Handles creating, reading and updating training events.

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            "name": "Introduction à l'analyse de données de métabarcoding 16S avec Galaxy",
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            "description": "L’objectif de cette formation est de se familiariser avec les étapes et les outils pour analyses de données de métabarcoding 16S. Nous proposons au personnel non-bioinformaticien de les accompagner dans la prise en main de ces étapes d’analyses en utilisant la plateforme de bio-analyse Galaxy. \r\n\r\nAprès une introduction au métabarcoding 16S, une session pratique sur la plateforme Galaxy couvrira comment :\r\n- évaluer la qualité de données de métabarcoding ,\r\n- analyser et visualiser une communauté microbienne à partir de données de métabarcoding 16S",
            "homepage": "",
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                "http://edamontology.org/topic_0637"
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            "keywords": [
                "Galaxy",
                "Metabarcoding"
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            "openTo": "Internal personnel",
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            "maxParticipants": null,
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                    "id": 16,
                    "name": "Université Clermont Auvergne",
                    "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/Universit%C3%A9%20Clermont%20Auvergne/?format=api"
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                    "id": 96,
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            "updated_at": "2024-02-08T11:18:18.945136Z",
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                "Graduate",
                "Professional (initial)",
                "Professional (continued)"
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            ],
            "difficultyLevel": "Novice",
            "trainingMaterials": [
                {
                    "id": 131,
                    "name": "16S Microbial Analysis with mothur",
                    "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/16S%20Microbial%20Analysis%20with%20mothur/?format=api"
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            ],
            "learningOutcomes": "At the end of the tutorial, learners would be able to:\r\n- Analyze of 16S rRNA sequencing data using the mothur toolsuite in Galaxy\r\n- Using a mock community to assess the error rate of your sequencing experiment\r\n- Visualize sample diversity using Krona and Phinch",
            "hoursPresentations": 1,
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        },
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            "id": 369,
            "name": "Introduction au profilage taxonomique et visualisation de communautés microbiennes à partir de données métagénomiques avec Galaxy",
            "shortName": "",
            "description": "L’objectif de cette formation est de se familiariser avec les étapes et les outils d’analyse de données de métagénomiques pour caractériser et visualiser des communautés microbiennes. 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 métagénomique, une session pratique sur la plateforme Galaxy couvrira comment :\r\n- assigner des taxons à des données de métagénomiques,\r\n- visualiser une communauté microbienne à partir d’assignations taxonomiques",
            "homepage": "",
            "is_draft": false,
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            ],
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                "http://edamontology.org/topic_3174",
                "http://edamontology.org/topic_0637"
            ],
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                "Galaxy"
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                "Galaxy - Basic usage"
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            "maxParticipants": null,
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            ],
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                {
                    "id": 130,
                    "name": "Taxonomic Profiling and Visualization of Metagenomic Data",
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            ],
            "learningOutcomes": "At the end of the tutorial, learners would be able to:\r\n- Explain what taxonomic assignment is\r\n- Explain how taxonomic assignment works\r\n- Apply Kraken and MetaPhlAn to assign taxonomic labels\r\n- Apply Krona and Pavian to visualize results of assignment and understand the output\r\n- Identify taxonomic classification tool that fits best depending on their data",
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        },
        {
            "id": 382,
            "name": "Introduction à l'analyse de données transcriptomiques avec Galaxy",
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            "homepage": "",
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            ],
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                "http://edamontology.org/topic_3170",
                "http://edamontology.org/topic_3308"
            ],
            "keywords": [
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                "RNA-seq",
                "Transcriptomics (RNA-seq)"
            ],
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            "openTo": "Internal personnel",
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            ],
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            ],
            "difficultyLevel": "Novice",
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                    "id": 144,
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                },
                {
                    "id": 145,
                    "name": "Introduction to Transcriptomics",
                    "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Introduction%20to%20Transcriptomics/?format=api"
                }
            ],
            "learningOutcomes": "At the end of the tutorial, learners would be able to:\r\n- Check a sequence quality report generated by FastQC for RNA-Seq data\r\n- Explain the principle and specificity of mapping of RNA-Seq data to an eukaryotic reference genome\r\n- Select and run a state of the art mapping tool for RNA-Seq data\r\n- Evaluate the quality of mapping results\r\n- Describe the process to estimate the library strandness\r\n- Estimate the number of reads per genes\r\n- Explain the count normalization to perform before sample comparison\r\n- Construct and run a differential gene expression analysis\r\n- Analyze the DESeq2 output to identify, annotate and visualize differentially expressed genes\r\n- Perform a gene ontology enrichment analysis\r\n- Perform and visualize an enrichment analysis for KEGG pathways",
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        },
        {
            "id": 373,
            "name": "Introduction à la segmentation des nucléoles et extraction de caractéristiques avec Galaxy",
            "shortName": "",
            "description": "L’objectif de cette formation est de se familiariser avec les premières étapes à l’analyse d’images. Nous proposons au personnel non-bioinformaticien de les accompagner dans la prise en main des ces étapes d’analyses en utilisant la plateforme de bio-analyse Galaxy. \r\n\r\nAprès une introduction à l’analyse d’images, une session pratique sur la plateforme Galaxy couvrira comment :\r\n- télécharger des images depuis  un répertoire d’images publiques,- segmenter une image\r\n- extraire les caractéristiques des images",
            "homepage": "",
            "is_draft": false,
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            ],
            "topics": [
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                "http://edamontology.org/topic_3382"
            ],
            "keywords": [
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            ],
            "prerequisites": [],
            "openTo": "Internal personnel",
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            "maxParticipants": null,
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            ],
            "logo_url": "https://mesocentre.uca.fr/medias/photo/logoaubi-2019minus_1553844844490-jpg?ID_FICHE=41175",
            "updated_at": "2024-02-08T11:28:41.024508Z",
            "audienceTypes": [
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                "Graduate",
                "Professional (initial)",
                "Professional (continued)"
            ],
