Group-Biomarkers Identification in Ovarian Carcinoma

In this paper, we propose group-biomarkers as an alternative to the traditional single biomarkers used to date for the detection of ovarian cancer. Group-biomarkers are a set of genes that are used simultaneously for the diagnosis of early-stage and/or recurrent cancer. We describe a procedure for identifying such group-biomarkers from a data set of gene expression levels corresponding to normal and diseased ovarian tissue as well as tissue from other organs. The procedure starts with a list of potential single biomarkers. It then uses an order preserving biclustering step to identify other genes that are co-regulated with the candidate single biomarkers across the normal and diseased ovarian tissue and tissue from other organ. We present a statistical analysis that demonstrates that group-biomarkers have a much better detection performance than single biomarkers as exhibited by receiver operating characteristics curves.

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