Training materials
Target audience: Graduate Students or Life scientists or This webinar is for wet-lab researchers and bio... or data manager or post-docs or postdocs
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lessons
Data Visualisation
• beginnerData visualisation Data Visualization -
hands-on tutorial
Gentle Introduction to Python
• beginnerPython script Software engineering Programming Python -
hands-on tutorial
Explore Protein Structures with ChimeraX
• beginnerProtein structure analysis Sequence analysis Structure visualisation ChimeraX Protein Structure analysis -
hands-on tutorial
Introduction to Research Data Management
• beginnerData quality management Data submission, annotation, and curation Research Data Management Research Publishing -
hands-on tutorial
Introduction to Git and Github
• beginnerSoftware engineering Git Github Version control -
hands-on tutorial
Bulk RNASeq analysis
•• intermediateTranscriptomics Gene expression Differential gene expression profiling Expression analysis Data analysis NGS RNASeq transcriptomics -
Using the Norwegian e-infrastructure for Life Science and usegalaxy.no
• beginnerNeLS Data storage data sharing Data analysis -
Training materials
Using bioinformatics to hunt SARS-CoV-2, its variants & its origins – a practical guide
• beginnerBioinformatics for schools, basic bioinformatics, SARS-CoV-2 pandemic, genome analysis, protein sequence analysis, protein structure analysis, virus variants, spike protein, training material -
PDF, slideck/ presentation
Elaboración de un Plan de Gestión de Datos (DMP): teoria y práctica
• beginnerData management FAIR data ELIXIR-CONVERGE DMP DMP tools DMP templates DMP evaluation Data managment plan research data management FAIR principles tools template competency evaluation online e-learning Spanish -
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