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More importantly, through a heat flux analysis, we found that the ratio of the latent heat flux to the sensible heat flux (ql/qs) can be used as a general criterion in designing the comfort performance of a cloth system.
For the flux analysis, we used our tool, written in OCaml, that implements the definitions below.
In our flux analysis, we consider the individual time intervals, where each of A, B and C increase and decrease.
In the charge flux analysis, we typically integrate over 10 60 s of current recordings and perform all current measurements and charge flux calculations in triplicate.
By performing C6-glucose metabolic flux analysis, we show for the first time that the tumors undergo metabolic re-programming toward anaerobic metabolism, thereby uncoupling glycolysis from oxidative phosphorylation.
For non-stationary metabolic flux analysis we developed a tool called "Isodyn" (from "isotopomer dynamics") [ 8- 10] that simulates C redistribution in metabolites by automatically constructing and solving large systems of differential equations for isotopomers.
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Using flux variability analysis, we will analyze the reconstructed model with respect to general (PNSB-wide) and species-specific network properties and utilize it to characterize phenotypic states for different environmental conditions.
In a process that closely resembles flux variability analysis, we add a reversible demand reaction for each metabolite in turn that allows for us to relax the steady-state assumption for metabolites of interest.
In this flux feasibility analysis, we evaluate whether a reaction set C is a cut set for objective set J by checking the feasibility of { v ∈ K| v C = 0, v j ≠ 0} for each objective j ∈ J through analysis of primal and dual feasible points in a sequence of linear programs.
On the basis of metabolite flux-sum analysis, we also found a viewpoint opposed to the widespread realization that in NZN111, NADH/NAD+ imbalance mainly resulted from the inactivation of PFL rather than the inactivation of LDH, which was consistent with the experimental results and gene expression profile of the wild-type E. coli and NZN111.
Through flux-sum analysis, we can identify metabolites which are in vivo essential and in silico blocked.
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