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 learning5
    • Ensembl learning5
    • Kernel methods5
    • Knowledge representation5
    • Machine learning5
    • Neural networks5
    • Recommender system5
    • Reinforcement learning5
    • Supervised learning5
    • Unsupervised learning5
    • Bayesian methods2
    • Biostatistics2
    • Descriptive statistics2
    • Gaussian processes2
    • Inferential statistics2
    • Markov processes2
    • Multivariate statistics2
    • Probabilistic graphical model2
    • Probability2
    • R2
    • R program2
    • R script2
    • Single-cell genomics2
    • Single-cell sequencing2
    • Statistics2
    • Statistics and probability2
    • Cloud computing1
    • Comparative transcriptomics1
    • Computer science1
    • Data rendering1
    • Data visualisation1
    • Enrichment1
    • Enrichment analysis1
    • Functional enrichment1
    • HPC1
    • High performance computing1
    • High-performance computing1
    • MicroRNA sequencing1
    • Molecular diagnostics1
    • Network1
    • Over-representation analysis1
    • Pathway1
    • Pathway or network1
    • Personalised medicine1
    • Pipelines1
    • Precision medicine1
    • RNA sequencing1
    • RNA-Seq1
    • RNA-Seq analysis1
    • Simulation experiment1
    • Small RNA sequencing1
    • Small RNA-Seq1
    • Small-Seq1
    • Software integration1
    • Tool integration1
    • Tool interoperability1
    • Transcriptome1
    • Transcriptome profiling1
    • Transcriptomics1
    • WTSS1
    • Whole transcriptome shotgun sequencing1
    • Workflows1
    • miRNA-seq1
    • Show N_FILTERS more
    • Operation
    • Mathematical modelling1
    • Modelling and simulation1
    • Show N_FILTERS more
    • Tool
    • COBREXA.jl1
    • Wikidata1
    • Show N_FILTERS more
    • Standard database or policy
    • Common Workflow Language1
    • Show N_FILTERS more
    • Content provider
    • Glittr.org12
    • Department of Bioinformatics - BiGCaT, Maastricht University1
    • PerMedCoE1
    • Show N_FILTERS more
    • Keyword
    • Machine learning5
    • Python3
    • R3
    • Single-cell sequencing2
    • Statistics2
    • Workflows2
    • Artificial intelligence1
    • Biological networks1
    • Biomodelling1
    • CWL1
    • Cloud computing1
    • Data science1
    • Data visualization1
    • Docking1
    • Enrichment analysis1
    • General1
    • HPC1
    • Large language models1
    • Literature1
    • Modeling1
    • Network analysis1
    • Nextflow1
    • Pathway analysis1
    • Pathways1
    • Pathways and Networks1
    • RNA-seq1
    • Rust1
    • Shiny1
    • Transcriptomics1
    • cell-level simulations1
    • commonwl1
    • life sciences1
    • molecular dynamics1
    • Show N_FILTERS more
    • Competency level
    • Not specified12
    • Beginner4
    • Intermediate1
    • Show N_FILTERS more
    • Licence
    • Apache License 2.0
    • License Not Specified2523
    • Creative Commons Attribution 4.0 International1249
    • Creative Commons Attribution Share Alike 4.0 International145
    • MIT License130
    • GNU General Public License v3.0 only50
    • Creative Commons Attribution Non Commercial No Derivatives 4.0 International45
    • Creative Commons Zero v1.0 Universal44
    • Creative Commons Attribution Non Commercial Share Alike 4.0 International42
    • Other (Not Open)24
    • Other (Non-Commercial)15
    • BSD 3-Clause "New" or "Revised" License14
    • Creative Commons Attribution Non Commercial 4.0 International12
    • Other (Attribution)6
    • Creative Commons Attribution 1.0 Generic5
    • Other (Open)4
    • CeCILL Free Software License Agreement v2.13
    • Creative Commons Attribution No Derivatives 4.0 International3
    • Artistic License 2.02
    • GNU Affero General Public License v3.0 only2
    • GNU General Public License v2.0 only2
    • Academic Free License v3.01
    • Creative Commons Attribution 2.0 Generic1
    • Creative Commons Attribution No Derivatives 2.0 Generic1
    • Creative Commons Attribution Non Commercial 2.0 Generic1
    • Creative Commons Attribution Non Commercial Share Alike 2.0 Generic1
    • Do What The F*ck You Want To Public License1
    • Open Data Commons Attribution License v1.01
    • The Unlicense1
    • Show N_FILTERS more
    • Target audience
    • Computational biologists1
    • Life Science Researchers1
    • PhD students1
    • Researchers1
    • bioinformaticians1
    • computational scientists1
    • tool authors1
    • Show N_FILTERS more
    • Author
    • Lauren Dupuis2
    • Adam Hospital1
    • BovReg1
    • Denise Slenter1
    • Friederike Ehrhart1
    • Genís Bayarri1
    • Google1
    • Health Data Science Sandbox1
    • LaurenDupuis1
    • Laurent Heirendt1
    • Lucía Fabio1
    • Lynn Langit1
    • Martina Kutmon1
    • Maxime Labonne1
    • Miroslav Kratochvil1
    • PAIR code1
    • Pau Andrio1
    • RStudio1
    • Salvatore Raieli1
    • St Elmo Wilken1
    • Ted Laderas1
    • fast.ai1
    • posit-conf-20231
    • Show N_FILTERS more
    • Contributor
    • Mine Cetinkaya-Rundel2
    • 1dimir1
    • Aaron M1
    • Abhik Banerjee1
    • Abraham Omorogbe1
    • Ada Orajiaku1
    • Adam Blake1
    • Adam MacBeth1
    • Adam Pearce1
    • Addison Luh1
    • Aditya Poddar1
    • Adrian Samoticha1
    • Adrian Taylor1
    • AdrienBaudemont1
    • Aelin1
    • Al Rifat Sabbir1
    • Alex Lai1
    • Alex Leoshko1
    • Alex Rossell Hayes1
    • Alexandra Imbrisca1
    • Alexandre Senges1
    • Alexey Sokolov1
    • Ali Soufali1
    • Aliet Expósito García1
    • Alix1
    • Amin Sharifi1
    • Andreas Hindborg1
    • Andrew Arnott1
    • Andrew Gaul1
    • Andrew Jones1
    • Andrew Kushyk1
    • Andrew Pollack-Gray1
    • Andrew Shao1
    • Andrew Walbran1
    • Andrie de Vries1
    • Andriy Redko1
    • Andy Coenen1
    • Andy George1
    • Ang1
    • Angela Li1
    • Anlun Xu1
    • Antonio Linhart1
    • Anurag Sisodiya1
    • Arman1
    • Arman Yessenamanov1
    • Arsile1
    • Arthur Milchior1
    • Attila Balazs1
    • Ayako Iwasaki1
    • Barbara Borges Ribeiro1
    • Barret Schloerke1
    • Beatriz Milz1
    • Becker A.1
    • Bjørn Dons1
    • Bjørn Jørgensen1
    • Bot-Kerem1
    • Bozhao1
    • Bradford Hovinen1
    • Bram Bonné1
    • Brandon Pollack1
    • Brian Daniels1
    • Bryan Hitchcock1
    • Caleb Maclennan1
    • Carlos Jimenez1
    • Carlos Pereira Atencio1
    • Carson Sievert1
    • Chan Wang1
    • Charisee Chiw1
    • Chayim Refael Friedman1
    • Chiin1
    • Choonghyun Ryu1
    • Christophe Dervieux1
    • Claudio Marcial Peon1
    • CodeMaster70001
    • Colin Fay1
    • Colin Finck1
    • Colin Pitrat1
    • Curly-Howard-Chungus Correspondence | Lamport-Cabot-Codd-Backus-Naur Form1
    • Damiano Ferrari1
    • Daniel1
    • Daniel Andrade1
    • Daniel Fernández Núñez1
    • Daniel Gorelik1
    • Danny Ra1
    • Danny Yoo1
    • Darkhan Kubigenov1
    • Dave Mills1
    • David E Worth1
    • David Failing1
    • David Kane1
    • Davide Guerri1
    • Dayo1
    • Denis Zvonov1
    • Der Chien1
    • Devin Pastoor1
    • Dezhi Wu1
    • Diego Romero1
    • Dima1
    • Diogo Anderson1
    • Dmitri Gribenko1
    • Show N_FILTERS more
    • Resource type
    • Tutorial4
    • Jupyter notebook1
    • Show N_FILTERS more
    • Node
    • Switzerland12
    • Netherlands2
    • Spain1
    • Show N_FILTERS more
  • Show materials from all spaces
  • Show disabled materials
  • Hide materials with broken links
  • Hide archived materials

