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HYBRID ENSEMBLE GENE SELECTION ALGORITHM FOR IDENTIFYING BIOMARKERS FROM BREAST CANCER GENE EXPRESSION PROFILES´╗┐

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Author(s): DR. S. ARUNA | DR. L.V. NANDAKISHORE

Journal: International Journal of Computer Science and Mobile Computing
ISSN 2320-088X

Volume: 2;
Issue: 9;
Start page: 153;
Date: 2013;
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Keywords: Ada boost | Correlated feature selection | Filters | Gene expression profiles | Sequential floating search algorithms | Support vector machines | Wrappers

ABSTRACT
Breast cancer is one of the major health hazard in the world. DNA gene expression profiles plays an importantrole in identifying the biomarkers for cancer which not only help in accurate diagnosis of the disease, also indiscovering drugs, minimizing the toxicity thus help in the effective management of the disease. In this paper wepropose an algorithm for determining the biomarkers. Our hybrid ensemble gene selection algorithm wasexperimented over breast cancer gene expression data of 24481 genes. The algorithm selected a marker genesubset of eight genes with an accuracy and BER of 96.9% and 0.033 respectively.
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