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Bootstrap scores were generated from 1000 replicates.
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A total score was generated.
The bootstrap scores provided by the five competing bootstrapping strategies (i.e., traditional bootstrap scores, secondary bootstrap scores, LS-based bootstrap scores, normalized secondary bootstrap scores and normalized LS-based bootstrap scores) were calculated for the original and noisy data and depicted in Figure 5 (for the Primate data) and Figure 6 and Table 1 (for the PheRS data).
The results presented in Figures 5 and 6, and in Table 1 demonstrate that the normalized secondary bootstrap scores were usually higher than the bootstrap scores yielded by the four other bootstrapping strategies, including the traditional bootstrapping method.
One hundred bootstrap samples were generated using the SEQBOOT program [51].
In our experiments, 100 bootstrap datasets were generated and ARACNe was used to generate a set of bootstrap networks.
Two hundred replicate bootstrap datasets were generated and used for evaluation of parameter estimate precision.
Bootstrap datasets were generated using the SEQBOOT program from the PHYLIP package ver. 3.66 [104].
Five hundred bootstrap replicates were generated.
Bootstrap values were generated from 10,000 replicates.
First 100 bootstrap samples were generated.
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