Training materials

  • Subscribe via email

Email Subscription

Register training material

Licence: Apache License 2.0

and Include archived: true

and Include broken links: true

17 materials found
  • PAIR-code/understanding-umap

    ELIXIR node event
    Machine learning Statistics and probability Single-cell sequencing Data visualisation Single-cell sequencing Data visualization Data science Machine learning Statistics
  • mlabonne/llm-course

    ELIXIR node event
    Machine learning Large language models Python Machine learning Artificial intelligence
  • google/comprehensive-rust

    ELIXIR node event
    Rust
  • lynnlangit/gcp-for-bioinformatics

    ELIXIR node event
    Computer science Cloud computing
  • LaurenDupuis/EJP-RD_Helis_Academy

    ELIXIR node event
    Pathway or network Enrichment analysis Pathways and Networks Enrichment analysis
  • hds-sandbox/scRNASeq_course

    ELIXIR node event
    Transcriptomics Single-cell sequencing RNA-Seq Single-cell sequencing RNA-seq Transcriptomics Python R
  • BovReg/nf-workshop20

    ELIXIR node event
    Workflows Workflows Nextflow
  • posit-conf-2023/python-modeling

    ELIXIR node event
    Machine learning Machine learning Python
  • laderast/gradual_shiny

    ELIXIR node event
    R script R Shiny
  • SalvatoreRa/tutorial

    ELIXIR node event
    Machine learning General Machine learning
  • 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.