Björn Grüning
Affiliations
Former Affiliations
Contributions
The following list includes only slides and tutorials where the individual or organisation has been added to the contributor list. This may not include the sum total of their contributions to the training materials (e.g. GTN css or design, tutorial datasets, workflow development, etc.) unless described by a news post.
Editorial Roles
This contributor has taken on additional responsibilities as an editor for the following topics. They are responsible for ensuring that the content is up to date, accurate, and follows GTN best practices.
- Topic: Galaxy Server administration
- Topic: Computational chemistry
- Topic: Contributing to the Galaxy Training Material
- Topic: Proteomics
- Topic: Variant Analysis
Tutorials
- Development in Galaxy / Generic plugins 🧐
- Development in Galaxy / Data source integration 🧐
- Development in Galaxy / Galaxy Interactive Tools 🧐
- Development in Galaxy / ToolFactory: Generating Tools From Simple Scripts 🧐
- Development in Galaxy / Contributing to BioBlend as a developer 🧐
- Development in Galaxy / JavaScript plugins ✍️ 🧐
- Development in Galaxy / Debugging Galaxy 🧐
- Development in Galaxy / Galaxy Webhooks ✍️ 🧐
- Development in Galaxy / Setting up a dev Onedata instance 🧐
- FAIR Data, Workflows, and Research / FAIR and its Origins 🧐
- FAIR Data, Workflows, and Research / DataPLANT ARCs 🧐
- FAIR Data, Workflows, and Research / Metadata 🧐
- FAIR Data, Workflows, and Research / Persistent Identifiers 🧐
- FAIR Data, Workflows, and Research / RO-Crate - Introduction 🧐
- FAIR Data, Workflows, and Research / Best practices for workflows in GitHub repositories 🧐
- FAIR Data, Workflows, and Research / FAIR Bioimage Metadata 🧐
- FAIR Data, Workflows, and Research / RO-Crate in Python 🧐
- FAIR Data, Workflows, and Research / Exporting Workflow Run RO-Crates from Galaxy 🧐
- FAIR Data, Workflows, and Research / Access 🧐
- FAIR Data, Workflows, and Research / REMBI - Recommended Metadata for Biological Images – metadata guidelines for bioimaging data 🧐
- FAIR Data, Workflows, and Research / Data Registration 🧐
- Single Cell / Converting NCBI Data to the AnnData Format 🧐
- Single Cell / Clustering 3K PBMCs with Scanpy 🧐
- Single Cell / Inferring single cell trajectories with Scanpy 🧐
- Single Cell / Analysis of plant scRNA-Seq Data with Scanpy 🧐
- Single Cell / Comparing inferred cell compositions using MuSiC deconvolution 🧐
- Single Cell / Pre-processing of 10X Single-Cell RNA Datasets 🧐
- Single Cell / Importing files from public atlases 🧐
- Single Cell / Evaluating Reference Data for Bulk RNA Deconvolution 🧐
- Single Cell / Understanding Barcodes 🧐
- Single Cell / Removing the effects of the cell cycle 🧐
- Single Cell / Single-cell quality control with scater 🧐
- Single Cell / Downstream Single-cell RNA analysis with RaceID 🧐
- Single Cell / Combining single cell datasets after pre-processing 🧐
- Single Cell / Filter, plot, and explore single cell RNA-seq data with Seurat 🧐
- Single Cell / Filter, plot and explore single-cell RNA-seq data with Scanpy (Python) 🧐
- Single Cell / Inferring single cell trajectories with Monocle3 🧐
- Single Cell / GO Enrichment Analysis on Single-Cell RNA-Seq Data 📝 🧐
- Single Cell / Converting between common single cell data formats 🧐
- Single Cell / Pre-processing of 10X Single-Cell ATAC-seq Datasets 🧐
- Single Cell / Bulk RNA Deconvolution with MuSiC 🧐
- Single Cell / Inferring single cell trajectories with Scanpy (Python) 🧐
- Single Cell / Inferring single cell trajectories with Monocle3 (R) 🧐
- Single Cell / Clustering 3K PBMCs with Seurat 🧐
- Single Cell / Filter, plot, and explore single cell RNA-seq data with Seurat (R) 🧐
- Single Cell / Scanpy Parameter Iterator 🧐
- Single Cell / Generating a single cell matrix using Alevin 🧐
- Single Cell / Filter, plot and explore single-cell RNA-seq data with Scanpy 🧐
- Single Cell / Pre-processing of Single-Cell RNA Data 🧐
- Single Cell / Generating a single cell matrix using Alevin and combining datasets (bash + R) 🧐
- Single Cell / Pseudobulk Analysis with Decoupler and EdgeR 🧐
- Single Cell / Single-cell ATAC-seq standard processing with SnapATAC2 📝 🧐
- Teaching and Hosting Galaxy training / Set up a Galaxy for Training 🧐
