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Modelling life cycle processes with descriptions of host abundance and habitat fragmentation produced the best outcome when coordinates were missing.
However, the following descriptions of host and parasite biology, as well as the general experimental schemes, are applicable to all experiments reported.
To explore factors that may affect the rate of parasite adaptation to host genotype, we describe a model that combines interacting descriptions of host genetics, parasite genetics and disease biology.
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In summary, our work has provided an extensive description of host defence responses to B. pseudomallei during an acute infection.
The description of host pathogen interactions at a molecular level shows differences in the mechanisms of aspergillosis and mucormycosis, including host immune response and susceptibility to macrophage-induced hyphal damage [ 34].
An increased understanding of tolerance to pathogen infection could lead to more efficient treatments for infectious diseases and a better description of host-pathogen interactions.
Among these, models including an explicit genetic description of host-parasite interaction, such as gene-for-gene (GfG) and matching-allele (MA) models, are particularly widespread.
More detail descriptions of these host overload detection algorithms could be found in elsewhere [3].
Alignment tasks are not trivial [ 16, 17], nor are accurate descriptions of a host of statistical issues.
However, these are highly generalized models with non-disease-specific mathematical descriptions of within-host processes.
This approach is particularly useful in the description of within host TB dynamics, as TB infections are large enough that the population of single mutants is expected to be substantial and therefore a focus on the probability of single resistance is less relevant than in related work on the emergence of resistance in cancer [43].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com