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Ordinary instructions operate on single data points stored in registers (RF1 & RF2), and the result is automatically stored in another register.
Although most of the instructions are either control instructions or instructions that operate on single data (ADD, SUB,...), the processor operates most of the time on vector data.
We also benchmarked against two methods that operate on single data types (either interaction network or gene expression data).
It can be used to prioritize genes based on single data sources or a combination of different sources.
Evaluations on single data sets especially on real data are unsuitable to establish differences in the prediction accuracy of inference methods.
Direct concatenation generally produces worse clustering and classification results than those based on single data (Fig. 2b and c and Table 1).
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Models based on multiple omics layers outperformed the models that were based on one single data set.
For methods based on monitoring of single data streams only, an aberration triggers an alert.
However, the significance of this relationship relies on a single data point based on one group of baboons [5].
In this paper both methods are compared on a single data set on soil pH where marked changes in parent material are expected to result in non-stationary variability.
Our analysis suggests that no one network, based on a single data type, captures the full spectrum of interactions.
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