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The structures enable construction of homology models of pathogen RNAP antibiotic complexes, enable in silico screening for new antibacterial agents, and enable rational design of improved antibacterial agents.
This technology has been experimentally validated in animal models of pathogen challenge and tumor protection following administration of a DNA vaccine and has led to extensive research into the mechanisms of protective immunity.
Therefore, in the literature, building new sustainable cropping systems relies on mathematical models of pathogen evolution [ 15, 23- 26].
The concept of the pathogen's immunological phenotype can help bridge the gap between the complexity of these interactions and theoretical models of pathogen evolution.
30, 101, 104 Uncertainty over evolutionary constraints and the strength of competition is a sticking point in these models of pathogen evolution.
Therefore, models of pathogen infection must examine this transmission potential and focus on how landscape features directly influence this potential and the resulting patterns of pathogen spread.
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Genome-scale metabolic models of pathogens are extensively exploited to predict putative drug targets with FBA frameworks [ 9- 11].
We present an agent-based model of pathogen spread that can be used to evaluate the impact on nosocomial risk of alternative management decisions adopted to deal with transitory nurse shortage.
We wished to determine if our model of pathogen spread, once parameterized with known information about the behaviour of bumble bees and their pathogens, could be used to predict patterns of disease near commercial greenhouses.
We constructed a spatially explicit model of pathogen spillover in bumble bees and, using laboratory experiments and the literature, estimated parameter values for the spillover of Crithidia bombi, a destructive pathogen commonly found in commercial Bombus.
These findings can be used as a model of pathogen global diversity.
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