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If all differentially regulated genes had been considered (large circles), there would have been many genes shared by these two studies and that is the most likely reason why the profiles from one study could be used to predict sample status from the other study.
We used partial least squares to predict sample age using training and testing sets.
When using gene expression data to predict sample properties, variables related to biomarkers are selected.
Classification techniques has been widely used in microarray analysis to predict sample phenotypes based on gene expression patterns.
For future work, we intend to integrate the function to predict sample size into our NLP software.
Using only a small number of markers, both AIMs and PCAIMs were able to predict sample origin accurately.
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Fault detection based on differential power is another proposed method that makes use of auto-regression technique to predict samples in the future [7].
Integrating data, in an automated manner, from multiple data resources including several pathway databases, drug target annotation resources and cancer genomics utilities we were able to predict sample-specific metabolic vulnerabilities, which result from a homozygous deletion event in the corresponding sample, and list drugs that can help exploit each particular vulnerability.
If positive and negative samples are imbalanced, classifiers apt to predict samples, as the majority class will achieve better accuracy.
(3) A random forests-based procedure is to identify gene sets that can accurately predict samples from different experimental conditions or are associated with the continuous phenotypes.
Two most important considerations in evaluation of survival prediction models are 1) predictability - ability to predict survival risks accurately and 2) reproducibility - ability to generalize to predict samples generated from different studies.
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