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
    • Bayesian methods2
    • Biostatistics2
    • Descriptive statistics2
    • Gaussian processes2
    • Inferential statistics2
    • Markov processes2
    • Multivariate statistics2
    • Probabilistic graphical model2
    • Probability2
    • Statistics2
    • Statistics and probability2
    • Bottom-up proteomics1
    • Comparative transcriptomics1
    • Discovery proteomics1
    • MS-based targeted proteomics1
    • MS-based untargeted proteomics1
    • Metaproteomics1
    • Peptide identification1
    • Protein and peptide identification1
    • Proteomics1
    • Quantitative proteomics1
    • Targeted proteomics1
    • Top-down proteomics1
    • Transcriptome1
    • Transcriptomics1
    • Show N_FILTERS more
    • Tool
    • Galaxy4
    • MultiQC2
    • BWA1
    • Bwa-mem21
    • DropletUtils1
    • PubMed1
    • SAMtools1
    • SRA Software Toolkit1
    • STAR1
    • fastp1
    • lofreq1
    • snpEff1
    • Show N_FILTERS more
    • Content provider
    • GTN5
    • Show N_FILTERS more
    • Keyword
    • Statistics and machine learning2
    • 10x1
    • Introduction to Galaxy Analyses1
    • ML1
    • Machine learning1
    • Pan-cancer1
    • Proteomics1
    • Single Cell1
    • cancer1
    • cancer biomarkers1
    • interactive-tools1
    • oncogenes and tumor suppressor genes1
    • Show N_FILTERS more
    • Competency level
    • Beginner4
    • Intermediate1
    • Show N_FILTERS more
    • Licence
    • Creative Commons Attribution 4.0 International5
    • Show N_FILTERS more
    • Target audience
    • Students5
    • Show N_FILTERS more
    • Author
    • Daniel Blankenberg
    • Bérénice Batut40
    • Saskia Hiltemann26
    • Subina Mehta23
    • Helena Rasche19
    • Anthony Bretaudeau17
    • Björn Grüning14
    • Anton Nekrutenko13
    • Mehmet Tekman13
    • Anne Fouilloux12
    • James Johnson12
    • Katherine Do12
    • Maria Doyle12
    • Anup Kumar11
    • Cristóbal Gallardo11
    • Delphine Lariviere11
    • Pavankumar Videm11
    • Pratik Jagtap11
    • Simon Gladman10
    • Wendi Bacon10
    • Yvan Le Bras10
    • Melanie Föll9
    • Simon Bray9
    • Kaivan Kamali8
    • Timothy J. Griffin8
    • Wolfgang Maier8
    • Anika Erxleben7
    • Anna Syme7
    • Julia Jakiela7
    • Nicola Soranzo7
    • Paul Zierep7
    • Praveen Kumar7
    • Diana Chiang Jurado6
    • Emma Leith6
    • Erwan Corre6
    • Jeremy Goecks6
    • Junhao Qiu6
    • Leonid Kostrykin6
    • Matthias Fahrner6
    • Paulo Cilas Morais Lyra Junior6
    • Stéphanie Robin6
    • Alex Ostrovsky5
    • Alexandre Cormier5
    • Christopher Barnett5
    • Dechen Bhuming5
    • Joachim Wolff5
    • Katarzyna Kamieniecka5
    • Khaled Jum'ah5
    • Krzysztof Poterlowicz5
    • Laura Leroi5
    • Ray Sajulga5
    • Valentin Loux5
    • Alireza Khanteymoori4
    • Amirhossein Naghsh Nilchi4
    • Bazante Sanders4
    • Clemens Blank4
    • Coline Royaux4
    • Daniela Schneider4
    • Dave Clements4
    • Florian Christoph Sigloch4
    • Florian Heyl4
    • Fotis E. Psomopoulos4
    • Helge Hecht4
    • Hélène Chiapello4
    • Khai Van Dang4
    • Lucille Delisle4
    • Mallory Freeberg4
    • Mateo Boudet4
    • Morgan Howells4
    • Mélanie Petera4
    • Nadia Goué4
    • Romane LIBOUBAN4
    • Vivek Bhardwaj4
    • Beatriz Serrano-Solano3
    • Belinda Phipson3
    • Engy Nasr3
    • Fabio Cumbo3
    • Fidel Ramirez3
    • Gildas Le Corguillé3
    • Jean-François Martin3
    • Marie Crane3
    • Marisa Loach3
    • Miguel Roncoroni3
    • Mo Heydarian3
    • Polina Polunina3
    • Riccardo Massei3
    • Tharindu Senapathi3
    • The Carpentries3
    • Torsten Seemann3
    • Workflow4Metabolomics core team3
    • Alyssa Pybus2
    • Andrea Bagnacani2
    • Anne Pajon2
    • Anne Siegel2
    • Brandon Pickett2
    • Camila Goclowski2
    • Chao Zhang2
    • Christoph Stritt2
    • Cristina Martins Rodrigues2
    • Daniela Brites2
    • Show N_FILTERS more
    • Contributor
    • Helena Rasche5
    • Saskia Hiltemann5
    • Björn Grüning4
    • Bérénice Batut3
    • Mehmet Tekman2
    • Anton Nekrutenko1
    • Anup Kumar1
    • Armin Dadras1
    • Cristóbal Gallardo1
    • Donny Vrins1
    • Hans-Rudolf Hotz1
    • Jayadev Joshi1
    • John Davis1
    • Martin Čech1
    • Melanie Föll1
    • Niall Beard1
    • Nicola Soranzo1
    • Pavankumar Videm1
    • Subina Mehta1
    • Teresa Müller1
    • Vijay1
    • Wendi Bacon1
    • William Durand1
    • Wolfgang Maier1
    • dlal-group1
    • Show N_FILTERS more
    • Resource type
    • e-learning5
    • Show N_FILTERS more
    • Related resource
    • Associated Training Datasets
    • Associated Workflows7
    • 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

Authors: Daniel Blankenberg

and Related resources: Associated Training Datasets

5 materials found
  • e-learning

    Pre-processing of 10X Single-Cell RNA Datasets

    • Beginner
    Transcriptomics 10x Single Cell
  • e-learning

    PAPAA PI3K_OG: PanCancer Aberrant Pathway Activity Analysis

    • Beginner
    Statistics and probability Machine learning Pan-cancer Statistics and machine learning cancer biomarkers oncogenes and tumor suppressor genes
  • e-learning

    Text-mining with the SimText toolset

    • Beginner
    Statistics and probability Statistics and machine learning interactive-tools
  • e-learning

    Machine Learning Modeling of Anticancer Peptides

    •• Intermediate
    Proteomics ML Proteomics cancer
  • e-learning

    NGS data logistics

    • Beginner
    Introduction to Galaxy Analyses
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.