| 基于WGCNA和SVM-RFE算法挖掘肺腺癌诊断和预后基因标志物 |
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| 引用本文： | 王美,王可心,谭建军,王京京.基于WGCNA和SVM-RFE算法挖掘肺腺癌诊断和预后基因标志物[J].生物化学与生物物理进展,2022,49(2):381-394. |
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| 作者姓名： | 王美 王可心 谭建军 王京京 |
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| 作者单位： | 北京工业大学环境与生命学部生物医学工程系，智能化生理测量与临床转化北京市国际科研合作基地，北京 100124,北京工业大学环境与生命学部生物医学工程系，智能化生理测量与临床转化北京市国际科研合作基地，北京 100124,北京工业大学环境与生命学部生物医学工程系，智能化生理测量与临床转化北京市国际科研合作基地，北京 100124,北京工业大学环境与生命学部生物医学工程系，智能化生理测量与临床转化北京市国际科研合作基地，北京 100124 |
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| 基金项目： | 北京市自然科学基金（2202002）和国家自然科学基金（21173014）资助项目。 |
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| 摘 要： | 目的 肺癌是世界上最常见的癌症之一,在众多肺癌患者中,肺腺癌(lung adenocarcinoma,LUAD)的死亡率最高.基因表达谱的变化与肿瘤的发生和发展过程有关,通过识别与LUAD患者相关的诊断和预后基因标志物,可以为肺腺癌的预防和治疗提供理论依据.方法 本研究以肿瘤基因组图谱(The Cancer Gene ...
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| 关 键 词： | 肺腺癌 基因标志物 加权基因共表达网络分析 递归特征消除算法 |
| 收稿时间： | 2021/1/13 0:00:00 |
| 修稿时间： | 2021/5/11 0:00:00 |
Identification of Gene Signatures Associated With Lung Adenocarcinoma Diagnosis and Prognosis Based on WGCNA and SVM-RFE Algorithm |
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| WANG Mei,WANG Ke-Xin,TAN Jian-Jun and WANG Jing-Jing.Identification of Gene Signatures Associated With Lung Adenocarcinoma Diagnosis and Prognosis Based on WGCNA and SVM-RFE Algorithm[J].Progress In Biochemistry and Biophysics,2022,49(2):381-394. |
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| Authors: | WANG Mei WANG Ke-Xin TAN Jian-Jun and WANG Jing-Jing |
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| Affiliation: | Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China,Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China,Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China,Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China |
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| Abstract: | |
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| Keywords: | lung adenocarcinoma gene signature WGCNA SVM-RFE |
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