FiatFlux-P - User-Level Workflow Design: A Bioinformatics Perspective - page 103

analysis) and absolute intracellular fluxes by 13 C-based metabolic flux analy-
sis (net flux computation) [95]. Currently, the analysis is restricted to GC-MS
derived mass spectral data of proteinogenic amino acids from cultures grown
on mixtures of uniformly labeled glucose (U- 13 C-glucose), 1- 13 C-glucose and
naturally labeled glucose. The software reads mass spectral data from 13 C-
labeling experiments that is provided in netCDF format (CDF: common data
format) and saves it in a .ff-file (FF: FiatFlux) for internal use. The data can
then directly be analyzed in the modules ratio and netto ,inwhichthe
METAFoR analysis and net flux computation are implemented, respectively.
Fig. 5.3 FiatFlux desktop user interface for METAFoR analysis
Figure 5.3 shows the user interface of FiatFlux for the METAFoR analysis.
When MS data is loaded, the software automatically detects and assigns the
amino acid fragments (displayed in the “MS Data” frame). Additionally, the
user has to specify the different experimental parameters. Then the mass
distribution vectors of the amino acid precursors (MDV M ) are calculated by
least square fitting (and displayed in the “Fitting” frame) and flux ratios are
estimated using probabilistic equations (and displayed in the “Flux ratios”
frame).
The visualization of the MDV M facilitates the diagnosis of faulty measure-
ments, such as outlier amino acid fragments that are indicated by abnormal
residuals. To exclude such faulty or redundant data from the calculations,