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For this analysis we used a dataset consisting mainly of experimentally identified protein-protein interactions, excluding homodimers and orthology-based predictions, and calculated the shortest path between any two nodes or proteins in the giant network component (i.e., the component containing the largest number of connected proteins) [41].

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We then applied the models thereby obtained to the test set for prediction and calculated the c-index from test set using the R package "survival".

So the feature also asks you to enter a margin of error (or 95 percent confidence interval) for your prediction, and calculates the probability that Mr. Romney will meet each threshold based upon it.

begin{aligned} {MSE}=displaystyle frac{SSE}{n} qquad {SDE} = displaystyle frac{displaystyle sumnolimits _{i=1}^{n}(Err_{i}-bar{E}rr_i)^{2}}{n} end{aligned} (9 Standard deviation of the error (SDE): For all the forecaster we compute the error for each field in the prediction, and calculate the standard deviation for each forecaster.

The variation of running time, mean square error (MSE), number of training and testing data, and other indices for measuring the accuracy in the prediction are defined and calculated in order to inspect advantages as well as the shortcomings of each algorithm.

In the simulated full cohort we derive a CHD risk prediction model, and calculate subsequent measures of predictive ability, thereby providing a "gold standard" to which results achieved with case-cohort samples can be compared.

Furthermore, to assess the capability of GX-FBA to accurately identify metabolically active reactions after a perturbation, we compared the results of our predictions with experimental measurements and calculated the average precision (0.88) and recall (0.99) values (see Figure 2a).

To do this we utilized the Transcription Factor Affinity Prediction (TRAP) tool [ 55] and calculated the binding prediction of 904 TFBSs (TRANSFAC vertebrate V$motifs [ 56]) within CpGi-related s-DMRs in human, as well as the orthologous chimpanzee and macaque sequences.

We evaluated the number of true/false positives predictions in the testing set and calculated Receiving Operator Characteristic (ROC) [18], which gives the quantitative measure of how good the discrimination is in identifying the protein localization.

The ensemble model exhibiting the highest predictive power (RMSEtest: 0.71; (R^{2}_{0 test}): 0.65), namely MS SVM Radial Ensemble, was used to make the predictions and to calculate the confidence intervals.

We assessed the external criterion validity by comparing the German Radboud Skills Questionnaire and the German Disabilities of the Arm, Shoulder and Hand Questionnaire and calculated the prediction intervals.

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