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Obviously, clustering optimization can also be used to assess the relative performance of alignment and distance methods if applied to other organisms and sequence regions.
Simulated data were used to evaluate the performance of alignment in various conditions.
This allows, for example, to test the influence of sequence number on performance of alignment programs.
The performance of alignment programs is traditionally tested on sets of protein sequences, of which a reference alignment is known.
They propose also criteria to compare the performance of alignment tools and evaluated Bowtie, BWA, mr- and mrsFAST, Novoalign, SHRiMP, and SOAPv2, considering accuracy and runtime.
To optimize the performance of alignment using BWA, the use of a seed region (option -l), the prohibition of indels close to read ends (option -i), the maximum number of gap opens (option -o) and gap penalties (options -O and –E), and the overall number of differences tole-rated in the alignment (option -n) were examined.
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At the same time, the lower performance of alignment-free methods might result from a loss of information, when encoding a longer sequence by means of shorter oligonucleotides.
Because we are interested in the performance of pairwise alignment, we choose the k2 dataset with 8976 pairwise alignments.
The performance of four alignment programs is measured in terms of concordance between any pair of aligners because no known truth for real sequencing data is available.
The performance of different alignment algorithms are measured in terms of concordance between any pair of aligners (for real sequencing data without known truth) and the accuracy of simulated read alignment.
Instead, the performance of shorter alignment groups such as BLAST-based methods and SSEARCH with MIQS.SCOP40-v is exceeded in alignment precision comparison.
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