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Computational models provide insight into how mental representations might be organized and transformed.
Full kinetic models provide insight into enzyme mechanism and kinetics and also support bioconversion process design and feasibility assessment.
More complex models provide insight into detailed physiological mechanisms, but their utility is maximized if one can quickly identify patient specific parameters.
The developed models provide insight into how the overall process-flow could be affected by errors (variability) due to both physical and data transfer across multiple systems.
QSAR and molecular docking models provide insight into the mechanism of inhibition and indicate the optimal direction of future synthetic efforts.
Animal and cellular models, including humanized models, provide insight into the function of genes and the mechanisms underlying rare diseases can be manipulated experimentally much more readily than humans for both ethical and technical reasons, allowing important questions that cannot be addressed in patients to be approached.
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Air quality models provide insights into the outcomes of future vehicle emission regulations and programs.
The great lesson for all those who use mathematical models as tools to understand the real world is that models provide insights, not answers.
Simulation models provide insights and uncertainties in soil-atmosphere-biosphere fluxes.
The mathematical models provide insights into the effect of quiescence on the basic kinetics of the response to targeted treatment of CML.
Additionally, univariate models provided insight on the magnitude and direction of NTZ effects.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com