• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>RSC Advances >Gene selection and cancer classification using Monte Carlo and nonnegative matrix factorization
【24h】

Gene selection and cancer classification using Monte Carlo and nonnegative matrix factorization

机译：基因选择和癌症分类使用蒙特卡罗和非负矩阵分解

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Cancer classification is a key problem for identifying the genomic biomarkers and treating cancerous tumors in clinical research. The gene data in gene expression profiling are potential biomarkers and can be used to classify cancer samples. However, with the high dimensionality of the gene data, the cancer samples are difficult to classify. The identification of the significant genes is critical for the classification. To identify the significant genes, nonnegative matrix factorization (NMF) uses the sparse basis vectors of the gene data to represent gene information. However, the basis vectors with the imposed sparseness lose much of the useful information in the gene data. To more effectively represent the useful information, a method named Monte Carlo-nonnegative matrix factorization (MC-NMF) is proposed by using Monte Carlo technique in this study. The method is used to classify two cancer samples. The results show that the method can effectively estimate the significance of the genes and classify cancer samples with a high accuracy.
机译：癌症分类是鉴定基因组生物标志物和治疗临床研究中癌症肿瘤的关键问题。基因表达分析中的基因数据是潜在的生物标志物，可用于对癌症样品进行分类。然而，随着基因数据的高维度，癌症样品难以进行分类。鉴定显着基因对于分类至关重要。为了鉴定显着的基因，非负基质分子（NMF）使用基因数据的稀疏基载体来表示基因信息。然而，具有施加的稀疏性的基础载体在基因数据中失去了大部分有用的信息。为了更有效地表示有用的信息，通过在本研究中使用Monte Carlo技术提出了一种名为Monte Carlo-Nonnegative矩阵分子（MC-NMF）的方法。该方法用于分类两种癌症样本。结果表明，该方法可以有效地估计基因的重要性，并以高精度对癌症样品进行分类。

著录项

  • 来源
    《RSC Advances》 |2016年第46期|共5页
  • 作者

    Chen Jing; Ma Qin; Hu Xiaoyan; Zhang Miao; Qin Dongdong; Lu Xiaoquan;

  • 作者单位

    Northwest Normal Univ Coll Chem &

    Chem Engn Key Lab Bioelectrochem &

    Environm Anal Gansu Prov Lanzhou 730070 Peoples R China;

    Northwest Normal Univ Coll Chem &

    Chem Engn Key Lab Bioelectrochem &

    Environm Anal Gansu Prov Lanzhou 730070 Peoples R China;

    Northwest Normal Univ Coll Chem &

    Chem Engn Key Lab Bioelectrochem &

    Environm Anal Gansu Prov Lanzhou 730070 Peoples R China;

    Northwest Normal Univ Coll Chem &

    Chem Engn Key Lab Bioelectrochem &

    Environm Anal Gansu Prov Lanzhou 730070 Peoples R China;

    Northwest Normal Univ Coll Chem &

    Chem Engn Key Lab Bioelectrochem &

    Environm Anal Gansu Prov Lanzhou 730070 Peoples R China;

    Northwest Normal Univ Coll Chem &

    Chem Engn Key Lab Bioelectrochem &

    Environm Anal Gansu Prov Lanzhou 730070 Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 化学;
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号