Training List
Handles creating, reading and updating training events.
GET /api/training/?format=api&offset=360&ordering=-audienceRoles
{ "count": 393, "next": "https://catalogue.france-bioinformatique.fr/api/training/?format=api&limit=20&offset=380&ordering=-audienceRoles", "previous": "https://catalogue.france-bioinformatique.fr/api/training/?format=api&limit=20&offset=340&ordering=-audienceRoles", "results": [ { "id": 377, "name": "RNASEQ ALIGNMENT, QUANTIFICATION AND TRANSCRIPT DISCOVERY WITH STATISTICS", "shortName": "RNASeq bioinfo / biostat", "description": "The Toulouse Genotoul bioinformatics platform, in collaboration with the Genotoul Biostatistics platform, and the MIAT unit, organize a 3,5 days long training course for bio-informaticians and biologists aiming at learning sequence analysis. It focuses on (protein coding) gene expression analysis using reads produced by ‘RNA-Seq’. This training session is designed to introduce sequences from ‘NGS’ (Next Generation Sequencing), particularly Illumina platforms (HiSeq). You will discover the standards file formats, learn about the usual biases of this type of data and run different kinds of analyses, such as spliced alignment on a reference genome, novel gene and transcript discovery, expression quantification of coding genes and transcripts. Finally you will be able to extract the differentially expressed genes.", "homepage": "https://bioinfo.genotoul.fr/index.php/events/rnaseq-alignment-transcripts-assemblies-statistics/", "is_draft": false, "costs": [ "Non-academic: 550€ + 20% taxes (TVA)", "Academic but non-INRAE: 170 € + 20% taxes (TVA)", "For INRAE's staff: 150 € no VAT charged;" ], "topics": [ "http://edamontology.org/topic_0203", "http://edamontology.org/topic_3308" ], "keywords": [ "NGS Data Analysis", "Expression" ], "prerequisites": [ "Linux/Unix", "Cluster", "Langage R de base" ], "openTo": "Everyone", "accessConditions": "Register on the training page : https://bioinfo.genotoul.fr/index.php/training-2/training/", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/642/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/739/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/300/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 15, "name": "MIAT", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/MIAT/?format=api" } ], "organisedByTeams": [ { "id": 33, "name": "Genotoul-biostat", "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-biostat/?format=api" }, { "id": 22, "name": "Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-bioinfo/?format=api" } ], "logo_url": "https://bioinfo.genotoul.fr/wp-content/uploads/bioinfo_logo-rvb-petit.png", "updated_at": "2025-12-09T09:40:46.927545Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Life scientists", "Biologists", "Bioinformaticians" ], "difficultyLevel": "Intermediate", "trainingMaterials": [ { "id": 136, "name": "Training RNASeq - biostat part - Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Training%20RNASeq%20-%20biostat%20part%20-%20Genotoul-bioinfo/?format=api" }, { "id": 135, "name": "Training RNASeq - bioinfo part - Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Training%20RNASeq%20-%20bioinfo%20part%20-%20Genotoul-bioinfo/?format=api" } ], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": 21, "personalised": false, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/754/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/612/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/721/?format=api" ] }, { "id": 275, "name": "Single-Cell : Transcriptomics, Spatial and Long reads", "shortName": "SincellTE", "description": "This workshop focuses on the large-scale study of heterogeneity across individual cells from a genomic, transcriptomic and epigenomic point of view. New technological developments enable the characterization of molecular information at a single cell resolution for large numbers of cells. The high dimensional omics data that these technologies produce raise novel methodological challenges for the analysis. In this regard, dedicated bioinformatics and statistical methods have been developed in order to extract robust information.\r\n\r\nThe workshop aims to provide such methods for engineers and researchers directly involved in functional genomics projects making use of single-cell technologies. A wide range of single cell topics will be covered in lectures, demonstrations and practical classes. Among others, the areas and issues to be addressed will include the choice of the most appropriate single-cell sequencing technology, the experimental design and the bioinformatics and statistical methods and pipelines. For this edition, new courses/practicals will focus on spatial transcriptomics, cell phenotyping and additional multi-omics.\r\n\r\nA wide range of single cell topics will be covered in lectures, demonstrations and practical classes. Among others, the areas and issues to be addressed will include the choice of the most appropriate single-cell sequencing technology, the experimental design and the bioinformatics and statistical methods and pipelines. For this edition, new courses/practicals will focus on spatial transcriptomics, cell phenotyping and additional multi-omics.\r\n\r\nRequirements : Participants must have prior experience on NGS data analysis with everyday use of R and good knowledge of Unix command line. Before the training, participants will be asked to familiarize themselves with the processing and primary analyses steps of scRNA-seq datasets with provided pedagogic material.\r\n\r\nIt is not necessary to have personal single-cell data to analyse.", "homepage": "", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [], "prerequisites": [ "Master", "Autre (Diplôme universitaire, école d'ingénieur ...)" ], "openTo": "Everyone", "accessConditions": "Participants must have prior experience on NGS data analysis with everyday use of R and/or Python and good knowledge of Unix command line. Before the training, participants are advised to familiarize themselves with the processing and primary analyses steps of scRNA-seq datasets. \r\nIt is not necessary to have personal single-cell data to analyse.", "maxParticipants": 30, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 4, "name": "IFB - ELIXIR-FR", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IFB%20-%20ELIXIR-FR/?format=api" } ], "organisedByTeams": [], "logo_url": "https://ressources.france-bioinformatique.fr/sites/default/files/sincellTE_logo_0_2.png", "updated_at": "2024-03-20T09:31:42.144175Z", "audienceTypes": [], "audienceRoles": [ "Researchers", "Life scientists", "Biologists", "Bioinformaticians" ], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/199/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/405/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/422/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/177/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/606/?format=api" ] }, { "id": 359, "name": "Comparaison de génomes microbiens", "shortName": "Comparaison de génomes microbiens", "description": "Objectifs pédagogiques\r\nConnaître les concepts et les principales méthodes bioinformatiques pour comparer un jeu de données de génomes microbiens. Construire et évaluer la qualité d’un jeu de données. Savoir mettre en œuvre une comparaison de génomes et en interpréter les résultats.