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
    • Diffraction experiment6
    • Imaging6
    • Microscopy6
    • Microscopy imaging6
    • Optical super resolution microscopy6
    • Photonic force microscopy6
    • Photonic microscopy6
    • Show N_FILTERS more
    • Tool
    • Galaxy6
    • Galaxy Image Analysis5
    • scikit-image4
    • Show N_FILTERS more
    • Content provider
    • GTN6
    • Show N_FILTERS more
    • Keyword
    • Overlay
    • jupyter-notebook53
    • Foundations of Data Science50
    • biodiversity47
    • microgalaxy41
    • Proteomics35
    • Single Cell35
    • Statistics and machine learning35
    • Ecology30
    • Microbiome27
    • Genome Annotation25
    • Transcriptomics24
    • Using Galaxy and Managing your Data24
    • FAIR Data, Workflows, and Research21
    • Imaging19
    • Variant Analysis18
    • Assembly17
    • fair16
    • jbrowse116
    • gmod15
    • interactive-tools15
    • work-in-progress15
    • Climate13
    • Introduction to Galaxy Analyses13
    • prokaryote13
    • paper-replication12
    • MIGHTS11
    • earth-system11
    • Image segmentation10
    • Sequence analysis10
    • assembly10
    • data stewardship10
    • eukaryote10
    • metabolomics10
    • plants10
    • 10x9
    • Computational chemistry9
    • DDA9
    • Metabolomics9
    • ai-ml9
    • covid199
    • cyoa9
    • elixir9
    • label-free9
    • metagenomics9
    • one-health9
    • Epigenetics8
    • ocean8
    • workflows8
    • EBV dataset7
    • EBV workflow7
    • collections7
    • dmp7
    • español7
    • metabarcoding7
    • nanopore7
    • SQL6
    • data management6
    • deutsch6
    • ecology6
    • illumina6
    • italiano6
    • transcriptomics6
    • 16S5
    • Digital Humanities5
    • Large Language Model5
    • R5
    • deconvolution5
    • label-TMT115
    • mouse5
    • rmarkdown-notebook5
    • ro-crate5
    • virology5
    • Bioimaging4
    • Conversion4
    • DIA4
    • Data management4
    • Evolution4
    • FAIR4
    • Multi-channel image4
    • Object feature extraction4
    • QC4
    • Visualisation4
    • bacteria4
    • diversity4
    • exposomics4
    • galaxy-intro4
    • gc-ms4
    • genetic composition EBV class4
    • lc-ms4
    • pangeo4
    • single-cell4
    • taxonomic profiling4
    • ChIP-seq3
    • Deep learning3
    • Image annotation3
    • RAD-seq3
    • Synthetic Biology3
    • amr3
    • apollo23
    • Show N_FILTERS more
    • Competency level
    • Beginner3
    • Intermediate3
    • Show N_FILTERS more
    • Licence
    • Creative Commons Attribution 4.0 International6
    • Show N_FILTERS more
    • Target audience
    • Students
    • Show N_FILTERS more
    • Author
    • Leonid Kostrykin4
    • Riccardo Massei3
    • Thomas Wollmann2
    • Anne Fouilloux1
    • Daniel Franco Barranco1
    • Even Moa Myklebust1
    • Saskia Hiltemann1
    • Show N_FILTERS more
    • Contributor
    • Beatriz Serrano-Solano6
    • Leonid Kostrykin6
    • Saskia Hiltemann6
    • Björn Grüning4
    • Diana Chiang Jurado2
    • Helena Rasche2
    • Riccardo Massei2
    • Thomas Wollmann2
    • Daniel Franco Barranco1
    • Even Moa Myklebust1
    • Maria Arrate Munoz Barrutia1
    • Show N_FILTERS more
    • Resource type
    • e-learning
    • Show N_FILTERS more
    • Related resource
    • Associated Workflows6
    • Associated Training Datasets5
    • Show N_FILTERS more
  • Show materials from all spaces
  • Show disabled materials
  • Show materials with broken links
  • Show archived materials

e-Learning

  • Subscribe via email

Email Subscription

Keywords: Overlay

and Resource type: e-learning

and Target audience: Students

6 e-learning materials found
  • ELIXIR TeSS

    e-learning

    Segmentation of Anatomical Structures in Medical 3-D Images

    • Beginner
    Imaging 3D image Computed tomography Conversion Image segmentation Imaging Medical imaging Object feature extraction Overlay Volume rendering
  • ELIXIR TeSS

    e-learning

    Execute a BiaPy workflow in Galaxy

    •• Intermediate
    Imaging 3D image Conversion Deep learning Image annotation Image segmentation Imaging Overlay Volume rendering
  • ELIXIR TeSS

    e-learning

    Voronoi segmentation

    •• Intermediate
    Imaging Image segmentation Imaging Multi-channel image Object counting Overlay Tessellation
  • ELIXIR TeSS

    e-learning

    Quantification of single-molecule RNA fluorescence in situ hybridization (smFISH) in yeast cell lines

    • Beginner
    Imaging IDR dataset Imaging Overlay Rasterisation Spot detection
  • ELIXIR TeSS

    e-learning

    Analyse HeLa fluorescence siRNA screen

    •• Intermediate
    Imaging Fluorescence microscopy High-throughput screening Image segmentation Image thresholding Imaging Object feature extraction Overlay
  • ELIXIR TeSS

    e-learning

    Introduction to Image Analysis using Galaxy

    • Beginner
    Imaging Conversion Fluorescence microscopy Image segmentation Image thresholding Imaging Object counting Overlay
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.