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Hierarchical tree of the scaffolds in the DUD datasets and reference ligands for a COX-2, b EGFR, c ER (antagonist), d SRC, e thrombin and f P38.
To evaluate MindTheGap, we generated artificial read datasets and reference genomes based on real genomes.
The detailed information for real-life short-read datasets and reference genomes was listed in Table 2.
Experiments that use data from Jonikas et al. closely follow the setup by Battle et al. and use the same datasets and reference pathways.
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Overview datasets and references included in the meta-analysis.
Similarly, a (non-exhaustive) trend is found between the dataset and reference conformers for triple bonds (8% versus 37%), lack of aromatic atoms (6% versus 21%), and presence of a ring system with more than six atoms (3% versus 28%).
We adopt a pragmatic approach by restricting ourselves to the input dataset and reference classification.
GeneStitch uses similarity between the genes included in a metagenomic dataset and reference genes available in a novel way and uses the matches between the de Bruijn graph assembly and the reference genes to improve the gene assembly.
We store the mismatch tally in a dataset called Counts and further quantities in the datasets Coverages, Deletions and Reference.
We used two kinds of datasets, i.e. test and reference datasets.
They are not suitable for interspecies alignments from metagenomic datasets, where query and reference can be from different species.
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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