Handles creating, reading and updating training materials.

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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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            "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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            "id": 105,
            "name": "Exploring Microscope Platform",
            "description": "\n \n\nHow to use the Microscope Platform to annotate and analyze microbial genomes.\n \n",
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            "doi": null,
            "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/Cours_MicroScope_mars2016_1-17.pdf",
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            "topics": [],
            "keywords": [
                "genomics",
                "Annotation",
                "Sequence analysis",
                "Transcriptomics",
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            "dateCreation": "2016-03-01",
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            "id": 104,
            "name": "Exploring microbiomes with the MicroScope Platform",
            "description": "This module is separated in different courses:\nMicroScope: General overview, Keyword search and gene cart functionalities\n\n\n\n\n\n\n\n\n\n\n\n\nFunctional annotation of microbial genomes\n\n\n\n\n\n\n\n\nFunctional annotation of microbial genomes: Prediction of enzymatic functions\n\n\n\n\n\n\n\n\nRelational annotation of bacterial genomes: synteny\n\n\n\n\n\n\n\n\nAutomatic functional assignation and expert annotation of genes\n\n\n\n\n\n\n\n\nRelational annotation of bacterial genomes: phylogenetic profiles\n\n\n\n\n\n\n\n\nRelational annotation of bacterial genomes: pan-genome analysis\n\n\n\n\n\n\n\n\nRelational annotation of bacterial genomes: metabolic pathways\n\n\n\n\nSyntactic re-annotation of public microbial genomes\n\n\n\n\nSyntactic annotation of microbial genomes\n\n\n\n\n \n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/Cours_MicroScope_mars2016_18-125.pdf",
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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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                "Annotation"
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        {
            "id": 100,
            "name": "REPET: TEdannot Tutorial",
            "description": "TEannot is able to annote a genome using DNA sequences library. This library can be a predicted TE library built by TEdenovo\n",
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            "doi": null,
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        {
            "id": 99,
            "name": " PASTEClassifier Tutorial",
            "description": "The PASTEClassifier (Pseudo Agent System for Transposable Elements Classification) is a transposable element (TE) classifier searching for structural features and similarity to classify TEs (  Hoede C. et al. 2014 )\n",
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                "Transposons"
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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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            "doi": null,
            "fileLocation": "http://genoweb.toulouse.inra.fr/~formation/15_FROGS/April2016/R_phyloseq/ModuleIntroInitR.pdf",
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            "topics": [],
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                "R",
                "Statistics",
                "Graphical analysis"
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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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            "doi": null,
            "fileLocation": "http://genoweb.toulouse.inra.fr/~formation/15_FROGS/April2016/R_phyloseq/phyloseq_formation_toulouse_201604.pdf",
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        },
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            "id": 96,
            "name": "Training on Galaxy : Metagenomics",
            "description": "Find Rapidly OTU with Galaxy Solution\n",
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            "doi": null,
            "fileLocation": "http://genoweb.toulouse.inra.fr/~formation/15_FROGS/April2016/FROGS_april_2016_Formation.pdf",
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                "Galaxy"
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        },
        {
            "id": 95,
            "name": "Exercices on Galaxy: metagenomics",
            "description": "Find Rapidly OTU with Galaxy Solution\n",
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            "doi": null,
            "fileLocation": "http://genoweb.toulouse.inra.fr/~formation/15_FROGS/April2016/FROGS_april_2016_Pratice.pdf",
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            "topics": [],
            "keywords": [
                "Metagenomics",
                "Galaxy"
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        },
        {
            "id": 94,
            "name": "Searching for sequence: Tutorial",
            "description": "Quick Search is dedicated to a quick search for sequences or sequence families in the databases available on the PBIL server. It is an alternative to WWW Query which allows more complex queries. Quick Search allows you to retrieve sequences or sequence families associated to a single word without specifying what is this word. You can enter indifferently a keyword, a sequence name or accession number, or a taxa name.\n",
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            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "http://www.prabi.fr/spip.php?article17",
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            "topics": [],
            "keywords": [
                "genomics",
                "Pattern recognition"
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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",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "http://www.prabi.fr/spip.php?article41",
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        },
        {
            "id": 92,
            "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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            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "http://www.prabi.fr/spip.php?article58",
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                "genomics",
                "proteomics"
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            ],
            "dateCreation": null,
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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",
            "communities": [],
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            "doi": null,
            "fileLocation": "http://www.prabi.fr/spip.php?article59",
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            "keywords": [
                "Phylogenetics"
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                    "id": 19,
