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These methods are termed reference-based alignment approaches, and de novo assembly approaches, respectively.
PISwap can begin with different types of network alignment approaches and then iteratively adjust the initial alignments by incorporating network topology information, trading it off for sequence information.
The resequenced reference reads were then mapped to the modified reference using the pipeline described above, as well as several variations, to investigate the performance of our pipeline vs. more standard alignment approaches and various degrees of filtering.
On the simulated local homologies, our method clearly outperforms other alignment approaches, and again the new algorithm introduced in this paper achieved significantly better results than older versions of DIALIGN.
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Structural superpositioning was accomplished using the secondary structure alignment approach and the program SSM Superimpose.
The results of our evaluation indicate that our clustered alignment approach and SCOW provide more accurate alignments than previous approaches.
Figure 2 demonstrates this for PRRN – a representative for an iterative alignment approach – and CLUSTALW as the standard progressive, non-iterative alignment program.
In contrast to previous hymenopteran phylogenetic studies, the internal relationships of the Evaniomorpha were highly supported and robust to the variation of alignment approach and phylogenetic inference approach.
In contrast, in this study the Aculeata + (Trigonalyoidea + Megalyroidea) clade was insensitive to variations in alignment approach and phylogenetic inference approach.
This method offers far greater coverage than any network alignment approach and fewer restrictions on module topology make it more suitable for error-prone data.
For the resulting spliced alignments, we applied the same clustering and filtering steps as for the targeted alignment approach, and found over two-thirds (231) of the 339 TIC events that were found by targeted alignment.
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