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首页> 外文期刊>Genomics >Glioma stages prediction based on machine learning algorithm combined with protein-protein interaction networks
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Glioma stages prediction based on machine learning algorithm combined with protein-protein interaction networks

机译:基于机器学习算法的胶质瘤阶段预测与蛋白质 - 蛋白质相互作用网络相结合

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摘要

Background: Glioma is the most lethal nervous system cancer. Recent studies have made great efforts to study the occurrence and development of glioma, but the molecular mechanisms are still unclear. This study was designed to reveal the molecular mechanisms of glioma based on protein-protein interaction network combined with machine learning methods. Key differentially expressed genes (DEGs) were screened and selected by using the protein-protein interaction (PPI) networks.
机译:背景:胶质瘤是最致命的神经系统癌症。 最近的研究已经努力研究胶质瘤的发生和发展,但分子机制仍然不清楚。 本研究旨在揭示基于蛋白质 - 蛋白质相互作用网络与机器学习方法相结合的胶质瘤的分子机制。 通过使用蛋白质 - 蛋白质相互作用(PPI)网络筛选和选择键差异表达基因(DEGS)。

著录项

  • 来源
    《Genomics》 |2020年第1期|共11页
  • 作者单位

    Shanghai Univ Sch Life Sci Shanghai 200444 Peoples R China;

    Sun Yat Sen Univ Dept Neurosurg Affiliated Hosp 3 Guangzhou Peoples R China;

    Shanghai Univ Sch Life Sci Shanghai 200444 Peoples R China;

    Shanghai Univ Sch Life Sci Shanghai 200444 Peoples R China;

    Shanghai Univ Sch Life Sci Shanghai 200444 Peoples R China;

    Shanghai Jiao Tong Univ Renji Hosp Med Sch New Pudong Dist 160 Pujian Rd Shanghai 200127;

    Shanghai Jiao Tong Univ Shanghai Gen Hosp Dept Radiol Sch Med Shanghai 200080 Peoples R China;

    Univ Elect Sci &

    Technol China Ctr Informat Biol Chengdu 610054 Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 医学遗传学;
  • 关键词

    DEGs; Machine learning; PPI networks; GO; KEGG; SVM; ANN; Random forest; Couple naive Bayes;

    机译:Degs;机器学习;PPI网络;GO;KEGG;SVM;ANN;随机森林;夫妇天真贝叶斯;

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