Handles creating, reading and updating training events.

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            "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»",
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                    "id": 88,
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            "updated_at": "2024-01-18T14:36:41.185563Z",
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            "id": 275,
            "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": "RNASEQ ALIGNMENT, QUANTIFICATION AND TRANSCRIPT DISCOVERY WITH STATISTICS",
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            "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/",
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                "http://edamontology.org/topic_3308",
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            "id": 344,
            "name": "Analyses Single Cell RNA-seq (ScRNA-seq) avec R",
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            "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)",
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                "R",
                "NGS Sequencing Data Analysis"
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                "Basic knowledge of R",
                "R programming"
            ],
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            "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",
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            "logo_url": "https://services.cbib.u-bordeaux.fr/utils/logo_cbib.png",
            "updated_at": "2023-08-31T09:19:56.754683Z",
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                "Bioinformaticians"
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            "difficultyLevel": "Intermediate",
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            "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...)",
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            "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/",
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                "http://edamontology.org/topic_0797",
                "http://edamontology.org/topic_0085",
                "http://edamontology.org/topic_3301"
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                    "name": "Laboratory of Bioinformatics Analyses for Genomics and Metabolism",
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                    "id": 67,
                    "name": "University of Paris-Saclay",
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            "updated_at": "2022-06-02T11:50:50.812642Z",
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            "name": "Introduction au text-mining avec AlvisNLP",
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            "description": "Objectifs pédagogiques\r\nCette formation est dédiée à l’analyse de données textuelles (text-mining). L’objectif est l’acquisition des principales techniques pour la Reconnaissance d’Entités Nommées (REN) à partir de textes. Les entités nommées étudiées dans cette formation sont des objets ou concepts d’intérêts mentionnés dans les articles scientifiques ou les champs en texte libre (taxons, gènes, protéines, marques, etc.).\r\n\r\nLes participants vont acquérir les compétences pratiques nécessaires pour effectuer de façon autonome une première approche pour une application de text-mining. Le format est celui de Travaux Pratiques utilisant AlvisNLP, un outil pour la création de pipelines en text-mining développé par l’équipe Bibliome de l’unité MaIAGE. La formation s’adresse à des chercheurs et ingénieurs en (bio)-informatique ou en maths-info-stats appliquées\r\n\r\nProgramme\r\n* Présentation du text-mining et de la Reconnaissance des Entités Nommées (REN)\r\n* Travaux Pratiques sur des techniques de REN en utilisant AlvisNLP\r\n* Projection de lexiques\r\n* Application de patrons\r\n* Apprentissage automatique",
            "homepage": "https://documents.migale.inrae.fr/trainings.html",
            "is_draft": false,
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            "topics": [
                "http://edamontology.org/topic_0605",
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            "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_0091",
                "http://edamontology.org/topic_0622"
            ],
            "keywords": [],
            "prerequisites": [
                "Master"
            ],
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                }
            ],
            "logo_url": null,
            "updated_at": "2022-06-02T11:50:50.812642Z",
            "audienceTypes": [
                "Graduate"
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            "audienceRoles": [
                "Biologists"
            ],
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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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                "Free to academics"
            ],
            "topics": [
                "http://edamontology.org/topic_3697",
                "http://edamontology.org/topic_3174",
                "http://edamontology.org/topic_0637"
            ],
            "keywords": [
                "Galaxy"
            ],
            "prerequisites": [
                "Galaxy - Basic usage"
            ],
            "openTo": "Internal personnel",
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                },
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                    "id": 16,
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            "updated_at": "2024-02-08T11:23:11.090144Z",
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                    "id": 130,
                    "name": "Taxonomic Profiling and Visualization of Metagenomic Data",
                    "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Taxonomic%20Profiling%20and%20Visualization%20of%20Metagenomic%20Data/?format=api"
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                "https://catalogue.france-bioinformatique.fr/api/event/599/?format=api"
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        },
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            "id": 372,
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            "homepage": "",
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                "http://edamontology.org/topic_3382"
