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
- Genome Annotation / Genome Annotation ✍️ 🧐
- Genome Annotation / Bacterial Genome Annotation 🧐
- Genome Annotation / CRISPR screen analysis 🧐
- Genome Annotation / Essential genes detection with Transposon insertion sequencing 🧐
- Genome Annotation / Genome annotation with Prokka 🧐
- Genome Annotation / Masking repeats with RepeatMasker 🧐
- Genome Annotation / Refining Genome Annotations with Apollo (eukaryotes) 🧐
- Genome Annotation / Genome annotation with Helixer 🧐
- Genome Annotation / Genome annotation with Funannotate 🧐
- Genome Annotation / Long non-coding RNAs (lncRNAs) annotation with FEELnc 🧐
- Genome Annotation / Genome annotation with Maker (short) 🧐
- Genome Annotation / Comparison of two annotation tools - Helixer and Braker3 🧐
- Genome Annotation / Genome annotation with Maker 🧐
- Genome Annotation / Refining Genome Annotations with Apollo (prokaryotes) 🧐
- Genome Annotation / Identification of AMR genes in an assembled bacterial genome 🧐
- Genome Annotation / Functional annotation of protein sequences 🧐
- 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 / NGS data logistics 🧐
- Introduction to Galaxy Analyses / Introduction to Genomics and Galaxy 🧐
- Introduction to Galaxy Analyses / Galaxy Basics for everyone 🧐
- Introduction to Galaxy Analyses / Data Manipulation Olympics 🧐
- Introduction to Galaxy Analyses / A short introduction to Galaxy 🧐
- Introduction to Galaxy Analyses / IGV Introduction 🧐
- Introduction to Galaxy Analyses / From peaks to genes ✍️ 🧐
- Introduction to Galaxy Analyses / Galaxy Basics for genomics ✍️ 🧐
- Microbiome / Calculating α and β diversity from microbiome taxonomic data 🧐
- Microbiome / Pathogen detection from (direct Nanopore) sequencing data using Galaxy - Foodborne Edition 🧐
- Microbiome / 16S Microbial analysis with Nanopore data 🧐
- Microbiome / Antibiotic resistance detection 🧐
- Microbiome / Query an annotated mobile genetic element database to identify and annotate genetic elements (e.g. plasmids) in metagenomics data 🧐
- Microbiome / Analyses of metagenomics data - The global picture 🧐
- Microbiome / Assembly of metagenomic sequencing data 🧐
- Microbiome / Metatranscriptomics analysis using microbiome RNA-seq data 🧐
- Microbiome / 16S Microbial Analysis with mothur (extended) 🧐
- Microbiome / Metatranscriptomics analysis using microbiome RNA-seq data (short) 🧐
- Teaching and Hosting Galaxy training / Training techniques to enhance learner participation and engagement 🧐
- Teaching and Hosting Galaxy training / Set up a Galaxy for Training 🧐
- Teaching and Hosting Galaxy training / Running a workshop as an instructor ✍️ 🧐
- Teaching and Hosting Galaxy training / Motivation and Demotivation 🧐
- Teaching and Hosting Galaxy training / Organizing a workshop 🧐
- Teaching and Hosting Galaxy training / Training Infrastructure as a Service 🧐
- Teaching and Hosting Galaxy training / Assessment and feedback in training and teachings 🧐
- Teaching and Hosting Galaxy training / Hybrid training 🧐
- Teaching and Hosting Galaxy training / Galaxy Admin Training 🧐
- Teaching and Hosting Galaxy training / Teaching online 🧐
- Metabolomics / Mass spectrometry imaging: Finding differential analytes 🧐
- Metabolomics / Mass spectrometry: GC-MS data processing (with XCMS, RAMClustR, RIAssigner, and matchms) 🧐
- Metabolomics / Mass spectrometry: LC-MS analysis 🧐
- Metabolomics / Mass spectrometry imaging: Examining the spatial distribution of analytes 🧐
- Metabolomics / Mass spectrometry: LC-MS preprocessing with XCMS 🧐
- Single Cell / Generating a single cell matrix using Alevin and combining datasets (bash + R) 🧐
- Single Cell / Understanding Barcodes 🧐
