Handles creating, reading and updating training events.

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                    "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/Universit%C3%A9%20Clermont%20Auvergne/?format=api"
                }
            ],
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                    "id": 87,
                    "name": "AuBi",
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                    "id": 96,
                    "name": "Mésocentre Clermont-Auvergne",
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            ],
            "logo_url": "https://mesocentre.uca.fr/medias/photo/logoaubi-2019minus_1553844844490-jpg?ID_FICHE=41175",
            "updated_at": "2024-02-08T11:23:11.090144Z",
            "audienceTypes": [
                "Undergraduate",
                "Graduate",
                "Professional (initial)",
                "Professional (continued)"
            ],
            "audienceRoles": [
                "Researchers",
                "Life scientists",
                "Biologists"
            ],
            "difficultyLevel": "Novice",
            "trainingMaterials": [
                {
                    "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"
                }
            ],
            "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",
            "hoursPresentations": 1,
            "hoursHandsOn": 2,
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            "personalised": null,
            "event_set": [
                "https://catalogue.france-bioinformatique.fr/api/event/599/?format=api"
            ]
        },
        {
            "id": 370,
            "name": "Introduction à l'analyse de données de métabarcoding 16S avec Galaxy",
            "shortName": "",
            "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": "",
            "is_draft": false,
            "costs": [
                "Free to academics"
            ],
            "topics": [
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                "http://edamontology.org/topic_0637"
            ],
            "keywords": [
                "Galaxy",
                "Metabarcoding"
            ],
            "prerequisites": [],
            "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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                    "id": 16,
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                    "id": 96,
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            "updated_at": "2024-02-08T11:18:18.945136Z",
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                "Graduate",
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                "Professional (continued)"
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            ],
            "difficultyLevel": "Novice",
            "trainingMaterials": [
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                    "id": 131,
                    "name": "16S Microbial Analysis with mothur",
                    "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/16S%20Microbial%20Analysis%20with%20mothur/?format=api"
                }
            ],
            "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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                "https://catalogue.france-bioinformatique.fr/api/event/595/?format=api"
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        },
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            "id": 371,
            "name": "Introduction à l'analyse de données métatranscriptomiques avec Galaxy",
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            "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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                "http://edamontology.org/topic_0085",
                "http://edamontology.org/topic_3941",
                "http://edamontology.org/topic_1775"
            ],
            "keywords": [
                "Galaxy"
            ],
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                "Galaxy - Basic usage"
            ],
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            ],
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                    "id": 132,
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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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        },
        {
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            "homepage": "",
            "is_draft": false,
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                "Free to academics"
            ],
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                "http://edamontology.org/topic_3382"
            ],
            "keywords": [
                "Galaxy"
            ],
            "prerequisites": [
                "Galaxy - Basic usage"
            ],
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            "maxParticipants": null,
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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": "2024-02-08T11:25:36.663764Z",
            "audienceTypes": [
                "Undergraduate",
                "Graduate",
                "Professional (initial)",
                "Professional (continued)"
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            "audienceRoles": [
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                "Life scientists",
                "Biologists"
            ],
            "difficultyLevel": "Novice",
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                {
                    "id": 133,
                    "name": "Introduction to image analysis using Galaxy",
                    "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Introduction%20to%20image%20analysis%20using%20Galaxy/?format=api"
                }
            ],
            "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": 373,
            "name": "Introduction à la segmentation des nucléoles et extraction de caractéristiques avec Galaxy",
            "shortName": "",
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            "homepage": "",
            "is_draft": false,
            "costs": [
                "Free to academics"
            ],
            "topics": [
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                "http://edamontology.org/topic_3382"
            ],
            "keywords": [
                "Galaxy"
            ],
            "prerequisites": [],
            "openTo": "Internal personnel",
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            "maxParticipants": null,
            "contacts": [
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            ],
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                    "id": 96,
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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": "2024-02-08T11:28:41.024508Z",
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                "Graduate",
                "Professional (initial)",
                "Professional (continued)"
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                "Biologists"
            ],
            "difficultyLevel": "Novice",
            "trainingMaterials": [
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                    "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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            "personalised": null,
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        },
        {
            "id": 374,
