A method for the detection of meaningful and reproducible group signatures from gene expression profiles |
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Authors: | Licamele Louis Getoor Lise |
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Affiliation: | Computer Science Department, University of Maryland, AV Williams Bldg, Rm 3228, College Park, Maryland 20742, USA. licamele@cs.umd.edu |
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Abstract: | Gene expression microarrays are commonly used to detect the biological signature of a disease or to gain a better understanding of the underlying mechanism of how a group of drugs treat a specific disease. The outcome of such experiments, e.g. the signature, is a list of differentially expressed genes. Reproducibility across independent experiments remains a challenge. We are interested in creating a method that can detect the shared signature of a group of expression profiles, e.g. a group of samples from individuals with the same disease or a group of drugs that treat the same therapeutic indication. We have developed a novel Weighted Influence-Rank of Ranks (WIMRR) method, and we demonstrate its ability to produce both meaningful and reproducible group signatures. |
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