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Beginner Level
Dominando a genômica: revelando insights por meio da análise de microarranjos
211Learners already enrolled
5-6 Avg Hours
CPD Accredited
Dominando a genômica: revelando insights por meio da análise de microarranjos
Aprenda a realizar várias análises bioinformáticas em dados de expressão gênica gerados usando a tecnologia de microarray.
Neste curso, você aprenderá uma gama completa de diferentes análises bioinformáticas sobre dados de expressão gênica gerados usando a tecnologia de microarray. Nesta jornada passo a passo, você aprende... Neste curso, você aprenderá uma gama completa de diferentes análises bioinformáticas sobre dados de expressão gênica gerados usando a tecnologia de microarray. Nesta jornada passo a passo, você aprenderá primeiro sobre o download de dados de microarray. Em seguida, você aprenderá a verificar a qualidade geral dos dados do microarray, visualizá-los e encontrar genes expressos diferencialmente (GEGs). Além disso, você aprenderá agrupamento e análise de ontologia genética (GO).
COURSE PUBLISHER Mohamad ZamaniDr. Mohammad Zamani bioinformatician
What You Will Learn In This Free Course
- Illustrate installing the CRAN or B...
- Assess the gene expression database...
- Identify and extract differentially...
- Apply Gene Ontology (GO) analysis o...
- Illustrate installing the CRAN or Bioconductor packages directly or indirectly in the R environment
- Assess the gene expression database on various features (options) and download the expression data
- Identify and extract differentially expressed genes (DEGs) after importing the expression matrix into geWorkbench
- Apply Gene Ontology (GO) analysis on DEGs using the corresponding database (DAVID)
- Explain the details of different microarray methods, including DNA microarray
- Evaluate the general format of the gene expression matrix and read the various information presented in the matrix
- Compute cluster analysis on DEGs using the Hierarchical clustering method in the geWorkbench
- Compute cluster analysis using the K-Means algorithm, cluster, and factoextra packages in the R environment
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