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10 materials found

Authors: Sonali Arora  or Brian Haas 


Working with DNA Sequences

Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1560 software packages, and an...

Keywords: Data Representation

Working with DNA Sequences https://tess.elixir-europe.org/materials/genomic-ranges-slides-02149c9c-1bd0-4bdf-b1c6-784a084a2ccd Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1560 software packages, and an active user community. Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images. Data Representation
Visualization of Genomic Data

Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1560 software packages, and an...

Scientific topics: RNA-Seq

Visualization of Genomic Data https://tess.elixir-europe.org/materials/visualization-of-genomic-data Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1560 software packages, and an active user community. Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images. RNA-Seq
Working with DNA Sequences

Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1560 software packages, and an...

Keywords: Data Representation

Working with DNA Sequences https://tess.elixir-europe.org/materials/genomic-ranges-slides Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1560 software packages, and an active user community. Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images. Data Representation
Copy Number

Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1560 software packages, and an...

Keywords: Copy Number

Copy Number https://tess.elixir-europe.org/materials/copy-number Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1560 software packages, and an active user community. Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images. Copy Number
Machine Learning

Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1560 software packages, and an...

Scientific topics: Machine learning

Machine Learning https://tess.elixir-europe.org/materials/machine-learning Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1560 software packages, and an active user community. Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images. Machine learning
Informatics for RNA-Seq Analysis 2018 Module 6-Functional Annotation and Analysis of Transcripts

Course providing an introduction to RNA-seq data analysis followed by integrated tutorials demonstrating the use of popular RNA-seq analysis packages.

Informatics for RNA-Seq Analysis 2018 Module 6-Functional Annotation and Analysis of Transcripts https://tess.elixir-europe.org/materials/informatics-for-rna-seq-analysis-2018-module-6-functional-annotation-and-analysis-of-transcripts Course providing an introduction to RNA-seq data analysis followed by integrated tutorials demonstrating the use of popular RNA-seq analysis packages. Researchers Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists Graduate Students
Informatics for RNA-Seq Analysis 2018 Module 5-Genome Guided and Genome-free Transcriptome Assembly

Course providing an introduction to RNA-seq data analysis followed by integrated tutorials demonstrating the use of popular RNA-seq analysis packages.

Informatics for RNA-Seq Analysis 2018 Module 5-Genome Guided and Genome-free Transcriptome Assembly https://tess.elixir-europe.org/materials/informatics-for-rna-seq-analysis-2018-module-5-genome-guided-and-genome-free-transcriptome-assembly Course providing an introduction to RNA-seq data analysis followed by integrated tutorials demonstrating the use of popular RNA-seq analysis packages. Researchers Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists Graduate students
Bioinformatics for Cancer Genomics 2018 Module 9-Gene Fusion and Rearrangements

Course covers the key bioinformatics concepts and tools required to analyze cancer genomic data sets and access and work with data sets in the cloud.

Bioinformatics for Cancer Genomics 2018 Module 9-Gene Fusion and Rearrangements https://tess.elixir-europe.org/materials/bioinformatics-for-cancer-genomics-2018-module-9-gene-fusion-and-rearrangements Course covers the key bioinformatics concepts and tools required to analyze cancer genomic data sets and access and work with data sets in the cloud. Researchers Graduate students Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists
Informatics for RNA-Seq Analysis 2017 Module 7-Functional Annotation and Analysis of Transcripts

Course providing an introduction to RNA-seq data analysis followed by integrated tutorials demonstrating the use of popular RNA-seq analysis packages.

Informatics for RNA-Seq Analysis 2017 Module 7-Functional Annotation and Analysis of Transcripts https://tess.elixir-europe.org/materials/informatics-for-rna-seq-analysis-2017-module-7-functional-annotation-and-analysis-of-transcripts Course providing an introduction to RNA-seq data analysis followed by integrated tutorials demonstrating the use of popular RNA-seq analysis packages. Researchers Biologists, Genomicists, Computer Scientists Graduate Students Post-Doctoral Fellows
Informatics for RNA-Seq Analysis 2017 Module 6-Genome-free De Novo Transcriptome Assembly

Course providing an introduction to RNA-seq data analysis followed by integrated tutorials demonstrating the use of popular RNA-seq analysis packages.

Informatics for RNA-Seq Analysis 2017 Module 6-Genome-free De Novo Transcriptome Assembly https://tess.elixir-europe.org/materials/informatics-for-rna-seq-analysis-2017-module-6-genome-free-de-novo-transcriptome-assembly Course providing an introduction to RNA-seq data analysis followed by integrated tutorials demonstrating the use of popular RNA-seq analysis packages. Researchers Biologists, Genomicists, Computer Scientists Graduate Students Post-Doctoral Fellows