Handles creating, reading and updating training materials.

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            "name": "Training RNASeq - biostat part - Genotoul-bioinfo",
            "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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            "name": "Supports FAIR data PLANT PHENO 2023",
            "description": "Ensemble des supports utilisés pour la version 2023 de la formation FAIR data PLANT PHENO",
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            "name": "Galaxy 101 for everyone",
            "description": "This practical aims at familiarizing you with the Galaxy user interface. It will teach you how to perform basic tasks such as importing data, running tools, working with histories, creating workflows and sharing your work. Not everyone has the same background and that’s ok!",
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            "name": "Welcome and Introduction",
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            "name": "Data-brokering script",
            "description": "This project generates metadata in JSON-LD format for plant and animal biological samples and submits them to the European Nucleotide Archive (ENA)'s BioSamples database. The metadata is extracted from an Excel file and validated against the Plant MIAPPE checklist for plant samples and against the BioSamples minimal checklist for animal samples. Samples are then either submitted as new entries or updated if they already exist in the database.",
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            "name": "Cluster TP - Genotoul-bioinfo",
            "description": "TP for cluster training (bioinfo genotoul facility)\r\nThis training session is organized by the Genotoul bioinfo platform and aims at learning sequence analysis. This training session has been designed so you can deal with the platform resources and its organization. You will learn to deal with the platform compute cluster and data banks. You will launch your first processing batch on the cluster and will learn how to track and manage them. The objective of this training is to learn you how to use computing ressources from GenoToul Bioinfo cluster (submit, manage & monitor jobs).",
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            "id": 131,
            "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": "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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            "id": 127,
            "name": "Quality Control with Galaxy",
            "description": "This tutorial covers the questions:\r\n- How to perform quality control of NGS raw data?\r\n- What are the quality parameters to check for a dataset?\r\n- How to improve the quality of a dataset?\r\n\r\nAt the end of the tutorial, learners would be able to:\r\n- Assess short reads FASTQ quality using FASTQE 🧬😎 and FastQC\r\n- Assess long reads FASTQ quality using Nanoplot and PycoQC\r\n- Perform quality correction with Cutadapt (short reads)\r\n-  Summarise quality metrics MultiQC\r\n- Process single-end and paired-end data",
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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": 46,
            "name": "BioBlend API",
            "description": "BioBlend module, a python library to use Galaxy API\n",
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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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            "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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            "name": "A Quick and focused overview of R data types and ggplot2 syntax",
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            "id": 99,
            "name": " PASTEClassifier Tutorial",
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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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