Handles creating, reading and updating training events.

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            "name": "RNAseq de novo assembly",
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            "description": "This training session has been designed to give you an overview of the methods and tools used to de novo assemble transcriptomic short reads. You will learn how to pre-process your raw data (fastq files), how an assembler works and how to use it. Finally you will learn how to assess the quality of your assemblies in order to choose the best one. Organized jointly by the Sigenae and bioinfo genotoul platforms.\n",
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            "name": "Single-Cell : Transcriptomics, Spatial and Long reads",
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            "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.",
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            "name": "DU \"séquençage haut débit et maladies génétiques\"",
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            "description": "Acquérir une formation en séquençage nouvelle génération appliqué aux maladies génétiques mendéliennes,des technologies de séquençage et approches expérimentales possibles aux outils bio-informatiques utilisés pour le traitement des données brutes, l'identification de variations génétiques et l'interprétation des résultats. Se familiariser avec le système Unix/Linux, la ligne de commande et la gestion et l'analyse de données sur un serveur à distance. Connaître et savoir utiliser les principaux logiciels dédiés à l'analyse de données de séquençage nouvelle génération, de l'alignement des séquences brutes à l'annotation de variations génétiques. Maîtriser les principaux navigateurs, bases de données et outils de prédiction couramment utilisés en génétique humaine et médicale. Connaître les différentes applications possibles du séquençage nouvelle génération pour le diagnostic de maladies génétiques, les principales règles à suivre et paramètres à considérer pour assurer la qualité des données produites dans un contexte de laboratoire médical, et les considérations éthiques que soulève le séquençage nouvelle génération pour l'interprétation et le rendu des résultats.\n",
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            "name": "NGS et Cancer (Canceropôle) : Analyse DNASeq",
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            "name": "NGS et Cancer (Canceropôle) : Analyse A-RNASeq",
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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.",
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            "name": "Introduction to the use of a computing cluster",
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            "description": "Knowledge of the concepts and best practices for using the computing resources of the mesocenter cluster Clermont Auvergne in a bioinformatics context.\r\nBecome familiar with the work environment of the computing cluster, become autonomous in the use of its resources and learn to use a scheduler. \r\nPresentation of the resources accessible on the cluster (computing nodes, storage spaces, tools).\r\nConcept of jobs, queues and parallel computing.\r\nJob management (submission, follow-up, deletion).",
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            "updated_at": "2023-01-24T10:21:58.347905Z",
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            "name": "Cycle « Initiation à la bioinformatique » - Module 4/4 : Initiation à la reconstruction phylogénétique en biologie moléculaire",
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            "description": "Bilille propose un cycle de découverte de la bioinformatique à destination des chercheur·euses, enseignant·es-chercheur·euses, ingénieur·es, technicien·nes et doctorant·es en biologie. Aucun pré-requis en informatique n'est attendu.\r\nLe cycle est constitué de quatre modules de deux jours:\r\n- Banques de données et BLAST\r\n- Alignement de séquences\r\n- Prédiction de gènes et annotation de protéines\r\n- Initiation à la reconstruction phylogénétique en biologie moléculaire\r\nCes modules peuvent être suivis indépendamment, mais ont une cohérence. Suivre chaque module peut aider à une meilleure compréhension des modules suivants.\r\nLes fiches descriptives des différents modules sont accessibles sur le site web de Bilille.\r\nLes objectifs du module 4 sont :\r\n- Comprendre les grands principes de l’évolution moléculaire et de la reconstruction phylogénétique\r\n- Savoir construire des alignements informatifs pour une analyse phylogénétique\r\n- Comprendre les modèles phylogénétiques probabilistes, les méthodes d'inférence et savoir les appliquer\r\n- Savoir reconstruire des arbres phylogénétiques en Maximum de vraisemblance (ML) et par Inférence Bayésienne (BI)\r\n- Etre capable d’analyser avec un regard critique les résultats obtenus",
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            "accessConditions": "- Il est conseillé mais non nécessaire d’avoir suivi le module 1/4 « Banques de données et Blast » et le module 2/4 « Alignements de séquences » du cycle d'initiation à la bioinformatique.",
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            "name": "Analyse des données RNA-Seq sous l’environnement Galaxy",
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            "description": "Introduction à l'analyse des données RNA-Seq sous l’environnement Galaxy",
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            "name": "Formations Universitaire",
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            "description": "\nOrganisatrice et responsable du module « cellule épithéliale et cancer » de l’option B2PCR du M2 BCPP (Biologie Cellulaire, Physiologie et Pathologies : Université Paris 5, 11 et 12 (depuis 2010).\nCours et jury M1 et M2R Magistère Européen de Génétique – UE Génétique Moléculaire des Maladies Génétiques (depuis 2011).\n\n",
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            "description": "Co-organisation Atelier Cancéropole Ile de France « Bioinformatique, NGS et Cancer» (avril 2014 et Nov 2014)\n",
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