- Teaching and Hosting Galaxy training / Assessment and feedback in training and teachings 🧐
- Teaching and Hosting Galaxy training / Hybrid training 🧐
- Teaching and Hosting Galaxy training / Motivation and Demotivation 🧐
- Teaching and Hosting Galaxy training / Teaching online 🧐
- Teaching and Hosting Galaxy training / Training Infrastructure as a Service 🧐
- Teaching and Hosting Galaxy training / Organizing a workshop 🧐
- Teaching and Hosting Galaxy training / Running a workshop as an instructor ✍️ 🧐
- Teaching and Hosting Galaxy training / Training techniques to enhance learner participation and engagement 🧐
- Teaching and Hosting Galaxy training / Galaxy Admin Training 🧐
- Using Galaxy and Managing your Data / Group tags for complex experimental designs 🧐
- Using Galaxy and Managing your Data / Getting started with Onedata distributed storage 🧐
- Using Galaxy and Managing your Data / Use Jupyter notebooks in Galaxy 🧐
- Using Galaxy and Managing your Data / Downloading and Deleting Data in Galaxy 🧐
- Using Galaxy and Managing your Data / Onedata user-owned storage 🧐
- Using Galaxy and Managing your Data / Annotate, prepare tests and publish Galaxy workflows in workflow registries 🧐
- Using Galaxy and Managing your Data / Creating, Editing and Importing Galaxy Workflows 🧐
- Using Galaxy and Managing your Data / Understanding Galaxy history system 📝 🧐
- Using Galaxy and Managing your Data / RStudio in Galaxy 🧐
- Using Galaxy and Managing your Data / Creating high resolution images of Galaxy Workflows 🧐
- Using Galaxy and Managing your Data / Exporting to Onedata remote 🧐
- Using Galaxy and Managing your Data / JupyterLab in Galaxy 🧐
- Using Galaxy and Managing your Data / Submitting sequence data to ENA 🧐
- Using Galaxy and Managing your Data / Name tags for following complex histories 🧐
- Using Galaxy and Managing your Data / Importing (uploading) data from Onedata 🧐
- Using Galaxy and Managing your Data / Automating Galaxy workflows using the command line 🧐
- Using Galaxy and Managing your Data / Using dataset collections 🧐
- Using Galaxy and Managing your Data / Extracting Workflows from Histories 🧐
- Using Galaxy and Managing your Data / Using Workflow Parameters 🧐
- Using Galaxy and Managing your Data / SRA Aligned Read Format to Speed Up SARS-CoV-2 data Analysis 🧐
- Using Galaxy and Managing your Data / Rule Based Uploader: Advanced 🧐
- Variant Analysis / Avian influenza viral strain analysis from gene segment sequencing data 🧐
- Variant Analysis / Somatic Variant Discovery from WES Data Using Control-FREEC 🧐
- Variant Analysis / Exome sequencing data analysis for diagnosing a genetic disease ✍️ 🧐
- Variant Analysis / From NCBI's Sequence Read Archive (SRA) to Galaxy: SARS-CoV-2 variant analysis 🧐
- Variant Analysis / Calling variants in diploid systems 🧐
- Variant Analysis / Microbial Variant Calling 🧐
- Variant Analysis / Calling very rare variants 🧐
- Variant Analysis / Mapping and molecular identification of phenotype-causing mutations 🧐
- Variant Analysis / Calling variants in non-diploid systems 🧐
- Variant Analysis / M. tuberculosis Variant Analysis 🧐
- Variant Analysis / Deciphering Virus Populations - Single Nucleotide Variants (SNVs) and Specificities in Baculovirus Isolates 🧐
- Variant Analysis / Trio Analysis using Synthetic Datasets from RD-Connect GPAP 🧐
- Variant Analysis / Identification of somatic and germline variants from tumor and normal sample pairs 🧐
- Variant Analysis / Mutation calling, viral genome reconstruction and lineage/clade assignment from SARS-CoV-2 sequencing data 🧐
- Galaxy Community Building / Creation of the labs in the different Galaxy instances for your community 🧐
- Galaxy Community Building / Creation of resources listing all the tools and their metadata relevant to your community 🧐
- Galaxy Community Building / Make your tools available on your subdomain 🧐
- Digital Humanities / Text-Mining Differences in Chinese Newspaper Articles 🧐
- Digital Humanities / Introduction to Digital Humanities in Galaxy 🧐
- Proteomics / MaxQuant and MSstats for the analysis of TMT data 🧐
- Proteomics / Label-free versus Labelled - How to Choose Your Quantitation Method ✍️ 🧐
