Handles creating, reading and updating training events.

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            "name": "Reproducible Research",
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            "description": "The following topics and tools are covered in the course:\r\n\r\n    Data management\r\n    Project organisation\r\n    Git\r\n    Conda\r\n    Snakemake\r\n    Nextflow\r\n    R Markdown\r\n    Jupyter\r\n    Docker\r\n    Singularity\r\n\r\nAt the end of the course, students should be able to:\r\n\r\n    Use good practices for data analysis and management\r\n    Clearly organise their bioinformatic projects\r\n    Use the version control system Git to track and collaborate on code\r\n    Use the package and environment manager Conda\r\n    Use and develop workflows with Snakemake and Nextflow\r\n    Use R Markdown and Jupyter Notebooks to document and generate automated reports for their analyses\r\n    Use Docker and Singularity to distribute containerized computational environments",
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            "description": "This training session, organized by Bioinfo Genotoul, Sigenae, NED (GenPhySE) and TWB, is designed to help you to deal with NGS data of 16S, 18S ... DNA produced with MiSeq from Illumina and Roche 454 technologies in the Galaxy workbench.\nYou will discover how to use our Galaxy instance, clean reads, clusterize them, do the taxonomic affiliation and perform statistics to interpret your results.\nPrerequisites: knowledge of R or in another programming language\n",
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            "name": "Galaxy : RNASeq alignment and transcripts assemblies",
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            "description": "As the command line training but with Galaxy. Organized jointly by the Sigenae and the Bioinfo Genotoul platforms.\n",
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            "description": "As the command line training but with Galaxy. Organized jointly by the Sigenae and bioinfo genotoul platforms.\n",
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            "description": "Galaxy is a workbench available for biologists from Sigenae Platform. Galaxy objectives are:\n    First, making bioinfo Linux tools accessible to biologists.\n    Then, it is possible to add Linux tools by developpers into Galaxy workbench.\n    Then, Galaxy is used to hide the complexity of the infrastructure and to allow creation, execution and sharing of workflows.\nYou will acquire the following competencies required for the other Galaxy trainning:\n    Login to Galaxy: Galaxy Workbench (To access to Galaxy, you need to have an LDAP Genotoul login and password).\n    Begin to use some tools provided (BWA, SAM tools, FastQC).\n    Work on files.\nOrganized jointly by the Sigenae and the Bioinfo Genotoul platform.\n",
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            "name": "Phylogenomy and selection pressure ",
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            "description": "This training session is organized by the bios4Biol CATI.\nMorning : phylogenomics\nThe morning course will provide insigths about sampling problems in phylogenomics studies (genes, species) and methodological aspects of phylogenomics studies with two major focus on super-matrix and super-tree methods.\nAfternoon : selection pressure\nThe afternoon course will be dedicated to the use of the PAML4 package in order to study selection pressures in a sequence alignment.\n",
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            "id": 29,
            "name": "Initiation à Python",
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            "description": "\nObjectifs\n\nInitiation à la programmation.\nRéalisation de tâches simples d'extractions d'informations.\nIdentifier les possibilités offertes par l'écriture de quelques lignes de codes.\n \n\n \n \n \n \nProgramme\n\n• Présentation de Python\n• Variables Python\n• Structures de contrôle\n• Réalisation de programmes simples\n• Gestion de fichiers\n• Fonctions\nIllustration avec des exercices de manipulation de fichiers de séquences\n",
            "homepage": "http://migale.jouy.inra.fr/",
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            "keywords": [
                "Programming Languages & Computer Sciences",
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            "name": "RNASeq analyses (using Galaxy and TOGGLe)",
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            "description": "This course offers an introduction to RNASeq analyses using two different workflow management systems: Galaxy and TOGGLe. This includes reference-based mapping, estimates of transcript levels, differential expression (DE) analyses, visualization of statistics results.\r\nPrerequisites\r\nWorkflow management system (Galaxy, TOGGLe)\r\n\r\nProgram\r\nMapping of RNASeq against a transcriptome reference with kallisto (Galaxy)\r\nMapping of RNASeq against an annotated genome reference with TopHat (TOGGLe)\r\nDifferential expression analysis using EdgeR and DESeq2\r\nPlots, clustering, co-expression network: degust, WGCNA\r\n\r\n\r\nLearning objectives\r\nManipulate packages/tools available for searching DE genes\r\nThink about different normalisation methods\r\nDetect differentially expressed genes\r\nCompare results between two approaches\r\n\r\n\r\nInstructors\r\nAlexis Dereeper - alexis.dereeper@ird.fr\r\nSebastien Cunnac - sebastien.cunnac@ird.fr\r\nSebastien Ravel - sebastien.ravel@cirad.fr\r\nChristine Tranchant  - christine.tranchant@ird.fr",
            "homepage": "https://southgreenplatform.github.io/trainings//rnaseq/",
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            "name": "Formation de base",
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            "id": 69,
            "name": "Methods for phylogenetics trees construction",
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            "description": "This training session is organized by the bios4Biol CATI and aims at training participants to construct and interpret phylogenetic trees.\nYou will discover how to choose an evolutionary model and a phylogenetic inference method (among distance, parsimony, maximum likelihood and Bayesian methods) and how to evaluate the robustness of a tree using bootstrap.\n",
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            "name": "Sequences alignment and phylogeny ",
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            "description": "This training session is organized by the bios4Biol CATI and the genotoul bioinfo platform and aims at initiating participants to molecular phylogenetics studies.\nYou will discover how to build a sequence dataset, to align sequences, to edit and refine the resulting alignment.\n",
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            "name": "Initiation à R",
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            "description": "\nObjectifs\n\n- Présenter le langage de programmation R et ses principes.\n- Utiliser les principales fonctionnalités de ce langage pour effectuer des calculs mathématiques, statistiques ou des représentations graphiques.\n- Attention : ce module n'est ni un module de statistique, ni un module d'analyse statistique des données.\n\nProgramme\n\n- Structures et manipulation de données.\n- Principaux éléments du langage de programmation (boucle, fonctions…).\n- Différentes représentations graphiques de données/résultats (plot, histogramme, boxplot).\n",
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            "id": 30,
            "name": "Python avancé",
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            "description": "\nObjectifs\n\nEtre autonome pour des manipulations simples visant à extraire, reformater des données issues de fichiers texte.\n \n\n \n \n \n \nProgramme\n\n- Expressions régulières\n- Gestion des erreurs\n- Biopython\n- Réalisation de programmes simples\n",
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            "id": 252,
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