- Single Cell / Importing files from public atlases 🧐
- Single Cell / Downstream Single-cell RNA analysis with RaceID 🧐
- Single Cell / Filter, plot, and explore single cell RNA-seq data with Seurat 🧐
- Single Cell / Removing the effects of the cell cycle 🧐
- Single Cell / Converting between common single cell data formats 🧐
- Single Cell / Inferring single cell trajectories with Scanpy (Python) 🧐
- Single Cell / Bulk RNA Deconvolution with MuSiC 🧐
- Single Cell / Inferring single cell trajectories with Scanpy 🧐
- Single Cell / Converting NCBI Data to the AnnData Format 🧐
- Single Cell / Comparing inferred cell compositions using MuSiC deconvolution 🧐
- Single Cell / Filter, plot and explore single-cell RNA-seq data with Scanpy 🧐
- Single Cell / Inferring single cell trajectories with Monocle3 🧐
- Single Cell / Pseudobulk Analysis with Decoupler and EdgeR 🧐
- Single Cell / Generating a single cell matrix using Alevin 🧐
- Single Cell / Clustering 3K PBMCs with Seurat 🧐
- Single Cell / Single-cell quality control with scater 🧐
- Single Cell / Pre-processing of 10X Single-Cell RNA Datasets 🧐
- Single Cell / Analysis of plant scRNA-Seq Data with Scanpy 🧐
- Single Cell / GO Enrichment Analysis on Single-Cell RNA-Seq Data 📝 🧐
- Single Cell / Single-cell ATAC-seq standard processing with SnapATAC2 📝 🧐
- Single Cell / Clustering 3K PBMCs with Scanpy 🧐
- Single Cell / Inferring single cell trajectories with Monocle3 (R) 🧐
- Single Cell / Evaluating Reference Data for Bulk RNA Deconvolution 🧐
- Single Cell / Filter, plot and explore single-cell RNA-seq data with Scanpy (Python) 🧐
- Single Cell / Scanpy Parameter Iterator 🧐
- Single Cell / Combining single cell datasets after pre-processing 🧐
- Single Cell / Pre-processing of Single-Cell RNA Data 🧐
- Single Cell / Pre-processing of 10X Single-Cell ATAC-seq Datasets 🧐
- Single Cell / Filter, plot, and explore single cell RNA-seq data with Seurat (R) 🧐
- Climate / Ocean Data View (ODV) 🧐
- Climate / Analyse Argo data 🧐
- Climate / Collaboration with JupyterGIS 🧐
- Climate / Getting your hands-on climate data 🧐
- Climate / Ocean's variables study 🧐
- Climate / Functionally Assembled Terrestrial Ecosystem Simulator (FATES) with Galaxy Climate JupyterLab 🧐
- Climate / Functionally Assembled Terrestrial Ecosystem Simulator (FATES) 🧐
- Climate / Nitrate DMQC for autonomous platforms such as Argo floats 🧐
- Climate / Visualize Climate data with Panoply netCDF viewer 🧐
- Variant Analysis / Trio Analysis using Synthetic Datasets from RD-Connect GPAP 🧐
- Variant Analysis / Exome sequencing data analysis for diagnosing a genetic disease ✍️ 🧐
- Variant Analysis / Deciphering Virus Populations - Single Nucleotide Variants (SNVs) and Specificities in Baculovirus Isolates 🧐
- Variant Analysis / Calling variants in diploid systems 🧐
- Variant Analysis / Identification of somatic and germline variants from tumor and normal sample pairs 🧐
- Variant Analysis / Somatic Variant Discovery from WES Data Using Control-FREEC 🧐
- Variant Analysis / Calling variants in non-diploid systems 🧐
- Variant Analysis / Avian influenza viral strain analysis from gene segment sequencing data 🧐
- Variant Analysis / Microbial Variant Calling 🧐
- Variant Analysis / M. tuberculosis Variant Analysis 🧐
- Variant Analysis / From NCBI's Sequence Read Archive (SRA) to Galaxy: SARS-CoV-2 variant analysis 🧐
- Variant Analysis / Calling very rare variants 🧐
- Variant Analysis / Mutation calling, viral genome reconstruction and lineage/clade assignment from SARS-CoV-2 sequencing data 🧐
- Variant Analysis / Mapping and molecular identification of phenotype-causing mutations 🧐
- Materials Science / Finding the muon stopping site with pymuon-suite in Galaxy 🧐
