Handles creating, reading and updating training materials.

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            "name": "Galaxy Configuration Hierarchy",
            "description": "How to configure your local instance of Galaxy\n",
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            "id": 40,
            "name": "Galactic Database",
            "description": "How to choose a database for Galaxy and configure it\n",
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            "doi": null,
            "fileLocation": "https://igbmc.github.io/egdw2017/day4/admin/02-database/index.html",
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            "id": 39,
            "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": 38,
            "name": "(Proxy) Web Server Choices and Configuration",
            "description": "Installation and configuration of NGiNX for Galaxy\n",
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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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            "fileLocation": "https://igbmc.github.io/egdw2017/day4/admin/05-compute-cluster/index.html",
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            "id": 36,
            "name": "Galaxy Administration",
            "description": "How to use the administation panel of Galaxy\n",
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            "doi": null,
            "fileLocation": "https://igbmc.github.io/egdw2017/day4/admin/06-admin/index.html",
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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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            "doi": null,
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            "id": 34,
            "name": "Users, Groups, and Quotas in Galaxy",
            "description": "How to handle Users, Groups, and Quotas in Galaxy\n",
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            "doi": null,
            "fileLocation": "https://igbmc.github.io/egdw2017/day4/admin/08-quota-users-groups/index.html",
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            "id": 33,
            "name": "Docker for Beginners",
            "description": "What is Docker?\nBuilding an image\nBioShadock & Orchestration\n",
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            "doi": null,
            "fileLocation": "https://vdda.github.io/revealJS_test/docker_intro2.html",
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            "keywords": [
                "Docker"
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            "id": 45,
            "name": "Galaxy Visualisation - Slides",
            "description": "Questions\n\n\n\tHow can visualization plugins benefit science?\n\n\n\nObjectives\n\n\n\tImplement a first Galaxy visualization\n\tUnderstand the client side vs. server side principle\n\n",
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            "doi": null,
            "fileLocation": "http://galaxyproject.github.io/training-material/Dev-Corner/slides/visualizations.html",
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            "dateCreation": "2017-01-18",
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            "id": 46,
            "name": "BioBlend API",
            "description": "BioBlend module, a python library to use Galaxy API\n",
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            "doi": null,
            "fileLocation": "http://galaxyproject.github.io/training-material/Dev-Corner/slides/bioblend_api.html",
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                "Python",
                "API"
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            "dateCreation": "2017-01-18",
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        {
            "id": 43,
            "name": "Galaxy Interactive Tour",
            "description": "Questions\nWhat is a Galaxy Interactive Tour?\nHow to create a Galaxy Interactive Tour?\nObjectives\nDiscover what is a Galaxy Interactive Tour\nBe able to create a Galaxy Interactive Tour\nBe able to add a Galaxy Interactive Tour in a Galaxy instance\n",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "http://galaxyproject.github.io/training-material/Dev-Corner/slides/interactive_tour.html",
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            "topics": [],
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            "dateCreation": "2017-01-18",
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        {
            "id": 44,
            "name": "Galaxy Visualisation - Tutorial",
            "description": "Visualizations may be very helpful in understanding data better. There is a whole range of visualizations, from rather simple scatter and barplots up to projections of high dimensional data or even entire genomes. Many of these visualizations often require a lot of tweaking and changes in settings like zooming in and assigning colors, etc. Therefore, visualizations are ideally interactive, and changing settings is often an initial step in exploring data. For this reason it may be inconvenient to make use of static galaxy tools because it lacks these interactive features. For these situations Galaxy offers the option to create visualizations plugins, file format specific javascripts that integrate with the history menu, without making redundant copies of data.\nIn this tutorial we shall go through how this system works and create a simple visualization plugin. The tool will create a visualization of the number of aligned reads per chromosome of a BAM file, and we will discuss possible optimizations and advantages and disadvantages of the proposed implementation.\n",
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            "doi": null,
            "fileLocation": "http://galaxyproject.github.io/training-material/Dev-Corner/tutorials/visualizations",
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            "topics": [],
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            "dateCreation": "2017-01-18",
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            "id": 47,
            "name": "ToolShed upload and tool-iuc PR",
            "description": "Questions\nWhat is a Tool Shed?\nHow to install tools and workflows from a Tool Shed into a Galaxy instance?\nWhat are the Tool Shed repository types?\nHow to publish with Planemo?\nObjectives\nDiscover what is a Tool Shed\nBe able to install tools and workflows from a Tool Shed into a Galaxy instance\nBe able to publish tools with Planemo\n",
            "communities": [],
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            "doi": null,
            "fileLocation": "https://igbmc.github.io/egdw2017/day2/toolshed/index.html",
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            "dateCreation": "2017-01-17",
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            "id": 48,
            "name": "Tool development and integration into Galaxy",
            "description": "Questions:\nWhat is a tool for Galaxy?\nHow to build a tool/wrapper with the good practices?\nHow to deal with the tool environment?\n \nObjectives:\nDiscover what is a wrapper and its structure\nUse the Planemo utilities to develop a good wrapper\nDeal with the dependencies\nWrite functional tests\nMake a tool ready for publishing in a ToolShed\n",
