Handles creating, reading and updating training events.

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            "name": "Les langages de workflows pour une analyse bioinformatique reproductible / Workflow languages for reproducible bioinformatics analysis",
            "shortName": "WF4bioinfo",
            "description": "L’Institut Français de Bioinformatique (IFB) organise en partenariat avec iPOP-UP (représenté par EDC) une formation sur les langages de workflows en bioinformatique à destination des bioinformaticien·ne·s et des bioanalystes. La formation abordera les fondamentaux et les fonctionnalités avancées des deux langages Snakemake et Nextflow. Ces outils sont en effet devenus indispensables pour assurer la reproductibilité et l’efficacité des analyses bioinformatiques. La formation sera structurée en deux séquences :\r\n- une journée commune qui abordera les grands principes des gestionnaires de workflow, en particulier dans le domaine de la bioinformatique et en lien avec les infrastructures de calcul de type cluster et cloud proposés au sein de l’IFB \r\n- une  journée de session pratique  avec 1 atelier snakemake et 1 atelier nextflow en parallèle au choix des participants. Nous proposons aux participants qui le souhaitent de travailler sur leur propre workflow dans une approche “Bring your own script” avec l’aide de l’équipe pédagogique.",
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                "Linux - Basic Knowledge"
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            "updated_at": "2024-03-26T16:42:31.487108Z",
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            "shortName": "W4E",
            "description": "Processing, statistical analysis, and annotation of metabolomics data is a complex task for experimenters since it involves many steps and requires a good knowledge of both the methodology and software tools. The Workflow4Metabolomics.org (W4M) online infrastructure provides a user-friendly and high-performance environment with advanced computational modules for building, running, and sharing complete workflows for LC-MS, GC-MS, FIA and NMR analysis. Such features are of major values for teaching computational metabolomics to experimenters, and previous courses using W4M since 2014 have been very successful.",
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            "name": "SHORT-READ ALIGNMENT AND SMALL SIZE VARIANTS CALLING",
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            "description": "This training session, organized jointly with the Sigenae platform, is designed to introduce NGS data, in particular Illumina Solexa technologies with command line. You will discover the new sequence formats, the assembly formats and the known biases of these technologies. You will use mapping on reference genome software, polymorphisms detection with the GATK pipeline and alignment visualization software.\r\n\r\nThis training is focused on the practice. It consists of modules with a large variety of exercises:\r\n\r\nDay 1 (09:00 am to 12:30 am): Fastq format / Sequence quality. Read mapping.\r\nDay 1 (14:00 pm to 17:00 pm): SAM format. Visualisation.\r\nDay 2 (09:00 am to 17:00 am): Variant calling. VCF format. Variant annotation (SNPeff / SNPsift).\r\n \r\nThe session will take place in the room ‘salle de formation’ at INRAE center of Toulouse-Auzeville.\r\n\r\nPrerequisites: ability to use a Unix environment (see Unix training) and Cluster (see Cluster training).\r\n \r\nTool box: FastQC, BWA, Samtools, Picard tools, GATK, SnpSift / SnpEff, IGV.",
            "homepage": "https://bioinfo.genotoul.fr/index.php/events/alignment-and-small-size-variants-calling/",
            "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;"
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            "topics": [
                "http://edamontology.org/topic_2885",
                "http://edamontology.org/topic_0102"
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                "Cluster"
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                    "name": "MIAT - Mathématiques et Informatique Appliquées de Toulouse",
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            "updated_at": "2025-12-01T11:54:41.351028Z",
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            "id": 301,
            "name": "MIAPPE, Minimum Information About Plant Phenotyping Experiments",
            "shortName": "MIAPPE",
            "description": "The Minimal Information About Plant Phenotyping Experiments (MIAPPE, www.miappe.org) standard has been designed by ELIXIR, EMPHASIS and Bioversity international to guide plant scientist in the management of experimental data. Furthermore, since genetic studies relies on the integration and the linking between phenotype and genotype datasets, relevant section of MIAPPE are beginning to be used for genotyping standards.\r\nThis formation will cover a general introduction of the MIAPPE principles and some examples to illustrate different use cases on the usage of MIAPPE for plant phenotyping data standardization.",
            "homepage": "",
            "is_draft": false,
            "costs": [
                "Free"
            ],
            "topics": [
                "http://edamontology.org/topic_3298",
                "http://edamontology.org/topic_3572",
                "http://edamontology.org/topic_0219",
                "http://edamontology.org/topic_0625",
                "http://edamontology.org/topic_0780"
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                "Données"
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                "none"
            ],
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                    "name": "URGI - US1164",
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            "updated_at": "2025-11-28T13:19:07.566534Z",
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            "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",
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                "http://edamontology.org/topic_3299",
                "http://edamontology.org/topic_0797",
                "http://edamontology.org/topic_0622"
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            "keywords": [
                "Genome annotation",
                "Comparative genomics"
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                    "id": 88,
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            "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png",
            "updated_at": "2026-02-12T10:45:53.661422Z",
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            "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.",
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            "id": 291,
            "name": "Formation au logiciel R",
            "shortName": "Formation au logiciel R",
            "description": "Introduction au logiciel R et à son utilisation pour réaliser des graphiques et faire des analyses statistiques basiques en biologie. Introduction aux bibliothèques R utiles en biologie.",
            "homepage": "http://www.prabi.fr/spip.php?article273",
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            "updated_at": "2022-06-02T11:50:50.812642Z",
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            "learningOutcomes": "- Acquérir les compétences nécessaires à l’utilisation du logiciel R\r\n- Connaître les principales analyses statistiques nécessaires en biologie et les utiliser sous R\r\n- Réaliser des graphiques sous R\r\n- Connaitre les bibliothèques R utiles en Biologie",
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            "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",
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