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            "name": "Introduction to Linux",
            "shortName": "Introduction to Linux - BiRD",
            "description": "Objectives\r\n- Understand the principles and advantages of the Linux system\r\n- Know and use the main bash commands. Ability to chain multiple commands using pipes\r\n- Launch programs with arguments\r\n- Gain independence to perform command line analyses\r\n\r\nPedagogical Content\r\n- Introduction to the Linux system.\r\n- File system: directory structure, paths, home directory, file and directory management.\r\n- Principle of protections: reading file attributes, access rights, management of user groups.\r\n- Shell usage: command reminders, input/output redirection, history, completion, launching programs with arguments.\r\n- Commands relevant to bioinformatics: grep, cut, sed, sort, more, etc.\r\n- Connection (ssh) - how to start a session from Linux or Windows PowerShell",
            "homepage": "https://pf-bird.univ-nantes.fr/training/",
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            "updated_at": "2024-02-19T09:37:34.209594Z",
            "type": "Training course",
            "start_date": "2024-03-18",
            "end_date": "2024-03-18",
            "venue": "Faculté de Pharmacie - Salle 450, 4ème étage",
            "city": "Nantes",
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            "name": "Analyse statistique de données RNA-Seq - Recherche des régions d’intérêt différentiellement exprimées - 2026",
            "shortName": "Analyse statistique de données RNA-Seq 2026",
            "description": "Objectifs pédagogiques\r\n* Se sensibiliser aux concepts et méthodes statistiques pour l’analyse de données transcriptomiques de type RNA-Seq.\r\n* Comprendre le matériel et méthodes (normalisation et tests statistiques) d’un article.\r\n* Réaliser une étude transcriptomique avec R dans l’environnement RStudio.\r\n\r\nProgramme\r\n* Planification expérimentale des expériences RNA-Seq (identification des biais, répétitions, biais contrôlables).\r\n* Normalisation et analyse différentielle : recherche de “régions d’intérêt” différentiellement exprimées (modèle linéaire généralisé).\r\n*Prise en compte de la multiplicité des tests.\r\n\r\nLe cours sera illustré par différents exemples. Un jeu de données à deux facteurs sera analysé avec les packages R DESeq2 et edgeR dans l’environnement RStudio.",
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                    "name": "INRAE",
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                    "id": 88,
                    "name": "BioinfOmics",
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            "updated_at": "2026-02-12T10:29:38.805654Z",
            "type": "Training course",
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            "name": "Linux et script pour la bioinformatique",
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            "description": "Pour la plupart des tâches communes, le système Linux (libre et gratuit) peut avantageusement remplacer les systèmes d'exploitation propriétaires tels que Windows ou MacOS. Les énormes avantages de Linux sont sa gratuité, son évolution constante et l'inexistence des virus. Ce stage est une initiation à l'utilisation du système d'exploitation Linux et des lignes de commande pour les non informaticiens, ainsi qu'une initiation à l'écriture et l'emploi de scripts (petits programmes) pour faciliter l'analyse de données. Il s'agit pour des débutants ou quasi débutants Linux d'utiliser le système et d'acquérir l'autonomie nécessaire pour résoudre les besoins communs simples d'analyse par la combinaison des méthodes à travers des scripts.\n \n",
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            "description": "In an effort to inform members of the research community about our annotation methods, to provide training for collaborators and other scientists who use the MicroScope platfom, and to inform scientific public on the analysis available in PkGDB (Prokaryotic Genome DataBase), we have developed a 4.5-day course in Microbial Genome Annotation and Comparative Analysis using the MaGe graphical interfaces.\r\n\r\nThis course will familiarize attendees with LABGeM’s annotation pipeline and the manual annotation software MaGe (Magnifying Genome) . No specific bioinformatics skill is required: detailed instruction on the algorithm developed in each annotation methods can be found in specific training courses on «Genomic sequences analysis». Here we focus on the general idea behind each method and, above all, the way you can interpret the corresponding results and combine them with other evidences in order to change or correct the current automatic functional annotation of a given gene, if necessary.\r\n\r\nThis course will also describe how to perform effective searches and analysis of procaryotic data using the graphical functionalities of the MaGe’s interfaces. Because of the numerous pre-computation available in our system (results of “common” annotation tools, synteny with all complete bacterial genomes, metabolic pathway reconstruction, fusion/fission events, genomic islands, …), many practical exercises allow attendees to get familiar with the use the MaGe graphical interfaces in order to efficiently explore these sets of results.",
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                "Sequence annotation"
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                "Licence"
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                    "name": "University of Évry Val d'Essonne",
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            "name": "Journées \"ReproHackathon\"",
            "shortName": "",
            "description": "Hackathon ReProVirtuFlow visant à tester les capacités des systèmes de workflows à reproduire une expérience scientifique",
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            "type": "Other",
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                "Linux - Basic Knowledge"
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            "updated_at": "2025-02-21T08:52:30.567397Z",
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        {
            "id": 89,
            "name": "Rendre ses outils disponibles sur un cloud OpenStack",
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            "name": "Cycle « Analyse de données de séquençage à haut-débit » - Module 5/6 : Analyses RNA-seq, bioinformatique- session Septembre 2021",
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