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In conclusion, the strength of the novel approach proposed in this work is that this method computes a prediction score, which is highly correlated with the true PFM similarity of two TFs, by integrating various weakly correlated sequence similarity measures.
A second advantage of the prediction framework presented in this work compared to nearest neighbor methods or similar approaches is the accurat similarity measure predicted by our approach, i.e., our method computes a prediction score which is highly correlated with the true PFM similarity of two TFs, by integrating various weakly correlated sequence similarity measures (see Figure 4).
These methods generate a correlated sequence of random samples that convey information about the desired probability distribution.
Thus, the correlated sequence change observed in the kinase and C-terminal tail suggests possible co-evolution of these two regions during mammalian ErbB kinase evolution.
CNFpred takes advantage of as many correlated sequence and structure features as possible to improve alignment accuracy.
However, some lower eukaryotes and parasitic worms diverge from the canonical ErbB features, and display correlated sequence changes in the JM, kinase, and C-terminal tail regions (Figure 1).
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It is interesting to note that for some fungi chromosomes (Figure 5), correlation sites are located far from subtelomeric areas and such correlated sequences may be extended along the entire chromosome length, though it is difficult to define the exact position of subtelomeric borders.
Phase coherence can be interpreted as phase shifts and amplitude changes over frequency between two correlated sequences, while phase synchrony indicates whether the phase shift is close to a constant over the specified time interval.
We can see that correlated sequences in a GSS-transformed trajectory are more often located equidistantly from the transition point.
In our analysis, we used an efficient entropy estimator derived from the Lempel-Ziv compression algorithm that converges to the entropy [19], [23], [24], and shows a robust performance when applied to correlated sequences [25] (see Materials and Methods).
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