Improving the prediction of chemotherapeutic sensitivity of tumors in breast cancer via optimizing the selection of candidate genes
作者: Lina JiangLiqiu HuangQifan KuangJuan ZhangMenglong LiZhining WenLi He
作者单位: 1College of Chemistry, Sichuan University, Chengdu 610064, PR China
2Biogas Institute of Ministry of Agriculture, Chengdu 610041, PR China
刊名: Computational Biology and Chemistry, 2014, Vol.49 , pp.71-78
来源数据库: Elsevier Journal
DOI: 10.1016/j.compbiolchem.2013.12.002
关键词: Cancer outcome predictionGene expression profilingGene prioritizationSupport vector machineBreast cancer
原始语种摘要: Abstract(#br)Estrogen receptor status and the pathologic response to preoperative chemotherapy are two important indicators of chemotherapeutic sensitivity of tumors in breast cancer, which are used to guide the selection of specific regimens for patients. Microarray-based gene expression profiling, which is successfully applied to the discovery of tumor biomarkers and the prediction of drug response, was suggested to predict the cancer outcomes using the gene signatures differentially expressed between two clinical states. However, many false positive genes unrelated to the phenotypic differences will be involved in the lists of differentially expressed genes (DEGs) when only using the statistical methods for gene selection, e.g. Student's t test, and subsequently affect the performance...
全文获取路径: Elsevier  (合作)
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影响因子:1.793 (2012)

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