Handles creating, reading and updating training materials.

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            "name": "HOVERGEN tutorial",
            "description": "HOVERGEN is a database containing homologous vertebrate protein and nucleotide sequences. It allows to easily select similar gene sequences from a wide range of vertebrates. Hence it becomes particularly useful in comparative genomics, phylogeny and evolutionary studies on a molecular level. HOVERGEN Clean contains only complete sequences which reattach to their family. Hence its library is smaller, but more reliable.\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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            "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": "Docker tutorial: Gene regulation",
            "description": "Get started with Docker!\nCreate a Docker account\nInstall Docker on your local host\nCreate shared repositories and download source data\nFetch the Docker image and run it with shared folders\nExecute the pipeline\n\nJVH / Mac\n",
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            "name": "Galaxy training material improvement and extension",
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            "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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            "name": "Galaxy: Initiation II",
            "description": "Galaxy II: common tools, quality control; alignment; data managment\n",
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            "description": "Galaxy docker integration\nEnable Galaxy to use BioContainers (Docker)\nGalaxy with Docker swarm\n",
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            "name": "From Biotea to Bioschemas: definition of profiles required to represent scholarly publications",
            "description": "\n \n\nFrom Biotea to Bioschemas: definition of profiles required to represent scholarly publications\n \n",
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            "description": "Find Rapidly OTU with Galaxy Solution\n",
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            "name": "Training on Galaxy : Metagenomics",
            "description": "Find Rapidly OTU with Galaxy Solution\n",
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            "name": "Exploring Pharmacogenomic LOD for Molecular Explanations of Gene-Drug Relationships",
            "description": "\n \n\nExploring Pharmacogenomic LOD for Molecular Explanations of Gene-Drug Relationships\n \n",
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            "name": "Enrichment and propagation of metagenomic experimental metadata",
            "description": "\n \n\nEnrichment and propagation of metagenomic experimental metadata\n \n",
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            "name": "200 billion sequences and counting: analysis, discovery and exploration of datasets with EBI Metagenomics",
            "description": "EBI metagenomics (EMG, https://www.ebi.ac.uk/metagenomics/) is a freely available hub for the analysis and exploration of metagenomic, metatranscriptomic, amplicon and assembly data. The resource provides rich functional and taxonomic analyses of user-submitted sequences, as well as analysis of publicly available metagenomic datasets held within the European Nucleotide Archive (ENA). EMG has recently undergone rapid expansion, with an over 10-fold increase in data volumes in the first 5 months of 2016. It now houses ~ 50k publicly available data sets, and represents one of the largest collections of analysed metagenomic data. As its data content has grown, EMG has increasingly become a platform for data discovery. To support this process, we have made a series of user-interface improvements, including the classification of projects by biome, presentation of results data for better visualisation and more convenient download, and provision of project level summary files. More recently, we have indexed project metadata for use with the EBI search engine, enabling exploration across different datasets. For example, users are able to search with a particular taxonomic lineage or protein function and discover the projects, samples and sequencing runs in which that lineage or function is found. This functionality allows users to explore associations between biomes, environmental conditions and organisms and functions (e.g., discovering protein coding sequences that correspond to certain enzyme families found in aquatic environments at a given temperature range). Here, we give an overview of the EMG data analysis pipeline and web site, and illustrate the use of the new search facility for data discovery.\n",
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            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_7/200_billions_sequences_and_counting_discovery_and_exploration_of_datasets_with_EBI_metagenomics/scormcontent/index.html",
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            "dateCreation": "2016-12-16",
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            "id": 89,
            "name": "Docker Tutorial",
            "description": "Docker is free software that automates the deployment of applications in software containers executant in isolation. A Docker container, away from traditional virtual machines, requires no separate operating system and not providing any but relies instead on the core functionality and uses the isolation of resources and namespaces separated to isolate the operating system as seen by the application.\n",
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            "name": "Initiation to Galaxy",
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            "name": "Variants: alignment and pre-treatment; GATK",
            "description": "DNA-seq Bioinformatics Analysis: from raw sequences to processed alignments\n",
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            "doi": null,
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            "name": "Development of BioJS components",
            "description": "\n \n\nDevelopment of BioJS components\n \n",
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