\r\n\r\nProgramme\r\n* Construction d’un jeu de données :\r\n* Téléchargement de données publiques\r\n* Evaluation de la qualité\r\n* Caractérisation de la diversité génomique\r\n* Stratégies de comparaison :\r\n* Construction de famille de protéines\r\n* Alignement de génomes complets\r\n* Analyse des résultats :\r\n o Notion de core et pan-génome\r\n o Notions élémentaires de phylogénomique\r\n o Visualisation et interprétation des résultats\r\n* Mise en pratique sur un jeu de données bactériens, utilisation des logiciels dRep et Roary sous Galaxy.", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_3299", "http://edamontology.org/topic_0622" ], "keywords": [ "Comparative genomics" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" } ], "organisedByTeams": [ { "id": 10, "name": "MIGALE", "url": "https://catalogue.france-bioinformatique.fr/api/team/MIGALE/?format=api" } ], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2024-01-18T14:13:49.810934Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Biologists", "Bioinformaticians" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "Connaître les concepts et les principales méthodes bioinformatiques pour comparer un jeu de données de génomes microbiens. \r\nConstruire et évaluer la qualité d’un jeu de données. \r\nSavoir mettre en œuvre une comparaison de génomes et en interpréter les résultats.", "hoursPresentations": 3, "hoursHandsOn": 3, "hoursTotal": 6, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/584/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/696/?format=api" ] }, { "id": 362, "name": "Analyse statistique de données RNA-Seq - Recherche des régions d’intérêt différentiellement exprimées", "shortName": "Analyse statistique de données RNA-Seq", "description": "Objectifs pédagogiques\r\n* Se sensibiliser aux concepts et méthodes statistiques pour l’analyse de données transcriptomiques de type RNA-Seq.\r\n* Comprendre le matériel et méthodes (normalisation et tests statistiques) d’un article.\r\n* Réaliser une étude transcriptomique avec R dans l’environnement RStudio.\r\n\r\nProgramme\r\n* Planification expérimentale des expériences RNA-Seq (identification des biais, répétitions, biais contrôlables).\r\n* Normalisation et analyse différentielle : recherche de “régions d’intérêt” différentiellement exprimées (modèle linéaire généralisé).\r\n*Prise en compte de la multiplicité des tests.\r\n\r\nLe cours sera illustré par différents exemples. Un jeu de données à deux facteurs sera analysé avec les packages R DESeq2 et edgeR dans l’environnement RStudio.", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_0203", "http://edamontology.org/topic_3170", "http://edamontology.org/topic_3308" ], "keywords": [ "Statistical differential analysis", "RNA-seq" ], "prerequisites": [ "Basic knowledge of R" ], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" } ], "organisedByTeams": [ { "id": 10, "name": "MIGALE", "url": "https://catalogue.france-bioinformatique.fr/api/team/MIGALE/?format=api" } ], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2024-01-18T14:50:06.093352Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Biologists", "Bioinformaticians" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "Objectifs pédagogiques :\r\nSe sensibiliser aux concepts et méthodes statistiques pour l’analyse de données transcriptomiques de type RNA-Seq.\r\nComprendre le matériel et méthodes (normalisation et tests statistiques) d’un article.\r\nRéaliser une étude transcriptomique avec R dans l’environnement RStudio.", "hoursPresentations": 4, "hoursHandsOn": 8, "hoursTotal": 12, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/786/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/587/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/695/?format=api" ] }, { "id": 388, "name": "Analysis of shotgun metagenomic data", "shortName": "", "description": "This training session is organized by the Genotoul bioinfo platform. This course is dedicated to the analysis of prokaryotic shotgun metagenomic data from Illumina and Pacbio HiFi sequencing technology. \r\n\r\nAfter an overview of metagenomics and the biases and limitations of analyses, we will look at the main steps involved in analysing metagenomic data and launch independent tools on the genobioinfo cluster.\r\nLearners will then test a workflow to automate processing on a test dataset (metagWGS ).\r\nOn the third day, learners will choose which analysis strategy to start with according to their experimental design and launch the first stage of metagWGS on their own data.\r\nBy the end of the course, trainees will be familiar with the scope, advantages and limitations of shotgun sequencing data analysis and will have started the analysis on their own data.\r\n\r\ncalendar\r\n \r\n\r\nThis training is focused on practice. It consists of several modules with a large variety of exercises:\r\n\r\nFirst Day\r\nStart at 09:00 am\r\nTour de table\r\nIntroduction to metagenomics, Illumina and Pacbio data, analysis stages, analysis limits, etc.\r\nPresentation of some key tools for each stage\r\nPractical work on the main stages launched independently\r\nEnd at 17:00 pm\r\nSecond Day\r\nStart at 09:00 am\r\nIntroduction to the advantages and disadvantages of workflows and containers\r\nLaunch of the data cleansing stage\r\nLaunch of the rest of the workflow and analysis of the multiQC report\r\nEnd at 17:00 pm\r\nThird Day – BYOD\r\nStart at 09:00 am\r\nDefine the analysis strategy and launch the start of the analysis of your own data.\r\nEnd at 17:00 pm maximum", "homepage": "https://bioinfo.genotoul.fr/index.php/events/analysis-of-shotgun-metagenomic-data/", "is_draft": false, "costs": [ "Non-academic for non-academic: 1650€ + 20% taxes (TVA)", "Academic non-INRAE for academic but non-INRAE: 510 € + 20% taxes (TVA)", "INRAE for INRAE's staff: 450 € no VAT charged" ], "topics": [ "http://edamontology.org/topic_3174" ], "keywords": [ "NGS Data Analysis", "Metagenomics" ], "prerequisites": [ "Linux/Unix", "Cluster" ], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/300/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" }, { "id": 37, "name": "MIAT - Mathématiques et Informatique Appliquées de Toulouse", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/MIAT%20-%20Math%C3%A9matiques%20et%20Informatique%20Appliqu%C3%A9es%20de%20Toulouse/?format=api" } ], "organisedByTeams": [ { "id": 22, "name": "Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-bioinfo/?format=api" } ], "logo_url": "https://bioinfo.genotoul.fr/wp-content/uploads/bioinfo_logo-rvb-petit.png", "updated_at": "2026-03-02T08:49:21.302798Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Life scientists", "Biologists", "Bioinformaticians" ], "difficultyLevel": "Intermediate", "trainingMaterials": [ { "id": 151, "name": "Metagenomic training - Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Metagenomic%20training%20-%20Genotoul-bioinfo/?format=api" } ], "learningOutcomes": "", "hoursPresentations": 3, "hoursHandsOn": 15, "hoursTotal": 18, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/670/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/758/?format=api" ] }, { "id": 412, "name": "Construction and analysis of eukaryotic pangenome graphs", "shortName": "", "description": "This training session is organized by the Genotoul-Bioinfo platform. This 2 days long course is dedicated to the construction and the analysis of eukaryotic pangenome graphs.\r\n\r\nWe will first present the concept of graph-based pangenome, then build one. We will then apply several tools for its analysis: use annotation, call variants, extract sub-graphs, visualize the graph, map reads, genotype individuals, and perform a GWAS on the graph. The different formats will also be presented.