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Transcriptomics for Biomedical Research Training Program #transcriptomics #dataanalysis #rnaseq
ะะพะบะฐะทะฐัั ะพะฟะธัะฐะฝะธะต
๐งฌ ๐๐๐ฏ๐๐ง๐๐ ๐๐จ๐ฎ๐ซ ๐๐ซ๐๐ง๐ฌ๐๐ซ๐ข๐ฉ๐ญ๐จ๐ฆ๐ข๐๐ฌ ๐๐ฑ๐ฉ๐๐ซ๐ญ๐ข๐ฌ๐ ๐ฐ๐ข๐ญ๐ก ๐๐ฆ๐ข๐๐ฌ๐๐จ๐ ๐ข๐!
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Embark on a comprehensive journey into ๐ง๐ฟ๐ฎ๐ป๐๐ฐ๐ฟ๐ถ๐ฝ๐๐ผ๐บ๐ถ๐ฐ๐ ๐ณ๐ผ๐ฟ ๐๐ถ๐ผ๐บ๐ฒ๐ฑ๐ถ๐ฐ๐ฎ๐น ๐ฅ๐ฒ๐๐ฒ๐ฎ๐ฟ๐ฐ๐ต with our training program, designed to build your expertise across three levels:
๐ฑ ๐๐ฒ๐ด๐ถ๐ป๐ป๐ฒ๐ฟ ๐๐ฒ๐๐ฒ๐น: Start with the fundamentals of Next-Generation Sequencing technologies, explore open databases like TCGA and GDC for data extraction, and master gene expression quantification. Learn to conduct exploratory data analysis and dive into pathway annotation using top-tier tools like iLINCS, DAVID, Reactome, and KEGG.
๐ ๐๐ป๐๐ฒ๐ฟ๐บ๐ฒ๐ฑ๐ถ๐ฎ๐๐ฒ ๐๐ฒ๐๐ฒ๐น: Elevate your skills with advanced pathway annotation, including GSEA, GO, and PPI network analysis. Visualize and validate your results with tools like Cytoscape, and apply both supervised and unsupervised machine learning techniques to RNA-Seq data. Get hands-on with R programming for RNA-Seq data analysis, visualization, and statistical analysis.
๐ค ๐๐ฑ๐๐ฎ๐ป๐ฐ๐ฒ๐ฑ ๐๐ฒ๐๐ฒ๐น: Take your knowledge to the next level with correlation, regression, and differential gene expression analysis using R. Delve into pathway annotation with KEGG & GSEA, and explore unsupervised machine learning methods like clustering in R. Gain insights into single-cell transcriptomics, including data analysis workflows and downstream analysis.
๐๐๐๐๐ฒ ๐ญ๐จ ๐๐ฑ๐๐๐ฅ ๐ข๐ง ๐๐๐-๐๐๐ช ๐๐๐ญ๐ ๐๐ง๐๐ฅ๐ฒ๐ฌ๐ข๐ฌ? ๐๐จ๐ข๐ง ๐ฎ๐ฌ ๐๐ง๐ ๐ญ๐ซ๐๐ง๐ฌ๐๐จ๐ซ๐ฆ ๐ฒ๐จ๐ฎ๐ซ ๐๐๐ซ๐๐๐ซ ๐ข๐ง ๐๐ข๐จ๐ฆ๐๐๐ข๐๐๐ฅ ๐ซ๐๐ฌ๐๐๐ซ๐๐ก!๐งโ๐ฌ
#Transcriptomics #Bioinformatics #RNASeq #DataScience #GeneExpression #PathwayAnalysis #SingleCell #MachineLearning #BiomedicalResearch #OmicsLogic #BioinformaticsTraining #GenomicResearch
๐
Embark on a comprehensive journey into ๐ง๐ฟ๐ฎ๐ป๐๐ฐ๐ฟ๐ถ๐ฝ๐๐ผ๐บ๐ถ๐ฐ๐ ๐ณ๐ผ๐ฟ ๐๐ถ๐ผ๐บ๐ฒ๐ฑ๐ถ๐ฐ๐ฎ๐น ๐ฅ๐ฒ๐๐ฒ๐ฎ๐ฟ๐ฐ๐ต with our training program, designed to build your expertise across three levels:
๐ฑ ๐๐ฒ๐ด๐ถ๐ป๐ป๐ฒ๐ฟ ๐๐ฒ๐๐ฒ๐น: Start with the fundamentals of Next-Generation Sequencing technologies, explore open databases like TCGA and GDC for data extraction, and master gene expression quantification. Learn to conduct exploratory data analysis and dive into pathway annotation using top-tier tools like iLINCS, DAVID, Reactome, and KEGG.
๐ ๐๐ป๐๐ฒ๐ฟ๐บ๐ฒ๐ฑ๐ถ๐ฎ๐๐ฒ ๐๐ฒ๐๐ฒ๐น: Elevate your skills with advanced pathway annotation, including GSEA, GO, and PPI network analysis. Visualize and validate your results with tools like Cytoscape, and apply both supervised and unsupervised machine learning techniques to RNA-Seq data. Get hands-on with R programming for RNA-Seq data analysis, visualization, and statistical analysis.
๐ค ๐๐ฑ๐๐ฎ๐ป๐ฐ๐ฒ๐ฑ ๐๐ฒ๐๐ฒ๐น: Take your knowledge to the next level with correlation, regression, and differential gene expression analysis using R. Delve into pathway annotation with KEGG & GSEA, and explore unsupervised machine learning methods like clustering in R. Gain insights into single-cell transcriptomics, including data analysis workflows and downstream analysis.
๐๐๐๐๐ฒ ๐ญ๐จ ๐๐ฑ๐๐๐ฅ ๐ข๐ง ๐๐๐-๐๐๐ช ๐๐๐ญ๐ ๐๐ง๐๐ฅ๐ฒ๐ฌ๐ข๐ฌ? ๐๐จ๐ข๐ง ๐ฎ๐ฌ ๐๐ง๐ ๐ญ๐ซ๐๐ง๐ฌ๐๐จ๐ซ๐ฆ ๐ฒ๐จ๐ฎ๐ซ ๐๐๐ซ๐๐๐ซ ๐ข๐ง ๐๐ข๐จ๐ฆ๐๐๐ข๐๐๐ฅ ๐ซ๐๐ฌ๐๐๐ซ๐๐ก!๐งโ๐ฌ
#Transcriptomics #Bioinformatics #RNASeq #DataScience #GeneExpression #PathwayAnalysis #SingleCell #MachineLearning #BiomedicalResearch #OmicsLogic #BioinformaticsTraining #GenomicResearch