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We calculated the degree of concordance between the expression patterns as the ratio of the number of genes simultaneously found expressed or not expressed in our samples by two or three of the microarray platforms to the total number of genes commonly represented by these platforms.
The other gene regulating the rate of spikelet formation – LOG, had a high expression in all the developmental stages analyzed and interestingly, we found a negative correlation between the expression patterns of both these genes (Figure2B).
The lack of correlation between the expression patterns in microarray and qRT-PCR in case of few genes in particular conditions, for example LOG in heat, LRK1 in drought etc., can be attributed to relatively lesser specificity of probes in microarray and array-platform bias (Lee et al. 2007).
No correlation between the expression patterns of these genes and the surface phenotypes of the tumors were detected in these analyses of limited numbers of samples.
A closer examination of the in situ hybridisation images revealed a difference between the expression patterns of neuroligin 3 and neurexin I in the mushroom bodies.
With respect to correlation or mutual information based approaches, these methods are potentially able to model higher-order dependencies between the expression patterns of genes.
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Further, we found an inverse-correlation between the expression pattern of LOG and CKX2, in most of the developmental stages analyzed here (Figure2B).
The Cox z-score measures the correlation between the expression pattern of a gene and survival of the patient.
There was no relation between the expression pattern of CK20 and disease recurrence (Table 1).
The lack of precise correlation between the expression pattern of the indicator and effector introduces significant uncertainty.
2) The relationship between the expression pattern of VEGF and the level of total circulating VEGF in the blood.
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between the expression change
between the subcell patterns
between the symptom patterns
between the activation patterns
between the stress patterns
between the signature patterns
between the glycosylation patterns
between the peptide patterns
between the regulation patterns
between the staining patterns
between the expression data
between the distribution patterns
between the expression profiles
between the activity patterns
between the score patterns
between the brain patterns
between the survival patterns
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