Multi-platform gene-expression mining and marker gene analysis
International Journal of Data Mining and Bioinformatics
An Innovative Approach to Enhance Collaboration in the Biomedical Field
International Journal of Systems Biology and Biomedical Technologies
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Integrative correlation: Properties and relation to canonical correlations
Journal of Multivariate Analysis
On a meaningful exploitation of machine and human reasoning to tackle data-intensive decision making
Intelligent Decision Technologies
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Motivation: Gene-expression microarrays are currently being applied in a variety of biomedical applications. This article considers the problem of how to merge datasets arising from different gene-expression studies of a common organism and phenotype. Of particular interest is how to merge data from different technological platforms. Results: The article makes two contributions to the problem. The first is a simple cross-study normalization method, which is based on linked gene/sample clustering of the given datasets. The second is the introduction and description of several general validation measures that can be used to assess and compare cross-study normalization methods. The proposed normalization method is applied to three existing breast cancer datasets, and is compared to several competing normalization methods using the proposed validation measures. Availability: The supplementary materials and XPN Matlab code are publicly available at website: https://genome.unc.edu/xpn Contact: shabalin@email.unc.edu Supplementary information: Supplementary data are available at Bioinformatics online.