\r\n\r\nBy the end of the course, trainees will be familiar with the topic, and able to run the major tools made to build an exploit a pangenome graph.", "homepage": "https://bioinfo.genotoul.fr/index.php/events/pangenome/", "is_draft": false, "costs": [ "Non-academic for non-academic: 1100€ + 20% taxes (TVA)", "INRAE for INRAE's staff: 300 € no VAT charged", "Academic non-INRAE for academic but non-INRAE: 340 € + 20% taxes (TVA)" ], "topics": [ "http://edamontology.org/topic_3796", "http://edamontology.org/topic_0625" ], "keywords": [ "Pangenomic" ], "prerequisites": [ "Linux/Unix", "Cluster" ], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/642/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" }, { "id": 37, "name": "MIAT - Mathématiques et Informatique Appliquées de Toulouse", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/MIAT%20-%20Math%C3%A9matiques%20et%20Informatique%20Appliqu%C3%A9es%20de%20Toulouse/?format=api" } ], "organisedByTeams": [ { "id": 22, "name": "Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-bioinfo/?format=api" } ], "logo_url": "https://bioinfo.genotoul.fr/wp-content/uploads/bioinfo_logo-rvb-petit.png", "updated_at": "2026-04-20T08:06:46.497837Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Life scientists", "Biologists", "Bioinformaticians" ], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 3, "hoursHandsOn": 15, "hoursTotal": 18, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/799/?format=api" ] }, { "id": 413, "name": "Galaxy Beyond Basics: Mastering Workflows, Automation, and Scalability", "shortName": "Galaxy avancée", "description": "Join us for an intensive, week-long, in-person training designed to elevate your Galaxy expertise to new heights. This workshop is tailored for data scientists, advanced Galaxy users, and team leaders who need to scale, automate, and publish their data analysis workflows for batch processing and production-level applications.\r\n\r\nOver five days, you’ll embark on a comprehensive journey through Galaxy’s advanced capabilities:\r\n\r\nMonday: Introduction & Workflow Development\r\n\r\nStart with a welcome and icebreaker to foster collaboration, followed by a brief overview of Galaxy and its workflow features. Dive into hands-on workflow development, where you’ll learn to design clean, efficient workflows, customize them with parameters, and generate user-friendly workflow reports—combining theory with practical application.\r\n\r\nTuesday: Workflow FAIRification, Documentation, and Export\r\n\r\nBegin with a recap of Day 1, then explore UseGalaxy.fr and its unique features. Learn to annotate workflows with metadata, apply best practices for FAIR compliance, and implement tests to ensure reliability. Publish your workflows to WorkflowHub and Dockstore via the IWC. Develop high-resolution workflow visualizations and create interactive tutorials using a “Choose Your Own Tutorial” approach. Finally, master workflow export by creating RO-Crates for reproducibility and submitting workflows to LifeMonitor for performance tracking.\r\n\r\nWednesday: Scaling Workflows & Galaxy Using Command-Line and API\r\n\r\nStart with a recap and real-world examples of large-scale Galaxy projects. Learn to execute workflows from the command line using Planemo, automate batch processing with shell scripts, and analyze performance for efficiency. Discover how to scale Galaxy use with BioBlend, designing Python scripts for batch workflow execution and evaluating scalability. The day concludes with an introduction to the “Bring Your Own Work” session.\r\n\r\nThursday: Bring Your Own Work (BYOW)\r\n\r\nDedicate the day to applying your new skills to your own projects. With guidance from trainers, refine your workflows, troubleshoot challenges, and implement solutions using your personal data. Collaborate with peers, document your progress, and optimize your workflows to leave with actionable results for your research.\r\n\r\nFriday: Storage, Data Management, Recap, and Closing\r\n\r\nThe final half-day begins with a recap of the week’s progress, followed by a session on “Bring Your Own Storage”, exploring how to integrate personal or institutional storage with Galaxy. Learn about managing databases in Galaxy and the IDC (Intergalactic Data Commission) effort for efficient data organization. The workshop concludes with a general recap, supplementary exercises, and feedback and closing remarks, ensuring you leave with a comprehensive understanding and resources for continued success.\r\n\r\nThis training will be conducted in French, while the materials (slides) will be in English.\r\n\r\nLearning Objectives\r\nAt the end of the workshop, you will be able to:\r\n\r\nWorkflow development\r\n Understand the key aspects of workflows by identifying their core components and purpose.\r\n Create clean, non-repetitive workflows by applying best practices for process design.\r\n Use workflow parameters to customize and optimize workflows for specific tasks.\r\n Generate user-friendly workflow reports to display workflow results in a structured way.\r\nWorkflow FAIRyfication\r\n Annotate a Galaxy workflow with essential metadata to ensure it is findable and reusable.\r\n Apply best practices to data analysis workflows to improve consistency and interoperability.\r\n Implement robust tests to validate workflow reliability and accuracy.\r\n Publish a Galaxy workflow on WorkflowHub and Dockstore via its integration into the IWC, demonstrating enhanced findability,accessibility, interroperability and usability for the scientific community.\r\nWorkflow Documentation\r\n Design a high-resolution workflow image optimized for documentation and presentations.\r\n Develop a hands-on tutorial with a “Choose Your Own Tutorial” approach, including:\r\n A step-by-step tutorial with skeleton generation from the workflow.\r\n A real-time tutorial that runs and explains the workflow interactively.\r\n Produce a final documentation package that includes both tutorial formats and high-resolution visuals.\r\nWorkflow Export\r\n Apply the process of creating a Galaxy Workflow Run RO-Crate by packaging a workflow with its metadata, inputs, and outputs, ensuring it is reproducible and FAIR-compliant.\r\n Evaluate the completeness and accuracy of a Galaxy Workflow Run RO-Crate by reviewing its structure, metadata, and included files for adherence to best practices.\r\n Submit a workflow to LifeMonitor, analyzing the platform’s feedback to assess workflow performance and improve its reliability for future use.\r\nWorkflow Scaling using command-line\r\nExecute workflows from the command line using the Planemo run subcommand, demonstrating the ability to run and monitor workflows outside the Galaxy interface.\r\nDevelop simple shell scripts to automate the execution of multiple workflows concurrently or sequentially, optimizing efficiency and scalability.\r\nAnalyze the performance and resource usage of workflows run via shell scripts, evaluating the effectiveness of scaling strategies for large-scale data processing.\r\nScaling Galaxy Use with the API and BioBlend\r\nUtilize the BioBlend library to programmatically interact with Galaxy, executing workflows, managing datasets, and automating repetitive tasks.\r\nDesign a Python script using BioBlend to scale Galaxy workflows for batch processing, ensuring efficient resource use and reproducibility.\r\nEvaluate the performance and scalability of workflows executed via BioBlend, comparing results with manual Galaxy interactions to identify improvements.\r\n“Bring Your Own Work”\r\nApply the concepts and tools learned during the training to develop or refine your own workflows using your personal data, with guidance from trainers.\r\nTroubleshoot challenges in your workflow or data analysis, implementing solutions with the support of trainers and peers.\r\nDemonstrate progress in your project by documenting your workflow, results, and any optimizations made during the sessions.