For validation simulated tumours were used which were derived from real patient data (liver metastases of a colorectal carcinoma and head and neck cancer, respectively).
Cross-validation simulates how well a model predicts new data and gives a statistical fraction of the total variation of the dependent variables that can be predicted by all the extracted components (QCUM) for the final model.
We demonstrated VarSim's completeness in both simulation and validation by simulating NA12878's personal genome with small variants from genome in a bottle (GiaB) high-confidence regions (Zook et al., 2014), and with SVs from 1000 genomes (Mills et al., 2011) and DGV (MacDonald et al., 2014).
The stochastic epidemiological model used for validation simulates disease progression in isolated groups of n individuals and provides the disease status of individuals (infected/not infected) over time as output.
The method uses flamelet tabulated detailed chemistry and is first applied to the simulation of laminar flames (1D and 2D) over various grids for validation, before simulating a turbulent burner studied experimentally by Sweeney et al. (2012).
This work also presents a systematic method for the model validation, allowing simulating the system under any operating conditions.
A first numerical application has been performed for preliminary validation purposes, simulating the flexural behaviour of representative section of a stiffened composite plate.
For this metabolic system, a detailed kinetic model (Jamshidi, 2001) is readily available for validation, by simulating the steady-state metabolic flux after gene knockouts.
We address the inherent limitation to the use of cross-validation by simulating a more realistic target-prediction experiment as a proxy.
In this process, especially for future scenario simulations, the validation of simulated carbon stock in contemporary land ecosystems would be of great importance, because bias in CMIP5 historical simulations is one cause of strong variability in the simulated future changes of carbon stock within CMIP5 and LUCID-CMIP5 simulations (Brovkin et al. [2013]; Anav et al. [2013]).
