知驿📋 资源介绍
《学业成长_4905_医学方-科研系列课程》是一套完整的技能学习资源，内容涵盖《06-数据挖掘—miRNA调节网络的构建》、《08-医学R语言快速入门与数据清洗》、《01-GEO、TCGA、Oncomine数据挖掘教程》、《07.医学方医学数据挖掘精品课程-手把手教您如何数据挖掘》 等8个模块。全资源共 408 个文件、约26GB，以视频、文档、课件等形式打包呈现，内容组织清晰、可直接对照目录学习使用。文件构成：视频 161 个、文档 85 个、压缩包 91 个。面向零基础入门到进阶的系统学习者；可按目录结构直接转存取用。
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🗂️ 完整文件清单（408 个文件 / 28.2GB）
📁 01-GEO、TCGA、Oncomine数据挖掘教程 34 项
📁 数据挖掘代码 19 项
📁 代码 18 项
📁 资料（脚本及源码） 10 项
📁 perl 6 项
- 📄 probe2symbol.pl2KB
- 📄 survival_time.pl1KB
- 📄 putFilesToOneDir.pl368
- 📄 mRNA_merge.pl2KB
- 📄 gb2symbol.pl739
- 📄 ensemblToSymbol.pl652
- 📄 TCGA.txt7KB
- 📄 GEO.txt7KB
- 📄 GEO中非cel文件脚本.txt2KB
📁 perl 4 项
- 📄 ensemblToSymbol.pl652
- 📄 mRNA_merge.pl2KB
- 📄 putFilesToOneDir.pl368
- 📄 survival_time.pl1KB
- 📄 GEO.txt7KB
- 📄 TCGA.txt7KB
- 📄 课时1 数据挖掘概述.mp4188.5MB
- 📄 课时3 GEO数据下载和数据质量分析.avi124.1MB
- 📄 课时8 蛋白互作网络.avi215.5MB
- 📄 课时2 GEO在线工具的应用.avi453.4MB
- 📄 课时13 Oncomine之差异分析及共表达分析.avi242.0MB
- 📄 课时9 TCGA数据下载.avi202.8MB
- 📄 课时10 TCGA数据整理和基因注释.avi212.5MB
- 📄 课时12 Oncomine概述及Meta分析.avi165.3MB
- 📄 课时4 原始数据预处理.avi193.7MB
- 📄 课时11 寻找差异基因和制作5年生存率.avi340.8MB
- 📄 课时14 非cel格式GEO芯片数据分析.mp449.2MB
- 📄 课时7 KEGG分析.avi221.6MB
- 📄 课时5 寻找差异基因及制作热图和火山图.avi287.2MB
- 📄 课时6 富集分析.avi268.2MB
📁 02-MIMIC临床数据使用入门 3 项
- 📄 MIMIC临床数据库使用入门 - 课时4-5.mp4517.1MB
- 📄 SQL QUERY.docx20KB
- 📄 MIMIC临床数据库使用入门 - 课时1-3.mp4653.3MB
📁 03 R语言可视化及绘图 22 项
- 📄 9、9.ggplot2之美学函数.mp4129.8MB
- 📄 18、18.主题函数&一页多图&高质量图片导出.mp4268.0MB
- 📄 5、5.低级绘图函数(1).mp4148.8MB
- 📄 医学方R语言可视化配套代码.pdf609KB
- 📄 1、1.par函数.mp4372.9MB
- 📄 19、19.venn图和火山图.mp4165.3MB
- 📄 13、13.几何对象之线图.mp4209.9MB
- 📄 20、20.nomogram和heatmap.mp4202.7MB
- 📄 7、7.图形颜色选取.mp4125.5MB
- 📄 2、2.散点图&盒形图.mp4348.0MB
- 📄 16、16.图例与标题.mp4336.0MB
- 📄 4、4.饼图&克利夫兰点图&条件图.mp4135.6MB
- 📄 10、10.几何对象之点图.mp4200.3MB
- 📄 14、14.几何对象之标签绘制.mp4159.8MB
- 📄 6、6.低级绘图函数（2）.mp4207.6MB
- 📄 15、15.坐标轴自定义函数.mp4250.6MB
- 📄 21、21.生存曲线.mp4136.7MB
- 📄 8、8.ggplot2之qplot.mp4191.7MB
- 📄 3、3.条形图&直方图.mp4289.2MB
- 📄 12、12.几何对象之盒形图和直方图.mp4183.4MB
- 📄 11、11.几何对象之条图.mp4151.2MB
