Research Topics
| W WiechertSummaryAffiliation: University of Siegen Country: Germany Publications
| Collaborators
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Detail Information
Publications
Modeling and simulation: tools for metabolic engineeringWolfgang 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....
Visualizing regulatory interactions in metabolic networksStephan 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...
Metabolic isotopomer labeling systems. Part I: global dynamic behaviorW 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...
13C metabolic flux analysisW 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...
A universal framework for 13C metabolic flux analysisW 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...
From stationary to instationary metabolic flux analysisWolfgang 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...
Investigating the dynamic behavior of biochemical networks using model familiesMarc Daniel Haunschild
Department of Simulation, University of Siegen, Paul-Bonatz-Strasse 9-11, D-57068 Siegen, Germany
Bioinformatics 21:1617-25. 2005..MMT2 supplies XML model specification and several software interfaces. The performance of MMT2 is illustrated by several examples from ongoing research projects. AVAILABILITY: http://www.simtec.mb.uni-siegen.de/ CONTACT: ...
The thermodynamic meaning of metabolic exchange fluxesWolfgang 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...
Bidirectional reaction steps in metabolic networks: III. Explicit solution and analysis of isotopomer labeling systemsW 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...
Visual exploration of isotope labeling networks in 3DP 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...
The topology of metabolic isotope labeling networksMichael 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...
Computational tools for isotopically instationary 13C labeling experiments under metabolic steady state conditionsKatharina 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...
Experimental design principles for isotopically instationary 13C labeling experimentsKatharina 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...
Translating biochemical network models between different kinetic formatsFrieder 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...
Unravelling the regulatory structure of biochemical networks using stimulus response experiments and large-scale model selectionS 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...
Metabolic isotopomer labeling systems. Part II: structural flux identifiability analysisNicole 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...
An introduction to 13C metabolic flux analysisWolfgang 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
Interpretation of metabolic flux maps by limitation potentials and constrained limitation sensitivitiesS Aljoscha Wahl
Institute of Biotechnology 2, , , 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...
13C labeling experiments at metabolic nonstationary conditions: an exploratory studySebastian 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...
MMT--a pathway modeling tool for data from rapid sampling experimentsJochen 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...
New tools for mass isotopomer data evaluation in (13)C flux analysis: mass isotope correction, data consistency checking, and precursor relationshipsS Aljoscha Wahl
, , , 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...
Metabolic flux analysis at ultra short time scale: isotopically non-stationary 13C labeling experimentsKatharina 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...
Serial 13C-based flux analysis of an L-phenylalanine-producing E. coli strain using the sensor reactorAljoscha 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...
Emerging Corynebacterium glutamicum systems biologyVolker 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...
