Handles creating, reading and updating training materials.

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            "name": "Introduction to python",
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            "fileName": "training-python-for-biology",
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                "Python Language"
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            "id": 134,
            "name": "Nucleoli segmentation and feature extraction using CellProfiler",
            "description": "This tutorial covers the following questions:\r\n- How do I run an image analysis pipeline on public data using CellProfiler?\r\n- How do I analyse the DNA channel of fluorescence siRNA screens?\r\n- How do I download public image data into my history?\r\n- How do I segment and label cell nuclei?\r\n- How do I segment nucleoli (as the absence of DNA)?\r\n- How do I combine nuclei and nucleoli into one segmentation mask?\r\n- How do I extract the background of an image?\r\n- How do I relate the nucleoli to their parent nucleus?\r\n- How do I measure the image and object features?\r\n- How do I measure the image quality?\r\n\r\nAt the end of the tutorial, 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.",
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            "fileLocation": "https://training.galaxyproject.org/training-material/topics/imaging/tutorials/tutorial-CP/tutorial.html",
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            "id": 130,
            "name": "Taxonomic Profiling and Visualization of Metagenomic Data",
            "description": "This tutorial covers the questions:\r\n- Which species (or genera, families, …) are present in my sample?\r\n- What are the different approaches and tools to get the community profile of my sample?\r\n- How can we visualize and compare community profiles?\r\n\r\nAt 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",
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            "name": "Galaxy III: Visualization",
            "description": "Visualization of Next Generation Sequencing Data using the Integrative Genomics Viewer (IGV)\n",
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            "doi": null,
            "fileLocation": "https://www.france-bioinformatique.fr/sites/default/files/G06_TP_IGV_2016.pdf",
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            "name": "Galaxy Handlers",
            "description": "Galaxy is a web application that uses handlers to perform actions.\nThere are two main types of actions that are carried out by handlers:\nRespond to user requests; These actions are carried out by web handlers\nManage the execution of tools; These actions are performed by job handlers.\nBy default, Galaxy is configured to run a single handler that handles both user queries and jobs.\nDepending on the number of users accessing your Galaxy instance or the number of jobs you need to manage you may need to start web handlers or additional job handlers.\n",
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            "id": 135,
            "name": "training RNASEQ Bioinfo part",
            "description": "Cette formation a pour but de vous aider à traiter les séquences courtes issues des plates-formes de séquençage Illumina. Vous y découvrirez les formats de séquences et d’alignement les biais connus et mettrez en œuvre des logiciels d'alignement épissé sur génome de référence, la recherche de nouveaux gènes, de nouveaux transcrits et la quantification de l'expression de ces gènes et transcrits.",
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            "id": 11,
            "name": "Improve Shiny and RStudio integration within Galaxy using Galaxy Interactive Environment",
            "description": "\n \n\nImprove Shiny and RStudio integration within Galaxy using Galaxy Interactive Environment\n \n",
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            "id": 27,
            "name": "Application of RDF-based models and tools for enhancing interoperable",
            "description": "\n \n\nApplication of RDF-based models and tools for enhancing interoperable use of biomedical resources\n \n",
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            "doi": null,
            "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/videos/scorms/application-of-rdf_8aed/scormcontent/index.html",
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            "id": 136,
            "name": "training RNASeq biostat part",
            "description": "This course is part of the INRAE training session about “bioinformatics and biostatistics analysis of RNA-seq data” and of the Biostatistics platform “Initiation à LA statistique, niveau 4”. \r\nThe material provided on the present webpage is related to the biostatistics part and covers the following topics:\r\n\r\nR and RStudio\r\ndesign of experiments\r\nvariability\r\ncount data normalization\r\ndifferential analysis\r\nThe material has originally been prepared by Ignacio Gonzales, Annick Moisan and myself. The class has already been taught by these persons but also by Gaëlle Lefort and Jérôme Mariette.\r\n\r\nPre-requisites: A background in R programming is necessary for this class. Before the class, please download the course material and install R, RStudio and the packages as described below. To produce high quality figures, I will use ggplot2 for plots but will not enter into details about the ggplot2 syntax. If you are not familiar with it, you can just use these command lines or switch to base plots instead.",
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            "doi": null,
            "fileLocation": "https://www.nathalievialaneix.eu/teaching/rnaseq.html",
            "fileName": "rnaseq.html",
            "topics": [],
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            "audienceTypes": [],
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            "difficultyLevel": "Intermediate",
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            "id": 137,
            "name": "Linux slides",
            "description": "Slides for linux session (genotoul bioinfo facility)",
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            "doi": null,
            "fileLocation": "https://bioinfo.genotoul.fr/wp-content/uploads/Formation_LINUX_GenoToul_2024.pdf",
            "fileName": "Formation_LINUX_GenoToul_2024.pdf",
            "topics": [],
            "keywords": [
                "Operating systems"
            ],
            "audienceTypes": [],
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            "difficultyLevel": "Novice",
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            "dateCreation": null,
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            "licence": "CC BY-NC-SA",
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            "id": 26,
