However, the verification of the applied diffusion models remains challenging.
Due to the uncertainty about the governing mechanisms contributing to rock avalanche motion, the development of mechanistic models remains challenging.
Despite decades of extensive research, the application of cell-based bone tissue engineering in clinically relevant models remains challenging.
However, the numerical implementation of cell-based models remains challenging, and little work has been done to understand to what extent implementation choices may influence model predictions.
These models have been widely used for about a decade, and although significant advances in theory and technology have been incorporated into their development, evaluating the veracity of simulated results from forest landscape models remains challenging.
Validation of flood models remains challenging due to a lack of available spatially-explicit data; traditionally measured data and validation approaches reveal little about the ability of a model to simulate the complex dynamics of floodplain flows, including the pathways, timeline, and impacts of an event.
Despite the availability of atomic level structure of a number of GPCRs (41 – 43), homology modeling remains challenging.
As there is no one in vitro model which can mimic all properties of the in vivo BBB, developing more reliable models remains challenging [ 4].
Although PCA is widely used for the dimensional reduction of biomedical data, with applications in visualization, clustering and regression, interpretation of PCA-based models remains challenging.
However, the experimental assessment of such cell-type specific intracell-type specificels remaintracellularng in a preclinical setting and to a greater extent in cancer patients.