\r\n\r\nRequirements\r\nPrior knowledge and experience using Galaxy\r\nPrior knowledge and experience using command line\r\nFluent in French (materials will be in English and discussions will happen in French)\r\nYour own computer\r\nOptional but encouraged: your own workflow and dataset for the Bring Your Own Work (BYOW) session. The workflow and the dataset must be shareable and non-sensitive (i.e., they must not contain any patient-related information or confidential data). The dataset size must be small.", "homepage": "https://training.galaxyproject.org/training-material/events/2026-10-12-Advanced-Galaxy-Training.html#overview", "is_draft": false, "costs": [ "700 euros HT" ], "topics": [ "http://edamontology.org/topic_3316", "http://edamontology.org/topic_0769", "http://edamontology.org/topic_0091" ], "keywords": [ "Reproducibility", "Galaxy", "Workflow development" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "NA", "maxParticipants": 20, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/810/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/762/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/116/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/362/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 3, "name": "IFB", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/IFB/?format=api" } ], "organisedByOrganisations": [ { "id": 43, "name": "IFB-core", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IFB-core/?format=api" } ], "organisedByTeams": [ { "id": 29, "name": "IFB Core", "url": "https://catalogue.france-bioinformatique.fr/api/team/IFB%20Core/?format=api" } ], "logo_url": "https://training.galaxyproject.org/training-material/assets/images/GTN.png", "updated_at": "2026-04-23T08:22:23.122272Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Computer scientists", "Bioinformaticians", "All" ], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "At the end of the workshop, you will be able to:\r\n\r\nWorkflow development\r\nUnderstand the key aspects of workflows by identifying their core components and purpose.\r\nCreate clean, non-repetitive workflows by applying best practices for process design.\r\nUse workflow parameters to customize and optimize workflows for specific tasks.\r\nGenerate user-friendly workflow reports to display workflow results in a structured way.\r\nWorkflow FAIRyfication\r\nAnnotate a Galaxy workflow with essential metadata to ensure it is findable and reusable.\r\nApply best practices to data analysis workflows to improve consistency and interoperability.\r\nImplement robust tests to validate workflow reliability and accuracy.\r\nPublish a Galaxy workflow on WorkflowHub and Dockstore via its integration into the IWC, demonstrating enhanced findability, accessibility, interroperability and usability for the scientific community.\r\nWorkflow Documentation\r\nDesign a high-resolution workflow image optimized for documentation and presentations.\r\nDevelop a hands-on tutorial with a “Choose Your Own Tutorial” approach, including:\r\nA step-by-step tutorial with skeleton generation from the workflow.\r\nA real-time tutorial that runs and explains the workflow interactively.\r\nProduce a final documentation package that includes both tutorial formats and high-resolution visuals.\r\nWorkflow Export\r\nApply the process of creating a Galaxy Workflow Run RO-Crate by packaging a workflow with its metadata, inputs, and outputs, ensuring it is reproducible and FAIR-compliant.\r\nEvaluate the completeness and accuracy of a Galaxy Workflow Run RO-Crate by reviewing its structure, metadata, and included files for adherence to best practices.\r\nSubmit a workflow to LifeMonitor, analyzing the platform’s feedback to assess workflow performance and improve its reliability for future use.\r\nWorkflow Scaling using command-line\r\nExecute workflows from the command line using the Planemo run subcommand, demonstrating the ability to run and monitor workflows outside the Galaxy interface.\r\nDevelop simple shell scripts to automate the execution of multiple workflows concurrently or sequentially, optimizing efficiency and scalability.\r\nAnalyze the performance and resource usage of workflows run via shell scripts, evaluating the effectiveness of scaling strategies for large-scale data processing.\r\nScaling Galaxy Use with the API and BioBlend\r\nUtilize the BioBlend library to programmatically interact with Galaxy, executing workflows, managing datasets, and automating repetitive tasks.\r\nDesign a Python script using BioBlend to scale Galaxy workflows for batch processing, ensuring efficient resource use and reproducibility.\r\nEvaluate the performance and scalability of workflows executed via BioBlend, comparing results with manual Galaxy interactions to identify improvements.\r\n“Bring Your Own Work”\r\nApply the concepts and tools learned during the training to develop or refine your own workflows using your personal data, with guidance from trainers.\r\nTroubleshoot challenges in your workflow or data analysis, implementing solutions with the support of trainers and peers.\r\nDemonstrate progress in your project by documenting your workflow, results, and any optimizations made during the sessions.", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": true, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/802/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/803/?format=api" ] }, { "id": 406, "name": "Analyse de données de métabarcoding", "shortName": "Métabarcoding", "description": "Cette formation est dédiée à l’analyse de données de type “metabarcoding” issues de la technologie de séquençage Illumina. Nous aborderons les différentes étapes bioinformatiques nécessaires pour transformer les données de séquençage brutes en table d’abondances. Nous présenterons également les outils et méthodologies classiquement utilisés pour décrire la diversité observée et comparer les échantillons.\r\n\r\nA l’issue des 4 jours de formation, les stagiaires connaîtront le périmètre, les avantages et limites des analyses de données de séquençage amplicons (métabarcoding). Ils seront capables d’utiliser les outils de FROGS sur les jeux de données de la formation (16S et ITS) et sauront utiliser l’application Easy16S.\r\n\r\nIls seront capables d’identifier les outils et méthodes adaptées au cadre de leurs analyses. S’ils ont en leur possession un jeu de données à analyser, ils sont encouragés à venir avec celui- ci.\r\n\r\nProgramme :\r\n\r\n\r\nAnalyses bioinformatiques sous Galaxy\r\n\r\n Introduction générale sur les données amplicons\r\n Présentation et mise en application avec la suite FROGS du nettoyage des données, du clustering, de la détection de chimères, de l’assignation taxonomique et des étapes annexes\r\n Conclusion, limite des méthodes, outils compagnons\r\n\r\nAnalyses statistiques avec Easy16S\r\n\r\n Introduction générale\r\n Import, manipulation et visualisation des données\r\n Mesure de diversités : Unifrac, Bray-Curtis, etc.\r\n Ordination et réduction de dimension : MDS\r\n Clustering et Heatmap\r\n Comparaison d’échantillons : PERMANOVA, adonis\r\n\r\nMise en application sur données personnelles ou publiques", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_3697" ], "keywords": [ "Metabarcoding" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" } ], "organisedByTeams": [ { "id": 10, "name": "MIGALE", "url": "https://catalogue.france-bioinformatique.fr/api/team/MIGALE/?format=api" } ], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2026-02-12T10:53:42.895487Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Biologists", "Bioinformaticians" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "Cette formation est dédiée à l’analyse de données de type “metabarcoding” issues de la technologie de séquençage Illumina. Nous aborderons les différentes étapes bioinformatiques nécessaires pour transformer les données de séquençage brutes en table d’abondances. Nous présenterons également les outils et méthodologies classiquement utilisés pour décrire la diversité observée et comparer les échantillons.