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Our approach is designed to support systematic benchmarking of API methods written in the Java language.
The results of our review of benchmarking studies published between 2000 and 2017 provide a foundation for discussing potential paths forward in systematic benchmarking of omic computational tools.
The life science and biomedical research community is interested in systematic benchmarking of previously published methods, but running algorithms developed by other researchers is a challenging task for tools with many dependencies and limited documentation.
Table 1 shows a systematic benchmarking of most methods discussed here on the RV11 dataset.
The systematic benchmarking of COSMOS' GenomeKey allowed us to build and investigate a "complexity roadmap" of NGS variant calling workflows in the cloud.
Indeed, since a single amino acid substitution can determine resistance to a given drug, systematic benchmarking of starting genetic material and resulting data was highly sought after.
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This is emphasised in the systematic benchmark of MACCS-like 166 key generation (Table 5).
These challenges should not discourage the research community from performing systematic benchmarking studies of computational biology methods.
In the near future, a broad and systematic benchmarking study of multiple species phylogenetic footprinting procedures for motif enrichment and de novo motif discovery would advance the field.
It was not our intention here to achieve a systematic benchmark comparison of different optimisation strategies.
Widespread community adoption of a systematic benchmarking practice remains a challenge.
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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