metabolic flux analysis
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Author(s):  
Mohsin Rahim ◽  
Mukundan Ragavan ◽  
Stanislaw Deja ◽  
Matthew E. Merritt ◽  
Shawn C. Burgess ◽  
...  

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Cara L. Sake ◽  
Alexander J. Metcalf ◽  
Michelle Meagher ◽  
Jorge Di Paola ◽  
Keith B. Neeves ◽  
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Author(s):  
Kevin L. Chu ◽  
Somnath Koley ◽  
Lauren M. Jenkins ◽  
Sally R. Bailey ◽  
Shrikaar Kambhampati ◽  
...  

2021 ◽  
Author(s):  
Collin Starke ◽  
Andre Wegner

MetAMDB (https://metamdb.tu-bs.de/) is an open source metabolic atom mapping database, providing atom mappings for around 75000 metabolic reactions. Each atom mapping can be inspected and downloaded either as a RXN file or as a graphic in SVG format. In addition, MetAMDB offers the possibility of automatically creating atom mapping models based on user-specified metabolic networks. These models can be of any size (small to genome scale) and can subsequently be used in standard 13C metabolic flux analysis software.


Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1577
Author(s):  
Philippe Bogaerts ◽  
Alain Vande Vande Wouwer

Metabolic flux analysis is often (not to say almost always) faced with system underdeterminacy. Indeed, the linear algebraic system formed by the steady-state mass balance equations around the intracellular metabolites and the equality constraints related to the measurements of extracellular fluxes do not define a unique solution for the distribution of intracellular fluxes, but instead a set of solutions belonging to a convex polytope. Various methods have been proposed to tackle this underdeterminacy, including flux pathway analysis, flux balance analysis, flux variability analysis and sampling. These approaches are reviewed in this article and a toy example supports the discussion with illustrative numerical results.


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