\r\n\r\nA l’issue des 4 jours de formation, les stagiaires connaîtront le périmètre, les avantages et limites des analyses de données de séquençage amplicons (métabarcoding). Ils seront capables d’utiliser les outils de FROGS sur les jeux de données de la formation (16S et ITS) et sauront utiliser l’application Easy16S.\r\n\r\nIls seront capables d’identifier les outils et méthodes adaptées au cadre de leurs analyses. S’ils ont en leur possession un jeu de données à analyser, ils sont encouragés à venir avec celui- ci.", "hoursPresentations": 12, "hoursHandsOn": 12, "hoursTotal": 24, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/792/?format=api" ] }, { "id": 395, "name": "AlphaFold et au-delà : Modélisation de la structure 3D des protéines avec des outils d’IA / AlphaFold & beyond: 3D Protein Structure Modeling with AI Tools", "shortName": "AlphaFold", "description": "L’Institut Français de Bioinformatique organise en partenariat avec l'IDRIS et les plateformes PRABI-AMS, BIOI2, CUBIC, RPBS et Bilille une nouvelle formation intitulée: “AlphaFold et au-delà : Modélisation de la structure 3D des protéines avec des outils d’IA / AlphaFold & beyond: 3D Protein Structure Modeling with AI Tools”.", "homepage": "https://moodle.france-bioinformatique.fr/course/view.php?id=43", "is_draft": false, "costs": [], "topics": [ "http://edamontology.org/topic_1317", "http://edamontology.org/topic_3542", "http://edamontology.org/topic_3534", "http://edamontology.org/topic_0736", "http://edamontology.org/topic_0091" ], "keywords": [ "Artificial Intelligence", "Comparative and de novo structure modeling", "alphafold", "Post-translational modifications" ], "prerequisites": [ "Linux/Unix" ], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 15, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/116/?format=api" ], "elixirPlatforms": [ { "id": 1, "name": "Training", "url": "https://catalogue.france-bioinformatique.fr/api/elixirplatform/Training/?format=api" } ], "communities": [], "sponsoredBy": [ { "id": 3, "name": "IFB", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/IFB/?format=api" } ], "organisedByOrganisations": [ { "id": 4, "name": "IFB - ELIXIR-FR", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IFB%20-%20ELIXIR-FR/?format=api" } ], "organisedByTeams": [], "logo_url": "https://moodle.france-bioinformatique.fr/pluginfile.php/1/core_admin/logocompact/300x300/1654772049/IFB-HAUT-COULEUR-PETIT.png", "updated_at": "2025-07-16T11:36:28.519489Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Life scientists", "Bioinformaticians" ], "difficultyLevel": "Advanced", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/725/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/804/?format=api" ] }, { "id": 405, "name": "Annotation et comparaison de génomes bactériens", "shortName": "Annotation et comparaison de génomes bactériens", "description": "Connaître les concepts et les principales méthodes bioinformatiques pour annoter automatiquement et comparer un jeu de données de génomes bactériens. Construire et évaluer la qualité d’un jeu de données publiques. Évaluer la qualité et annoter automatiquement un jeu de données. Savoir mettre en oeuvre une comparaison de génomes et en interpréter les résultats.\r\n\r\nProgramme :\r\n\r\n* Construction d’un jeu de données :\r\n Téléchargement de données publiques\r\n Evaluation de la qualité d’un jeu de données\r\n\r\n* Principes et mise en œuvre d’une annotation automatique d’un génome bactérien\r\n\r\n * Caractérisation de la diversité génomique\r\n\r\n * Construction de pangénomes\r\n\r\n * Analyse des résultats :\r\n Résultats et métriques d’un pangénome\r\n Notions élémentaires de phylogénomique\r\n Visualisation et interprétation des résultats\r\n\r\n * Mise en pratique sur un jeu de données bactériens, utilisation des logiciels dRep, Quast, Bakta et PPanGGOLiN sous Galaxy.", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_3299", "http://edamontology.org/topic_0797", "http://edamontology.org/topic_0622" ], "keywords": [ "Genome annotation", "Comparative genomics" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" } ], "organisedByTeams": [ { "id": 10, "name": "MIGALE", "url": "https://catalogue.france-bioinformatique.fr/api/team/MIGALE/?format=api" } ], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2026-02-12T10:45:53.661422Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Biologists", "Bioinformaticians" ], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "Connaître les concepts et les principales méthodes bioinformatiques pour annoter automatiquement et comparer un jeu de données de génomes bactériens. Construire et évaluer la qualité d’un jeu de données publiques. Évaluer la qualité et annoter automatiquement un jeu de données. Savoir mettre en oeuvre une comparaison de génomes et en interpréter les résultats.", "hoursPresentations": 6, "hoursHandsOn": 6, "hoursTotal": 12, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/791/?format=api" ] }, { "id": 371, "name": "Introduction à l'analyse de données métatranscriptomiques avec Galaxy", "shortName": "", "description": "L’objectif de cette formation est de se familiariser avec les étapes et les outils d’analyse de données métatranscriptomiques dans le but de comprendre les fonctions d’une communauté microbienne. Nous proposons au personnel non-bioinformaticien de les accompagner dans la prise en main de ces étapes en utilisant la plateforme de bio-analyse Galaxy. \r\n\r\nAprès une introduction à la métatranscriptomique, une session pratique sur la plateforme Galaxy couvrira comment :\r\n- assigner des taxons à des données de métatranscriptomiques,\r\n- extraire des informations fonctionnelles au sein de données de métatranscriptomiques,\r\n- combiner informations taxonomiques et fonctionnelles pour faciliter la compréhension des fonctions d’une communauté microbienne", "homepage": "", "is_draft": false, "costs": [ "Free to academics" ], "topics": [ "http://edamontology.org/topic_3697", "http://edamontology.org/topic_0085", "http://edamontology.org/topic_1775", "http://edamontology.org/topic_3941" ], "keywords": [ "Galaxy" ], "prerequisites": [ "Galaxy - Basic usage" ], "openTo": "Internal personnel", "accessConditions": "Formation ouverte au personnel de l’UCA & Associés\r\nAvoir un ordinateur portable et un accès wifi eduroam\r\nAvoir un compte sur la plateforme Galaxy (Faire une demande le cas échéant sur hub.mesocentre.uca.fr)\r\nÊtre familier avec Galaxy", "maxParticipants": null, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/261/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 1, "name": "CNRS - IFB", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/CNRS%20-%20IFB/?format=api" }, { "id": 16, "name": "Université Clermont Auvergne", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/Universit%C3%A9%20Clermont%20Auvergne/?format=api" } ], "organisedByOrganisations": [ { "id": 87, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/AuBi/?format=api" }, { "id": 96, "name": "Mésocentre Clermont-Auvergne", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/M%C3%A9socentre%20Clermont-Auvergne/?format=api" } ], "organisedByTeams": [ { "id": 31, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/team/AuBi/?format=api" } ], "logo_url": "https://mesocentre.uca.fr/medias/photo/logoaubi-2019minus_1553844844490-jpg?ID_FICHE=41175", "updated_at": "2024-02-08T11:22:23.706233Z", "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "trainingMaterials": [ { "id": 132, "name": "Metatranscriptomics analysis using microbiome RNA-seq data", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Metatranscriptomics%20analysis%20using%20microbiome%20RNA-seq%20data/?format=api" } ], "learningOutcomes": "At the end of the tutorial, learners would be able to:\r\n- Choose the best approach to analyze metatranscriptomics data\r\n- Understand the functional microbiome characterization using metatranscriptomic results\r\n- Understand where metatranscriptomics fits in ‘multi-omic’ analysis of microbiomes\r\n- Visualise a community structure", "hoursPresentations": 1, "hoursHandsOn": 2, "hoursTotal": 3, "personalised": null, "event_set": [] }, { "id": 412, "name": "Construction and analysis of eukaryotic pangenome graphs", "shortName": "", "description": "This training session is organized by the Genotoul-Bioinfo platform. This 2 days long course is dedicated to the construction and the analysis of eukaryotic pangenome graphs.