Normalization strategies for cDNA microarrays.

By J. Schuchhardt, Dieter Beule, A. Malik, Eryc Wolski, H. Eickhoff, H. Lehrach, H. Herzel. Nucleic Acids Research, 2000

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Three-parameter lognormal distribution ubiquitously found in cDNA microarray data and its application to parametric data treatment (2004, neutral): “Parameters µ and σ were found for each data grid, a group of data for DNA spots that were printed by an identical pin in order to avoid divergences caused by pin-based differences [ 27 ].”
Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper – Excel-based tool using pair-wise correlations (2004, methodology): “This affects more advanced methods of gene expression study such as real-time PCR (Pfaffl 2001) or microarrays (Schuchhardt et al. 2000), as well as the traditional blotting methods.”
Cluster analysis for gene expression data: a survey (2004, background): “Those questions are beyond the scope of this survey; an examination of the problem of missing value estimation appears in [69], and the problem of data normalization is addressed in [32, 55].”