- Sequence analysis / Quality and contamination control in bacterial isolate using Illumina MiSeq Data 🧐
- Sequence analysis / NCBI BLAST+ against the MAdLand 🧐
- Sequence analysis / Quality Control 🧐
- Sequence analysis / Mapping 🧐
- Visualisation / Genomic Data Visualisation with JBrowse 🧐
- Visualisation / Visualisation with Circos 🧐
- Visualisation / Ploting a Microbial Genome with Circos 🧐
- Galaxy Server administration / Ansible 🧐
- Galaxy Server administration / Galaxy usage on SURF Research Cloud 🧐
- Galaxy Server administration / Galaxy Interactive Tools 🧐
- Galaxy Server administration / Reference Data with CVMFS 🧐
- Galaxy Server administration / Create a subdomain for your community on UseGalaxy.eu 🧐
- Galaxy Server administration / Galaxy Monitoring with Reports ✍️ 🧐
- Galaxy Server administration / Upgrading Galaxy 🧐
- Galaxy Server administration / Customizing the look of Galaxy (Manual) 🧐
- Galaxy Server administration / Setting up Celery Workers for Galaxy 🧐
- Galaxy Server administration / Adding file-sources to Galaxy 🧐
- Galaxy Server administration / External Authentication 🧐
- Galaxy Server administration / Mapping Jobs to Destinations using TPV ✍️ 🧐
- Galaxy Server administration / Deploying a compute cluster in OpenStack via Terraform 🧐
- Galaxy Server administration / Automation with Jenkins 🧐
- Galaxy Server administration / Managing Galaxy on Kubernetes 🧐
- Galaxy Server administration / Galaxy Tool Management with Ephemeris 🧐
- Galaxy Server administration / Reference Data with CVMFS without Ansible 🧐
- Galaxy Server administration / Galaxy Installation with Ansible 🧐
- Galaxy Server administration / Use Apptainer containers for running Galaxy jobs 🧐
- Galaxy Server administration / Galaxy Monitoring with Telegraf and Grafana 🧐
- Galaxy Server administration / Customizing the look of Galaxy 🧐
- Galaxy Server administration / Galaxy Installation on Kubernetes 🧐
- Galaxy Server administration / Data Libraries 🧐
- Galaxy Server administration / Running Jobs on Remote Resources with Pulsar 🧐
- Galaxy Server administration / Galaxy Database schema ✍️ 🧐
- Galaxy Server administration / Connecting Galaxy to a compute cluster ✍️ 🧐
- Galaxy Server administration / Galaxy Monitoring with gxadmin 🧐
- Galaxy Server administration / Distributed Object Storage 🧐
- Galaxy Server administration / Training Infrastructure as a Service (TIaaS) 🧐
- Galaxy Server administration / Configuring the Onedata connectors (remotes, Object Store, BYOS, BYOD) 🧐
- Proteomics / Machine Learning Modeling of Anticancer Peptides 🧐
- Proteomics / Clinical Metaproteomics 1: Database-Generation 🧐
- Proteomics / Label-free versus Labelled - How to Choose Your Quantitation Method ✍️ 🧐
- Proteomics / Clinical Metaproteomics 3: Verification 🧐
- Proteomics / Proteogenomics 3: Novel peptide analysis 🧐
- Proteomics / Mass spectrometry imaging: Loading and exploring MSI data ✍️ 🧐
- Proteomics / metaQuantome 1: Data creation 🧐
- Proteomics / MaxQuant and MSstats for the analysis of label-free data 🧐
- Proteomics / Secretome Prediction ✍️ 🧐
- Proteomics / metaQuantome 3: Taxonomy 🧐
- Proteomics / Clinical Metaproteomics 4: Quantitation 🧐
- Proteomics / Peptide and Protein ID using SearchGUI and PeptideShaker ✍️ 🧐
- Proteomics / EncyclopeDIA 🧐
- Proteomics / Metaproteomics tutorial 🧐
- Proteomics / Peptide and Protein Quantification via Stable Isotope Labelling (SIL) ✍️ 🧐
- Proteomics / Proteogenomics 2: Database Search 🧐
- Proteomics / Detection and quantitation of N-termini (degradomics) via N-TAILS ✍️ 🧐
- Proteomics / Library Generation for DIA Analysis 🧐
- Proteomics / MaxQuant and MSstats for the analysis of TMT data 🧐
