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If any one of the predictions made using the algorithm matched the 5′ gene miRNA, then a score (S) of 1 was assigned to the prediction, so the maximum score was 3. To improve the reliability of the prediction, the predicted miRNAs were predicated against the miRCancer database (30) to determine whether those miRNAs had been recorded.
The distance of the actual prediction to the decision boundary (0) reflects the reliability of the prediction and the severity of the predicted effect (large distance = high reliability and severity [ 17]).
A primer pair annealing to the beginning and the end of the predicted coding sequence was used to check the reliability of the prediction.
The algorithm provides a combined score indicating the reliability of the prediction; the more positive the score the more reliable the prediction.
Here, we present a database of the human α-helical transmembrane proteome, including the predicted and/or experimentally established topology of each transmembrane protein, together with the reliability of the prediction.
The reliability of the prediction results was successfully verified by the test results.
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Previous studies showed that local calibration of dynamic modulus (E∗) and creep compliance predictive model improved the reliability of the predictions.
To quantify the reliability of the predictions and assess which parameters are important to achieve a reliable prediction, we implemented a RF approach (Fig. 1c).
The reliability of the predictions is related to the similarity scores.
An uncertainty analysis is implemented to evaluate the reliability of the predictions.
The test for domain of applicability was also carried out for checking reliability of the predictions.
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