- Proteomics / Proteogenomics 3: Novel peptide analysis 🧐
- Proteomics / Label-free data analysis using MaxQuant 🧐
- Proteomics / Statistical analysis of DIA data 🧐
- Proteomics / Multiomics data analysis using MultiGSEA 🧐
- Proteomics / Mass spectrometry imaging: Loading and exploring MSI data ✍️ 🧐
- Proteomics / metaQuantome 2: Function 🧐
- Proteomics / metaQuantome 1: Data creation 🧐
- Proteomics / Annotating a protein list identified by LC-MS/MS experiments 🧐
- Proteomics / Clinical Metaproteomics 4: Quantitation 🧐
- Proteomics / Metaproteomics tutorial 🧐
- Proteomics / Peptide Library Data Analysis 🧐
- Proteomics / Clinical Metaproteomics 2: Discovery 🧐
- Proteomics / Clinical Metaproteomics 3: Verification 🧐
- Proteomics / Peptide and Protein ID using OpenMS tools ✍️ 🧐
- Proteomics / Secretome Prediction ✍️ 🧐
- Proteomics / Peptide and Protein Quantification via Stable Isotope Labelling (SIL) ✍️ 🧐
- Proteomics / Proteogenomics 2: Database Search 🧐
- Proteomics / Protein FASTA Database Handling ✍️ 🧐
- Proteomics / Proteogenomics 1: Database Creation 🧐
- Proteomics / EncyclopeDIA 🧐
- Proteomics / Detection and quantitation of N-termini (degradomics) via N-TAILS ✍️ 🧐
- Proteomics / DIA Analysis using OpenSwathWorkflow 🧐
- Proteomics / Clinical Metaproteomics 5: Data Interpretation 🧐
- Proteomics / Machine Learning Modeling of Anticancer Peptides 🧐
- Proteomics / Peptide and Protein ID using SearchGUI and PeptideShaker ✍️ 🧐
- Proteomics / MaxQuant and MSstats for the analysis of label-free data 🧐
- Proteomics / metaQuantome 3: Taxonomy 🧐
- Proteomics / Library Generation for DIA Analysis 🧐
- Proteomics / Clinical Metaproteomics 1: Database-Generation 🧐
- Metabolomics / Mass spectrometry imaging: Finding differential analytes 🧐
- Metabolomics / Mass spectrometry imaging: Examining the spatial distribution of analytes 🧐
- Metabolomics / Mass spectrometry: LC-MS preprocessing with XCMS 🧐
- Metabolomics / Mass spectrometry: GC-MS data processing (with XCMS, RAMClustR, RIAssigner, and matchms) 🧐
- Metabolomics / Mass spectrometry: LC-MS analysis 🧐
- Visualisation / Visualisation with Circos 🧐
- Visualisation / Genomic Data Visualisation with JBrowse 🧐
- Visualisation / Ploting a Microbial Genome with Circos 🧐
- Climate / Ocean's variables study 🧐
- Climate / Analyse Argo data 🧐
- Climate / Functionally Assembled Terrestrial Ecosystem Simulator (FATES) with Galaxy Climate JupyterLab 🧐
- Climate / Visualize Climate data with Panoply netCDF viewer 🧐
- Climate / Getting your hands-on climate data 🧐
- Climate / Collaboration with JupyterGIS 🧐
- Climate / Ocean Data View (ODV) 🧐
- Climate / Nitrate DMQC for autonomous platforms such as Argo floats 🧐
- Climate / Functionally Assembled Terrestrial Ecosystem Simulator (FATES) 🧐
- Materials Science / Finding the muon stopping site with pymuon-suite in Galaxy 🧐
- Evolution / Tree thinking for tuberculosis evolution and epidemiology 🧐
- Evolution / Identifying tuberculosis transmission links: from SNPs to transmission clusters 🧐
- Introduction to Galaxy Analyses / How to reproduce published Galaxy analyses 🧐
- Introduction to Galaxy Analyses / IGV Introduction 🧐
- Introduction to Galaxy Analyses / NGS data logistics 🧐
- Introduction to Galaxy Analyses / Galaxy Basics for everyone 🧐
- Introduction to Galaxy Analyses / From peaks to genes ✍️ 🧐
- Introduction to Galaxy Analyses / Galaxy Basics for genomics ✍️ 🧐
- Introduction to Galaxy Analyses / Introduction to Genomics and Galaxy 🧐
- Introduction to Galaxy Analyses / Data Manipulation Olympics 🧐
- Introduction to Galaxy Analyses / A short introduction to Galaxy 🧐
- Computational chemistry / Running molecular dynamics simulations using NAMD 🧐
- Computational chemistry / Running molecular dynamics simulations using GROMACS 🧐
- Computational chemistry / Virtual screening of the SARS-CoV-2 main protease with rxDock and pose scoring 🧐
- Computational chemistry / Analysis of molecular dynamics simulations 🧐
- Computational chemistry / High Throughput Molecular Dynamics and Analysis ✍️ 🧐
- Computational chemistry / Setting up molecular systems 🧐
- Computational chemistry / Protein-ligand docking 🧐
- Foundations of Data Science / Introduction to sequencing with Python (part four) 🧐
