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Simulated data were used to evaluate the performance of alignment in various conditions.
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.
On the other hand, the performance of alignment approaches depends on whether the lag is close to an integer number of the time steps of the experiment, and they need to be adjusted for each pair as the lags of different gene pairs vary greatly.
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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.
Minimum entropy or maximum contrast of the synthetic profile, such as the average range profile (ARP) of the aligned profiles, is used as the criterion to evaluate the performance of range alignment.
Since the true alignment of the real data is not unknown, it is difficult to precisely and directly assess the performance of network alignment methods.
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