Training materials
Difficulty level: Intermediate
and Keywords: Biomedical Literature or Data analysis or statistics or Coding or Knowledge graph
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Bioinformatics, Computational Biology, Computer Science, Programming, Coding, Education, Data Science, Transcriptomics, Machine Learning
R for Data Science
•• intermediateBioinformatics Computational biology Machine learning Transcriptomics Computational Biology Coding Programming Data Science Data Analysis Computer Science Machine Learning -
Online material, online course
Workshop on Resources for Plant Sciences, 2023
•• intermediatePlant biology service bundle eLearning EeLP plant science Data Visualization Gene Ontology Knowledge graph MIAPPE -
hands-on tutorial
Hands-on for 'Supervised Learning with Hyperdimensional Computing' tutorial
•• intermediateStatistics and probability statistics -
e-learning
Explore and Visualize Your Data with Python
•• intermediateData visualisation Bioinformatics Python Data analysis -
hands-on tutorial
Bulk RNASeq analysis
•• intermediateTranscriptomics Gene expression Differential gene expression profiling Expression analysis Data analysis NGS RNASeq transcriptomics -
Intermediate Research Software Development Skills In Python
•• intermediateintermediate Coding software engineering Carpentries Incubator -
hands-on tutorial
Hands-on for 'Introduction to Machine Learning using R' tutorial
•• intermediateStatistics and probability statistics interactive-tools -
Video, Training materials, E-learning
Validate Graph Data with SHACL
•• intermediateMedical informatics FAIR data Data management Computer science Validation Data handling Clinical data SHACL Data validation RDF Knowledge graph GraphDB RDF graph validation -
Video, Training materials, Mock data, E-learning
How to use Python and R with RDF Data
•• intermediateComputer science Data management FAIR data Medical informatics Query and retrieval Data handling Data retrieval Clinical data SPARQL Query data RDF Knowledge graph Python R GraphDB -
Video
Data Gravity in the Life Sciences: Lessons learned from the HCA and other federated data projects
•• intermediateData architecture, analysis and design Cloud computing Data analysis Standards Translational research
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