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Good normalization procedures for miRNA expression are still lacking.
Further indications for good normalization are the distributions of between (MSQbetween) and within (MSQwithin) group variances and their relation to each other.
For a good normalization scheme, the estimates of the location and scale parameters of the matching score distribution must be robust and efficient.
A good normalization method should result in similar expression values for replicates and thus in small MSQwithin values hardly crossing this artificial MSQbetween.
However, good normalization protocols still have to be implemented to facilitate data exchange and comparison.
Therefore, cdc2 expression levels provided a good normalization baseline.
Therefore, specific markers and good normalization procedures are needed.
Good practice in data normalization for gene expression analysis therefore relies on the identification, experimental validation and use of several reference genes.
On the contrary, good results are obtained from MOEA/D without normalization for the deceptive rescaled DTLZ1-4 test problems.
Good results were not obtained from MOEA/D without normalization for the WFG4-9, rescaled DTLZ1-4, and minus WFG4-9 test problems.
Although the resulting alignment parameters already allow for a good registration to the template, we further improved normalization for the MTL regions by adding landmarks to the template.
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