Handles creating, reading and updating training materials.

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            "name": "16S Microbial Analysis with mothur",
            "description": "This tutorial covers the questions:\r\n- What is the effect of normal variation in the gut microbiome on host health?\r\n\r\nAt 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",
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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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            "id": 29,
            "name": "Adding bioschemas markup to data repository",
            "description": "\n \n\nAdding bioschemas markup to data repository\n \n",
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            "id": 28,
            "name": "Alternative episodes for the 4 Open Source Software",
            "description": "\n \n\nAlternative episodes for the 4 Open Source Software (4OSS) lesson focused on different Open Source technologies: Github, Docker, Jupyter Notebook and so on\n \n",
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            "id": 97,
            "name": "Analysis of community composition data using phyloseq",
            "description": "Learn about and become familiar with phyloseq R package for the analysis of microbial census data\n",
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            "fileLocation": "http://genoweb.toulouse.inra.fr/~formation/15_FROGS/April2016/R_phyloseq/phyloseq_formation_toulouse_201604.pdf",
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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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            "id": 98,
            "name": "A Quick and focused overview of R data types and ggplot2 syntax",
            "description": "R and RStudio overview.\n",
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            "fileLocation": "http://genoweb.toulouse.inra.fr/~formation/15_FROGS/April2016/R_phyloseq/ModuleIntroInitR.pdf",
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            "id": 91,
            "name": "A Simple Phylogenetic Tree Construction (part 1)",
            "description": "Understand the method behind constructing a phylogenetic tree from the search for sequences to the analysis of the tree.\nGet to grips with various bio-informatic software (BLAST, CLUSTALw, SeaView and Phylo_win).\n",
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            "fileLocation": "http://www.prabi.fr/spip.php?article59",
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            "id": 90,
            "name": "A Simple Phylogenetic Tree Construction (part 2)",
            "description": "Understand the method used in identifying an unknown sequence.\nUnderstand the limitations of this method\nGet to grips with various software (CLUSTALw, SeaView, Phylo_win and Njplot)\n",
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            "doi": null,
            "fileLocation": "http://www.prabi.fr/spip.php?article60",
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            "id": 81,
            "name": "Assessing microbial biogeography by using a metagenomic approach",
            "description": "Soils are highly complex ecosystems and are considered as one of the Earth’s main reservoirs of biological diversity. Bacteria account for a major part of this biodiversity, and it is now clear that such microorganisms have a key role in soil functioning processes. However, environmental factors regulating the diversity of below-ground bacteria still need to be investigated, which limits our understanding of the distribution of such bacteria at various spatial scales. The overall objectives of this study were: (i) to determine the spatial patterning of bacterial community diversity in soils at a broad scale, and (ii) to rank the environmental filters most influencing this distribution.\nThis study was performed at the scale of the France by using the French Soil Quality Monitoring Network. This network includes more than 2,200 soil samples along a systematic grid sampling. For each soil, bacterial diversity was characterized using a pyrosequencing approach targeting the 16S rRNA genes directly amplified from soil DNA, obtaining more than 18 million of high-quality sequences.\nThis study provides the first estimates of microbial diversity at the scale of France, with for example, bacterial richness ranging from 555 to 2,007 OTUs (on average: 1,289 OTUs). It also provides the first extensive map of bacterial diversity, as well as of major bacterial taxa, revealing a bacterial heterogeneous and spatially structured distribution at the scale of France. The main factors driving bacterial community distribution are the soil physico-chemical properties (pH, texture...) and land use (forest, grassland, crop system...), evidencing that bacterial spatial distribution at a broad scale depends on local filters such as soil characteristics and land use when regarding the community (quality, composition) as a whole. Moreover, this study also offers a better evaluation of the impact of land uses on soil microbial diversity and taxa, with consequences in terms of sustainability for agricultural systems.\n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_4/Assessing_microbial_biogeography_by_using_a_metagenomic_approach/scormcontent/index.html",
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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": 129,
            "name": "Bacterial Genome Annotation",
            "description": "This tutorial covers the questions:\r\n- Which genes are on a draft bacterial genome?\r\n- Which other genomic components can be found on a draft bacterial genome?\r\n\r\nAt the end of the tutorial, learners would be able to:\r\n- Run a series of tools to annotate a draft bacterial genome for different types of genomic components\r\n- Evaluate the annotation\r\n- Process the outputs to format them for visualization needs\r\n- Visualize a draft bacterial genome and its annotations",
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            "fileLocation": "https://training.galaxyproject.org/training-material/topics/genome-annotation/tutorials/bacterial-genome-annotation/tutorial.html",
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                "http://edamontology.org/topic_3301",
                "http://edamontology.org/topic_0219"
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            "keywords": [
                "Bacterial isolate",
                "Annotation",
                "Galaxy"
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                "Professional (continued)"
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            "id": 46,
            "name": "BioBlend API",
            "description": "BioBlend module, a python library to use Galaxy API\n",
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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",
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            "id": 24,
            "name": "bio-tools - EDAM drop-in hackathon - discussions",
            "description": "bio.tools, EDAM drop-in hackathon and discussions\n",
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            "id": 23,
            "name": "Building a semantic search engine for biology publications using event stream processing",
            "description": "\n \n\nBuilding a semantic search engine for biology publications using event stream processing\n \n",
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            "name": "Chip-seq Analysis",
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            "id": 114,
            "name": "Chip Seq: Annotation and visualization Lesson",
            "description": "How to add biological meaning to peaks\n",
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            "doi": null,
            "fileLocation": "http://dputhier.github.io/EBA_2015_ChIP-Seq/slides/ChIP-seq_annotation_MD_2015.pdf",
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            "id": 113,
            "name": "Chip Seq: Annotation and visualization Tutorial",
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            "id": 111,
            "name": "Chip-seq: Discovering motifs in peaks with RSAT",
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