Handles creating, reading and updating training materials.

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            "name": "Docker for Beginners",
            "description": "What is Docker?\nBuilding an image\nBioShadock & Orchestration\n",
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            "doi": null,
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                "Docker"
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            "dateCreation": "2017-01-19",
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            "name": "Processing_large_files_with_sed_awk_2024",
            "description": "This “Sed and AWK to modify large text files” training session is organized by the Genotoul bioinfo platform.\r\n\r\nThe Linux sed command is a powerful and very fast text editor without an interface. Sed can select, substitute, add, delete, and modify text in files and streams. Sed relies heavily on regular expressions for pattern matching and text selection. We’ll manipulate regexes and the sed command to modify and filter several type of file often used in bioinformatics.\r\n\r\nAWK enables to easily process columns in large text files but is also a quite powerfull programming language. This training session aims at introducing you AWK principles. You will learn about variables, operators and functions useful to manipulate very large files. \r\n\r\nFor example you can use AWK to generate your unix command lines to be launched on the cluster. AWK enables to process millions of lines in text files. The course includes short feature presentations between long hands-on sessions in which you will be able to understand the global ideas as well as details.",
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            "doi": null,
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                "Professional (continued)"
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            "difficultyLevel": "Intermediate",
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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,
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            "name": "Third generation sequencing :  the revolution of long reads",
            "description": "Introduction on sequencing: available technologies, library types, applications ...\n",
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            "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",
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            "difficultyLevel": "Intermediate",
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            "name": "Transcriptome de novo assembly",
            "description": "Not available\n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/A01_Galaxy_RNASeq_denovo_ITMO2016_0.pdf",
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            "name": "Chip-seq Analysis",
            "description": "Quality, normalisation and peak calling\n",
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            "doi": null,
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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,
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            "keywords": [
                "genomics",
                "Annotation",
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            "id": 67,
            "name": "Galaxy: Initiation II",
            "description": "Galaxy II: common tools, quality control; alignment; data managment\n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/G045_16-11-21-galaxy-tp-initiation-II-0.3.pdf",
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        },
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            "id": 61,
            "name": "Differential gene expression analysis : Practical part",
            "description": "RNA-seq: Differential gene expression analysis practical session\n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/R01b_EBA2016_TP_RNA-seq.pdf",
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            "name": "RNA-seq: Differential gene expression analysis",
            "description": "Transcriptome analysis provides information about the identity and quantity of all RNA molecules\n",
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            "id": 60,
            "name": "Differential analysis of RNA-Seq data",
            "description": "Design, describe, explore and model\n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/R02-R03_slidesRoscoff_stats_HVaret.pdf",
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            "dateCreation": "2016-11-23",
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            "id": 58,
            "name": "Isoform discovery and quanti cation from RNA-Seq data",
            "description": "Not available\n",
            "communities": [],
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/R04_EBA2016_RNAseq_Isoforms.pdf",
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        {
            "id": 64,
            "name": "Variants: alignment and pre-treatment; GATK",
            "description": "DNA-seq Bioinformatics Analysis: from raw sequences to processed alignments\n",
            "communities": [],
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/V01_ITMO_2016_EG_from_fastq_to_mapping_1.pdf",
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            "topics": [],
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            "dateCreation": "2016-11-22",
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        {
            "id": 59,
            "name": "Variant annotation",
            "description": "Add meta-information on variant to facilitate interpretation\n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/V06_variants_annotation.pdf",
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            "topics": [],
            "keywords": [
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            "dateCreation": "2016-11-23",
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        },
        {
            "id": 57,
            "name": "DNA - seq Bioinformatics Analysis",
            "description": "Detection of Copy Number Variations\n \n",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/V07_ITMO_2016_EG_CNV.pdf",
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            "dateCreation": "2016-11-23",
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            "id": 56,
            "name": "RADSeq Data Analysis",
            "description": "Introduction to RADSeq through STACKS on Galaxy\n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/V08_Yvan%20Le%20Bras%20-%20Training%20RADSeq_0.pdf",
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            "topics": [],
            "keywords": [
                "NGS"
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            "dateCreation": "2016-11-23",
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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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            "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",
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            "dateCreation": "2016-12-15",
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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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            "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",
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            "topics": [],
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            "dateCreation": null,
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        },
        {
            "id": 30,
            "name": "Welcome message",
            "description": "Presentation of the workshop (Chairman: Claudine Médigue)\n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_1/welcome_message/scormcontent/index.html",
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            "topics": [],
            "keywords": [
                "Metagenomics",
                "biohackaton"
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            "dateCreation": "2016-12-15",
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