- Proteomics / DIA Analysis using OpenSwathWorkflow 🧐
- Proteomics / Peptide and Protein ID using OpenMS tools ✍️ 🧐
- Proteomics / Annotating a protein list identified by LC-MS/MS experiments 🧐
- Proteomics / metaQuantome 2: Function 🧐
- Proteomics / Protein FASTA Database Handling ✍️ 🧐
- Proteomics / Peptide Library Data Analysis 🧐
- Proteomics / Clinical Metaproteomics 5: Data Interpretation 🧐
- Proteomics / Label-free data analysis using MaxQuant 🧐
- Proteomics / Proteogenomics 1: Database Creation 🧐
- Proteomics / Statistical analysis of DIA data 🧐
- Proteomics / Multiomics data analysis using MultiGSEA 🧐
- Proteomics / Clinical Metaproteomics 2: Discovery 🧐
- Digital Humanities / Introduction to Digital Humanities in Galaxy 🧐
- Digital Humanities / Text-Mining Differences in Chinese Newspaper Articles 🧐
- Using Galaxy and Managing your Data / JupyterLab in Galaxy 🧐
- Using Galaxy and Managing your Data / Onedata user-owned storage 🧐
- Using Galaxy and Managing your Data / Getting started with Onedata distributed storage 🧐
- Using Galaxy and Managing your Data / Submitting sequence data to ENA 🧐
- Using Galaxy and Managing your Data / Extracting Workflows from Histories 🧐
- 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 / Creating high resolution images of Galaxy Workflows 🧐
- Using Galaxy and Managing your Data / Understanding Galaxy history system 📝 🧐
- Using Galaxy and Managing your Data / Use Jupyter notebooks in Galaxy 🧐
- Using Galaxy and Managing your Data / Exporting to Onedata remote 🧐
- Using Galaxy and Managing your Data / Group tags for complex experimental designs 🧐
- Using Galaxy and Managing your Data / Using Workflow Parameters 🧐
- Using Galaxy and Managing your Data / Automating Galaxy workflows using the command line 🧐
- Using Galaxy and Managing your Data / Importing (uploading) data from Onedata 🧐
- Using Galaxy and Managing your Data / Using dataset collections 🧐
- Using Galaxy and Managing your Data / Rule Based Uploader: Advanced 🧐
- Using Galaxy and Managing your Data / Name tags for following complex histories 🧐
- Using Galaxy and Managing your Data / Downloading and Deleting Data in Galaxy 🧐
- Using Galaxy and Managing your Data / SRA Aligned Read Format to Speed Up SARS-CoV-2 data Analysis 🧐
- Using Galaxy and Managing your Data / RStudio in Galaxy 🧐
- Computational chemistry / Setting up molecular systems 🧐
- Computational chemistry / Virtual screening of the SARS-CoV-2 main protease with rxDock and pose scoring 🧐
- Computational chemistry / Protein-ligand docking 🧐
- Computational chemistry / High Throughput Molecular Dynamics and Analysis ✍️ 🧐
- Computational chemistry / Analysis of molecular dynamics simulations 🧐
- Computational chemistry / Running molecular dynamics simulations using GROMACS 🧐
- Computational chemistry / Running molecular dynamics simulations using NAMD 🧐
- Ecology / Marine Omics identifying biosynthetic gene clusters 🧐
- Ecology / Obis marine indicators 🧐
- Ecology / Cleaning GBIF data using OpenRefine 🧐
- Ecology / Ecoregionalization workflow tutorial 🧐
- Ecology / Sentinel 2 biodiversity 🧐
- Ecology / RAD-Seq to construct genetic maps 🧐
- Ecology / From NDVI data with OpenEO to time series visualisation with Holoviews 🧐
- Ecology / Compute and analyze biodiversity metrics with PAMPA toolsuite 🧐
- Ecology / Creating metadata using Ecological Metadata Language (EML) standard with EML Assembly Line functionalities 🧐
- Ecology / Regional GAM 🧐
- Ecology / Life Traits Ecoregionalization workflow 🧐
- Ecology / RAD-Seq de-novo data analysis 🧐
- Ecology / QGIS Web Feature Services 🧐
- Ecology / Creating FAIR Quality assessment reports and draft of Data Papers from EML metadata with MetaShRIMPS 🧐
