Training materials
Target audience: Biologists with little or no prior computationa... or PhD Students or Researcher or Staff
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e-learning
Identifiers in Bioinformatics
• beginnerData management Data identity and mapping Data handling Data retrieval Database search Interoperability Identifiers Standards -
e-learning
Interoperable File Formats
• beginnerData management Formatting Interoperability File formats Standards -
Slides
Life Sciences Research Data Management 2023 Course by ELIXIR Norway
• beginnerData management Data submission, annotation, and curation Data handling Deposition Data retrieval -
e-learning
Vocabularies for bioinformatics
• beginnerBioinformatics Data management Data submission, annotation, and curation Data handling Data retrieval Database search Ontologies Interoperability Standardised vocabulary Standards -
lessons
Visualisation with RStudio
• beginnerData visualisation Data Visualization R RStudio ggplot2 -
lessons
Data Visualisation
• beginnerData visualisation Data Visualization -
E-Learning, Training materials
Biology meets Programming - Introduction to Bioinformatics using Python
• beginnerBioinformatics Biology Python Python biologists Programming Data Analysis Sequence Analysis -
course materials, Online material, Training materials
Cloud-SPAN Genomics
• beginnerBioinformatics Software engineering Genomics DNA polymorphism Workflows Data architecture, analysis and design Shell Command line Cloud computing HPC Data analysis High performance computing -
course materials, online course, Training materials
Cloud-SPAN Prenomics
• beginnerBioinformatics Software engineering Genomics Query and retrieval Data handling Cloud computing Shell Command line Amazon Web Services genomics HPC Data analysis bioinformatics -
Slides
Data Management Planning workshop for new Life Science Projects
• beginnerData management Deposition Data handling Data retrieval data management plan NeLS TSD metadata sensitive data publication data protection storage identifiers DMP licensing Compliance data life cycle - collect data life cycle - reuse data life cycle - analyse data life cycle - process data life cycle - preserve data life cycle - share data life cycle - plan
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