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Complex mathematical expressions can define species or global quantities, but writing complex expressions in a model containing many entities/functions can be difficult and error prone.
Examples of the latter approach include the LeMoNe (Learning Module Networks) algorithm of Joshi et al. [ 16] which generates a number of possible models explaining regulation activity and with every single model containing many regulators.
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This model contains many real-world factors such as cell workload balance, limitation of delivery time, and also negative effects of wasted time resulting from machine failure.
Because our model contains many free parameters, it is extremely difficult to estimate probabilistic distributions of all parameters simultaneously within a feasible time.
The model contains many features described for the generic model that would help filter noise.
The proposed model contains many of the existing models as particular cases.
The G. metallireducens metabolic model contains many additional reactions reflecting these specific metabolic capabilities that the G. sulfurreducens model does not have.
Since the output of the model contains many data, there are numerous ways to measure and weigh the effects of a parameter change in the model.
Since the developed model contains many more parameters than can be estimated from three time series of data, it was required to use local sensitivity analysis to determine which parameters should be re-estimated.
Moreover, traditional CAD models containing many small (and possibly trimmed) patches are not directly usable for IgA.
A black-box approach can be used more universally, but results in models containing many parameters that cannot easily be interpreted.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com