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Therefore, we studied the relationship between the evolutionary information and experimentally measured stability changes.
For real-value prediction, EASE-AA achieved the correlation of predicted and experimentally measured stability changes of 0.51.
For real-value prediction, EASE-AA achieved a correlation between predicted and experimentally measured stability changes of 0.51.
APE1 148Glu tertiary structure revealed significant variations due to protein folding in the mutated region between predicted and measured stability changes.
Regarding the real-value prediction of stability changes, the correlation of the predicted and experimentally measured stability changes reached a correlation coefficient of 0.62 to 0.83 [ 9– 15, 15].
We demonstrated that the relationship between evolutionary predictive features derived from PSSM and experimentally measured stability changes from our data set agree with these general assumptions about sequence conservation.
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We find that the calculated stability changes are correlated with the experimentally measured in vivo folding efficiencies.
By outfitting expert slackline walkers at Santa Monica Beach with wireless devices that measure movement and stability, the researchers are testing whether stability changes along the length of the slackline as the model suggests.
This measure allows identifying the parts of the protein that, for geometrical reasons, when mutated, would result in relevant protein stability changes.
Stability change of a protein can be measured by computing the change in its Gibbs-free energy upon folding.
At the individual level, stability was measured using individual change scores, such that a score of zero signified identical responses in Rounds 2 and 3. We recruited 141 participants into Round 1 and retained 118 to the end of Round 3 (82% retention) [ 16].
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