![](bg4.png)
iments do not overlap, see figure 1. In our interpre-
tation this indicates the inadequacy of this approach.
However the model fits remarkably to individual ex-
periments, we would like to point out that this only
proves the models flexibility to capture the different
sigmoidal shapes.
By introducing a constant to the model, propor-
tional to the initial glucose bolus we managed to
achieve a good overall fit of the model with the same
set of parameters on different experiments (figure 2).
The trade-off is that MSE values to particular exper-
iments are moderately high. We found that our ap-
proach was adequate in fitting several experiments.
The random variables in the objective function re-
sulted that the algorithm is dynamically changing the
weights between the experiments, and ensures a good
convergence even if the sum of the error surfaces
would get difficult.
The sigmoid shape of the glucose uptake was found
slightly varying on the different experiments. This
might be a consequence of the different activity of
the glucose uptake systems revealed by (Castro et al.,
2009), or the differences between the transport of the
glucose monomers. We are also aware of that the glu-
cose uptake might be influenced by other factors, for
example the biomass, a feedback mechanism from the
inside of the cell or the energy level of the cell accord-
ing to (Papagianni et al., 2007). The model could be
extended to involve these aspects.
5 CONCLUSIONS AND FUTURE
WORK
Here we introduced a model to Lactococcus lactis
glucose uptake, and an approach based on PSO to fit it
to three glucose perturbation experiments with differ-
ent glucose input. With our approach a good overall
fit was achieved to the data using one set of parame-
ters. We think that this could be a future way towards
unified modeling of data with different experimental
conditions.
We can not exclude that our model is not complete,
and additional terms might be missing from it. Our
future work will aim to identify these terms. We
are also considering the distinct modeling of the glu-
cose monomers and to extend the identification of the
model to aerobic conditions.
ACKNOWLEDGEMENTS
This work was supported by project DynaMo
(PTDC/EEA-ACR/69530/2006) FCT, Portugal.
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