            ],
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                "Galaxy"
            ],
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                "Galaxy - Basic usage"
            ],
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            ],
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            ],
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            "updated_at": "2024-02-08T11:25:36.663764Z",
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            ],
            "difficultyLevel": "Novice",
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                    "id": 133,
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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": 316,
            "name": "IMGT® standards, databases, tools and web resources",
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            "description": "Presentation of IMGT® patterns and resources for the study of genes, expressed repertoires and three-dimensional structures of immunoglobulins (antibodies) and T cell receptors.",
            "homepage": "https://www.imgt.org/",
            "is_draft": false,
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                "http://edamontology.org/topic_3930",
                "http://edamontology.org/topic_3948"
            ],
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                "Protein structures",
                "Immune repertoire analysis",
                "Monoclonal antibody",
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            ],
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            ],
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                    "id": 54,
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            ],
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                "Bioinformaticians"
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                "https://catalogue.france-bioinformatique.fr/api/event/485/?format=api"
            ]
        },
        {
            "id": 384,
            "name": "EBAII - Ecole de Bioinformatique niveau intermédiaire",
            "shortName": "EBAII N2",
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            "homepage": "",
            "is_draft": false,
            "costs": [
                "Priced"
            ],
            "topics": [
                "http://edamontology.org/topic_3391",
                "http://edamontology.org/topic_3366",
                "http://edamontology.org/topic_0092",
                "http://edamontology.org/topic_3168",
                "http://edamontology.org/topic_0091"
            ],
            "keywords": [
                "Biostatistics",
                "Sequence analysis",
                "NGS Sequencing Data Analysis"
            ],
            "prerequisites": [],
            "openTo": "Everyone",
            "accessConditions": "La formation s’adresse à des biologistes directement impliqués dans des projets “Next Generation Sequencing” (NGS)  avec un niveau de base en ligne de commande, R, et (au choix) RNA-seq, ChIP-seq ou variants DNA-seq.",
            "maxParticipants": null,
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            "logo_url": "https://www.sb-roscoff.fr/sites/www.sb-roscoff.fr/files/styles/large/public/images/station-biologique-roscoff-roscoff-4404.jpg",
            "updated_at": "2024-12-05T07:33:48.573507Z",
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            ],
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                "https://catalogue.france-bioinformatique.fr/api/event/644/?format=api"
            ]
        },
        {
            "id": 382,
            "name": "Introduction à l'analyse de données transcriptomiques avec Galaxy",
            "shortName": "",
            "description": "L’objectif est de se familiariser avec les étapes d’analyses des données transcriptomiques ou RNA-seq avec référence pour extraire les gènes et fonctions différentiellement exprimés. 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\n\r\nAprès une introduction à la transcriptomique, une session pratique sur la plateforme Galaxy couvrira comment :\r\n- évaluer la qualité des données transcriptomiques,\r\n- aligner des données transcriptomiques sur un génome de référence,\r\n- estimer le nombre de séquences par gènes,\r\n- construire et faire une analyse d’expression différentielle des gènes\r\n- faire une analyse de l’enrichissement fonctionnel des gènes différentiellement exprimés",
            "homepage": "",
            "is_draft": false,
            "costs": [
                "Free to academics"
            ],
            "topics": [
                "http://edamontology.org/topic_3308",
                "http://edamontology.org/topic_1775",
                "http://edamontology.org/topic_0203",
                "http://edamontology.org/topic_3170"
            ],
            "keywords": [
                "Galaxy",
                "RNA-seq",
                "Transcriptomics (RNA-seq)"
            ],
            "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": [
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                },
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                    "name": "Université Clermont Auvergne",
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            ],
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            ],
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            ],
            "logo_url": "https://mesocentre.uca.fr/medias/photo/logoaubi-2019minus_1553844844490-jpg?ID_FICHE=41175",
            "updated_at": "2024-06-06T08:06:54.982689Z",
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                "Professional (continued)"
            ],
            "audienceRoles": [
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                "Life scientists",
                "Biologists"
            ],
            "difficultyLevel": "Novice",
            "trainingMaterials": [
                {
                    "id": 144,
                    "name": "Reference-based RNA-Seq data analysis with Galaxy",
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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",
            "hoursPresentations": 1,
            "hoursHandsOn": 7,
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            "personalised": null,
            "event_set": [
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        },
        {
