Training eSupport System
  • Log In
    • Log in with LS Login
    • Login
    • Register
  • Spaces
  • Events
  • Materials
  • Workflows
  • Collections
  • e-Learning
  • Learning paths
  • Directory
    • Providers
    • Nodes

TeSSHub makes use of some necessary cookies to provide its core functionality. Additionally, we make use of Google Analytics to discover how people are using TeSSHub in order to help us improve the service. To opt out of this, choose the "Allow necessary cookies" option.

See our Privacy Policy for more information.

You can modify your cookie preferences at any time here, or from the link in the footer.

Allow necessary cookies Allow all cookies
  1. Home
  2. Materials

Filter

  • Sort

  • Filter Clear filters

    • Date added
    • In the last 24 hours
    • In the last 1 week
    • In the last 1 month
    • Scientific topic
    • Python program
    • R152
    • R program152
    • R script152
    • Bayesian methods42
    • Biostatistics42
    • Descriptive statistics42
    • Gaussian processes42
    • Inferential statistics42
    • Markov processes42
    • Multivariate statistics42
    • Probabilistic graphical model42
    • Probability42
    • Statistics42
    • Statistics and probability42
    • Comparative transcriptomics34
    • Data rendering34
    • Data visualisation34
    • Transcriptome34
    • Transcriptomics34
    • MicroRNA sequencing31
    • RNA sequencing31
    • RNA-Seq31
    • RNA-Seq analysis31
    • Small RNA sequencing31
    • Small RNA-Seq31
    • Small-Seq31
    • Transcriptome profiling31
    • WTSS31
    • Whole transcriptome shotgun sequencing31
    • miRNA-seq31
    • Active learning20
    • Ensembl learning20
    • Kernel methods20
    • Knowledge representation20
    • Machine learning20
    • Neural networks20
    • Recommender system20
    • Reinforcement learning20
    • Single-cell genomics20
    • Single-cell sequencing20
    • Supervised learning20
    • Unsupervised learning20
    • Genome annotation19
    • Exomes17
    • Genomes17
    • Genomics17
    • Personal genomics17
    • Synthetic genomics17
    • Viral genomics17
    • Whole genomes17
    • Chromosome walking16
    • Clone verification16
    • DNA-Seq16
    • DNase-Seq16
    • High throughput sequencing16
    • High-throughput sequencing16
    • NGS16
    • NGS data analysis16
    • Next gen sequencing16
    • Next generation sequencing16
    • Panels16
    • Primer walking16
    • Sanger sequencing16
    • Sequencing16
    • Targeted next-generation sequencing panels16
    • R markdown11
    • Python7
    • Python script7
    • py7
    • Variant pattern analysis6
    • Algorithms5
    • Computer programming5
    • Data structures5
    • Enrichment5
    • Enrichment analysis5
    • Functional enrichment5
    • Integrative omics5
    • Multi-omics5
    • Multiomics5
    • Over-representation analysis5
    • Pan-omics5
    • Panomics5
    • Programming languages5
    • Software development5
    • Software engineering5
    • Bottom-up proteomics4
    • Data management4
    • Discovery proteomics4
    • MS-based targeted proteomics4
    • MS-based untargeted proteomics4
    • Metadata management4
    • Metagenomics4
    • Metaproteomics4
    • Peptide identification4
    • Protein and peptide identification4
    • Proteomics4
    • Quantitative proteomics4
    • Research data management (RDM)4
    • Shotgun metagenomics4
    • Show N_FILTERS more
    • Content provider
    • Glittr.org5
    • PaN Training2
    • Show N_FILTERS more
    • Keyword
    • R
    • Python138
    • Data science30
    • Reproducibility5
    • Shiny5
    • Unix/Linux5
    • Artificial intelligence3
    • Containerization3
    • General3
    • Version control3
    • Docker2
    • Large language models2
    • Programming2
    • Quarto2
    • Cloud computing1
    • Show N_FILTERS more
    • Competency level
    • Not specified7
    • Show N_FILTERS more
    • Licence
    • License Not Specified6
    • BSD 3-Clause "New" or "Revised" License1
    • Show N_FILTERS more
    • Author
    • Hacking for Science2
    • rnorm2
    • Sean Davis1
    • UC Davis Bioinformatics Core Training Page1
    • Vince Carey1
    • Show N_FILTERS more
    • Contributor
    • rnorm2
    • Alexandru Mahmoud1
    • Hacking for Science1
    • Hannah Lyman1
    • Matt Bannert1
    • Matt Settles1
    • Sam Hunter1
    • Sean Davis1
    • Vince Carey1
    • bpdurbin1
    • jessyjli1
    • najoshi1
    • Show N_FILTERS more
    • Node
    • Switzerland5
    • Show N_FILTERS more
  • Only show materials from current space
  • Show disabled materials
  • Show materials with broken links
  • Show archived materials

Training materials

  • Subscribe via email
  • Harvest using OAI-PMH

Email Subscription

Harvest using OAI-PMH

Exchange content using OAI-PMH

Use an OAI-PMH compatible tool to harvest metadata using the OAI-PMH endpoint. In particular, this endpoint can be used for exchanging content between different TeSS instances. See the TeSS documentation for more details.

Register training material

Scientific topics: Python program

and Keywords: R

and Across all spaces: true

7 materials found
  • seandavi/agentic-coding-intro

    ELIXIR node event
    R script Python script Large language models Artificial intelligence R Python
  • rnorm/book_sample

    Python script R script Data science Python R
  • h4sci/h4sci-course

    Python script R script Data science Python R
  • rnorm/book_sample

    ELIXIR node event
    Python script R script R Python Data science
  • vjcitn/BiocPyInterop

    ELIXIR node event
    Python script R script R Python
  • ucdavis-bioinformatics-training/2020-Bioinformatics_Prerequisites_Workshop

    ELIXIR node event
    Python script R script Computer science General Unix/Linux R Python Cloud computing
  • h4sci/h4sci-course

    ELIXIR node event
    Python script R script Data science R Python
Training eSupport System
[email protected]
Contribute
About TeSSHub
Browse Spaces
Funding & acknowledgements
Privacy
Cookie preferences
Version: 1.5.1
Source code
API documentation
Bioschemas testing tool

TeSSHub has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 676559.