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We believe our method generates better alignments of interacting residues due to its use of a contact map representation of protein interfaces instead of the all-atom-based representation used by MAPPIS.
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For LR dataset, wavelet method generated better result than LPC-to-CC.
Nevertheless, visual inspection reveals that for some of these pairs one of the methods generates better superposition of the interacting helices.
Table 6 shows that all methods generate better mean performances than the classical CSP algorithm with all 22 monopolar channels (mean classification accuracy, Acc ¯ = 77.26 % ), indicating the interest of time-frequency selection and electrode reduction.
Further, the number of targets for which our method generates models better than HHpred by at least 0.10 is 197, whereas HHpred is better than our method by this margin for only 49 targets.
Experimental results confirm that our method generates significantly better alignments and threading results than the best profile-based methods on several large benchmarks.
As shown in Figure 3, our method generates models better than HHpred by at least 0.05 for 342 targets, whereas HHpred is better than our method by this margin for only 93 targets.
Simulations are conducted to validate the theoretical analysis and demonstrate that the proposed method generates considerably better convergence rates and tracking properties than existing methods, particularly in low signal-to-noise ratio environments.
Therefore, we can say that, compared to other methods, the SS algorithm (i) generates better estimations with less number of samples; (ii) provides more accurate results; and (iii) is less sensitive to parameter tuning.
Several cement manufacturing process examples demonstrate that this method can generate better effect comparing to autonomous approach.
The proposed joint correction method can generate better images after only several iterations (although we pre-set the iteration number as 10, the joint correction needs only about three iterations to reach the convergence) with the help of high-precision initialization estimation.
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