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The proposed approach is demonstrated with two examples using experimental measurements from laboratory systems.
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An illustrative example using experimental data is provided to showcase the effectiveness of the proposed methodology.
One example of using experimental evolution to study the relationship between robustness and evolvability comes from Paul Turner's lab at Yale University.
The validation of the presented model was carried out on an example supersonic ejector using experimental, numerical and analytical data.
After defining all the initial metabolite concentrations, kinetic rate equations and fluxes, the exported draft kinetic model (SBML file) is ready for further parameterization (for example, parameter fitting using experimental data available on the repository) and analysis in external tools such as the COPASI [ 33] and the SBToolbox for Matlab [ 32].
An application example is presented using experimental results obtained from the literature.
A generic flow control process is put forward and illustrated using experimental examples.
The curve shapes produced by the model are typical of those produced using experimental data (for examples, see [ 14, 15]) albeit over shorter time periods (as discussed above).
For example, [ 37] assigned E. coli genes to the non-essential and essential categories using experimental evidence and known function.
The methods are illustrated by identification examples using both artificial and experimental data.
For example, using an experimental design of four-fold biological replication and no technical replication, we showed that detection of mutants in the 4295 mutant yeast deletion collection with two-fold (or more) change between conditions can be achieved with 96% power at a 5% false discovery rate (FDR) using as few as 6 million reads per condition.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com