            "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,
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                "Free to academics"
            ],
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                "http://edamontology.org/topic_3301",
                "http://edamontology.org/topic_0219",
                "http://edamontology.org/topic_0097"
            ],
            "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,
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                    "id": 16,
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            ],
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                    "id": 96,
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            ],
            "logo_url": "https://mesocentre.uca.fr/medias/photo/logoaubi-2019minus_1553844844490-jpg?ID_FICHE=41175",
            "updated_at": "2024-02-08T11:22:51.682232Z",
            "audienceTypes": [
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                "Graduate",
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                "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,
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            "personalised": null,
            "event_set": [
                "https://catalogue.france-bioinformatique.fr/api/event/598/?format=api"
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        },
        {
            "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": "",
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            ],
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                "http://edamontology.org/topic_0085",
                "http://edamontology.org/topic_3941",
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                    "name": "Université Clermont Auvergne",
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            "updated_at": "2024-02-08T11:22:23.706233Z",
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                    "id": 132,
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            "hoursHandsOn": 2,
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            "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png",
            "updated_at": "2024-01-18T14:43:04.391836Z",
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            "id": 287,
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            "description": "This course offers an introduction to ONT data analysis. It includes 5 issues: basecalling, reads quality control, assemblies and polishing/correction, contig quality and structural variants detection.",
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            "is_draft": false,
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                "Free"
            ],
            "topics": [
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                "http://edamontology.org/topic_0196",
                "http://edamontology.org/topic_3168"
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            "prerequisites": [
                "Linux and knowledge of NGS formats"
            ],
            "openTo": "Everyone",
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            "logo_url": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png",
            "updated_at": "2023-01-24T10:21:58.467251Z",
            "audienceTypes": [
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            "audienceRoles": [
                "Life scientists",
                "Biologists"
            ],
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                    "name": "SG-ONT-slides",
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            ],
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            "hoursPresentations": 6,
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        },
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            "id": 388,
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            "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"
            ],
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                "NGS Data Analysis",
                "Metagenomics"
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                "Cluster"
            ],
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                    "id": 82,
                    "name": "INRAE",
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            "logo_url": "http://bioinfo.genotoul.fr/wp-content/uploads/bioinfo_logo-rvb-petit.png",
            "updated_at": "2024-12-06T20:57:37.754921Z",
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                "Bioinformaticians"
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            "difficultyLevel": "Intermediate",
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        },
        {
            "id": 290,
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            "shortName": "NGS-analysis-cli",
            "description": "This hands-on course will teach bioinformatic approaches for analyzing Illumina sequencing data. Our goal is to introduce the command line skills you need to make the most of your NGS data. \r\nDuring this 4-day training we will first introduce the Linux environment, shell commands and basic R scripting.  And then we will focus on two NGS data analyses -- small RNA-seq and RNA-seq -- based on published datasets from the model organism Arabidopsis thaliana",
            "homepage": "https://www.ibmp.cnrs.fr/bioinformatics-trainings/",
            "is_draft": false,
            "costs": [
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            ],
            "topics": [
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                "http://edamontology.org/topic_3170",
                "http://edamontology.org/topic_2269",
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            ],
            "keywords": [],
            "prerequisites": [
                "none"
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            "openTo": "Internal personnel",
            "accessConditions": "This training is dedicated to academics working in a laboratory of Unistra/CNRS.",
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            ],
            "logo_url": null,
            "updated_at": "2024-01-22T14:51:37.215331Z",
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            ],
            "difficultyLevel": "Novice",
            "trainingMaterials": [],
