Training materials
Difficulty level: Intermediate
and Scientific topics: Data quality management or Drug discovery or NMR-based metabolomics or Natural language processing or Oncology or Ontology and terminology or Transcriptomics
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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 -
Presentation
FAIRtracks and Omnipy – FAIRtracks interoperability story
•• intermediateData submission, annotation, and curation Data identity and mapping Data quality management Data governance Workflows Data handling -
hands-on tutorial
Mass spectrometry: GC-MS data processing (with XCMS, RAMClustR, RIAssigner, and matchms)
•• intermediateMetabolomics -
hands-on tutorial
Bulk RNASeq analysis
•• intermediateTranscriptomics Gene expression Differential gene expression profiling Expression analysis Data analysis NGS RNASeq transcriptomics -
Slides, course materials, hands-on tutorial
Organisation and utilisation of hologenomic datasets – course notes
•• intermediateMetatranscriptomics Sample collections Metabolomics Metagenomics hologenomics metagenomics MGnify Workshop -
hands-on tutorial
Hands-on for 'Visualization of RNA-Seq results with Volcano Plot in R' tutorial
•• intermediatetranscriptomics interactive-tools -
hands-on tutorial
Mass spectrometry: LC-MS preprocessing with XCMS
•• intermediateMetabolomics -
hands-on tutorial
Mass spectrometry imaging: Finding differential analytes
•• intermediateMetabolomics -
slides
An introduction to scRNA-seq data analysis
•• intermediateTranscriptomics Single Cell -
PDF
IUPHAR/BPS Guide to Pharmacology online tutorial
•• intermediatePharmacology Drug discovery
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