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The final TMHs are determined by the smoothed propensity plot.
Several decades ago, most predictors were based on identifying maximally valued regions of sequences; essentially looking for peaks, or troughs, in some form of a propensity plot.
This method is able to capture much of the overall structure of a propensity plot in a single but discriminatory and self-consistent value.
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The amino acid propensity plots for all of the organisms are shown in figure 1.
The value of individual propensity plots is limited.
Our protocol enables us to abstract key features from propensity plots while remaining free of any text-based alignment scheme.
From comparison of aggregation propensity plots, appearance of new peaks or increase in previous peaks could be observed, showing the proposed increase in aggregation propensity of corresponding mutant.
The protocol described here takes propensity plots produced from the 544 scales in AAindex (Kawashima et al., 2008), averages them, and generates a single value characteristic of a whole sequence.
Bendability/curvature propensity plots were constructed with the help of the B end.it server (http://hydra.icgeb.trieste.it/dna/bend_it.html) using defaults parameters with the exception of a 20-nucleotide window size.
The curvature-propensity plot of the region containing cps3p showed two prominent peaks around positions −61 and −18.
The curvature-propensity plot, constructed using DNase I-based trinucleotide parameters, shows four peaks around positions −125, −98, −43 and −17 of magnitudes ≥ 9.0 (data not shown).
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