The symbol represents experimental measurement which is in good agreement with the model prediction represented by solid line.
The fitness of an ensemble was represented by the resulting performance of that ensemble on the BVM resistance prediction (represented by the AUC).
Thus, BF is a summary of the evidence provided by the data in favor of one prediction, represented by a statistical model, as opposed to another.
Among the 25 COG categories, "general function prediction" represented the largest group, followed by "translation, ribosomal structure and biogenesis", "replication, recombination and repair" and "transcription" (Additional file 2: Figure S2).
A total of 33,205 annotated sequences were clustered into 25 COG categories in which the cluster of "General function prediction" represented the largest group (5,021, 15.1%) followed by "Transcription" (3,230, 9.7%), "Replication, recombination and repair" (2,660, 8.0%), and "Posttranslational modification, protein turnover, and chaperones" (2,539, 7.7%).
A NOR without prediction, represented here by I2, would switch off the expression almost immediately, but Out is still expressed for some time (that is, there is a delay in pulling the output signal low, which starts to occur just at the end of the 1-0 inperiodriod, and continues through the subsequent 0-1 inperiodriod).
Prediction represents Model execution results for a set of Compounds during the training or validation/testing exercises.
The results suggest that for symmetric, non-probabilistic treatments, subjects behave close to the inefficient equilibrium prediction, representing undervaccination.
Our structure prediction protocol RAGTOP (RNA-As-Graphs Topology Prediction) represents RNA structures as tree graphs and samples graph topologies to produce candidate graphs.
In this way, citation prediction represents one step on the path to creating algorithmic or robot "scientists" (11) that are more creative, risky, persistent, and wide-reading than ourselves (12).
This study is based on a multi-label classification (MLC) technique for modeling correlations between several HTS assays, meaning that a single prediction represents a subset of assigned correlated labels instead of one label.