- Ecology / RAD-Seq Reference-based data analysis 🧐
- Ecology / Champs blocs indicators 🧐
- Galaxy Community Building / Make your tools available on your subdomain 🧐
- Galaxy Community Building / Creation of resources listing all the tools and their metadata relevant to your community 🧐
- Galaxy Community Building / Creation of the labs in the different Galaxy instances for your community 🧐
- Foundations of Data Science / Make & Snakemake 🧐
- Foundations of Data Science / Introduction to sequencing with Python (part two) 🧐
- Foundations of Data Science / SQL Educational Game - Murder Mystery 🧐
- Foundations of Data Science / Introduction to sequencing with Python (part one) 🧐
- Foundations of Data Science / Introduction to sequencing with Python (part four) 🧐
- Foundations of Data Science / Introduction to sequencing with Python (part three) 🧐
- Foundations of Data Science / Versioning your code and data with git 🧐
- Foundations of Data Science / Data manipulation with Pandas 🧐
- Foundations of Data Science / A (very) brief history of genomics 🧐
- Imaging / Quantification of electrophoresis gel bands using QuPath and Galaxy imaging tools 🧐
- Imaging / End-to-End Tissue Microarray Image Analysis with Galaxy-ME 🧐
- Imaging / Introduction to Image Analysis using Galaxy 🧐
- Imaging / Tracking of mitochondria and capturing mitoflashes 🧐
- Imaging / Overview of the Galaxy OMERO-suite - Upload images and metadata in OMERO using Galaxy 📝 🧐
- Imaging / Object tracking using CellProfiler 🧐
- Imaging / Voronoi segmentation 🧐
- 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 / Using BioImage.IO models for image analysis in Galaxy 🧐
- Imaging / Analyse HeLa fluorescence siRNA screen 🧐
- Imaging / Nucleoli segmentation and feature extraction using CellProfiler 🧐
- Imaging / Parameter tuning and optimization - Evaluating nuclei segmentation with Galaxy 🧐
- Transcriptomics / CLIP-Seq data analysis from pre-processing to motif detection 🧐
- Transcriptomics / Whole transcriptome analysis of Arabidopsis thaliana 🧐
- Transcriptomics / Reference-based RNAseq data analysis (long) 🧐
- Transcriptomics / De novo transcriptome reconstruction with RNA-Seq 🧐
- Transcriptomics / 3: RNA-seq genes to pathways 🧐
- Transcriptomics / Differential abundance testing of small RNAs 🧐
- Transcriptomics / RNA-RNA interactome data analysis 🧐
- Transcriptomics / Reference-based RNA-Seq data analysis 🧐
- Transcriptomics / 1: RNA-Seq reads to counts 🧐
- Transcriptomics / Visualization of RNA-Seq results with heatmap2 🧐
- Transcriptomics / RNA-Seq analysis with AskOmics Interactive Tool 🧐
- Transcriptomics / Pathway analysis with the MINERVA Platform 🖥 🧐
- Transcriptomics / Genome-wide alternative splicing analysis 🧐
- Transcriptomics / 2: RNA-seq counts to genes 🧐
- Transcriptomics / Visualization of RNA-Seq results with Volcano Plot 🧐
- Transcriptomics / GO Enrichment Analysis 🧐
- Transcriptomics / RNA Seq Counts to Viz in R 🧐
- Transcriptomics / De novo transcriptome assembly, annotation, and differential expression analysis 🧐
- Epigenetics / CUT&RUN data analysis 🧐
- Epigenetics / Infinium Human Methylation BeadChip 🧐
- Epigenetics / Hi-C analysis of Drosophila melanogaster cells using HiCExplorer 🧐
- Epigenetics / Identification of the binding sites of the T-cell acute lymphocytic leukemia protein 1 (TAL1) 🧐
- Epigenetics / DNA Methylation data analysis 🧐
- Epigenetics / Formation of the Super-Structures on the Inactive X 🧐
- Epigenetics / Identification of the binding sites of the Estrogen receptor 🧐
- Epigenetics / ATAC-Seq data analysis 🧐
- Contributing to the Galaxy Training Material / Creating Interactive Galaxy Tours ✍️ 🧐
