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However, complex animal model systems typically have significant limitations on cohort sizes, number of samples, and the ability to perform follow-up and validation experiments.
In tumour biology, model systems typically involve cancer cells that have been passaged numerous times in vitro to provide cancer cell lines [ 1].
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A biological model system typically has different levels of invariant features along its 'major' axes.
The RBL-2H3 tumor mast cell is commonly used as a model system, typically by priming cells with monoclonal IgE specific for a hapten.
Such model systems do typically arise in geobiochemical modelling where the reproduction of these properties is vital.
Such model systems are typically generated from an osteosarcoma primary tumor, but undergo many changes due to culturing or interactions with a different host species, which may result in differences in gene expression between primary tumor cells, and tumor cells from the model system.
Models for complex systems typically do not fit neatly within a single domain, however.
In these classical symbiotic model systems, the symbionts are typically elusive outside the host, and can even be considered as members of the rare biosphere., The symbiont population is therefore mainly found dwelling in the host cells or tissues.
To combine these two filtering approaches, current model-based hybrid recommendation systems typically require extensive feature engineering to construct a user profile.
Given these limitations current systems typically build models from the kinematics of the vocal tract which can be directly observed.
Analytic modeling for performance evaluation of distributed systems typically requires the solution of large multichain queueing network models.
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