- 📄 17、17.坐标系转换函数与图片分面函数.mp4203.6MB
📁 04-R语言与高级医学统计学 33 项
- 📄 5.mp454.2MB
- 📄 1.mp443.2MB
- 📄 10.mp433.9MB
- 📄 29.mp434.6MB
- 📄 13.mp439.5MB
- 📄 22.mp439.2MB
- 📄 16.mp428.9MB
- 📄 19.mp424.2MB
- 📄 25.mp440.6MB
- 📄 20.mp434.7MB
- 📄 6.mp475.7MB
- 📄 21.mp461.8MB
- 📄 27.mp460.5MB
- 📄 24.mp435.9MB
- 📄 14.mp427.6MB
- 📄 3.mp426.2MB
- 📄 11.mp427.3MB
- 📄 31.mp454.1MB
- 📄 28.mp434.9MB
- 📄 15.mp441.6MB
- 📄 12.mp469.6MB
- 📄 9.mp444.8MB
- 📄 17.mp4101.6MB
- 📄 8.mp429.9MB
- 📄 32.mp434.7MB
- 📄 26.mp434.7MB
- 📄 4.mp445.8MB
- 📄 18.mp449.2MB
- 📄 30.mp452.5MB
- 📄 7.mp460.4MB
- 📄 33.mp455.8MB
- 📄 23.mp472.1MB
- 📄 2.mp464.5MB
📁 05-豪斯医生数据挖掘之WGCNA详解 12 项
- 📄 医学方豪斯医生WGCNA配套代码.pdf126KB
- 📄 课时08.与临床信息相结合.mp4357.6MB
- 📄 课时04.WGCNA理论和算法3.mp4156.6MB
- 📄 课时02.WGCNA理论和算法1.mp4198.7MB
- 📄 ClinicalTraits.txt7KB
- 📄 课时05.WGCNA理论和算法4.mp4141.8MB
- 📄 课时01.使用cytoscape寻找核心基因.MP4154.8MB
- 📄 课时07.寻找基因模块.mp4245.0MB
- 📄 课时06.输入文件准备.mp4349.1MB
- 📄 课时09.确定核心基因.mp4299.6MB
- 📄 课时03.WGCNA理论和算法2.mp4344.1MB
- 📄 epr.txt32.8MB
📁 06-数据挖掘—miRNA调节网络的构建 369 项
📁 01、TCGA概述 3 项
- 📄 02、TCGA概述.mp417.6MB
- 📄 03、TCGA概述.mp437.1MB
- 📄 01、TCGA概述.mp468.5MB
📁 02、构建调控关系理论 3 项
- 📄 01、构建调控关系理论.mp418.9MB
- 📄 03、构建调控关系理论.mp4141.7MB
- 📄 02、构建调控关系理论.mp466.5MB
📁 03、WGCNA理论 4 项
- 📄 03、WGCNA理论.mp421.0MB
- 📄 04、WGCNA理论.mp453.2MB
- 📄 01、WGCNA理论.mp424.3MB
- 📄 02、WGCNA理论.mp418.9MB
📁 04、数据下载 4 项
- 📄 01、数据下载.mp455.2MB
- 📄 03、数据下载.mp447.1MB
- 📄 02、数据下载.mp452.1MB
- 📄 04、数据下载.mp496.1MB
📁 05、提取蛋白编码基因 5 项
- 📄 01、提取蛋白编码基因.mp465.0MB
- 📄 02、提取蛋白编码基因.mp451.9MB
- 📄 04、提取蛋白编码基因.mp456.8MB
- 📄 03、提取蛋白编码基因.mp456.9MB
- 📄 05、提取蛋白编码基因.mp4105.1MB
📁 06、差异分析 3 项
- 📄 02、差异分析.mp441.6MB
- 📄 03、差异分析.mp498.3MB
- 📄 01、差异分析.mp452.2MB
📁 07、基于算法构建调控 4 项
- 📄 04、基于算法构建调控.mp464.9MB
- 📄 03、基于算法构建调控.mp454.6MB
- 📄 02、基于算法构建调控.mp458.4MB
- 📄 01、基于算法构建调控.mp464.7MB
📁 08、cytoscape构建网络 2 项
- 📄 02、cytoscape构建网络.mp4105.8MB
- 📄 01、cytoscape构建网络.mp460.0MB
📁 09、数据库预测 4 项
- 📄 01、数据库预测.mp447.5MB
- 📄 02、数据库预测.mp4272.3MB
- 📄 04、数据库预测.mp496.8MB
- 📄 03、数据库预测.mp444.6MB
