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

TeSS makes use of some necessary cookies to provide its core functionality. Additionally, we make use of Google Analytics to discover how people are using TeSS 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
    • Active learning4
    • Bayesian methods4
    • Biostatistics4
    • Descriptive statistics4
    • Ensembl learning4
    • Gaussian processes4
    • Inferential statistics4
    • Kernel methods4
    • Knowledge representation4
    • Machine learning4
    • Markov processes4
    • Multivariate statistics4
    • Neural networks4
    • Probabilistic graphical model4
    • Probability4
    • Recommender system4
    • Reinforcement learning4
    • Statistics4
    • Statistics and probability4
    • Supervised learning4
    • Unsupervised learning4
    • Python2
    • Python program2
    • Python script2
    • R2
    • R program2
    • R script2
    • py2
    • Comparative transcriptomics1
    • MicroRNA sequencing1
    • Network1
    • Pathway1
    • Pathway or network1
    • RNA sequencing1
    • RNA-Seq1
    • RNA-Seq analysis1
    • Small RNA sequencing1
    • Small RNA-Seq1
    • Small-Seq1
    • Transcriptome1
    • Transcriptome profiling1
    • Transcriptomics1
    • WTSS1
    • Whole transcriptome shotgun sequencing1
    • miRNA-seq1
    • Show N_FILTERS more
    • Content provider
    • Glittr.org11
    • Show N_FILTERS more
    • Keyword
    • Python5
    • Machine learning4
    • Statistics4
    • Data science2
    • R2
    • Pathways and Networks1
    • Quarto1
    • RNA-seq1
    • Reproducibility1
    • Transcriptomics1
    • Version control1
    • Show N_FILTERS more
    • Competency level
    • Not specified11
    • Show N_FILTERS more
    • Licence
    • Creative Commons Attribution 4.0 International10
    • License Not Specified1
    • Show N_FILTERS more
    • Author
    • SIB Swiss Institute of Bioinformatics11
    • Show N_FILTERS more
    • Contributor
    • Saskia Hiltemann592
    • Helena Rasche501
    • Björn Grüning420
    • Bérénice Batut261
    • Nicola Soranzo179
    • Martin Čech128
    • Anthony Bretaudeau107
    • Cristóbal Gallardo104
    • Niall Beard90
    • Toby Hodges79
    • Wendi Bacon77
    • Nate Coraor70
    • François Michonneau67
    • Armin Dadras64
    • Gildas Le Corguillé63
    • Erin Becker61
    • Marius van den Beek60
    • William Durand59
    • Zhian N. Kamvar58
    • Mine Cetinkaya-Rundel56
    • Robert Andrews55
    • Simon Gladman54
    • Tracy Teal53
    • Katrin Leinweber52
    • Raniere Silva52
    • W. Trevor King50
    • maneesha50
    • Andy Boughton49
    • Beatriz Serrano-Solano48
    • Teresa Müller48
    • Katie Anne Mills47
    • Lucille Delisle46
    • Maxim Belkin46
    • Mehmet Tekman46
    • Yvan Le Bras45
    • Canadian Bioinformatics Workshops43
    • Munazah Andrabi43
    • David Pérez-Suárez42
    • Gabriel A. Devenyi42
    • Abby Cabunoc Mayes41
    • EvanWill41
    • Ian Lee41
    • Jon Pipitone41
    • Jonah Duckles41
    • Michael Hansen41
    • Piotr Banaszkiewicz41
    • Brandon Curtis40
    • David Mawdsley40
    • Greg Wilson40
    • Jemma Stachelek40
    • Pavankumar Videm40
    • Remi Rampin40
    • Allen Lee39
    • Andrew Sanchez39
    • Michael R. Crusoe39
    • James Allen38
    • Jeff Oliver38
    • Joel Nothman38
    • Nick Young38
    • Rémi Emonet38
    • naught10138
    • Rayna M Harris37
    • William L. Close37
    • Marie Josse36
    • Wolfgang Maier36
    • Melanie Föll35
    • Sarah Brown35
    • Anup Kumar32
    • Gerard Capes32
    • Maria Doyle32
    • trk30
    • Ana Conrado29
    • Stephan Druskat29
    • K.E. Koziar28
    • Simon Bray28
    • Subina Mehta28
    • Alex Whan27
    • Renato Alves27
    • Christina K.26
    • Paula Andrea Martinez26
    • Anne Fouilloux25
    • Michael Joseph25
    • Anthony Gitter24
    • Donny Vrins24
    • João Rodrigues24
    • Geert van Geest23
    • Peter van Heusden23
    • Sarah Stevens21
    • Wolmar Nyberg Åkerström21
    • actions-user21
    • Henry Schreiner20
    • Hilmar Lapp20
    • Julia Jakiela20
    • Robert Davey20
    • Bazante Sanders19
    • Leonid Kostrykin19
    • The Gulbenkian Training Programme in Bioinformatics19
    • Anton Nekrutenko18
    • Elin Kronander18
    • Niclas Jareborg18
    • Show N_FILTERS more
    • Node
    • Switzerland11
    • Show N_FILTERS more
  • Show materials from all spaces
  • Show disabled materials
  • Show materials with broken links
  • Show archived materials

Training materials

  • Subscribe via email

Email Subscription

Register training material

Contributors: Wandrille D.

11 materials found
  • sib-swiss/intermediate-machine-learning-training

    ELIXIR node event
    Machine learning Machine learning Python Data science
  • sib-swiss/reproducible-analysis-training

    ELIXIR node event
    R script Reproducibility Quarto R Version control
  • sib-swiss/pytorch-practical-training

    ELIXIR node event
    Machine learning Machine learning Python
  • sib-swiss/introduction-to-statistics-with-python-training

    ELIXIR node event
    Statistics and probability Statistics Python
  • sib-swiss/RNAseq-introduction-training

    ELIXIR node event
    Transcriptomics RNA-Seq Pathway or network Transcriptomics RNA-seq Pathways and Networks
  • sib-swiss/statistics-and-machine-learning-training

    ELIXIR node event
    Machine learning Statistics and probability Statistics Machine learning
  • sib-swiss/intro-bayesian-statistics-training

    ELIXIR node event
    Statistics and probability Statistics
  • sib-swiss/intro-machine-learning-training

    ELIXIR node event
    Machine learning Statistics and probability Machine learning Statistics
  • sib-swiss/first-steps-with-R-training

    ELIXIR node event
    R script R
  • sib-swiss/intermediate-python-training

    ELIXIR node event
    Python script Python Data science
  • 1
  • 2
Training eSupport System
[email protected]
Contribute
About TeSS
Browse Spaces
Funding & acknowledgements
Privacy
Cookie preferences
Version: 1.5.1
Source code
API documentation
Bioschemas testing tool

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