\r\n\r\nWe will first present the concept of graph-based pangenome, then build one. We will then apply several tools for its analysis: use annotation, call variants, extract sub-graphs, visualize the graph, map reads, genotype individuals, and perform a GWAS on the graph. The different formats will also be presented.\r\n\r\nBy the end of the course, trainees will be familiar with the topic, and able to run the major tools made to build an exploit a pangenome graph.", "homepage": "https://bioinfo.genotoul.fr/index.php/events/pangenome/", "is_draft": false, "costs": [ "Non-academic for non-academic: 1100€ + 20% taxes (TVA)", "INRAE for INRAE's staff: 300 € no VAT charged", "Academic non-INRAE for academic but non-INRAE: 340 € + 20% taxes (TVA)" ], "topics": [ "http://edamontology.org/topic_3796", "http://edamontology.org/topic_0625" ], "keywords": [ "Pangenomic" ], "prerequisites": [ "Linux/Unix", "Cluster" ], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/642/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" }, { "id": 37, "name": "MIAT - Mathématiques et Informatique Appliquées de Toulouse", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/MIAT%20-%20Math%C3%A9matiques%20et%20Informatique%20Appliqu%C3%A9es%20de%20Toulouse/?format=api" } ], "organisedByTeams": [ { "id": 22, "name": "Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-bioinfo/?format=api" } ], "logo_url": "https://bioinfo.genotoul.fr/wp-content/uploads/bioinfo_logo-rvb-petit.png", "updated_at": "2026-04-20T08:06:46.497837Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Life scientists", "Biologists", "Bioinformaticians" ], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 3, "hoursHandsOn": 15, "hoursTotal": 18, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/799/?format=api" ] }, { "id": 289, "name": "Introduction to galaxy: looking for variants in prokaryotes", "shortName": "Introduction to galaxy", "description": "This course will focus on the technical aspects of using a galaxy server. Accessible without any prerequisite in computer science, it will allow you to master the different fundamental tools of galaxy and will open the doors of bioinformatics analysis for your different projects.\r\nDifferent questions will be addressed through an example of variants analysis in a prokaryotic organism. At the end of this course, on any accessible galaxy instance, you will be able to:\r\n- upload your data\r\n- map them on a reference genome\r\n- find the variants (SNPs) and analyze the results\r\n- generate, manipulate and share your workflows, data and histories\r\n- find the right tools for other analyses and use them in your own project.\r\n\r\nUnless all participants speak French, the course will be taught in English.", "homepage": "https://pliniuscursus.univ-amu.fr/formation/galaxy-platform/", "is_draft": false, "costs": [ "Free to academics" ], "topics": [ "http://edamontology.org/topic_0622", "http://edamontology.org/topic_0091" ], "keywords": [], "prerequisites": [ "Master" ], "openTo": "Internal personnel", "accessConditions": "The first sessions are only available for IM2B students.", "maxParticipants": 12, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [ { "id": 23, "name": "PACA-Bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/team/PACA-Bioinfo/?format=api" } ], "logo_url": null, "updated_at": "2022-06-02T11:50:50.812642Z", "audienceTypes": [ "Graduate" ], "audienceRoles": [ "Biologists" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 1, "hoursHandsOn": 5, "hoursTotal": 6, "personalised": null, "event_set": [] }, { "id": 368, "name": "Introduction à l'annotation de génomes bactériens avec Galaxy", "shortName": "", "description": "L’objectif est cette formation de se familiariser avec les étapes et les outils pour annoter des génomes bactériens. Nous proposons au personnel non-bioinformaticien de les accompagner dans la prise en main de l’annotation de génomes bactériens en utilisant la plateforme de bio-analyse Galaxy. \r\n\r\nAprès une introduction à l’annotation de génomes bactériens, une session pratique sur la plateforme Galaxy couvrira comment :\r\n- faire tourner une série d’outils pour annoter un génome bactérien avec différents éléments génomiques,\r\n- évaluer l’annotation\r\n- visualiser un génome bactérien et ses annotations", "homepage": "", "is_draft": false, "costs": [ "Free to academics" ], "topics": [ "http://edamontology.org/topic_0097", "http://edamontology.org/topic_3301", "http://edamontology.org/topic_0622", "http://edamontology.org/topic_0219" ], "keywords": [ "Bacterial isolate", "Galaxy", "Structural and functional annotation of genomes" ], "prerequisites": [ "Galaxy - Basic usage" ], "openTo": "Internal personnel", "accessConditions": "Formation ouverte au personnel de l’UCA & Associés\r\nAvoir un ordinateur portable et un accès wifi eduroam\r\nAvoir un compte sur la plateforme Galaxy (Faire une demande le cas échéant sur hub.mesocentre.uca.fr)\r\nÊtre familier avec Galaxy", "maxParticipants": null, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/261/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 1, "name": "CNRS - IFB", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/CNRS%20-%20IFB/?format=api" }, { "id": 16, "name": "Université Clermont Auvergne", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/Universit%C3%A9%20Clermont%20Auvergne/?format=api" } ], "organisedByOrganisations": [ { "id": 87, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/AuBi/?format=api" }, { "id": 96, "name": "Mésocentre Clermont-Auvergne", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/M%C3%A9socentre%20Clermont-Auvergne/?format=api" } ], "organisedByTeams": [ { "id": 31, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/team/AuBi/?format=api" } ], "logo_url": "https://mesocentre.uca.fr/medias/photo/logoaubi-2019minus_1553844844490-jpg?ID_FICHE=41175", "updated_at": "2024-02-08T11:22:51.682232Z", "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "trainingMaterials": [ { "id": 129, "name": "Bacterial Genome Annotation", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Bacterial%20Genome%20Annotation/?format=api" } ], "learningOutcomes": "At the end of the tutorial, learners would be able to:\r\n- Run a series of tools to annotate a draft bacterial genome for different types of genomic components\r\n- Evaluate the annotation\r\n- Process the outputs to format them for visualization needs\r\n- Visualize a draft bacterial genome and its annotations", "hoursPresentations": 1, "hoursHandsOn": 2, "hoursTotal": 3, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/598/?format=api" ] }, { "id": 344, "name": "Analyses Single Cell RNA-seq (ScRNA-seq) avec R", "shortName": "", "description": "Cette formation introduira notamment la librairie Seurat permettant la manipulation et l'analyse de données Single Cell RNA-seq ainsi que la visualisation des résultats d'analyse\r\n\r\n- Rappels des concepts du séquençage Single Cell RNA-seq\r\n- Importation des données Single Cell dans R\r\n- Intégration de données Single Cell multiples\r\n- Quality Check et pré-traitement des données\r\n- Normalisation de données\r\n- Identification de marqueurs\r\n- Clustering et assignation cellulaire\r\n- Analyse différentielle des groupes cellulaires\r\n- Savoir intégrer les données de spatialisation\r\n- Savoir intégrer les données de trajectoire\r\n- Savoir intégrer les données de communication cellulaire\r\n- Savoir intégrer les données d'épigénétique (ATAC-seq)", "homepage": "https://cnrsformation.cnrs.fr/analyses-single-cell-rna-seq-scrna-seq-avec-r?axe=176", "is_draft": false, "costs": [], "topics": [], "keywords": [ "Bioinformatics & Biomedical", "R Language", "R", "NGS Sequencing Data Analysis" ], "prerequisites": [ "Basic knowledge of R", "R programming" ], "openTo": "Everyone", "accessConditions": "Maîtrise du langage R\r\nAvoir suivi le stage \"Langage R : introduction\" ou niveau équivalent.