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The alignments of U1, U2, U4, U5, and U6 were downloaded from Rfam [44] and covariance models for these alignments were built using the INFERNAL-cmbuild programme.
Although we considered best-case similarity between any two conceptually translated long open reading frames (see Materials and Methods), we found that codon substitution patterns do not support the hypothesis of protein-coding ability, as the Ka/Ks ratios for these alignments are mostly in the range 0.5 1.5.
Default input parameters were used for these alignments.
Initial models for these alignments were made using RNAalifold [ 117].
Consensus secondary structures for these alignments were inferred using the program RNAalifold [ 48].
SBM sets were computed for these alignments as described in the Methods section.
Similar(42)
KA was calculated for each of these alignments as described above.
For each of these alignments, phylogenetic trees were inferred (PhyML, WAG+I+Γ4 [ 43]) and patristic distances were computed for each of the different chaetognath sequences (Additional file 4).
For each of these alignments, we ran a number of current multiple-sequence RNA secondary structure prediction programs, including Murlet v0.1.1 (Kiryu et al., 2007), LocARNA v1.2.2a (Will et al., 2007), and RNA Sampler v1.3 (Xu et al., 2007).
When the same amount of missing data was distributed in a pattern typical of EST unigenes, phylogenies were much less accurate: mean stQD for trees computed from these alignments ranged from 0.17 for ML to 0.34 for MP.
This has major ramifications for both the designers of large-scale multiple sequence alignment algorithms, and for the users of these alignments.
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