- Foundations of Data Science / Versioning your code and data with git 🧐
- Foundations of Data Science / Introduction to sequencing with Python (part one) 🧐
- Foundations of Data Science / Data manipulation with Pandas 🧐
- Foundations of Data Science / Introduction to sequencing with Python (part three) 🧐
- Foundations of Data Science / A (very) brief history of genomics 🧐
- Foundations of Data Science / SQL Educational Game - Murder Mystery 🧐
- Foundations of Data Science / Make & Snakemake 🧐
- Foundations of Data Science / Introduction to sequencing with Python (part two) 🧐
- Sequence analysis / NCBI BLAST+ against the MAdLand 🧐
- Sequence analysis / Mapping 🧐
- Sequence analysis / Quality Control 🧐
- Sequence analysis / Quality and contamination control in bacterial isolate using Illumina MiSeq Data 🧐
- Statistics and machine learning / Age prediction using machine learning 🧐
- Statistics and machine learning / Predicting Mutation Impact with Zero-shot Learning using a pretrained DNA LLM 🧐
- Statistics and machine learning / Machine learning: classification and regression 🧐
- Statistics and machine learning / Unsupervised Analysis of Bone Marrow Cells with Flexynesis ✍️ 🧐
- Statistics and machine learning / Identifing Survival Markers of Brain tumor with Flexynesis ✍️ 🧐
- Statistics and machine learning / A Docker-based interactive Jupyterlab powered by GPU for artificial intelligence in Galaxy 🧐
- Statistics and machine learning / Modeling Breast Cancer Subtypes with Flexynesis ✍️ 🧐
- Statistics and machine learning / Supervised Learning with Hyperdimensional Computing 🧐
- Statistics and machine learning / Prepare Data from CbioPortal for Flexynesis Integration ✍️ 🧐
- Statistics and machine learning / Optimizing DNA Sequences for Biological Functions using a DNA LLM 🧐
- Statistics and machine learning / Regression in Machine Learning 🧐
- Statistics and machine learning / Introduction to deep learning 🧐
- Statistics and machine learning / Interval-Wise Testing for omics data 🧐
- Statistics and machine learning / Galaxy Tabular Learner - Building a Model using Chowell clinical data 🧐
- Statistics and machine learning / Fine tune large protein model (ProtTrans) using HuggingFace 🧐
- Statistics and machine learning / Introduction to Machine Learning using R 🧐
- Statistics and machine learning / Basics of machine learning 🧐
- Statistics and machine learning / Classification in Machine Learning 🧐
- Statistics and machine learning / Text-mining with the SimText toolset 🧐
- Statistics and machine learning / Deep Learning (Part 3) - Convolutional neural networks (CNN) 🧐
- Statistics and machine learning / Fine-tuning a LLM for DNA Sequence Classification 🧐
- Statistics and machine learning / Pretraining a Large Language Model (LLM) from Scratch on DNA Sequences 🧐
- Statistics and machine learning / Clustering in Machine Learning 🧐
- Statistics and machine learning / Generating Artificial Yeast DNA Sequences using a DNA LLM 🧐
- Transcriptomics / 3: RNA-seq genes to pathways 🧐
- Transcriptomics / 1: RNA-Seq reads to counts 🧐
- Transcriptomics / Visualization of RNA-Seq results with Volcano Plot 🧐
- Transcriptomics / De novo transcriptome assembly, annotation, and differential expression analysis 🧐
- Transcriptomics / De novo transcriptome reconstruction with RNA-Seq 🧐
- Transcriptomics / Visualization of RNA-Seq results with heatmap2 🧐
- Transcriptomics / Pathway analysis with the MINERVA Platform 🖥 🧐
- Transcriptomics / Reference-based RNAseq data analysis (long) 🧐
- Transcriptomics / RNA-Seq analysis with AskOmics Interactive Tool 🧐
- Transcriptomics / 2: RNA-seq counts to genes 🧐
- Transcriptomics / Differential abundance testing of small RNAs 🧐
- Transcriptomics / RNA Seq Counts to Viz in R 🧐
- Transcriptomics / CLIP-Seq data analysis from pre-processing to motif detection 🧐
- Transcriptomics / RNA-RNA interactome data analysis 🧐
- Transcriptomics / GO Enrichment Analysis 🧐
- Transcriptomics / Whole transcriptome analysis of Arabidopsis thaliana 🧐
- Transcriptomics / Reference-based RNA-Seq data analysis 🧐
- Transcriptomics / Genome-wide alternative splicing analysis 🧐
- Imaging / Parameter tuning and optimization - Evaluating nuclei segmentation with Galaxy 🧐
