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It's going to take work, and some sacrifice and business model evolution, for an open standard to emerge.
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We used the GTR+Γ model of evolution for each partition in the nucleotide data set and the binary model of evolution (BINGAMMA) for the RY data set.
As model of evolution for the ML reconstructions we employed the Markov k-state 1 (Mk1) parameter model, with equal probability for any particular character change.
We used Modeltest version 3.06 [59] to select the Akaike Information Criterion best-fit model of evolution for each dataset separately.
For the combined dataset one model of evolution for the concatenation of the three genes was used for the ML analysis.
Modeltest was used to identify the most appropriate model of evolution for both the entire dataset and for each gene individually.
The discovery of HEV variants in rabbits [17] and rats [35] indicates, however, a more complex model of evolution for HEV.
We used jModeltest to estimate the best-fit model of evolution for the ITS data.
The software requires setting multiple parameters that define the assumed model of evolution for these genomes.
Overall, our results clearly support the BD model of evolution for these two gene families.
The model of evolution for the ML analysis was determined using ModelTest 3.7 in Paup.
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