biomathematics

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biomathematics

(bī′ō-măth′ə-măt′ĭks)
n. (used with a sing. verb)
The application of mathematical principles to biological processes.

bi′o·math′e·mat′i·cal adj.
bi′o·math′e·ma·ti′cian (-mə-tĭsh′ən) n.
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References in periodicals archive ?
An overview of the amyloid biomathematical methodology is described briefly, followed by the screening of tau PET radiotracers using the biomathematical methodology.
2014b, The MathWorks, US) [5], to support the screening of amyloid radiotracers based on the proposed amyloid biomathematical screening methodology.
In this paper, we evaluated the feasibility of extending a previously developed amyloid biomathematical screening methodology to support the screening of candidate tau radiotracers during compound development.
However, we were limited by the small number of reported kinetic parameters and SUVR values to fully assess the amyloid biomathematical model for screening tau radiotracers.
However, there were also issues with metabolites crossing the BBB (e.g., [[sup.11]C] PBB3), but the amyloid biomathematical screening methodology could not be used to predict the possibility of metabolites crossing this barrier.
The amyloid biomathematical screening methodology could not predict off-target binding, and the inclusion of multiple binding sites appeared to be required for tau radiotracers to correct for this issue.
Thus, it is not feasible to directly apply the amyloid biomathematical screening methodology to tau radiotracers due to the increased complexity of evaluating the binding of tau radiotracers, namely, target-binding, off-target binding, and non-specific binding.
Watabe, "Biomathematical screening of amyloid radiotracers with clinical usefulness index," Alzheimer's and Dementia: Translational Research & Clinical Interventions, vol.
Dinges, "Optimization of biomathematical model predictions for cognitive performance impairment in individuals: accounting for unknown traits and uncertain states in homeostatic and circadian processes," Sleep, vol.
This is a useful adjunct to the usual biomathematical modeling approach using reproductive numbers at different points in time, representing the average number of infections, excluding SSEs, caused by infected individuals in successive generations at time t throughout the SARS epidemic (Riley et al.