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In the first approach the distance was based on the number of nucleotides that vary between the homologous anchors (Inter-Anchor Distance 1 - IAD 1) whereas Hamming distance based on binary events was used as the second distance measure ( Inter-Anchor Distance 2 - IAD 2).
Relative evolutionary distance was based on the accepted phylogenetic tree.
The ML distance was based on the best fit model and calculated using PAUP v4.0b10 [ 41].
This search distance was based on our finding that the majority (62 %) of linkages between two SNPs (linkage disquilibrium R > 0.8) was within 1 Kb (Additional file 3: Figure S3).
The standard Euclidean distance was used for Uppsala datasets, but for the van't Veer dataset, because of different scales and possible outliers, the distance was based on Spearman rank correlation.
This clustering distance was based on the 4.3 kb length of EAV-HP genome, indicating that any subsequent EAV-HP LTR alignments detected within 5 kb of one-another using BLAT on the chicken reference genome could reasonably be considered to be the result of a single integration.
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This distance is based on a geometrical interpretation of beamforming.
The 1-km distance is based on average walking distance to metro stations in Beijing.
Euclidean distance is based on L2 norm and does not work well with high-dimensional data.
Hellinger distance is based on L1 norm and it is proven that in high-dimensional data, L1 norm works better than L2 norm.
Figure 2 shows the PPFD evolution measured between two points, IS (0 mm distance) and BS (105 mm distance), while the value at 120 mm distance is based on calculation.
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