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        },
        {
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            "name": "Annotation and analysis of prokaryotic genomes using the MicroScope platform - novembre 2022",
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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.",
            "homepage": "https://labgem.genoscope.cns.fr/professional-trainings/microscope-professional-trainings/training-annotation-analysis-of-prokaryotic-genomes-using-the-microscope-platform/",
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                "2500 € for private companies",
                "1350 € for academics",
                "945 € for students"
            ],
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                "http://edamontology.org/topic_0797",
                "http://edamontology.org/topic_0085",
                "http://edamontology.org/topic_3301"
            ],
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                "Genome analysis",
                "Sequence annotation"
            ],
            "prerequisites": [
                "Licence"
            ],
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            ],
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            "logo_url": null,
            "updated_at": "2022-06-02T11:50:50.627601Z",
            "type": "Training course",
            "start_date": "2022-11-21",
            "end_date": "2022-11-25",
            "venue": "Evry University Paris Saclay",
            "city": "Evry",
            "country": "France",
            "geographical_range": "International",
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            "registration_opening": "2022-01-24",
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        },
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            "id": 415,
            "name": "Introduction to Machine Learning Using R - 2021",
            "shortName": "",
            "description": "With the rise in high-throughput sequencing technologies, the volume of omics data has grown exponentially in recent times and a major issue is to mine useful knowledge from these data which are also heterogeneous in nature. Machine learning (ML) is a discipline in which computers perform automated learning without being programmed explicitly and assist humans to make sense of large and complex data sets. The analysis of complex high-volume data is not trivial and classical tools cannot be used to explore their full potential. Machine learning can thus be very useful in mining large omics datasets to uncover new insights that can advance the field of bioinformatics.\r\n\r\nThis 2-day course will introduce participants to the machine learning taxonomy and the applications of common machine learning algorithms to omics data. The course will cover the common methods being used to analyse different omics data sets by providing a practical context through the use of basic but widely used R libraries. The course will comprise a number of hands-on exercises and challenges where the participants will acquire a first understanding of the standard ML processes, as well as the practical skills in applying them on familiar problems and publicly available real-world data sets.",
            "homepage": "https://fpsom.github.io/2021-06-ml-elixir-fr/",
            "is_draft": false,
            "costs": [
                "Free"
            ],
            "topics": [],
            "keywords": [],
            "prerequisites": [],
            "openTo": "Everyone",
            "accessConditions": "",
            "maxParticipants": 30,
            "contacts": [
                "https://catalogue.france-bioinformatique.fr/api/userprofile/556/?format=api"
            ],
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                    "name": "IFB",
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                    "name": "Elixir-FR",
                    "url": "https://catalogue.france-bioinformatique.fr/api/organisation/Elixir-FR/?format=api"
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                    "name": "Elixir",
                    "url": "https://catalogue.france-bioinformatique.fr/api/organisation/Elixir/?format=api"
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            ],
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            "logo_url": "https://www.dissco.eu/wp-content/uploads/Elixir-Europe-logo-1.png",
            "updated_at": "2022-06-02T11:50:50.627601Z",
            "type": "Training course",
            "start_date": "2021-06-16",
            "end_date": "2021-06-17",
            "venue": "",
            "city": "",
            "country": "",
            "geographical_range": "International",
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}