Handles creating, reading and updating training materials.

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            "name": "Chip-seq: Functional Annotation tutorial",
            "description": "Global Objective\nGiven a set of ChIP-seq peaks annotate them in order to find associated genes, genomic categories and functional terms.\n",
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            "name": "Chip-seq: Introduction to the Workshop",
            "description": "Data visualization, quality control, normalization & peak calling\nPeak annotation\nFrom peaks to motifs\n",
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            "name": "Chip-seq: Motif Analysis Tutorial",
            "description": "Introduction\nGoal\nThe aim is to :\nGet familiar with motif analysis of ChIP-seq data.\nLearn de novo motif discovery methods.\nIn practice :\nMotif discovery with peak-motifs\nDifferential analysis\nRandom controls\n",
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            "name": "Chip-seq: Pattern Analysis tutorial",
            "description": "Goal\nThe aim is to :\nGet familiar with motif analysis of ChIP-seq data.\nLearn de novo motif discovery methods.\nIn practice :\nMotif discovery with peak-motifs\nDifferential analysis\nRandom controls\n",
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            "id": 117,
            "name": "Chip-seq: Peak calling tutorial",
            "description": "The aim is to :\nUnderstand how to process reads to obtain peaks (peak-calling).\nBecome familiar with differential analysis of peaks\nIn practice :\nObtain dataset from GEO\nAnalyze mapped reads\nObtain set(s) of peaks, handle replicates\nDifferential analysis of peak\n",
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            "id": 139,
            "name": "Cluster Slides",
            "description": "Slides for Cluster training (bioinfo genotoul facility)",
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            "fileLocation": "https://bioinfo.genotoul.fr/wp-content/uploads/Formation_cluster_SLURM_2024.pdf",
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                "Cluster"
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            "difficultyLevel": "Novice",
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                    "id": 22,
                    "name": "Genotoul-bioinfo",
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            "dateCreation": null,
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        {
            "id": 37,
            "name": "Connecting Galaxy to a compute cluster",
            "description": "Problems\nRunning jobs on the Galaxy server negatively impacts Galaxy UI performance\nEven adding one other host helps\nCan restart Galaxy without interrupting jobs\nSolution:\nConnecter Galaxy to a computing cluster\n",
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            "doi": null,
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                "Cluster"
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            "id": 93,
            "name": "Cross Taxa Tutorial",
            "description": "How query databases according to complex taxonomic critera\nCross-Taxa allows to retrieve gene families that are shared by a given set of taxa, or which are specific to a set of taxa. It is also possible to select genes families which are associated to a certain set of taxa but which are not found in a second set of taxa. Any taxonomic level can be used.\n",
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            "fileLocation": "http://www.prabi.fr/spip.php?article41",
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            "id": 22,
            "name": "CWL support in Galaxy",
            "description": "\n \n\nCWL support in Galaxy\n \n",
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            "doi": null,
            "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/videos/scorms/cwl-support-in-galaxy_f872/scormcontent/index.html",
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                "biohackaton 2018"
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            "dateCreation": "2019-03-21",
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            "id": 21,
            "name": "Data clearinghouse, validation and curation of BioSamples - ENA - Breeding API endpoints - MAR databases",
            "description": "\n \n\nData clearinghouse, validation and curation of BioSamples/ENA/Breeding API endpoints/MAR databases\n \n",
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            "doi": null,
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                "biohackaton 2018"
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            "dateCreation": "2019-03-21",
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            "id": 87,
            "name": "Deciphering the human intestinal tract microbiome using metagenomic computational methods",
