Although the classification method is highly automated, attention to three parameters should be highlighted: minimum read label score, minimum difference between the best selected read label score and the competing alternatives and maximum number of taxonomic labels retrieved per k-mer.
When calculating prediction performance, we labeled the maximum score inside each ChIP-seq peak region with a positive label and labeled the maximum scores for the negative regions upstream/downstream/between the peak regions with negative labels (Figure 1).
Scores for alertness (maximum score = 400), hedonic tone (maximum score = 300), and anxiety (maximum score = 150) were derived from these scales.
The maximum Z-score of all labeling patterns was found for each reaction, giving a metric for the maximum potential for reaction flux determination using C-labeled glucose.
Minimum and maximum ROC scores are shown.
Maximum hub scores vary widely across diseases.
A higher score (maximum score = 25) indicates greater tissue responsiveness.
Once these models are learned in the training process, the candidate windows are placed into these classifiers, and the label from the classifier, which results in the maximum classification score is returned.
The five domains assessed include motor function (upper limb maximum score = 66; lower limb maximum score = 34), sensory function (maximum score = 24), balance (maximum score = 14), joint range of motion (maximum score = 44), and joint pain (maximum score = 44).
align= center"Minimum score: 0; Maximum score: 30.
