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In order to obtain better insight on specific ortholog prediction by GreenPhyl, we classified these predictions in two classes: (i) If one method predicts an n1/n2 orthologous relationship and the other method predicts an n3/n4 relationship, then "extended orthologs" are n1/n2 relationships not included in n3/n4 ones (see Figure 4).
If a method predicts an unknown but real protein complex (which is not similar with any of the known complexes), all of these evaluation metrics will regard it as a false positive.
The first method predicts an optimal polymer length of L eq ∗ = 574 while the latter suggests L eq ∗ ≈ 550 − 575, indistinguishable from the optimal length found in the finite-time dynamical assembly simulations.
(ii) If one method predicts an n1/n2 orthologous relationship never predicted by the other method, then the new orthologs are considered as "in-specific orthologs" We evaluated the number of 'extended' and 'in-specific' orthologs for Inparanoid and GreenPhyl using the list of 56 TF families previously used (additional file 5).
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The context-adaptive interpolation (CAI) method predicts a center pixel from its four-neighbor pixels.
The conventional LTP method predicts a speech segment by utilizing a previous speech segment at one pitch period before [10 12].
The Taguchi method predicts a parameter setting that will result in the best performance based on the initial definition.
The proposed method predicts a higher breakdown pressure than the conventional one, which may better estimate the breakdown pressure.
Bondi's group contribution method predicts a lower fractional free volume (FFV) with increasing ionic block length.
It is shown that the RC method predicts a faster trend for the moisture transfer into the enclosure compared to the CFD.
The statistical design method predicts a maximum conversion to 99% for the optimum values of three process variables, reaction temperature 10 °C, nanocatalyst amount 6 g/l and reaction time 60 min.
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