- Imaging / Introduction to Image Analysis using Galaxy 🧐
- Imaging / Quantification of electrophoresis gel bands using QuPath and Galaxy imaging tools 🧐
- Imaging / Nucleoli segmentation and feature extraction using CellProfiler 🧐
- Imaging / End-to-End Tissue Microarray Image Analysis with Galaxy-ME 🧐
- Imaging / Overview of the Galaxy OMERO-suite - Upload images and metadata in OMERO using Galaxy 📝 🧐
- Imaging / Voronoi segmentation 🧐
- Imaging / Tracking of mitochondria and capturing mitoflashes 🧐
- Imaging / Using BioImage.IO models for image analysis in Galaxy 🧐
- Imaging / Quantification of single-molecule RNA fluorescence in situ hybridization (smFISH) in yeast cell lines 🧐
- Imaging / Training Custom YOLO Models for Segmentation of Bioimages 🧐
- Imaging / Analyse HeLa fluorescence siRNA screen 🧐
- Imaging / Object tracking using CellProfiler 🧐
- Assembly / Decontamination of a genome assembly 🧐
- Assembly / Unicycler assembly of SARS-CoV-2 genome with preprocessing to remove human genome reads 🧐
- Assembly / De Bruijn Graph Assembly 🧐
- Assembly / Assembly of the mitochondrial genome from PacBio HiFi reads 🧐
- Assembly / Using the VGP workflows to assemble a vertebrate genome with HiFi and Hi-C data 🧐
- Assembly / Genome Assembly of a bacterial genome (MRSA) sequenced using Illumina MiSeq Data 🧐
- Assembly / Chloroplast genome assembly 🧐
- Assembly / Genome assembly using PacBio data 🧐
- Assembly / Unicycler Assembly 🧐
- Assembly / Genome Assembly Quality Control 🧐
- Assembly / ERGA post-assembly QC 🧐
- Assembly / Vertebrate genome assembly using HiFi, Bionano and Hi-C data - Step by Step 🧐
- Assembly / Making sense of a newly assembled genome 🧐
- Assembly / Genome Assembly of MRSA from Oxford Nanopore MinION data (and optionally Illumina data) 🧐
- Assembly / An Introduction to Genome Assembly 🧐
- Ecology / Life Traits Ecoregionalization workflow 🧐
- Ecology / From NDVI data with OpenEO to time series visualisation with Holoviews 🧐
- Ecology / Creating metadata using Ecological Metadata Language (EML) standard with EML Assembly Line functionalities 🧐
- Ecology / Champs blocs indicators 🧐
- Ecology / QGIS Web Feature Services 🧐
- Ecology / Obis marine indicators 🧐
- Ecology / Creating FAIR Quality assessment reports and draft of Data Papers from EML metadata with MetaShRIMPS 🧐
- Ecology / RAD-Seq de-novo data analysis 🧐
- Ecology / Sentinel 2 biodiversity 🧐
- Ecology / Marine Omics identifying biosynthetic gene clusters 🧐
- Ecology / Compute and analyze biodiversity metrics with PAMPA toolsuite 🧐
- Ecology / RAD-Seq Reference-based data analysis 🧐
- Ecology / RAD-Seq to construct genetic maps 🧐
- Ecology / Cleaning GBIF data using OpenRefine 🧐
- Ecology / Ecoregionalization workflow tutorial 🧐
- Ecology / Regional GAM 🧐
- Contributing to the Galaxy Training Material / Creating a new tutorial 🧐
- Contributing to the Galaxy Training Material / Including a new topic 🧐
- Contributing to the Galaxy Training Material / Contributing to the Galaxy Training Network with GitHub 🧐
- Contributing to the Galaxy Training Material / Adding Quizzes to your Tutorial 🧐
- Contributing to the Galaxy Training Material / Creating content in Markdown 📝 🧐
- Contributing to the Galaxy Training Material / Tools, Data, and Workflows for tutorials ✍️ 🧐
- Contributing to the Galaxy Training Material / FAIR-by-Design methodology 🧐
- Contributing to the Galaxy Training Material / Creating Interactive Galaxy Tours ✍️ 🧐
- Contributing to the Galaxy Training Material / GTN Metadata 🧐
- Contributing to the Galaxy Training Material / Updating diffs in admin training 🧐
- Contributing to the Galaxy Training Material / Adding auto-generated video to your slides 🧐
- Contributing to the Galaxy Training Material / Preview the GTN website as you edit your training material ✍️ 🧐
- Contributing to the Galaxy Training Material / Principles of learning and how they apply to training and teaching 🧐
- Contributing to the Galaxy Training Material / Design and plan session, course, materials 🧐
- Contributing to the Galaxy Training Material / Teaching Python 🧐
- Contributing to the Galaxy Training Material / Contributing with GitHub via its interface 🧐
