increase is not guaranteed when isotopomer measurements are used in addition to positional enrichment data...
  10. ncbi Visual exploration of isotope labeling networks in 3D
    P Droste
    Simulation Group, Institute of Systems Engineering, Faculty 11 12, University of Siegen, 57068 Siegen, Germany
    Bioprocess Biosyst Eng 31:227-39. 2008
    ..All features of CumoVis are explained with an educational example and a realistic network describing carbon flow in the citric acid cycle...
  11. pmc The topology of metabolic isotope labeling networks
    Michael Weitzel
    Institute of Biotechnology, Research Centre Julich, 52425 Julich, Germany
    BMC Bioinformatics 8:315. 2007
    ..In this context, the global analysis of ILN topology turns out to be a clue for realizing large speedup factors in all required computational procedures...
  12. ncbi Computational tools for isotopically instationary 13C labeling experiments under metabolic steady state conditions
    Katharina Nöh
    Department of Simulation, Faculty 11 12, University of Siegen, D 57068 Siegen, Germany
    Metab Eng 8:554-77. 2006
    ..It will be shown that although still not all fluxes are identifiable, the quality of flux estimates can be strongly improved in the instationary case. Moreover, statements about the size of some immeasurable pool sizes can be made...
  13. ncbi Experimental design principles for isotopically instationary 13C labeling experiments
    Katharina Nöh
    Department of Simulation, Faculty 11 12, University of Siegen, D 57068 Siegen, Germany
    Biotechnol Bioeng 94:234-51. 2006
    ..Finally, a framework for almost optimal experimental design of isotopically instationary experiments is proposed which provides a practical guideline for the analysis of large-scale networks...
  14. doi Translating biochemical network models between different kinetic formats
    Frieder Hadlich
    Department of Simulation, Institute of Systems Engineering, University of Siegen, Germany
    Metab Eng 11:87-100. 2009
    ..Moreover, the local and global approximation capabilities of the models are elucidated and some pitfalls of traditional single model approaches to data evaluation are revealed...
  15. ncbi Unravelling the regulatory structure of biochemical networks using stimulus response experiments and large-scale model selection
    S A Wahl
    Department of Simulation, Institute of Systems Engineering, Faculty 11 12, University of Siegen, Paul Bonatz Str 9 11, Siegen 57068, Germany
    Syst Biol (Stevenage) 153:275-85. 2006
    ..It is illustrated by the example of the aromatic amino acid synthesis pathway in Escherichia coli...
  16. ncbi Metabolic isotopomer labeling systems. Part II: structural flux identifiability analysis
    Nicole Isermann
    IMR, Department of Simulation, University of Siegen, Germany
    Math Biosci 183:175-214. 2003
    ..Moreover, several small examples are worked out to illustrate the influence of input metabolite labeling and the paradox of information loss due to network simplification...
  17. ncbi An introduction to 13C metabolic flux analysis
    Wolfgang Wiechert
    Department of Simulation, IMR, Paul Bonatz Str 9 11, University of Siegen, D 57068 Siegen, Germany
    Genet Eng (N Y) 24:215-38. 2002
  18. ncbi Interpretation of metabolic flux maps by limitation potentials and constrained limitation sensitivities
    S Aljoscha Wahl
    Institute of Biotechnology 2, Forschungszentrum Julich GmbH, Julich, Germany
    Biotechnol Bioeng 94:263-72. 2006
    ..It can be shown that the reachable yield is drastically reduced by the measured efflux into the TCA cycle, while the oxidative pentose-phosphate pathway only plays a secondary role on the reachable maximum...
  19. pmc 13C labeling experiments at metabolic nonstationary conditions: an exploratory study
    Sebastian Aljoscha Wahl
    Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
    BMC Bioinformatics 9:152. 2008
    ..In metabolic flux analysis, the use of 13C labeled substrates together with isotopomer modeling solved the problem of underdetermined networks and increased the accuracy of flux estimations significantly...
  20. ncbi MMT--a pathway modeling tool for data from rapid sampling experiments
    Jochen Hurlebaus
    Institut fuer Biotechnologie 2, Forschungszentrum Juelich GmbH, 52425 Julich, Germany
    In Silico Biol 2:467-84. 2002
    ..The integration of all necessary algorithms in one tool allows fast model analysis and comparison. Complex models have been developed to describe the central metabolic pathways of Escherichia coli during a glucose pulse experiment...
  21. ncbi New tools for mass isotopomer data evaluation in (13)C flux analysis: mass isotope correction, data consistency checking, and precursor relationships
    S Aljoscha Wahl
    Institut für Biotechnologie 1, Forschungszentrum Julich, 52525 Jülich, Germany
    Biotechnol Bioeng 85:259-68. 2004
    ..A versatile MatLab tool for the rapid correction and consistency checking of MS spectra is presented. Practical examples for the described methods are also given...
  22. ncbi Metabolic flux analysis at ultra short time scale: isotopically non-stationary 13C labeling experiments
    Katharina Nöh
    Institute of Biotechnology, Forschungszentrum Julich GmbH, D 52425 Julich, Germany
    J Biotechnol 129:249-67. 2007
    ..This offers new insight into the biological operation of the metabolic network in vivo...
  23. ncbi Serial 13C-based flux analysis of an L-phenylalanine-producing E. coli strain using the sensor reactor
    Aljoscha Wahl
    Institute of Biotechnology, Forschungszentrum Julich GmbH, 52425 Julich, Germany
    Biotechnol Prog 20:706-14. 2004
    ..Hence, pps overexpression should be performed to optimize the existing production strain...
  24. ncbi Emerging Corynebacterium glutamicum systems biology
    Volker F Wendisch
    Institute of Biotechnology 1, Research Center Juelich, Germany
    J Biotechnol 124:74-92. 2006
    ..glutamicum. We will present current developments that advanced our insight into fundamental biology of C. glutamicum and that in the future will enable novel biotechnological applications for the improvement of amino acid production...