subtilis (data of both organisms were taken from [5]), S. cerevisiae [30], Hansenula polymorpha and two Pseudomonas strains. On average, the metabolic flux ratio analysis with Flux-P runs about three to five times faster than the manual analysis.

The same holds for the calculation of the flux distribution in netFlux. Hence, a complete 13C-based MFA (including file upload to the BKM120 price server) performed with Flux-P requires about 4 min instead of 12 to 20 min needed for a manual analysis. As metabolic flux experiments do not only produce a single data set that has to be analyzed, but often 20, 50 or even 150 data sets, this means that the time spent for the data analyses for Inhibitors,research,lifescience,medical an experiment is now only about 1:20 h, 3:20 h,

or 10 h instead of up to 6:40 h, 16:40 h, or 50 h, respectively. Furthermore the manual analysis requires the full attention of an (experienced) Inhibitors,research,lifescience,medical human user, hence it is expensive in the sense that it can easily consume a whole man-week of work. In contrast, the automatic analysis workflows run autonomously in the background, possibly overnight, so that the researcher can focus on other tasks in the meantime. For analysis Inhibitors,research,lifescience,medical procedures that do not involve human interaction, it is easy to see that the automation of the in silico experiment using workflow technology increases the speed of the analyses without influencing the results at all. However, workflow realizations of usually interactive analysis processes do not necessarily impact the quality of the results: it is often possible Inhibitors,research,lifescience,medical to identify quantifiable criteria in the human expert’s analysis behavior, and apply these for at least heuristic user interaction emulation. The quality of the calculated metabolic flux ratios and intracellular fluxes was investigated Inhibitors,research,lifescience,medical by a systematic comparison with the results of the manual analysis. In general, calculated ratios and reaction rates, automatically and manually calculated, coincided quite well. As an example a comparison of automatically and

manually calculated flux distributions and metabolic flux ratios are shown in Figure 5 and Figure 6. For the estimation of the E. coli and B. subtilis flux distributions, data from 1-13C and U-13C-labeling experiments were available Olopatadine and combined for the analysis (using the workflow shown in Figure 4A). These comprehensive datasets resulted in flux distributions with very high congruency (linear correlation coefficients above 0.99). Moreover, we checked if the data analysis workflow is consistent by repeating the analysis of several datasets 20 times. In all calculations both metabolic flux ratios and fluxes were almost identical with only minor differences in the metabolic flux ratios that did not impact the net flux distribution. Figure 6 Consistency of metabolic flux ratio analysis calculated with Flux-P. H. polymorpha metabolic flux ratios (unpublished data) calculated manually with FiatFlux and with Flux-P show high congruency.