- Contributing to the Galaxy Training Material / Teaching Python 🧐
- Contributing to the Galaxy Training Material / FAIR-by-Design methodology 🧐
- 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 / Creating a new tutorial 🧐
- Contributing to the Galaxy Training Material / Design and plan session, course, materials 🧐
- Contributing to the Galaxy Training Material / Contributing with GitHub via its interface 🧐
- Contributing to the Galaxy Training Material / Tools, Data, and Workflows for tutorials ✍️ 🧐
- 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 / Updating diffs in admin training 🧐
- Contributing to the Galaxy Training Material / Adding auto-generated video to your slides 🧐
- Contributing to the Galaxy Training Material / GTN Metadata 🧐
- Contributing to the Galaxy Training Material / Creating content in Markdown 📝 🧐
- Contributing to the Galaxy Training Material / Adding Quizzes to your Tutorial 🧐
- FAIR Data, Workflows, and Research / DataPLANT ARCs 🧐
- 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 / Data Registration 🧐
- FAIR Data, Workflows, and Research / FAIR and its Origins 🧐
- FAIR Data, Workflows, and Research / REMBI - Recommended Metadata for Biological Images – metadata guidelines for bioimaging data 🧐
- FAIR Data, Workflows, and Research / Metadata 🧐
- FAIR Data, Workflows, and Research / RO-Crate - Introduction 🧐
- FAIR Data, Workflows, and Research / Exporting Workflow Run RO-Crates from Galaxy 🧐
- FAIR Data, Workflows, and Research / Access 🧐
- FAIR Data, Workflows, and Research / RO-Crate in Python 🧐
- FAIR Data, Workflows, and Research / Persistent Identifiers 🧐
- Statistics and machine learning / Unsupervised Analysis of Bone Marrow Cells with Flexynesis ✍️ 🧐
- 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 / Predicting Mutation Impact with Zero-shot Learning using a pretrained DNA LLM 🧐
- Statistics and machine learning / Interval-Wise Testing for omics data 🧐
- Statistics and machine learning / Basics of machine learning 🧐
- Statistics and machine learning / Fine-tuning a LLM for DNA Sequence Classification 🧐
- Statistics and machine learning / Classification in Machine Learning 🧐
- Statistics and machine learning / Fine tune large protein model (ProtTrans) using HuggingFace 🧐
- Statistics and machine learning / Generating Artificial Yeast DNA Sequences using a DNA LLM 🧐
- Statistics and machine learning / Prepare Data from CbioPortal for Flexynesis Integration ✍️ 🧐
- Statistics and machine learning / Pretraining a Large Language Model (LLM) from Scratch on DNA Sequences 🧐
- Statistics and machine learning / Age prediction using machine learning 🧐
- Statistics and machine learning / Identifing Survival Markers of Brain tumor with Flexynesis ✍️ 🧐
- Statistics and machine learning / Modeling Breast Cancer Subtypes with Flexynesis ✍️ 🧐
- Statistics and machine learning / Introduction to Machine Learning using R 🧐
- Statistics and machine learning / Clustering in Machine Learning 🧐
- Statistics and machine learning / Introduction to deep learning 🧐
- Statistics and machine learning / Supervised Learning with Hyperdimensional Computing 🧐
- Statistics and machine learning / A Docker-based interactive Jupyterlab powered by GPU for artificial intelligence in Galaxy 🧐
- Statistics and machine learning / Optimizing DNA Sequences for Biological Functions using a DNA LLM 🧐
- Statistics and machine learning / Machine learning: classification and regression 🧐
- Statistics and machine learning / Regression in Machine Learning 🧐
- Statistics and machine learning / Galaxy Tabular Learner - Building a Model using Chowell clinical data 🧐
- Assembly / Genome assembly using PacBio data 🧐
