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During the simulation, a classifier model is first trained on very few annotations and we measure the number and quality of correctly predicted annotations in the next chunk of the data, which subsequently is added to the training, simulating the annotation process.
If no or only very few annotations are available for the organism in question, intervals can still be clustered in an unsupervised manner.
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We found very few annotation errors in UniProt and those that we found were mostly small corrections that we made to the generic description of some proteins.
Very few TE annotations encompass entire contigs (Additional file 1: Figure S6), with only 332 contigs in A. tequilana and 171 in A. deserti entirely covered by a TE annotation (±10 nt from each end).
Supporting the quality of the studies databases, we found in the thorough analysis of the C. elegans Wormbase dataset that the vast majority of alternatively spliced isoforms included are well supported by experimental evidence, and only very few cases represent annotation mistakes.
We found the major centers responsible for genome annotation generally had very few missed genes, and their annotations missed fewer genes on average than annotations from smaller centers.
Therefore, there should be very few revisions in the annotations due to changed tree topology.
In comparison to A: "Pezizomycotina abundant" clusters, far fewer member ORFs have any InterPro entries and very few InterPro or Funcat annotations show enrichment (Tables 3).
Without annotation very few data points of any category are in the comfort zone (Supplementary Fig. S7).
Using a generic sequence tagger, we showed that annotating very few sentences already produces enough correct predictions to be useful, suggesting that interactive annotation is a worthwhile enterprise from the beginning of an annotation project.
However, the ability to predict polysaccharide substrates and catalytic potentials of these enzymes was impeded by the lack of specific annotations in the databases because very few of the highest scoring BLASTP alignments have corresponding KEGG E.C. annotations.
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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