Sentence examples for majority of mathematical from inspiring English sources

The majority of mathematical models used to describe this novel mechanical behavior are based on percolation models of microstructural connectivity.

It is a prerequisite for other concepts in undergraduate level and its traces are visible in the majority of mathematical courses at university level.

The majority of mathematical models assumes that only one virus can infect a given cell at a time.

In contrast to the vast majority of mathematical models for the NFκB signaling pathway, the present model considers IKK phosphorylation independently of IκBα and NFκB.

So far, the majority of mathematical models of biochemical pathways have been developed based on data collected from different sources [6].

The majority of mathematical models (Schnell and Maini, 2003) describing enzymatic activity are Michaelis-Menten-type (MM) models, that is, they describe the dependency of the initial reaction speed on the initial substrate concentration.

Although some scientists have long believed that black carbon is a major force in climate change, the vast majority of previous mathematical models had predicted that the particles had only a modest impact.

So far, the majority of the mathematical models in PFV have been developed for redox proteins undergoing a single-step electron transfer reactions.

The majority of these mathematical approaches are quite dissimilar to the agent-based modeling presented here, in that ours is an agent-based computational model, essentially devoid of theoretically derived equations.

The majority of existing mathematical models [ 4, 11– 20] give a good representation of either the first two stages [ 11, 13, 21– 24] or the last stage of the infection [ 25] but do not describe the three stages observed in HIV infection in a single framework.

Except for biologically detailed modeling studies, the overwhelming majority of works in mathematical neuroscience have treated neurons as point neurons, i.e., a linear aggregation of synaptic input followed by a nonlinearity in the generation of somatic action potentials was assumed to characterize a neuron.