Training materials
Difficulty level: Intermediate
and Scientific topics: Omics or Transcriptomics or Computational biology
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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 -
Tutorial, Presentation
Materials from 'Introduction to High Performance Computing for Life Scientists' course
•• intermediateComputational biology HPC GPU parallel computing -
e-learning
High Performance Computing in Life Sciences
•• intermediateComputational biology High performance computing Data storage -
hands-on tutorial
Bulk RNASeq analysis
•• intermediateTranscriptomics Gene expression Differential gene expression profiling Expression analysis Data analysis NGS RNASeq transcriptomics -
hands-on tutorial
Hands-on for 'Visualization of RNA-Seq results with Volcano Plot in R' tutorial
•• intermediateTranscriptomics transcriptomics interactive-tools -
slides
Slides for 'An introduction to scRNA-seq data analysis' tutorial
•• intermediateTranscriptomics single-cell español -
Tutorial
Tutorial on CARNIVAL
•• intermediateMolecular interactions, pathways and networks Gene expression Omics RNA-Seq Network analysis RNA-Seq analysis HPC Signaling RNAseq, transcriptomics -
Tutorial, Documentation
BioSimulators tutorial and help
•• intermediateSystems biology Computational biology Simulation experiment Modelling and simulation Modeling biomodel dynamic simulations COMBINE OMEX SED-ML SBML BNGL -
Documentation
BioSimulations tutorial and help
•• intermediateComputational biology Systems biology Simulation experiment Visualisation Modelling and simulation SystemsBiology ComputationalBiology Computational modelling Modeling Biomodelling Model Kinetic modeling SED-ML COMBINE -
Bioinformatics Summer School 2019
•• intermediateProteomics RNA-Seq Omics Statistics and probability Data handling