- Genome Annotation / Masking repeats with RepeatMasker 🧐
- Genome Annotation / Refining Genome Annotations with Apollo (prokaryotes) 🧐
- Genome Annotation / Genome annotation with Maker 🧐
- Genome Annotation / Long non-coding RNAs (lncRNAs) annotation with FEELnc 🧐
- Genome Annotation / CRISPR screen analysis 🧐
- Genome Annotation / Genome annotation with Helixer 🧐
- Genome Annotation / Genome annotation with Maker (short) 🧐
- Genome Annotation / Bacterial Genome Annotation 🧐
- Genome Annotation / Genome annotation with Funannotate 🧐
- Genome Annotation / Refining Genome Annotations with Apollo (eukaryotes) 🧐
- Genome Annotation / Functional annotation of protein sequences 🧐
- Genome Annotation / Identification of AMR genes in an assembled bacterial genome 🧐
- Genome Annotation / Comparison of two annotation tools - Helixer and Braker3 🧐
- Genome Annotation / Genome Annotation ✍️ 🧐
- Genome Annotation / Essential genes detection with Transposon insertion sequencing 🧐
- Genome Annotation / Genome annotation with Prokka 🧐
- Galaxy Server administration / Data Libraries 🧐
- Galaxy Server administration / Create a subdomain for your community on UseGalaxy.eu 🧐
- Galaxy Server administration / Deploying a compute cluster in OpenStack via Terraform 🧐
- Galaxy Server administration / Galaxy Database schema ✍️ 🧐
- Galaxy Server administration / Configuring the Onedata connectors (remotes, Object Store, BYOS, BYOD) 🧐
- Galaxy Server administration / Galaxy usage on SURF Research Cloud 🧐
- Galaxy Server administration / Galaxy Monitoring with Telegraf and Grafana 🧐
- Galaxy Server administration / Connecting Galaxy to a compute cluster ✍️ 🧐
- Galaxy Server administration / Distributed Object Storage 🧐
- Galaxy Server administration / Galaxy Tool Management with Ephemeris 🧐
- Galaxy Server administration / Reference Data with CVMFS 🧐
- Galaxy Server administration / Galaxy Monitoring with Reports ✍️ 🧐
- Galaxy Server administration / Galaxy Interactive Tools 🧐
- Galaxy Server administration / Setting up Celery Workers for Galaxy 🧐
- Galaxy Server administration / Galaxy Installation on Kubernetes 🧐
- Galaxy Server administration / Training Infrastructure as a Service (TIaaS) 🧐
- Galaxy Server administration / Use Apptainer containers for running Galaxy jobs 🧐
- Galaxy Server administration / Customizing the look of Galaxy 🧐
- Galaxy Server administration / Mapping Jobs to Destinations using TPV ✍️ 🧐
- Galaxy Server administration / Reference Data with CVMFS without Ansible 🧐
- Galaxy Server administration / Ansible 🧐
- Galaxy Server administration / Upgrading Galaxy 🧐
- Galaxy Server administration / Galaxy Monitoring with gxadmin 🧐
- Galaxy Server administration / Automation with Jenkins 🧐
- Galaxy Server administration / Galaxy Installation with Ansible 🧐
- Galaxy Server administration / Customizing the look of Galaxy (Manual) 🧐
- Galaxy Server administration / Running Jobs on Remote Resources with Pulsar 🧐
- Galaxy Server administration / External Authentication 🧐
- Galaxy Server administration / Adding file-sources to Galaxy 🧐
- Galaxy Server administration / Managing Galaxy on Kubernetes 🧐
- Epigenetics / CUT&RUN data analysis 🧐
- Epigenetics / Infinium Human Methylation BeadChip 🧐
- Epigenetics / Identification of the binding sites of the Estrogen receptor 🧐
- Epigenetics / ATAC-Seq data analysis 🧐
- Epigenetics / Identification of the binding sites of the T-cell acute lymphocytic leukemia protein 1 (TAL1) 🧐
- Epigenetics / Formation of the Super-Structures on the Inactive X 🧐
- Epigenetics / Hi-C analysis of Drosophila melanogaster cells using HiCExplorer 🧐
- Epigenetics / DNA Methylation data analysis 🧐
- Microbiome / Metatranscriptomics analysis using microbiome RNA-seq data (short) 🧐
- Microbiome / Calculating α and β diversity from microbiome taxonomic data 🧐
- Microbiome / Assembly of metagenomic sequencing data 🧐
- Microbiome / Pathogen detection from (direct Nanopore) sequencing data using Galaxy - Foodborne Edition 🧐
- Microbiome / 16S Microbial analysis with Nanopore data 🧐
- Microbiome / 16S Microbial Analysis with mothur (extended) 🧐
- Microbiome / Metatranscriptomics analysis using microbiome RNA-seq data 🧐