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            "homepage": "https://pf-bird.univ-nantes.fr/training/cluster/",
            "is_draft": false,
            "costs": [
                "Free"
            ],
            "topics": [],
            "keywords": [],
            "prerequisites": [
                "Linux - Basic Knowledge"
            ],
            "openTo": "Everyone",
            "accessConditions": "Have an account on the BiRD cluster.",
            "maxParticipants": 20,
            "contacts": [
                "https://catalogue.france-bioinformatique.fr/api/userprofile/596/?format=api"
            ],
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            "organisedByTeams": [
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                    "name": "BiRD",
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                }
            ],
            "logo_url": null,
            "updated_at": "2024-02-08T15:56:16.390499Z",
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            "event_set": [
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        },
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            "id": 375,
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            "homepage": "https://pf-bird.univ-nantes.fr/training/rnaseq/",
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            ],
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                }
            ],
            "logo_url": null,
            "updated_at": "2024-02-08T16:07:26.347245Z",
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            ]
        },
        {
            "id": 376,
            "name": "Train-the-Trainer",
            "shortName": "TtT",
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            "accessConditions": "",
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            "contacts": [
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                "https://catalogue.france-bioinformatique.fr/api/userprofile/556/?format=api",
                "https://catalogue.france-bioinformatique.fr/api/userprofile/639/?format=api"
            ],
            "elixirPlatforms": [
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            ],
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                {
                    "id": 6,
                    "name": "Elixir-FR",
                    "url": "https://catalogue.france-bioinformatique.fr/api/organisation/Elixir-FR/?format=api"
                },
                {
                    "id": 63,
                    "name": "TAGC",
                    "url": "https://catalogue.france-bioinformatique.fr/api/organisation/TAGC/?format=api"
                }
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            "organisedByTeams": [
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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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            "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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            "homepage": "https://abims.sb-roscoff.fr/module/r_dataviz",
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            "id": 380,
            "name": "INTRODUCTION TO PYTHON",
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            "description": "The Toulouse Genotoul bioinformatics platform, organizes a 2 days long training course for non computer scientist and biologists aiming at learning the foundation of Python programming. In this training you will learn the basics of programming (variables, functions, control structures such as “if” condition, “for” loop”), writing simple programs which read files, and write results to others. The training course does not require any knowledge in programming, but basic Linux/bash commands are required (cd, ls).\r\n\r\nThis training focuses on practice. It consists of modules with a large variety of exercises described hereunder (PROVISIONAL SCHEDULE):\r\n\r\nUsing a Jupyter notebook (Day 1).\r\nUsing variables (Day 1).\r\nBasic operations and functions (Day 1).\r\nReading a file, writing to a file (Day 1).\r\nCharacter string manipulation (Day 1).\r\nLists and dictionaries (Day 2).\r\nThe if and for controls (Day 2).\r\nBases of algorithms (Day 2).",
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            "id": 381,
            "name": "HOW TO RUN A NF-CORE NEXTFLOW WORKFLOW ON GENOTOUL ?",
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            "description": "This training session is organized by the Genotoul bioinfo platform and aims at learning nf-core workflow submission, error understanding, resuming jobs and ressource reservation. We will present and practice:\r\n\r\nthe Nextflow software\r\nthe nf-core community and pipelines\r\nWhat is a singularity image ?\r\nWhere are installed the nf-core workflows ? Which version do I use ?\r\nHow to run a workflow and which config file is used ?\r\nWhich kind of error I can get ?\r\nHow to resume failed jobs?\r\nHow to handle genome indexes ?\r\nHow to monitor my process and then well configure my workflow ?\r\nHow do you best adjust CPU and RAM reservations?\r\nThis is NOT a bioinformatic training on a particular workflow or a training on how to develop a workflow.\r\n\r\nThis training is focused on practice. It consists of several modules with a large variety of exercises:\r\n\r\nStart at 09:00 am\r\nEnd at 17:00 pm",
            "homepage": "https://bioinfo.genotoul.fr/index.php/events/how-to-run-a-nf-core-nextflow-workflow-on-genotoul-2/",
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            "id": 382,
            "name": "Introduction à l'analyse de données transcriptomiques avec Galaxy",
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            "id": 383,
            "name": "Artificial Intelligence and Machine Learning in Life Sciences: from foundations to applications",
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            "description": "Artificial intelligence (AI) has permeated our lives, transforming how we live and work. Over the past few years, a rapid and disruptive acceleration of progress in AI has occurred, driven by significant advances in widespread data availability, computing power and machine learning. Remarkable strides were made in particular in the development of foundation models - AI models trained on extensive volumes of unlabelled data. Moreover, given the large amounts of omics data that are being generated and made accessible to researchers due to the drop in the cost of high-throughput technologies, analysing these complex high-volume data is not trivial, and the use of classical statistics can not explore their full potential. As such, Machine Learning (ML) and Artificial Intelligence (AI) have been recognized as key opportunity areas, as evidenced by a number of ongoing activities and efforts throughout the community.\r\n\r\nHowever, beyond the technological advances, it is equally important that the individual researchers acquire the necessary knowledge and skills to fully take advantage of Machine Learning. Being aware of the challenges, opportunities and constraints that ML applications entail, is a critical aspect in ensuring high quality research in life sciences.\r\n\r\nRecognizing this need, this week-long training will bring together experts from four ELIXIR Nodes and deliver a hands-on, high-intensity course available for members from all ELIXIR Nodes.\r\n\r\nLearners will be guided across the various steps in Machine Learning, from the foundational concepts, through the deep learning and generative AI techniques, closely complemented by insights into the existing reporting (DOME Recommendations) and regulatory frameworks (EU AI Act).",
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