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            ],
            "dateCreation": null,
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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",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "http://www.prabi.fr/spip.php?article60",
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            "keywords": [
                "Phylogenetics"
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            ],
            "dateCreation": null,
            "dateUpdate": null,
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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",
            "communities": [],
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            "doi": null,
            "fileLocation": "http://bioserv.rpbs.univ-paris-diderot.fr/tutorials.html",
            "fileName": "missing.txt",
            "topics": [],
            "keywords": [
                "Docker"
            ],
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            "dateCreation": null,
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        },
        {
            "id": 88,
            "name": "From Samples to Data : Assuring Downstream Analysis with Upstream Planning",
            "description": "Metagenomic studies have gained increasing popularity in the years since the introduction of next generation sequencing. NGS allows for the production of millions of reads for each sample without the intermediate step of cloning. However, just as in the past, the quality of the data generate by this powerful technology depends on sample preparation, library construction and the selection of appropriate sequencing technology and sequencing depth. Here we explore the different variables involved in the process of preparing samples for sequencing analysis including sample collection, DNA extraction and library construction. We also examine the various sequencing technologies deployed for routine metagenomic analysis and considerations for their use in different model systems including humans, mouse and the environment. Future developments such as long-reads will also be discussed to provide a complete picture of important aspects prior to data analyses which play a critical role in the success of metagenomic studies.\n",
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            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_1/From_Samples_to_Data_Assuring_Downstream_Analysis_with_Upstream_Planning/scormcontent/index.html",
            "fileName": "missing.txt",
            "topics": [],
            "keywords": [
                "Metagenomics"
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            "dateCreation": null,
            "dateUpdate": null,
            "licence": "CC BY-NC-ND",
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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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            "elixirPlatforms": [],
            "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",
            "fileName": "missing.txt",
            "topics": [],
            "keywords": [
                "Metagenomics"
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            "audienceTypes": [],
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            "dateCreation": "2016-12-15",
            "dateUpdate": null,
            "licence": "CC BY-NC-ND",
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                "https://catalogue.france-bioinformatique.fr/api/userprofile/713/?format=api"
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        },
        {
            "id": 86,
            "name": "Gut metagenomics in cardiometabolic diseases",
            "description": "Cardio-metabolic and Nutrition-related diseases (CMDs) represent an enormous burden for health care. They are characterized by very heterogeneous phenotypes progressing with time. It is virtually impossible to predict who will or will not develop cardiovascular comorbidities. There is a clear need to intervene earlier in the natural cycle of the disease, before irreversible tissue damages develop. Predictive tools still remain elusive and environmental factors (food, nutrition, physical activity and psychosocial factors) play major roles in the development of these interrelated pathologies. Poor nutritional environment and lifestyle also promote health deterioration resulting in CMD progression. In the last few years, the characterization of the gut microbiome (i.e. collective bacteria genome) and gut-derived molecules (i.e. metabolites, lipids, inflammatory molecules) has opened up new avenues for the generation of fundamental knowledge regarding putative shared pathways in CMD. The gut microbiome is likely to have an even greater impact than genetic factors given its close relationship with environmental factors. In metabolic disorders, the discoveries that low bacterial gene richness associates with cardiovascular risks stimulate encourage these developments. Due to the complexity of the gut microbiome, and its interactions with human (host) metabolism as well as with the immune system, it is only through integrative analyses where metabolic network models are used as scaffold for analysis that it will be possible to identify markers and shared pathways, which will contribute to improve patient stratification and develop new modes of patient care.\n",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_2/Gut_metagenomics_in_cardiometabolic_diseases/scormcontent/index.html",
            "fileName": "missing.txt",
            "topics": [],
            "keywords": [
                "Metagenomics"
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            "dateCreation": "2016-12-15",
            "dateUpdate": null,
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        },
        {
            "id": 85,
            "name": "Exploiting collisions between DNA molecules to characterize the genomic structures of complex communities",
            "description": "Meta3C is an experimental and computational approach that exploits the physical contacts experienced by DNA molecules sharing the same cellular compartments. These collisions provide a quantitative information that allows interpreting and phasing the genomes present within complex mixes of species without prior knowledge. Not only the exploitation of chromosome physical 3D signatures hold interesting premises regarding solving the genome sequences from discrete species, but it also allows assigning mobile elements such as plasmids or phages to their hosts.\n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_2/Exploiting_collisions_between_DNA_molecules_to_characterize_the_genomic_structures_of_complex_communities/scormcontent/",
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            "topics": [],
            "keywords": [
                "Metagenomics"
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            "dateCreation": "2016-12-15",
            "dateUpdate": null,
            "licence": "CC BY-NC-ND",
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}