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            "doi": null,
            "fileLocation": "http://galaxyproject.github.io/training-material/Dev-Corner/slides/tool_integration.html",
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            "dateCreation": "2017-01-16",
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        {
            "id": 50,
            "name": "Welcome and Introduction",
            "description": "\n \n\nIntroduction message of the EGDW 2017\n \n",
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            "doi": null,
            "fileLocation": "https://ressources.france-bioinformatique.fr/sites/default/files/introduction.pdf",
            "fileName": " introduction.pdf",
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            "dateCreation": "2017-01-16",
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        {
            "id": 66,
            "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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            "topics": [],
            "keywords": [
                "genomics"
            ],
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            "dateCreation": "2017-01-09",
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            "id": 76,
            "name": " Reconstructing genomes from metagenomes: The holy grail of microbiology",
            "description": "Shotgun metagenomics provides insights into a larger context of naturally occurring microbial genomes when short reads are assembled into contiguous DNA segments (contigs). Contigs are often orders of magnitude longer than individual sequences, offering improved annotations, and key information about the organization of genes in cognate genomes. Several factors affect the assembly performance, and the feasibility of the assembly-based approaches varies across environments. However, increasing read lengths, novel experimental approaches, advances in computational tools and resources, and improvements in assembly algorithms and pipelines render the assembly-based metagenomic workflow more and more accessible. The utility of metagenomic assembly remarkably increases when contigs are organized into metagenome-assembled genomes (MAGs). Often-novel MAGs frequently provide deeper insights into bacterial lifestyles that would otherwise remain unknown as evidenced by recent discoveries. The increasing rate of the recovery of MAGs presents new opportunities to link environmental distribution patterns of microbial populations and their functional potential, and transforms the field of microbiology by providing a more complete understanding of the microbial life, ecology, and evolution.\n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_5/Reconstructing_genomes_from_metagenomes_the_holy_grail_of_microbiology/scormcontent/index.html",
            "fileName": "missing.txt",
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            "keywords": [
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            "dateCreation": "2016-12-16",
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        {
            "id": 75,
            "name": "Fast filtering, mapping and assembly of 16S ribosomal RNA",
            "description": "The application of next-generation sequencing technologies to RNA or DNA directly extracted from a community of organisms yields a mixture of nucleotide fragments. The task to distinguish amongst these and to further categorize the families of ribosomal RNAs (or any other given marker) is an important step for examining the phylogenetic classification of the constituting species. In this perspective, we have developed  a complete bioinformatics suite, called MATAM, capable of handling large sets of  reads in a fast and accurate way. MATAM covers all steps of the analysis, from the identification of reads of interest in the raw sequencing data to the reconstruction of the  full-length sequences of the marker and alignment to a reference database for taxonomic assignment. Part of MATAM is based on the SortMeRNA software, also developed by the team.\n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_6/Fast_filtering_mapping_and_assembly_of_16S_rRNA/scormcontent/index.html",
            "fileName": "missing.txt",
            "topics": [],
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            "dateCreation": "2016-12-16",
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            "id": 69,
            "name": "New perspectives on nitrite-oxidizing bacteria - linking genomes to physiology",
            "description": "It is a generally accepted characteristic of the biogeochemical nitrogen cycle that nitrification is catalyzed by two distinct clades of microorganisms. First, ammonia-oxidizing bacteria and archaea convert ammonia to nitrite, which subsequently is oxidized to nitrate by nitrite-oxidizing bacteria (NOB). The latter were traditionally perceived as physiologically restricted organisms and were less intensively studied than other nitrogen-cycling microorganisms. This picture is contrasted by new discoveries of an unexpected high diversity of mostly uncultured NOB and a great physiological versatility, which includes complex microbe-microbe interactions and lifestyles outside the nitrogen cycle. Most surprisingly, close relatives to NOB perform complete nitrification (ammonia oxidation to nitrate), a process that had been postulated to occur under conditions selecting for low growth rates but high growth yields.\nThe existence of Nitrospira species that encode all genes required for ammonia and nitrite oxidation was first detected by metagenomic analyses of an enrichment culture for nitrogen-transforming microorganisms sampled from the anoxic compartment of a recirculating aquaculture system biofilter. Batch incubations and FISH-MAR experiments showed that these Nitrospira indeed formed nitrate from the aerobic oxidation of ammonia, and used the energy derived from complete nitrification for carbon fixation, thus proving that they indeed represented the long-sought-after comammox organisms. Their ammonia monooxygenase (AMO) enzymes were distinct from canonical AMOs, therefore rendering recent horizontal gene transfer from known ammonia-oxidizing microorganisms unlikely. Instead, their AMO displayed highest similarities to the “unusual” particulate methane monooxygenase from Crenothrix polyspora, thus shedding new light onto the function of this sequence group. This recognition of a novel AMO type indicates that a whole group of ammonia-oxidizing microorganisms has been overlooked, and will improve our understanding of the environmental abundance and distribution of this functional group. Data mining of publicly available metagenomes already indicated a widespread occurrence in natural and engineered environments like aquifers and paddy soils, and drinking and wastewater treatment systems.\n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_8/New_perspectives_on_nitrite_xidizing_bacteria/scormcontent/index.html",
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            "dateCreation": "2016-12-16",
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