Event List
Handles creating, reading and updating events.
GET /api/event/?format=api&offset=280&ordering=accessConditions
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null }, { "id": 283, "name": "Cluster", "shortName": "", "description": "", "homepage": "", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "", "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Training course", "start_date": "2017-03-06", "end_date": null, "venue": "", "city": "Salle de formation Inra", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 604, "name": "Hackathon - Improving the annotation of Galaxy resources for microbial data analysis and beyond", "shortName": "", "description": "This 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"http://edamontology.org/topic_0769" ], "keywords": [ "EDAM", "Annotation", "Galaxy" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": null, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 1, "name": "CNRS - IFB", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/CNRS%20-%20IFB/?format=api" } ], "organisedByOrganisations": [ { "id": 4, "name": "IFB", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IFB/?format=api" }, { "id": 87, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/AuBi/?format=api" } ], "organisedByTeams": [ { "id": 29, "name": "IFB Core", "url": "https://catalogue.france-bioinformatique.fr/api/team/IFB%20Core/?format=api" }, { "id": 31, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/team/AuBi/?format=api" } ], "logo_url": null, "updated_at": "2024-02-19T10:09:50.076964Z", "type": "Workshop", "start_date": "2024-03-11", "end_date": "2024-03-15", "venue": "Online with a\r\n • a Zoom room, open the whole week\r\n • 2 daily stand-ups to accommodate different time zones\r\n • Several brainstorming meetings\r\n • microGalaxy Matrix chat for communication", "city": "", "country": "", "geographical_range": "International", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": "2024-02-19", "registration_closing": null, "registration_status": "open", "courseMode": "Online" }, { "id": 125, "name": "Assemblage de génome", "shortName": "", "description": "", "homepage": "", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], 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"communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "https://ressources.france-bioinformatique.fr/sites/default/files/logo-cnrs_0_0.png", "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Training course", "start_date": "2017-03-27", "end_date": "2017-03-31", "venue": "", "city": "Montpellier", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 579, "name": "Manipulation de données avec R, introduction à tidyverse (session 2024)", "shortName": "Introduction à tidyverse (2024)", "description": "Objectifs pédagogiques\r\nA l’issue de la formation, les stagiaires seront capables de :\r\n* utiliser les principales fonctions des packages dplyr et tidyr de l’écosystème du « tidyverse »\r\n* lire les données et les ranger dans un format « tidy »\r\n* manipuler les données : filtrer, sélectionner, trier, produire des résultats par groupe, fusionner plusieurs tables\r\n* mettre en forme et pivoter les tables de données\r\n\r\nProgramme\r\n* Principes du tidyverse\r\n* Principales fonctions de manipulation de données du package dplyr : ajouter de nouvelles variables, sélectionner des colonnes, filtrer des lignes, trier, grouper, fusionner des tables\r\n* Enchaînements des opérations à l’aide de « pipe »\r\n* Mise en forme, jointure et pivot de données avec le package tidyr\r\n* Mise en application sur un exemple d’analyse de données de transcriptomique.", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_0605" ], "keywords": [ "R Language", "Tidyverse" ], "prerequisites": [ "Basic knowledge of R" ], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ 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"realisation_status": "past", "registration_opening": "2024-01-08", "registration_closing": "2024-03-20", "registration_status": "closed", "courseMode": "Onsite" }, { "id": 643, "name": "Artificial Intelligence and Machine Learning in Life Sciences: from foundations to applications 2025", "shortName": "AI & ML in LS 2025", "description": "Artificial intelligence (AI) has permeated our lives, transforming how we live and work. Over the past few years, a rapid and disruptive acceleration of progress in AI has occurred, driven by significant advances in widespread data availability, computing power and machine learning. Remarkable strides were made in particular in the development of foundation models - AI models trained on extensive volumes of unlabelled data. Moreover, given the large amounts of omics data that are being generated and made accessible to researchers due to the drop in the cost of high-throughput technologies, analysing these complex high-volume data is not trivial, and the use of classical statistics can not explore their full potential. As such, Machine Learning (ML) and Artificial Intelligence (AI) have been recognized as key opportunity areas, as evidenced by a number of ongoing activities and efforts throughout the community.\r\n\r\nHowever, beyond the technological advances, it is equally important that the individual researchers acquire the necessary knowledge and skills to fully take advantage of Machine Learning. 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