            "description": "In 2010, the MetaHIT consortium published a 3.3M microbiota gene catalog generated by whole genome shotgun metagenomic sequencing, representing a mixture of bacteria, archaea, parasites and viruses coming from 124 human stool metagenomic samples [Qin et al, Nature 2010].\nHowever most of the genes were fragmented, taxonomically and functionally unknown, making it difficult to define and select biomarkers of interest for genome-wide association studies.\nSince that, this human gene catalog was improved multiple times, with the last update by [Li et al, Nature Biotechnology, 2014], which generated a 10M gene catalog using more than 1000 metagenomic samples and including some prevalent human microbe genome available at that time. Along with the catalog update, the scientific community developed new tools to challenge the complexity of this dataset and provided new ways to assemble, annotate, quantify and classify the genes coming from these catalogs.\nIn this talk we will discuss the main approaches related to the computational treatment of the different gene catalog other the time, illustrated by the different papers that deciphered step by step the hidden information of our microbiota and his link with our health.\n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_1/Deciphering_the_human_intestinal_tract_microbiome_using_metagenomic_computational_methods/scormcontent/index.html",
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            "topics": [],
            "keywords": [
                "Metagenomics"
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            "dateCreation": "2016-12-15",
            "dateUpdate": null,
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            "id": 35,
            "name": "Defining and importing genomes, Data Managers into Galaxy",
            "description": "Intro to built in datasets\nBuilt in data hierarchy\nSome problems\nData Managers\n",
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            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "https://igbmc.github.io/egdw2017/day4/admin/07-genomes-datamanagers/index.html",
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            "topics": [],
            "keywords": [
                "Galaxy"
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            "dateCreation": "2017-01-19",
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        },
        {
            "id": 49,
            "name": "Development in Galaxy",
            "description": "Galaxy is an open-source project. Everyone can contribute to its development with core Galaxy development, integration of softwares in Galaxy environment, ... Here, you will find some materials to learn how to contribute to Galaxy project.\n",
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            "doi": null,
            "fileLocation": "https://github.com/galaxyproject/training-material/tree/master/Dev-Corner",
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            "id": 20,
            "name": "Development of a catalog of federated SPARQL queries in the field of Rare Diseases",
            "description": "\n \n\nDevelopment of a catalog of federated SPARQL queries in the field of Rare Diseases\n \n",
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            "doi": null,
            "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/videos/scorms/development-of-a-catalog_f08f/scormcontent/index.html",
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        },
        {
            "id": 19,
            "name": "Development of a GA4GH-compliant, language-agnostic workflow execution service",
            "description": "\n \n\nDevelopment of a GA4GH-compliant, language-agnostic workflow execution service\n \n",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/videos/scorms/development-of-a-ga4gh_a1db/scormcontent/index.html",
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        },
        {
            "id": 18,
            "name": "Development of BioJS components",
            "description": "\n \n\nDevelopment of BioJS components\n \n",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/videos/scorms/development-of-bioj_292a/scormcontent/index.html",
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            "id": 60,
            "name": "Differential analysis of RNA-Seq data",
            "description": "Design, describe, explore and model\n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/R02-R03_slidesRoscoff_stats_HVaret.pdf",
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            "dateCreation": "2016-11-23",
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            "id": 61,
            "name": "Differential gene expression analysis : Practical part",
            "description": "RNA-seq: Differential gene expression analysis practical session\n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/R01b_EBA2016_TP_RNA-seq.pdf",
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            "dateCreation": "2016-11-22",
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        {
            "id": 110,
            "name": "DNA-seq analysis: From raw reads to processed alignments",
            "description": "Objectives:\nMapping the DNA-seq data to the reference genome\nProcess the alignments for the variant calling\n",
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            "doi": null,
            "fileLocation": "http://ecole-bioinfo-aviesan.sb-roscoff.fr/sites/ecole-bioinfo-aviesan.sb-roscoff.fr/files/files/elodie_girard-itmo2015_mapping_preprocess.pdf",
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            "id": 57,
            "name": "DNA - seq Bioinformatics Analysis",
            "description": "Detection of Copy Number Variations\n \n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/V07_ITMO_2016_EG_CNV.pdf",
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            "dateCreation": "2016-11-23",
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