            "audienceRoles": [
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            ],
            "difficultyLevel": "Novice",
            "trainingMaterials": [
                {
                    "id": 134,
                    "name": "Nucleoli segmentation and feature extraction using CellProfiler",
                    "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Nucleoli%20segmentation%20and%20feature%20extraction%20using%20CellProfiler/?format=api"
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            ],
            "learningOutcomes": "At the end, learners would be able to:\r\n- How to download images from a public image repository.\r\n- How to segment cell nuclei using CellProfiler in Galaxy.\r\n- How to segment cell nucleoli using CellProfiler in Galaxy.\r\n- How to extract features for images, nuclei and nucleoli.",
            "hoursPresentations": 1,
            "hoursHandsOn": 2,
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        },
        {
            "id": 367,
            "name": "Introduction à l'analyse de données de séquençage avec contrôle qualité et alignement sur un génome de référence avec Galaxy",
            "shortName": "",
            "description": "L’objectif de cette formation est de se familiariser avec les premières étapes communes à toutes les analyses de données de séquençage : le contrôle qualité des données et l’alignement sur un génome de référence. Nous proposons au personnel non-bioinformaticien de les accompagner dans la prise en main des ces étapes d’analyses en utilisant la plateforme de bio-analyse Galaxy. \r\n\r\nAprès une introduction aux données de séquençage, une session pratique sur la plateforme Galaxy couvrira comment :\r\n- évaluer la qualité de données de séquençage,\r\n- améliorer la qualité de données de séquençage\r\n- aligner des données sur un génome de référence",
            "homepage": "",
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                "http://edamontology.org/topic_0102"
            ],
            "keywords": [
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            ],
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            ],
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                "Graduate",
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                "Professional (continued)"
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            ],
            "difficultyLevel": "Novice",
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                    "id": 128,
                    "name": "Mapping with Galaxy",
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                },
                {
                    "id": 127,
                    "name": "Quality Control with Galaxy",
                    "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Quality%20Control%20with%20Galaxy/?format=api"
                }
            ],
            "learningOutcomes": "At the end of the tutorial, learners would be able to:\r\n- Assess short reads FASTQ quality using FASTQE 🧬😎 and FastQC\r\n- Assess long reads FASTQ quality using Nanoplot and PycoQC\r\n- Perform quality correction with Cutadapt (short reads)\r\n-  Summarise quality metrics MultiQC\r\n- Process single-end and paired-end data\r\n- Define what mapping is\r\n- Perform mapping of reads on a reference genome\r\n- Evaluate the mapping output",
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        },
        {
            "id": 372,
            "name": "Introduction à l'analyse d’images avec Galaxy",
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            "homepage": "",
            "is_draft": false,
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            ],
            "topics": [
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                "http://edamontology.org/topic_3382"
            ],
            "keywords": [
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            "maxParticipants": null,
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            ],
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            ],
            "difficultyLevel": "Novice",
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                    "name": "Introduction to image analysis using Galaxy",
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            ],
            "learningOutcomes": "At the end of the tutorial, learners would be able to:\r\n- How to handle images in Galaxy.\r\n- How to perform basic image processing in Galaxy",
            "hoursPresentations": 1,
            "hoursHandsOn": 2,
            "hoursTotal": 3,
            "personalised": null,
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        },
        {
            "id": 366,
            "name": "Initiation à l’utilisation de la plateforme de bio-analyse Galaxy",
            "shortName": "",
            "description": "L’objectif est de se familiariser avec l’interface utilisateur de Galaxy. \r\n\r\nAprès une introduction à Galaxy, une session pratique sur la plateforme Galaxy couvrira comment :\r\n- Importer des données\r\n- Identifier des outils\r\n- Faire une analyse\r\n- Gérer un historique\r\n- Créer un workflow",
            "homepage": "",
            "is_draft": false,
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            ],
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            ],
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                "Galaxy"
            ],
            "prerequisites": [],
            "openTo": "Internal personnel",
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            "maxParticipants": null,
            "contacts": [
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                "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api"
            ],
            "elixirPlatforms": [],
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            "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"
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            ],
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                    "name": "AuBi",
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                    "name": "Mésocentre Clermont-Auvergne",
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            ],
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            "updated_at": "2024-02-08T10:47:23.782242Z",
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            ],
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                    "name": "Galaxy 101 for everyone",
                    "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Galaxy%20101%20for%20everyone/?format=api"
                }
            ],
            "learningOutcomes": "At the end of the tutorial, learners would be able to:\r\n- Assess short reads FASTQ quality using FASTQE 🧬😎 and FastQC\r\n- Assess long reads FASTQ quality using Nanoplot and PycoQC\r\n- Perform quality correction with Cutadapt (short reads)\r\n-  Summarise quality metrics MultiQC\r\n- Process single-end and paired-end data\r\n- Define what mapping is\r\n- Perform mapping of reads on a reference genome\r\n- Evaluate the mapping output",
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            "hoursHandsOn": 2,
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            "personalised": null,
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                "https://catalogue.france-bioinformatique.fr/api/event/592/?format=api"
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        },
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            "id": 371,
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                "http://edamontology.org/topic_0085",
                "http://edamontology.org/topic_1775",
                "http://edamontology.org/topic_3941"
            ],
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            ],
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                "Galaxy - Basic usage"
            ],
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                },
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                    "id": 16,
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            ],
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            ],
            "logo_url": "https://mesocentre.uca.fr/medias/photo/logoaubi-2019minus_1553844844490-jpg?ID_FICHE=41175",
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            ],
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            ],
            "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",
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}