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                "https://catalogue.france-bioinformatique.fr/api/event/589/?format=api",
                "https://catalogue.france-bioinformatique.fr/api/event/454/?format=api",
                "https://catalogue.france-bioinformatique.fr/api/event/660/?format=api"
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        },
        {
            "id": 295,
            "name": "Introduction to the use of a computing cluster",
            "shortName": "",
            "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).",
            "homepage": "https://mesocentre.uca.fr/",
            "is_draft": false,
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                "Free to academics"
            ],
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                "http://edamontology.org/topic_0091",
                "http://edamontology.org/topic_0605"
            ],
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                "Linux and knowledge of NGS formats"
            ],
            "openTo": "Internal personnel",
            "accessConditions": "Have an account on the Mesocentre UCA computing cluster (make a request if necessary on the site https://hub.mesocentre.uca.fr)\r\nAlternation of theoretical courses and practical work.\r\nCOME WITH A LAPTOP with an operational Eduroam connection.\r\nThe training is in French.",
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                    "name": "AuBi",
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            ],
            "logo_url": null,
            "updated_at": "2023-01-24T10:21:58.347905Z",
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                "Computer scientists"
            ],
            "difficultyLevel": "Novice",
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            "hoursHandsOn": 4,
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        },
        {
            "id": 320,
            "name": "Ecole Thématique de Bioinformatique Intégrative / Integrative Bioinformatics Training School",
            "shortName": "ETBII",
            "description": "Dans l’objectif de développer et fédérer des compétences en bioinformatique intégrative au sein de la communauté, l’IFB propose une nouvelle école thématique ayant un double objectif :\r\n- une montée en compétences théoriques et pratiques des bioinformaticiens,\r\n- la constitution de matériel pédagogique partagé sur ce sujet.\r\n\r\nCette école rassemble une équipe pédagogique de 10 personnes et pourra accueillir 30 participants pour sa première édition.\r\nL’ensemble de la formation reposera sur l’utilisation des ressources de calcul et de la plateforme pédagogique de l’Institut Français de Bioinformatique.\r\n\r\nObjectifs pédagogiques \r\n\r\nLa formation a pour but :\r\n- d’introduire les concepts de bases et les différents types d’approches utilisées en bioinformatique intégrative,\r\n- de proposer un approfondissement et une mise en pratique d’une de ces approches sur un/des jeux de données intégrant différents types de données omiques. Cette mise en oeuvre permettra de balayer l’ensemble des points d’attention d’une analyse intégrative,  de la préparation des données jusqu’à l’interprétation des résultats,\r\n- de créer, améliorer et partager les ressources pédagogiques (supports de formation, jeux de données, tutoriels) sur le thème de la bioinformatique intégrative.\r\n\r\nA la fin de cette formation les participants :\r\n- auront acquis un socle de connaissances générales en bioinformatique intégrative, \r\n- auront mis en oeuvre une analyse intégrative depuis la préparation des données jusqu’à l’analyse critique de résultats sur un/des jeux de données proposés lors de la formation,\r\n- auront contribué à constituer du matériel pédagogique partagé sur le sujet.\r\n\r\nPré-requis\r\n- Connaissances de base en Unix/shell, R et/ou Python \r\n- Autonomie dans la gestion de son poste de travail (installation de librairies et maîtrise des environnements de packaging type conda)",
            "homepage": "https://www.france-bioinformatique.fr/formation/etbii/",
            "is_draft": false,
            "costs": [
                "770 TTC pour les académiques  et 1540 TTC pour les privés"
            ],
            "topics": [
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                "http://edamontology.org/topic_3391",
                "http://edamontology.org/topic_3366"
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                "Dimension reduction",
                "Semantic web",
                "Integration of heterogeneous data",
                "Data Integration",
                "Tool integration"
            ],
            "prerequisites": [
                "Linux and knowledge of NGS formats",
                "Basic knowledge of R"
            ],
            "openTo": "Everyone",
            "accessConditions": "Cette formation est ouverte à toute la communauté mais cette première édition s’adresse en priorité à des bioinformaticien·ne·s des plateformes membres et équipes associées IFB souhaitant contribuer à la constitution de matériel pédagogique pour se préparer au montage de futures formations sur ce thème.",
            "maxParticipants": 30,
            "contacts": [
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            ],
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                    "name": "CNRS - IFB",
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                    "name": "IFB Core",
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            ],
            "logo_url": "https://drive.google.com/file/d/1a_fuOgqOU812GRJLApGMofJ87WTlxDI0/view?usp=sharing",
            "updated_at": "2024-12-03T15:46:48.157120Z",
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            "audienceRoles": [
                "Life scientists",
                "Computer scientists",
                "Bioinformaticians"
            ],
            "difficultyLevel": "Novice",
            "trainingMaterials": [],
            "learningOutcomes": "A la fin de cette formation les participants :\r\n- auront acquis un socle de connaissances générales  en bioinformatique intégrative, \r\n- auront mis en oeuvre une analyse intégrative depuis la préparation des données jusqu’à l’analyse critique de résultats sur un/des jeux de données proposés lors de la formation,\r\n- auront contribué à constituer du matériel pédagogique partagé sur le sujet.",
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            ]
        }
    ]
}