- Assembly / Using the VGP workflows to assemble a vertebrate genome with HiFi and Hi-C data 🧐
- Assembly / Unicycler assembly of SARS-CoV-2 genome with preprocessing to remove human genome reads 🧐
- Assembly / An Introduction to Genome Assembly 🧐
- Assembly / Vertebrate genome assembly using HiFi, Bionano and Hi-C data - Step by Step 🧐
- Assembly / Decontamination of a genome assembly 🧐
- Assembly / Genome Assembly Quality Control 🧐
- Assembly / Unicycler Assembly 🧐
- Assembly / Making sense of a newly assembled genome 🧐
- Assembly / De Bruijn Graph Assembly 🧐
- Assembly / Chloroplast genome assembly 🧐
- Assembly / Assembly of the mitochondrial genome from PacBio HiFi reads 🧐
- Assembly / ERGA post-assembly QC 🧐
- Assembly / Genome Assembly of MRSA from Oxford Nanopore MinION data (and optionally Illumina data) 🧐
- Assembly / Genome Assembly of a bacterial genome (MRSA) sequenced using Illumina MiSeq Data 🧐
- Development in Galaxy / Galaxy Interactive Tools 🧐
- Development in Galaxy / ToolFactory: Generating Tools From Simple Scripts 🧐
- Development in Galaxy / Galaxy Webhooks ✍️ 🧐
- Development in Galaxy / Contributing to BioBlend as a developer 🧐
- Development in Galaxy / Debugging Galaxy 🧐
- Development in Galaxy / Setting up a dev Onedata instance 🧐
- Development in Galaxy / Generic plugins 🧐
- Development in Galaxy / JavaScript plugins ✍️ 🧐
- Development in Galaxy / Data source integration 🧐
- 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
- Materials Science / Introduction to Muon Spectroscopy 🧐
- Development in Galaxy / Galaxy from a developer point of view 🧐
- Genome Annotation / Introduction to Genome Annotation 🧐
- Genome Annotation / Genome annotation with Prokka 🧐
- Introduction to Galaxy Analyses / Introduction to Galaxy 🧐
- Introduction to Galaxy Analyses / A Short Introduction to Galaxy 🧐
- Introduction to Galaxy Analyses / Options for using Galaxy 🧐
- Microbiome / Introduction to Microbiome Analysis 🧐
- Microbiome / Introduction to metatranscriptomics 🧐
- Teaching and Hosting Galaxy training / Overview of the Galaxy Training Material for Instructors 🧐
- Metabolomics / Mass spectrometry: LC-MS preprocessing - advanced 🧐
- Single Cell / Single-cell Formats and Resources 🧐
- Single Cell / Automated Cell Annotation 🧐
- Single Cell / An introduction to scRNA-seq data analysis 🧐
- Single Cell / GO Enrichment Analysis on Single-Cell RNA-Seq Data 🧐
- Single Cell / Clustering 3K PBMCs with Scanpy 🧐
- Single Cell / Trajectory analysis 🧐
- Single Cell / Plates, Batches, and Barcodes 🧐
- Single Cell / Dealing with Cross-Contamination in Fixed Barcode Protocols 🧐
- Climate / Functionally Assembled Terrestrial Ecosystem Simulator (FATES) 🧐
- Variant Analysis / Introduction to Variant analysis 🧐
- Sequence analysis / Quality Control 🧐
- Sequence analysis / Mapping 🧐
- Visualisation / Visualisations in Galaxy 🧐
- Visualisation / JBrowse 🧐
- Visualisation / Circos 🧐
- Galaxy Server administration / Ansible 🧐
- Galaxy Server administration / Galactic Database 🧐
- Galaxy Server administration / Galaxy Interactive Tools 🧐
- Galaxy Server administration / Galaxy from an administrator's point of view ✍️ 🧐
- Galaxy Server administration / Reference Data with CVMFS 🧐
- Galaxy Server administration / Advanced customisation of a Galaxy instance ✍️ 🧐
- Galaxy Server administration / Terraform 🧐
- Galaxy Server administration / uWSGI 🧐
- Galaxy Server administration / Gearing towards production 🧐
- Galaxy Server administration / Galaxy Tool Management with Ephemeris 🧐
- Galaxy Server administration / Server Maintenance: Cleanup, Backup, and Restoration ✍️ 🧐
- Galaxy Server administration / Reference Genomes in Galaxy 🧐