📁 医学方miRNA调节网络的构建配套代码 327 项
📁 DEmiRNA 1 项
- 📄 diffmiRNAExp.txt98KB
📁 DEmRNA 1 项
- 📄 diffmRNAExp.txt5.1MB
📁 merge 7 项
- 📄 diffmRNAExp.txt5.1MB
- 📄 node.txt27KB
- 📄 diffmiRNAExp.txt98KB
- 📄 .Rhistory18KB
- 📄 rmRNA.txt3.6MB
- 📄 edge.txt573KB
- 📄 rmiRNA.txt97KB
📁 miRNA 96 项
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📁 74180be2-3650-48e9-ae51-e3600e897398 4 项
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- 📄 f82e6b9f-c1cb-4b10-9188-5f4c5e61f711.mirbase21.mirnas.quantification.txt.parcel171
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- 📄 metadata.cart.2018-01-17T14_59_36.956035.json389KB
- 📄 miRNAmatrix.txt220KB
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📁 mRNA 189 项
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📁 pro 11 项
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📁 star 14 项
📁 target 9 项
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📁 07.医学方医学数据挖掘精品课程-手把手教您如何数据挖掘 14 项
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- 📄 7.KEGG分析(修复).mp4392.2MB
- 📄 9.TCGA数据下载.mp4335.9MB
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- 📄 8.蛋白互作网络.mp4306.8MB
- 📄 13.Oncomine之差异分析及共表达分析.mp4401.4MB
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- 📄 课程脚本代码.zip10KB
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- 📄 4.原始数据预处理.mp4350.5MB
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📁 08-医学R语言快速入门与数据清洗 38 项
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- 📄 01.R语言、Rstudio简介.avi323.0MB
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- 📄 19.data.table包.avi142.5MB
- 📄 37.生存分析与COX回归.avi112.4MB
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- 📄 03.数值型&逻辑型向量.avi176.0MB
- 📄 04.逻辑表达式&字符串向量.avi104.4MB
- 📄 36.模型诊断与Logistic回归.avi118.2MB
- 📄 18.dplyr包.avi153.1MB
- 📄 10.条件与循环.avi132.6MB
- 📄 28.时间序列简介.avi103.4MB
- 📄 29.时间序列分析.avi143.0MB
- 📄 05.因子型变量.avi156.6MB
- 📄 15.apply函数家族.avi94.4MB
- 📄 21.缺失值的识别与处理（2）.avi168.9MB
- 📄 17.plyr包.avi200.9MB
- 📄 12.数据的读取与写出.avi137.7MB
- 📄 20.缺失值的识别与处理（1）.avi132.7MB