\r\nAfin de vérifier que votre maîtrise du langage R est suffisante pour pouvoir suivre ce stage, nous vous invitons à effectuer et à renvoyer le test téléchargeable\r\nhttps://cnrsformation.cnrs.fr/data/STG_23294_55153.docx", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/154/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 6, "name": "CNRS formation entreprise", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/CNRS%20formation%20entreprise/?format=api" } ], "organisedByOrganisations": [ { "id": 1, "name": "CNRS formation entreprises", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/CNRS%20formation%20entreprises/?format=api" } ], "organisedByTeams": [ { "id": 6, "name": "CBiB", "url": "https://catalogue.france-bioinformatique.fr/api/team/CBiB/?format=api" } ], "logo_url": "https://services.cbib.u-bordeaux.fr/utils/logo_cbib.png", "updated_at": "2023-08-31T09:19:56.754683Z", "audienceTypes": [ "Graduate", "Professional (initial)" ], "audienceRoles": [ "Biologists", "Bioinformaticians" ], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "- Savoir expertiser et manipuler des données issues d'expériences Single Cell RNA-seq\r\n- Savoir mener une analyse différentielle à de multiples niveaux\r\n- Savoir intégrer des données complémentaires pour l'analyse Single Cell RNA-seq (spatial, trajectoire, cell communication, cell identification...)", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/650/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/653/?format=api" ] }, { "id": 406, "name": "Analyse de données de métabarcoding", "shortName": "Métabarcoding", "description": "Cette formation est dédiée à l’analyse de données de type “metabarcoding” issues de la technologie de séquençage Illumina. Nous aborderons les différentes étapes bioinformatiques nécessaires pour transformer les données de séquençage brutes en table d’abondances. Nous présenterons également les outils et méthodologies classiquement utilisés pour décrire la diversité observée et comparer les échantillons.\r\n\r\nA l’issue des 4 jours de formation, les stagiaires connaîtront le périmètre, les avantages et limites des analyses de données de séquençage amplicons (métabarcoding). Ils seront capables d’utiliser les outils de FROGS sur les jeux de données de la formation (16S et ITS) et sauront utiliser l’application Easy16S.\r\n\r\nIls seront capables d’identifier les outils et méthodes adaptées au cadre de leurs analyses. S’ils ont en leur possession un jeu de données à analyser, ils sont encouragés à venir avec celui- ci.\r\n\r\nProgramme :\r\n\r\n\r\nAnalyses bioinformatiques sous Galaxy\r\n\r\n Introduction générale sur les données amplicons\r\n Présentation et mise en application avec la suite FROGS du nettoyage des données, du clustering, de la détection de chimères, de l’assignation taxonomique et des étapes annexes\r\n Conclusion, limite des méthodes, outils compagnons\r\n\r\nAnalyses statistiques avec Easy16S\r\n\r\n Introduction générale\r\n Import, manipulation et visualisation des données\r\n Mesure de diversités : Unifrac, Bray-Curtis, etc.\r\n Ordination et réduction de dimension : MDS\r\n Clustering et Heatmap\r\n Comparaison d’échantillons : PERMANOVA, adonis\r\n\r\nMise en application sur données personnelles ou publiques", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_3697" ], "keywords": [ "Metabarcoding" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" } ], "organisedByTeams": [ { "id": 10, "name": "MIGALE", "url": "https://catalogue.france-bioinformatique.fr/api/team/MIGALE/?format=api" } ], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2026-02-12T10:53:42.895487Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Biologists", "Bioinformaticians" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "Cette formation est dédiée à l’analyse de données de type “metabarcoding” issues de la technologie de séquençage Illumina. Nous aborderons les différentes étapes bioinformatiques nécessaires pour transformer les données de séquençage brutes en table d’abondances. Nous présenterons également les outils et méthodologies classiquement utilisés pour décrire la diversité observée et comparer les échantillons.\r\n\r\nA l’issue des 4 jours de formation, les stagiaires connaîtront le périmètre, les avantages et limites des analyses de données de séquençage amplicons (métabarcoding). Ils seront capables d’utiliser les outils de FROGS sur les jeux de données de la formation (16S et ITS) et sauront utiliser l’application Easy16S.\r\n\r\nIls seront capables d’identifier les outils et méthodes adaptées au cadre de leurs analyses. S’ils ont en leur possession un jeu de données à analyser, ils sont encouragés à venir avec celui- ci.", "hoursPresentations": 12, "hoursHandsOn": 12, "hoursTotal": 24, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/792/?format=api" ] }, { "id": 315, "name": "Using sed and awk to modify large large text files", "shortName": "", "description": "Many analysis generate large result text files which have to be checked, merged, split, reduced. Several tools have been developed and are available on Unix to do this, including sed and AWK. During this course you will be trained to process large files with sed and AWK. Sed is tool enabling to select and process lines. You can easily insert, delete, modify, append lines to very large files with millions of lines. AWK will enable to perform more fine tuned file modifications based on columns. It includes also more mathematical and string functions. The course is based mainly on exercises with small sections presenting concepts and commands.", "homepage": "https://bioinfo.genotoul.fr/index.php/events/modify-and-extract-information-from-large-text-files-day-2-3/", "is_draft": false, "costs": [ "Non-academic: 550€ + 20% taxes (TVA)", "Academic but non-INRAE: 170 € + 20% taxes (TVA)", "For INRAE's staff: 150 € no VAT charged;" ], "topics": [ "http://edamontology.org/topic_3316" ], "keywords": [], "prerequisites": [ "Linux/Unix" ], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/338/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 37, "name": "MIAT - Mathématiques et Informatique Appliquées de Toulouse", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/MIAT%20-%20Math%C3%A9matiques%20et%20Informatique%20Appliqu%C3%A9es%20de%20Toulouse/?format=api" } ], "organisedByTeams": [ { "id": 22, "name": "Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-bioinfo/?format=api" } ], "logo_url": "https://bioinfo.genotoul.fr/wp-content/uploads/bioinfo_logo-rvb-petit.png", "updated_at": "2025-12-09T10:31:46.651968Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Biologists" ], "difficultyLevel": "Novice", "trainingMaterials": [ { "id": 146, "name": "Processing large files with sed awk - Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Processing%20large%20files%20with%20sed%20awk%20%20-%20Genotoul-bioinfo/?format=api" } ], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": false, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/478/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/479/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/611/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/631/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/669/?format=api" ] }, { "id": 360, "name": "Modélisation in silico de structures 3D de protéines. Prédiction de mutations, de fixation de ligands", "shortName": "Modélisation de structures 3D de protéines", "description": "Objectifs pédagogiques\r\nA l’issue de la formation, les stagiaires connaîtront les principales fonctionnalités du logiciel PyMOL. Ils seront capables de les appliquer pour visualiser leur système biologique d’intérêt, et d’effectuer des commandes basiques d’identification de poches catalytiques, de profilage de surface électrostatique, et de mutations d’acides aminés.