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We first present the algorithms used by TopHat and Cufflinks in ranking and reporting alignments and genes and then discuss our modifications to retain all fragment and partial fragment (unpaired reads) alignments.
Never glitch in ranked matches.
On the other hand, in many cases the alignment between the target and an appropriate template is good enough to build a good model, but the alignment method ranks this alignment lower than an alignment with a wrong template.
In addition, we have re-ranked the alignment results by assigning the larger weight of 3 to short-range electrostatic interactions (versus a weight of 1 to vdW interactions and hydrogen bonds).
To compare methods we needed to rank their alignments meaningfully.
Second, for each group in the ranked order, variationBlast assembles the global alignment between the entire group and the read sequence based on the local alignments and reports SVs accordingly.
The ranks of all 186 registration instances (from 4 different alignment families) based on volumetric MRI data are shown in the ranked parallel coordinates plot in the bottom panel.
In addition, the following uniqueness criterion was imposed to make sure that the two best alignments were unambiguous: for a query with three or more alignments, the alignments ranking third or worse were compared with the second best alignment (constituting the "short" partner of the reconstructed transcript).
Variable sites in the full plastome alignment were ranked using both tree-independent and tree-dependent methods – i.e. without and with the consideration of an underlying phylogenetic framework, respectively.
All alignments are ranked by their scores in descending order.
These measures can be used to rank different network alignments.
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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