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Based on our benchmarks (Table 1), we estimate this analysis would have completed in ~9 days on a single CPU using the same algorithm.

Note however that as already stated, these packages do not focus on integer stoichiometric matrices and thus have a much broader scope that might explain their poor performance on our benchmarks.

DSGA, like ISOpure, models h n as a linear combination of a set of provided normal profiles but, unlike ISOpure, does not regularize its estimate of c n. Thus, we suspect that its performance on our benchmarks would be similar to that of ISOpure-evenprior.

We observed speed-ups up to factor 10 on various benchmark data when using this option while the alignment quality was still reasonably high, in the sense that the average sum-of-pair score and average column score on our benchmarks deteroriated around 5%10%10% only.

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We now give guidelines for the computation of PH based on our benchmarking.

Based on our benchmarking, we indicate which algorithms and implementations are best suited to different types of data sets.

Based on our benchmarking of the HMMerThread software discussed below, we found that this combined probability is a robust scoring mechanism for remotely conserved HMMerThread domains.

Based on our benchmark, it is at least 10× faster than any alternative methods.

We found that for DELTA-BLAST this threshold yielded the best homology detection performance on our benchmark set.

Based on our benchmark analysis, the Oases 67-mer-assembly (dnOST) was selected as the representative for the seed oat transcriptome.

Based on our benchmark analysis, TBEST is a tool of choice for detection of significantly distinct branches in hierarchical trees grown from biological data.

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