- Microbiome / Analyses of metagenomics data - The global picture 🧐
- Microbiome / Query an annotated mobile genetic element database to identify and annotate genetic elements (e.g. plasmids) in metagenomics data 🧐
- Microbiome / Antibiotic resistance detection 🧐
- Introduction to Galaxy Analyses / Von Peaks zu Genen ✍️
- Introduction to Galaxy Analyses / De picos a genes ✍️
- Introduction to Galaxy Analyses / Dai picchi ai geni ✍️
Slides
- Development in Galaxy / Galaxy from a developer point of view 🧐
- Materials Science / Introduction to Muon Spectroscopy 🧐
- Development in Galaxy / Generic plugins 🧐
- Development in Galaxy / Tool Shed: sharing Galaxy tools 🧐
- Development in Galaxy / Tool Dependencies and Containers ✍️ 🧐
- Development in Galaxy / Architecture 01 - Galaxy Ecosystem and Projects
- Development in Galaxy / Tool development and integration into Galaxy ✍️ 🧐
- Development in Galaxy / Galaxy Interactive Environments ✍️ 🧐
- Development in Galaxy / Galaxy Interactive Tours ✍️ 🧐
- Development in Galaxy / Tool Dependencies and Conda ✍️ 🧐
- Development in Galaxy / Visualizations: JavaScript Plugins ✍️ 🧐
- Development in Galaxy / Scripting Galaxy using the API and BioBlend 🧐
- Development in Galaxy / Galaxy Webhooks ✍️ 🧐
- Development in Galaxy / Prerequisites for building software/conda packages 🧐
- Single Cell / Clustering 3K PBMCs with Scanpy 🧐
- Single Cell / Plates, Batches, and Barcodes 🧐
- Single Cell / An introduction to scRNA-seq data analysis 🧐
- Single Cell / GO Enrichment Analysis on Single-Cell RNA-Seq Data 🧐
- Single Cell / Trajectory analysis 🧐
- Single Cell / Single-cell Formats and Resources 🧐
- Single Cell / Automated Cell Annotation 🧐
- Single Cell / Dealing with Cross-Contamination in Fixed Barcode Protocols 🧐
- Teaching and Hosting Galaxy training / Overview of the Galaxy Training Material for Instructors 🧐
- Using Galaxy and Managing your Data / Galaxy workflows in Dockstore 🧐
- Using Galaxy and Managing your Data / Submitting SARS-CoV-2 sequences to ENA 🧐
- Variant Analysis / Introduction to Variant analysis 🧐
- Proteomics / Introduction to proteomics, protein identification, quantification and statistical modelling 🧐
- Metabolomics / Mass spectrometry: LC-MS preprocessing - advanced 🧐
- Visualisation / Visualisations in Galaxy 🧐
- Visualisation / Circos 🧐
- Visualisation / JBrowse 🧐
- Climate / Functionally Assembled Terrestrial Ecosystem Simulator (FATES) 🧐
- Introduction to Galaxy Analyses / Introduction to Galaxy 🧐
- Introduction to Galaxy Analyses / Options for using Galaxy 🧐
- Introduction to Galaxy Analyses / A Short Introduction to Galaxy 🧐
- Sequence analysis / Mapping 🧐
- Sequence analysis / Quality Control 🧐
- Statistics and machine learning / Regression in Machine Learning 🧐
- Statistics and machine learning / Fine-tuning Protein Language Model 🧐
- Statistics and machine learning / Introduction to Machine learning 🧐
- Statistics and machine learning / Classification in Machine Learning 🧐
- Statistics and machine learning / Convolutional neural networks (CNN) Deep Learning - Part 3 🧐
- Transcriptomics / Introduction to Transcriptomics 🧐
- Transcriptomics / Identification of non-canonical ORFs and their potential biological function 🧐
-
Imaging
/
Nucleoli Segmentation
&
Feature Extraction
using CellProfiler 🧐 - Assembly / Unicycler assembly of SARS-CoV-2 genome with preprocessing to remove human genome reads 🧐
- Assembly / Genome assembly and assembly QC - Introduction short version 🧐
- Assembly / Unicycler Assembly 🧐
- Contributing to the Galaxy Training Material / Contributing with GitHub via command-line 🧐
- Contributing to the Galaxy Training Material / Overview of the Galaxy Training Material 🧐
- Contributing to the Galaxy Training Material / Creating Slides 🧐
- Genome Annotation / Introduction to Genome Annotation 🧐
- Genome Annotation / Genome annotation with Prokka 🧐
- Galaxy Server administration / uWSGI 🧐
- Galaxy Server administration / Galaxy on the Cloud 🧐
- Galaxy Server administration / Terraform 🧐
- Galaxy Server administration / Galaxy Monitoring with Telegraf and Grafana ✍️ 🧐
- Galaxy Server administration / Connecting Galaxy to a compute cluster ✍️ 🧐
- Galaxy Server administration / Storage Management 🧐