\r\n\r\nAussi, ils connaîtront les bases et les outils de bioinformatique structurale et seront autonomes pour effectuer des modèles de protéines par prédiction (Alphafold2), calculer les meilleures poses de fixation de leur(s) ligand(s) (Autodock4) et reconstruire l’éventuel assemblage biologique.\r\n\r\nBonus : Ils s’approprieront ces outils avec une demi-journée dédiée à la modélisation de leur système d’étude : protéines, interactions protéines/ADN, arrimage de ligand, etc.\r\n\r\nProgramme\r\nVisualiser :\r\n* Maîtriser les bases de la visualisation des protéines en 3D avec PyMOL.\r\nComprendre :\r\n* Analyser des structures 3D de protéines (RX ou RMN).\r\n* Identifier des homologues avec HHpred.\r\n* Modéliser par prédiction sa protéine d’intérêt avec Alphafold2.\r\nPrédire :\r\n* Savoir calculer des meilleures poses de ligands avec Autodock.\r\n* Prédir et modéliser les mutations in silico.\r\n\r\n- Points forts et limites des différents outils\r\n- ️“hand- on tutorials”\r\n- Plus une session dédiée : «bring your own protein»", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_1317" ], "keywords": [ "Protein structures", "2D/3D", "Protein/protein interaction modelisation" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" } ], "organisedByTeams": [], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2024-01-18T14:36:41.185563Z", "audienceTypes": [ "Professional (initial)" ], "audienceRoles": [ "Biologists", "Bioinformaticians" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "A l’issue de la formation, les stagiaires connaîtront les principales fonctionnalités du logiciel PyMOL. Ils seront capables de les appliquer pour visualiser leur système biologique d’intérêt, et d’effectuer des commandes basiques d’identification de poches catalytiques, de profilage de surface électrostatique, et de mutations d’acides aminés.\r\n\r\nAussi, ils connaîtront les bases et les outils de bioinformatique structurale et seront autonomes pour effectuer des modèles de protéines par prédiction (Alphafold2), calculer les meilleures poses de fixation de leur(s) ligand(s) (Autodock4) et reconstruire l’éventuel assemblage biologique.\r\n\r\nBonus : Ils s’approprieront ces outils avec une demi-journée dédiée à la modélisation de leur système d’étude : protéines, interactions protéines/ADN, arrimage de ligand, etc.", "hoursPresentations": 4, "hoursHandsOn": 8, "hoursTotal": 12, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/585/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/699/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/783/?format=api" ] }, { "id": 359, "name": "Comparaison de génomes microbiens", "shortName": "Comparaison de génomes microbiens", "description": "Objectifs pédagogiques\r\nConnaître les concepts et les principales méthodes bioinformatiques pour comparer un jeu de données de génomes microbiens. Construire et évaluer la qualité d’un jeu de données. Savoir mettre en œuvre une comparaison de génomes et en interpréter les résultats.\r\n\r\nProgramme\r\n* Construction d’un jeu de données :\r\n* Téléchargement de données publiques\r\n* Evaluation de la qualité\r\n* Caractérisation de la diversité génomique\r\n* Stratégies de comparaison :\r\n* Construction de famille de protéines\r\n* Alignement de génomes complets\r\n* Analyse des résultats :\r\n o Notion de core et pan-génome\r\n o Notions élémentaires de phylogénomique\r\n o Visualisation et interprétation des résultats\r\n* Mise en pratique sur un jeu de données bactériens, utilisation des logiciels dRep et Roary sous Galaxy.", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_3299", "http://edamontology.org/topic_0622" ], "keywords": [ "Comparative genomics" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" } ], "organisedByTeams": [ { "id": 10, "name": "MIGALE", "url": "https://catalogue.france-bioinformatique.fr/api/team/MIGALE/?format=api" } ], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2024-01-18T14:13:49.810934Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Biologists", "Bioinformaticians" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "Connaître les concepts et les principales méthodes bioinformatiques pour comparer un jeu de données de génomes microbiens. \r\nConstruire et évaluer la qualité d’un jeu de données. \r\nSavoir mettre en œuvre une comparaison de génomes et en interpréter les résultats.", "hoursPresentations": 3, "hoursHandsOn": 3, "hoursTotal": 6, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/584/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/696/?format=api" ] }, { "id": 279, "name": "Annotation and analysis of prokaryotic genomes using the MicroScope platform", "shortName": "MicroScope training", "description": "In an effort to inform members of the research community about our annotation methods, to provide training for collaborators and other scientists who use the MicroScope platfom, and to inform scientific public on the analysis available in PkGDB (Prokaryotic Genome DataBase), we have developed a 4.5-day course in Microbial Genome Annotation and Comparative Analysis using the MaGe graphical interfaces.\r\n\r\nThis course will familiarize attendees with LABGeM’s annotation pipeline and the manual annotation software MaGe (Magnifying Genome) . No specific bioinformatics skill is required: detailed instruction on the algorithm developed in each annotation methods can be found in specific training courses on «Genomic sequences analysis». Here we focus on the general idea behind each method and, above all, the way you can interpret the corresponding results and combine them with other evidences in order to change or correct the current automatic functional annotation of a given gene, if necessary.\r\n\r\nThis course will also describe how to perform effective searches and analysis of procaryotic data using the graphical functionalities of the MaGe’s interfaces. Because of the numerous pre-computation available in our system (results of “common” annotation tools, synteny with all complete bacterial genomes, metabolic pathway reconstruction, fusion/fission events, genomic islands, …), many practical exercises allow attendees to get familiar with the use the MaGe graphical interfaces in order to efficiently explore these sets of results.", "homepage": "https://labgem.genoscope.cns.fr/professional-trainings/microscope-professional-trainings/training-annotation-analysis-of-prokaryotic-genomes-using-the-microscope-platform/", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_0085", "http://edamontology.org/topic_3301", "http://edamontology.org/topic_0797" ], "keywords": [], "prerequisites": [ "Licence" ], "openTo": "Everyone", "accessConditions": "External training sessions can also be scheduled on demand, in France or abroad. 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