Consensus miRNA expression profiles derived from interplatform normalization of microarray data

cDNA Microarray Data Normalization

Impact of normalization on miRNA microarray expression profiling.

Profiling miRNA levels in cells with miRNA microarrays is becoming a widely used technique. Although normalization methods for mRNA gene expression arrays are well established, miRNA array normalization has so far not been investigated in detail. In this study we investigate the impact of normalization on data generated with the Agilent miRNA array platform. We have developed a method to select...

Enhanced quantile normalization of microarray data to reduce loss of information in gene expression profiles.

In microarray experiments, removal of systematic variations resulting from array preparation or sample hybridization conditions is crucial to ensure sensible results from the ensuing data analysis. For example, quantile normalization is routinely used in the treatment of both oligonucleotide and cDNA microarray data, even though there might be some loss of information in the normalization proce...

Normalization of Microarray Data

DNA microarrays are a powerful technology for analysis of gene expression levels within cells. Both the cDNA and oligonucleotide technologies for microarrays are fairly young and are prone to a broad collection of errors and inaccuracies [KYML02]. In this paper we briefly discuss some sources of error and detail a variety of methods for normalizing the data with respect to some of these error s...

Data Mining For Gene Expression Profiles From Dna Microarray

Microarray technology has supplied a large volume of data, which changes many problems in biology into the problems of computing. As a result techniques for extracting useful information from the data are developed. In particular, microarray technology has been applied to prediction and diagnosis of cancer, so that it expectedly helps us to exactly predict and diagnose cancer. To precisely clas...