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These and other alternative formulations of the underlying optimization problem can be easily accommodated in the framework presented here.
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In conjunction with the existing theory, the framework presented here provides a more complete picture of a capsid's structure and therefore can help contribute to the development of more effective antiviral strategies.
It has been also illustrated that the framework presented here, in addition to the older and newer predictions (some of which have been already tested and/or materialized), could lead to very far-reaching implications and applications in many branches of science and technology, including nanomedicine and molecular biology.
We encourage others to apply the framework presented here in other settings to further refine our understanding of what medical students do and how it is perceived.
The framework presented here may prove useful in protein engineering to tune metal selectivity.
The framework presented here draws on experience in other natural resource management contexts and on research on governance and institutional design to provide lessons learned and illustrative examples.
The framework presented here can assist researchers in identifying and distinguishing different areas of research at the important intersection of translational medicine and health services research.
In future work, it would be interesting to extend the framework presented here to model tumour normal admixture, aneuploidy, CNV and nucleotide identity.
The framework presented here addresses this issue.
The framework presented here is easily incorporated into such estimation.
The framework presented here aims to bring us closer towards predictive computational models of oncolytic virus replication in vitro.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com