Training eSupport System
  • Log In
    • Log in with UmbrellaID
    • Log in with Helmholtz AAI
    • Login
  • About
  • Events
  • Materials
  • Workflows
  • Collections
  • Learning paths
  • Spaces
  • Directory
    • Providers

PaN-Training makes use of some necessary cookies to provide its core functionality.

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
  1. Home
  2. Materials

Filter

  • Sort

  • Filter Clear filters

    • Scientific topic
    • Data visualisation
    • Python68
    • Python program68
    • Python script68
    • py68
    • Active learning17
    • Ensembl learning17
    • Kernel methods17
    • Knowledge representation17
    • Machine learning17
    • Neural networks17
    • Recommender system17
    • Reinforcement learning17
    • Supervised learning17
    • Unsupervised learning17
    • Data rendering10
    • Bayesian methods9
    • Biostatistics9
    • Descriptive statistics9
    • Gaussian processes9
    • Inferential statistics9
    • Markov processes9
    • Multivariate statistics9
    • Probabilistic graphical model9
    • Probability9
    • Statistics9
    • Statistics and probability9
    • MicroRNA sequencing8
    • RNA sequencing8
    • RNA-Seq8
    • RNA-Seq analysis8
    • Small RNA sequencing8
    • Small RNA-Seq8
    • Small-Seq8
    • Transcriptome profiling8
    • WTSS8
    • Whole transcriptome shotgun sequencing8
    • miRNA-seq8
    • Comparative transcriptomics7
    • Transcriptome7
    • Transcriptomics7
    • R6
    • R program6
    • R script6
    • Single-cell genomics5
    • Single-cell sequencing5
    • Bioinformatics3
    • Cloud computing3
    • Computer science3
    • HPC3
    • High performance computing3
    • High-performance computing3
    • Chromosome walking2
    • Clone verification2
    • DNA-Seq2
    • DNase-Seq2
    • Exomes2
    • FAIR data2
    • Findable, accessible, interoperable, reusable data2
    • Genome annotation2
    • Genomes2
    • Genomics2
    • High throughput sequencing2
    • High-throughput sequencing2
    • NGS2
    • NGS data analysis2
    • Next gen sequencing2
    • Next generation sequencing2
    • Panels2
    • Personal genomics2
    • Primer walking2
    • Sanger sequencing2
    • Sequencing2
    • Synthetic genomics2
    • Targeted next-generation sequencing panels2
    • Viral genomics2
    • Whole genomes2
    • Aerobiology1
    • Algorithms1
    • Antimicrobial stewardship1
    • Behavioural biology1
    • Biological rhythms1
    • Biological science1
    • Biology1
    • Biomathematics1
    • Biomedical informatics1
    • Bottom-up proteomics1
    • Chronobiology1
    • Clinical informatics1
    • Computational biology1
    • Computer programming1
    • Cryobiology1
    • Data management1
    • Data structures1
    • Discovery proteomics1
    • Dynamic systems1
    • Dynamical systems1
    • Dynymical systems theory1
    • Enrichment1
    • Enrichment analysis1
    • Show N_FILTERS more
    • Content provider
    • Elixir TeSS10
    • Show N_FILTERS more
    • Keyword
    • Python
    • Data visualization10
    • R3
    • Data science2
    • General2
    • Online Repository2
    • Business Inteligence1
    • CONVERGE1
    • Clinical data1
    • Dashboard1
    • Data Management1
    • Data analysis1
    • Data management1
    • Data mining1
    • Data visualisation1
    • Enrichment analysis1
    • FAIR Data1
    • FAIR Data, Workflows, and Research1
    • FAIR data1
    • GraphDB1
    • Herpetology1
    • Java1
    • Knowledge graph1
    • Machine learning1
    • Mock data1
    • RDF1
    • RNA-seq1
    • RStudio1
    • Reproducibility1
    • Rmarkdown1
    • SPARQL1
    • Snakemake1
    • Transcriptomics1
    • Unix/Linux1
    • Variant analysis1
    • Version control1
    • Workflows1
    • ggPlot1
    • Show N_FILTERS more
    • Difficulty level
    • Not specified9
    • Intermediate1
    • Show N_FILTERS more
    • Licence
    • License Not Specified6
    • MIT License2
    • BSD 3-Clause "New" or "Revised" License1
    • Creative Commons Attribution 4.0 International1
    • Show N_FILTERS more
    • Target audience
    • Life scientists, bioinformaticians and researchers who are familiar with writing Python code and core Python elements, and would like to use it in their daily data exploration and visualization tasks.1
    • Show N_FILTERS more
    • Author
    • BioINForm1
    • Fred Hutch Data Science Lab1
    • Kyran Dale1
    • NIAID BCBB1
    • R. Burke Squires1
    • Rohan Alexander1
    • Scott Reed1
    • Teaching materials at the Harvard Chan Bioinformatics Core1
    • The Carpentries Incubator1
    • UW Interactive Data Lab1
    • Wandrille Duchemin1
    • Show N_FILTERS more
    • Contributor
    • BioINForm1
    • Fred Hutch Data Science Lab1
    • Kyran Dale1
    • NIAID BCBB1
    • R. Burke Squires1
    • Rohan Alexander1
    • Scott Reed1
    • Teaching materials at the Harvard Chan Bioinformatics Core1
    • The Carpentries Incubator1
    • UW Interactive Data Lab1
    • Show N_FILTERS more
    • Resource type
    • e-learning1
    • Show N_FILTERS more
    • Status
    • Active1
    • Show N_FILTERS more
  • Only show materials from current space
  • Show disabled materials
  • Show materials with broken links
  • Show archived materials
    • Date added
    • In the last 24 hours
    • In the last 1 week
    • In the last 1 month

Training materials

  • Subscribe via email

Email Subscription

Register training material

Scientific topics: Data visualisation

and Keywords: Python

and Across all spaces: true

10 materials found
  • Kyrand/dataviz-with-python-and-js-ed-2

    Data visualisation Data science Data visualization Java Python
  • scottmreed/molecular_informatics

    Data visualisation Data science Data visualization Python
  • RohanAlexander/tswd

    Data visualisation Data visualization Python R
  • burkesquires/python_biologist

    Workflows Data visualisation Machine learning Data visualization Python Reproducibility Snakemake
  • fhdsl/better_plots

    Data visualisation Data visualization Python R
  • bioinform-org/bioinforming-hs

    Data visualisation Data visualization General Python
  • uwdata/visualization-curriculum

    Data visualisation Data visualization Python
  • carpentries-incubator/python-interactive-data-visualizations

    Data visualisation Data visualization Python
  • e-learning

    Explore and Visualize Your Data with Python

    •• intermediate
    Data visualisation Bioinformatics Data analysis Python
  • hbctraining/Training-modules

    FAIR data Data visualisation R markdown Enrichment analysis RNA-Seq Transcriptomics Variant pattern analysis Data visualization General Python …
Training eSupport System
pan-training@hzdr.de
Imprint
Contribute
About PaN-Training
Funding & acknowledgements
Privacy
Cookie preferences
Version: 1.5.1
Source code
API documentation

The training portal for the photon & neutron community is supported through the European Union's Horizon 2020 research and innovation programme, under grant agreement 857641, 823852, the Horizon Europe Framework under grant agreement 101129751, and the consortium DAPHNE4NFDI in the context of the work of the NFDI e.V. under the DFG - project number 460248799.