the dna microarray is an important technique that allows researchers to analyze many gene expression data in parallel. although the data can be more significant if they come out of separate experiments, one of the most challenging phases in the microarray context is the integration of separate expression level datasets that have gathered through different techniques. in this paper, we present a...

The DNA microarray is an important technique that allows researchers to analyze many gene expression data in parallel. Although the data can be more significant if they come out of separate experiments, one of the most challenging phases in the microarray context is the integration of separate expression level datasets that have gathered through different techniques. In this paper, we prese...

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The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature biomarkers. Microarray platform integration can be conceptually...

The upcoming availability of public microarray repositories and of large compendia of gene expression information opens up a new realm of possibilities for microarray data analysis. An essential challenge is the efficient integration of microarray data generated by different research groups on different array platforms. This review focuses on the problems associated with this integration, which...

Microarrays are one of the latest breakthroughs in experimental molecular biology. Thousands of different research groups generate tens of thousands of microarray gene expression profiles based on different tissues, species, and conditions. Combining such vast amount of microarray data sets is an important and yet challenging problem. In this paper, we introduce a “correlation signature” method...