            "name": "Assessing the FAIRness of Training Materials",
            "description": "\n \n\nAssessing the FAIRness of Training Materials\n \n",
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            "doi": null,
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            "id": 25,
            "name": "Bioconda packaging of the Regulatory Sequence Analysis Tools (RSAT)",
            "description": "\n \n\nBioconda packaging of the Regulatory Sequence Analysis Tools (RSAT)\n \n",
            "communities": [],
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            "doi": null,
            "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/videos/scorms/bioconda-packaging_e168/scormcontent/index.html",
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            "id": 82,
            "name": "Sequencing 6000 chloroplast genomes : the PhyloAlps project",
            "description": "Biodiversity is now commonly described by DNA based approches. Several actors are currently using DNA to describe biodiversity, and most of the time they use different genetic markers that is hampering an easy sharing of the accumulated knowledges. Taxonomists rely a lot on the DNA Barcoding initiative, phylogeneticists often prefer markers with better phylogenic properties, and ecologists, with the coming of the DNA metabarcoding, look for a third class of markers easiest to amplify from environmental DNA. Nevertheless they have all the same need of the knowledge accumulated by the others. But having different markers means that the sequecences have been got from different individuals in differente lab, following various protocoles. On that base, building a clean reference database, merging for each species all the available markers becomes a challenge. With the phyloAlps project we implement genome skimming at a large  scale and propose it as a new way to set up such universal reference database usable by taxonomists, phylogeneticists, and ecologists. The Phyloalps project is producing for each species of the Alpine flora at least a genome skim composed of six millions of 100bp sequence reads. From such data it is simple to extract all chloroplastic, mitochondrial and nuclear rDNA markers commonely used. Moreover, most of the time we can get access to the complete chloroplast genome sequence and to a shallow sequencing of many nuclear genes. This methodes have already been successfully applied to algeae, insects and others animals. With the new single cell sequencing methods it will be applicable to most of the unicellular organisms. The good question is now : Can we consider the genome skimming as the next-generation DNA barcode ?\n",
            "communities": [],
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_3/Sequencing_6000_chloroplast_genomes_the_PhyloAlps_project/scormcontent/",
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            "topics": [],
            "keywords": [
                "Metagenomics"
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            "dateCreation": "2016-12-16",
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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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            "doi": null,
            "fileLocation": "http://www.prabi.fr/spip.php?article41",
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                "genomics"
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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",
            "communities": [],
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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": 101,
            "name": "REPET: TEdenovo tutorial",
            "description": "The TEdenovo pipeline follows a philosophy in three first steps:\nDetection of repeated sequences (potential TE)\nClustering of these sequences\nGeneration of consensus sequences for each cluster, representing the ancestral TE\n",
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            "doi": null,
            "fileLocation": "https://urgi.versailles.inra.fr/Tools/REPET/TEdenovo-tuto",
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            "keywords": [
                "genomics",
                "Annotation"
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            "dateCreation": null,
            "dateUpdate": null,
            "licence": "CeCILL",
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        },
        {
            "id": 119,
            "name": "Visualization of NGS data with IGV",
            "description": "Visualisation of next-gen sequencing data with Integrative Genomics Viewer\n",
            "communities": [],
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            "doi": null,
            "fileLocation": "http://ecole-bioinfo-aviesan.sb-roscoff.fr/sites/ecole-bioinfo-aviesan.sb-roscoff.fr/files/files/IGV-Roscoff-Septembre2015.pdf",
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                "Data visualization",
                "NGS"
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        },
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            "id": 17,
            "name": "Enrichment and propagation of metagenomic experimental metadata",
            "description": "\n \n\nEnrichment and propagation of metagenomic experimental metadata\n \n",
            "communities": [],
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            "doi": null,
            "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/videos/scorms/enrichment-and-propagation_4418/scormcontent/index.html",
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        },
        {
            "id": 120,
            "name": "Initiation to Galaxy",
            "description": "DNA-sequence analysis: from raw reads to variants calling within the galaxy environement.\n",
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            "doi": null,
            "fileLocation": "http://ecole-bioinfo-aviesan.sb-roscoff.fr/sites/ecole-bioinfo-aviesan.sb-roscoff.fr/files/files/GALAXY-TP-INITIATION-Roscoff-Septembre2015.pdf",
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        {
            "id": 106,
            "name": "Genomic copy number Tutorial",
            "description": "We will analyze the copy number variations of a human tumor (parotid gland carcinoma), limited to the chr17, from a WES (whole-exome sequencing) experiment. All genomic coordinates correspond to the 2009 build of the reference human genome (hg19 / GRC37).\n",
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            "doi": null,
            "fileLocation": "http://ecole-bioinfo-aviesan.sb-roscoff.fr/sites/ecole-bioinfo-aviesan.sb-roscoff.fr/files/files/CNV_TD_guidelines_BJ.pdf",
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                "Structural genomics",
                "Copy number"
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