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In particular, studies in monkeys and humans have discovered a neural mirror system that demonstrates an internal correlation between the representations of perceptual and motor functionalities.
In the 'model-free' approach [1], [2], the internal dynamics are quantified using a generalized order parameter, S2, which characterizes the amplitude of motion, and an internal correlation time τi.
It has recently been reported that only about 30% of the modules defined by GO terms and 57% of the modules defined by KEGG pathways display an internal correlation higher than the expected by chance [14].
Only around 30% of the modules defined by GO terms and 57% of the modules defined by KEGG pathways display an internal correlation higher than the expected by chance.
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The Lipari Szabo model-free formalism assumes that the internal motion of the N H vector is uncorrelated with the overall rotational motion of the protein and is characterized by two parameters: a generalized order parameter, S, which defines the amplitude of the motion, and an effective internal correlation time, τe, which measures the time scale.
For microarray data, there was a good internal correlation between quantile normalised and non-normalised data for a given miRNA, however, the internal correlation between the relative expression by RT PCR of miR-210, and miR-210, normalised to three control genes, was noisier.
In addition, normal tissue gave a tighter internal correlation, signified by higher correlations, than the tumor tissue subset, which as a group showed less internal correlation.
A high internal correlation is maintained within local regions of interest.
Correlation analysis was performed to examine a possible internal correlation between CXCL8, CXCL10, calgranulin B and CXCL2.
As expected, large functional modules (more than 100 transcripts) tend to have a strong internal correlation whereas small modules show more variability (see Figure 2).
We also provided separate estimates for each of the Gene Ontologies (30% in BP; 30% in MF; 46% in CC), showing that, in general, GO Biological Processes or Molecular Function have a weaker internal correlation than KEGG pathways or GO Cellular Component.
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