- Galaxy Server administration / User, Role, Group, Quota, and Authentication managment ✍️ 🧐
- Galaxy Server administration / Galaxy on the Cloud 🧐
- Galaxy Server administration / Empathy 🧐
- Galaxy Server administration / Galaxy Monitoring with Telegraf and Grafana ✍️ 🧐
- Galaxy Server administration / Connecting Galaxy to a compute cluster ✍️ 🧐
- Galaxy Server administration / Galaxy Monitoring with gxadmin ✍️ 🧐
- Galaxy Server administration / Storage Management 🧐
- Galaxy Server administration / Docker and Galaxy ✍️ 🧐
- Galaxy Server administration / Galaxy Troubleshooting 🧐
- Galaxy Server administration / Server: Other ✍️ 🧐
- Galaxy Server administration / Galaxy Monitoring ✍️ 🧐
- Proteomics / Introduction to proteomics, protein identification, quantification and statistical modelling 🧐
- Using Galaxy and Managing your Data / Submitting SARS-CoV-2 sequences to ENA 🧐
- Using Galaxy and Managing your Data / Galaxy workflows in Dockstore 🧐
-
Imaging
/
Nucleoli Segmentation
&
Feature Extraction
using CellProfiler 🧐 - Transcriptomics / Introduction to Transcriptomics 🧐
- Transcriptomics / Identification of non-canonical ORFs and their potential biological function 🧐
- Epigenetics / EWAS Epigenome-Wide Association Studies Introduction 🧐
- Epigenetics / Introduction to DNA Methylation data analysis 🧐
- Epigenetics / Introduction to ChIP-Seq data analysis 🧐
- Epigenetics / ChIP-seq data analysis 🧐
- Contributing to the Galaxy Training Material / Overview of the Galaxy Training Material 🧐
- Contributing to the Galaxy Training Material / Contributing with GitHub via command-line 🧐
- Contributing to the Galaxy Training Material / Creating Slides 🧐
- Statistics and machine learning / Convolutional neural networks (CNN) Deep Learning - Part 3 🧐
- Statistics and machine learning / Introduction to Machine learning 🧐
- Statistics and machine learning / Classification in Machine Learning 🧐
- Statistics and machine learning / Fine-tuning Protein Language Model 🧐
- Statistics and machine learning / Regression in Machine Learning 🧐
- 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 🧐
- Development in Galaxy / Galaxy Interactive Tours ✍️ 🧐
- Development in Galaxy / Prerequisites for building software/conda packages 🧐
- Development in Galaxy / Tool Dependencies and Containers ✍️ 🧐
- Development in Galaxy / Galaxy Webhooks ✍️ 🧐
- Development in Galaxy / Tool development and integration into Galaxy ✍️ 🧐
- Development in Galaxy / Architecture 01 - Galaxy Ecosystem and Projects
- Development in Galaxy / Scripting Galaxy using the API and BioBlend 🧐
- Development in Galaxy / Tool Shed: sharing Galaxy tools 🧐
- Development in Galaxy / Generic plugins 🧐
- Development in Galaxy / Visualizations: JavaScript Plugins ✍️ 🧐
- Development in Galaxy / Galaxy Interactive Environments ✍️ 🧐
- Development in Galaxy / Tool Dependencies and Conda ✍️ 🧐
- 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 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
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add nfdi4boimage and de.NBI to the funding
imaging -
try migrating labeller to new version
Reviewed 1098 PRs
We love our community reviewing each other's work!
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Add ELIXIR-STEERS grant
template-and-tools -
Update WorkflowHub IDs
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Add maximilianh to CONTRIBUTORS.yaml
template-and-tools -
Update CONTRIBUTORS.yaml add Arthur Barreau & Nadine Le Bris
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[New Tutorial] Intro to Galaxy as an RDM Platform
introductiontemplate-and-toolsfaqs
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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