Handles creating, reading and updating events.

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            "shortName": "Analyse de données NGS sous Galaxy 2026",
            "description": "Objectifs pédagogiques\r\nConnaître les concepts et méthodes bioinformatiques utilisés pour l’analyse primaire de données issues de séquenceurs nouvelle génération (NGS). Savoir effectuer un alignement sur un génome de référence, un assemblage de novo d’un génome bactérien\r\n\r\nProgramme\r\nThéorie\r\n* Présentation des différents types de technologies de séquençage (lectures longues et courtes)\r\n\r\nPratique : Analyse des données de séquençage d’un génome bactérien\r\n* Contrôle qualité\r\n* Assemblage de-novo\r\n* Nettoyage des données\r\n* Assemblage\r\n* Visualisation et statistiques sur l’assemblage\r\n* Alignement de lectures sur un génome de référence et visualisation\r\nTous les TPs seront réalisés sous l’environnement d’exécution de traitements Galaxy.",
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            "name": "Initiation à l’utilisation de Galaxy",
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            "description": "Objectifs pédagogiques :\r\nCette formation propose une introduction sur l’interface utilisateur et les fonctionnalités générales d’une plateforme Galaxy.\r\nA l’issue de la formation, les apprenants seront en mesure de :\r\n* connaître les caractéristiques et le fonctionnement d’un portail Galaxy,\r\n* appliquer sur des cas concrets en bioinformatique,\r\n* être autonome dans le traitement de fichiers et l’exécution d’outils.\r\n\r\nProgramme :\r\n* Prise en main d’un portail Galaxy\r\n* Utilisation de l’historique\r\n* Téléchargement des données à traiter\r\n* Manipulation de fichiers\r\n* Paramétrage et exécution d’outils\r\n* Récupération et visualisation de résultats",
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            "updated_at": "2026-02-12T10:34:28.195643Z",
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            "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.",
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            "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",
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            "updated_at": "2026-02-12T10:55:22.536502Z",
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                "http://edamontology.org/topic_0092"
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            "keywords": [
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            "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.",
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            "updated_at": "2026-03-26T14:14:19.457285Z",
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            "name": "FAIR Bioinfo Grand-Ouest",
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            "id": 798,
            "name": "Formation metabarcoding ABiMS SeBiMER",
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            "description": "Le séquençage à haut débit des amplicons de marqueurs taxonomiques tels l’ADN ribosomique, les gènes COI/COX ou les ITS a ouvert de nouveaux horizons dans l’étude des communautés de macro et micro-organismes et l’étude des écosystèmes.\r\n\r\nLe but de cette formation est, d’une part, d’introduire les concepts clés liés aux analyses de metabarcoding et de les illustrer au moyen de cas concrets d’analyse et, d’autre part, de former les utilisateurs aux traitements de données de metabarcoding au travers de l’usage du logiciel SAMBA (Noël et al., in submission).",
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            "homepage": "https://bioinfo.genotoul.fr/index.php/events/pangenome/",
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                "INRAE for INRAE's staff: 300 € no VAT charged",
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                    "id": 88,
                    "name": "BioinfOmics",
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                },
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            "description": "This training session is organized by the Genotoul bioinfo platform and aims at learning sequence analysis. This training session has been designed to familiarize yourself with the platform resources and its organization. You will learn to access the platform from your work station, what is an Linux environment and how to use it, how to create and manipulate files, how to transfer them from and to your personal computer.\r\n\r\nThis training is focused on practice. It consists of 3 modules with a large variety of exercises:\r\n\r\n- Connect to « genotoul » server (09:00 am to 10:30 am): Platform presentation, Linux basics, opening an user account, Putty installation, first connection.\r\n- Files and basics commands  (10:45 am to 12:00 pm): types of files and secure access, file manipulation commands, text editors and viewers, disk space management .\r\n- Transfers and file manipulation (14:00 pm to 17:00 pm): download/transfer, compress/uncompress, utility commands and data extraction, output redirections.",
            "homepage": "https://bioinfo.genotoul.fr/index.php/events/linux-2-2/",
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            "costs": [
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                "Academic but non-INRAE: 170 € + 20% taxes (TVA)",
                "For INRAE's staff: 150 € no VAT charged;"
            ],
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                "http://edamontology.org/topic_3316"
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            "logo_url": "https://bioinfo.genotoul.fr/wp-content/uploads/bioinfo_logo-rvb-petit.png",
            "updated_at": "2026-04-20T08:19:30.914358Z",
            "type": "Training course",
            "start_date": "2026-09-28",
            "end_date": "2026-09-28",
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            "name": "Galaxy Beyond Basics: Mastering Workflows, Automation, and Scalability 2026",
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            "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\nRequirements\r\n\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.",
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