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Here we identify the neoplastic and non-neoplastic component of lymphoma microenvironment using transcriptomics and proteomics followed by Systems Biology modeling to generates specific hypotheses and then tests these using reductionist methods.
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Therefore, we rely on modeling to generate estimates by country and region, and for the world.
We used Hierarchical Bayes modeling to generate the mean relative importance score for each adverse event.
We used mathematical modeling to generate two simple mechanisms capable of analog implementation of such an operation.
This may call for the use of more complex generative models to generate such textures.
We used GeneSpider and a linear model to generate datasets, while GNW has nonlinearities built in to its dataset generation.
(The Upshot team, at the _Times, _even allowed readers to use its model to generate their own forecasts).
He used computer models to generate the cosmic chords from creation for the first million years and condensed them to five seconds.
(The Upshot team, at the Times, even allowed readers to use its model to generate their own forecasts).
The E.P.A. doesn't require upfront data on new chemicals; the agency uses precautionary models to generate worst-case scenarios.
Suppose we select m individual models to generate hybrid forecasting.
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