- Galaxy Server administration / Galaxy Monitoring ✍️ 🧐
- Galaxy Server administration / Galaxy Tool Management with Ephemeris 🧐
- Galaxy Server administration / Galaxy from an administrator's point of view ✍️ 🧐
- Galaxy Server administration / Reference Genomes in Galaxy 🧐
- Galaxy Server administration / Reference Data with CVMFS 🧐
- Galaxy Server administration / Galaxy Interactive Tools 🧐
- Galaxy Server administration / Empathy 🧐
- Galaxy Server administration / User, Role, Group, Quota, and Authentication managment ✍️ 🧐
- Galaxy Server administration / Galaxy Troubleshooting 🧐
- Galaxy Server administration / Ansible 🧐
- Galaxy Server administration / Advanced customisation of a Galaxy instance ✍️ 🧐
- Galaxy Server administration / Gearing towards production 🧐
- Galaxy Server administration / Server: Other ✍️ 🧐
- Galaxy Server administration / Galaxy Monitoring with gxadmin ✍️ 🧐
- Galaxy Server administration / Docker and Galaxy ✍️ 🧐
- Galaxy Server administration / Galactic Database 🧐
- Galaxy Server administration / Server Maintenance: Cleanup, Backup, and Restoration ✍️ 🧐
- Epigenetics / EWAS Epigenome-Wide Association Studies Introduction 🧐
- Epigenetics / Introduction to ChIP-Seq data analysis 🧐
- Epigenetics / Introduction to DNA Methylation data analysis 🧐
- Epigenetics / ChIP-seq data analysis 🧐
- Microbiome / Introduction to Microbiome Analysis 🧐
- Microbiome / Introduction to metatranscriptomics 🧐
- Single Cell / Introducción al análisis de datos de scRNA-seq 🧐
- Single Cell / Una introducción al análisis de datos scRNA-seq 🧐
FAQs
Events
- 2023 Galaxy Admin Training (Ghent) 🎪
- Galaxy Training Academy 2025 🧑🏫
- A Galaxy Introduction for Everyone 🧑🏫
- 2025 Galaxy Admin Training (Brno) 🧑🏫
- Workshop on high-throughput sequencing data analysis with Galaxy 🧑🏫
- Galaxy Training Academy 2026 🧑🏫
- Galaxy Training Academy 2024 🧑🏫
GitHub Activity
github Issues Reported
75 Merged Pull Requests
See all of the github Pull Requests and github Commits by Björn Grüning.
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dekcd has two entries
template-and-tools -
add links into the bio
template-and-tools -
Update ORGANISATIONS.yaml with a few BIOs
template-and-tools -
add nfdi4boimage and de.NBI to the funding
imaging -
try migrating labeller to new version
Reviewed 1106 PRs
We love our community reviewing each other's work!
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Add new contributor Niklas Mayle to CONTRIBUTORS.yaml
template-and-tools -
Update outdated parts of genomics intro and add a sort step
introductionGTA -
Updating broken data link in "Getting your hands-on climate data" tutorial
climate -
reduce size of image to prevent page loading problems
microbiome -
fix: update Zenodo links to direct file links
imaging
News
4th Mycobacterium tuberculosis complex NGS made easy
8 July 2024
Tuberculosis (TB) is a big killer in many countries of the world, particularly in those with low and middle income. Next-generation sequencing has been key in improving our understanding of drug resistance acquisition and of transmission of Mycobacterium tuberculosis. Yet, the need for expertise guiding NGS implementation in laboratories and the lack of bioinformatic expertise, are main obstacles hindering the implementation of NGS into TB programs.
GTN is now integrated with WorkflowHub
2 September 2025
Thanks to a collaborative effort between the teams at Galaxy Training Network (GTN), WorkflowHub, and Australian BioCommons, GTN workflows are now registered automatically with WorkflowHub. The existing set of workflows can be viewed here: GTN on WorkflowHub. For every new tutorial that is added to the GTN, any workflows that it contains will now also be pushed to WorkflowHub.
GTN is now integrated with WorkflowHub
2 September 2025
Thanks to a collaborative effort between the teams at Galaxy Training Network (GTN), WorkflowHub, and Australian BioCommons, GTN workflows are now registered automatically with WorkflowHub. The existing set of workflows can be viewed here: GTN on WorkflowHub. For every new tutorial that is added to the GTN, any workflows that it contains will now also be pushed to WorkflowHub.
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