Event List
Handles creating, reading and updating events.
GET /api/event/?format=api&offset=300&ordering=accessConditions
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Which version do I use ?\r\nHow to run a workflow and which config file is used ?\r\nWhich kind of error I can get ?\r\nHow to resume failed jobs?\r\nHow to handle genome indexes ?\r\nHow to monitor my process and then well configure my workflow ?\r\nHow do you best adjust CPU and RAM reservations?\r\nThis is NOT a bioinformatic training on a particular workflow or a training on how to develop a workflow.\r\n\r\nThis training is focused on practice. 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session 2022", "description": "OBJECTIF\r\n- Savoir inférer un arbre phylogénétique et l'interpréter\r\n\r\nPRÉREQUIS\r\n- Savoir ce à quoi correspondent des séquences génétiques homologues\r\n- Avoir déjà utilisé les logiciels de base en bioinformatique\r\n- Connaître les notions de base en statistiques (tests, lois probabilistes usuelles, méthodes simples d'estimation de paramètres)\r\n- Avoir des notions de programmation\r\n\r\nPROGRAMME\r\n- Lignes de commandes Linux\r\n- Le format Newick\r\n- Dessin d'arbres\r\n- Alignements multiples et nettoyage\r\n- Modèles d'évolution\r\n- Choix de modèles\r\n- Définitions et propriétés des arbres\r\n- Méthodes de parcimonie\r\n- Méthodes de distance\r\n- Maximum de vraisemblance\r\n- Reconstruction phylogénétique Bayésienne\r\n- Bootstraps et autres supports de branches", "homepage": "https://cnrsformation.cnrs.fr/phylogenie-moleculaire-formation-de-base?axe=146", "is_draft": false, "costs": [ "1200 €" ], "topics": [ "http://edamontology.org/topic_3293", "http://edamontology.org/topic_0084", "http://edamontology.org/topic_3299" ], "keywords": [ "Phylogeny", "Evolution and Phylogeny", "Molecular evolution", "Phylogenetics" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/241/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 1, "name": "CNRS formation entreprises", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/CNRS%20formation%20entreprises/?format=api" } ], "organisedByTeams": [ { "id": 7, "name": "ATGC", "url": "https://catalogue.france-bioinformatique.fr/api/team/ATGC/?format=api" } ], "logo_url": "http://www.atgc-montpellier.fr/pictures/ATGClogo.svg", "updated_at": "2023-05-17T10:17:18.992615Z", "type": "Training course", "start_date": "2022-03-30", "end_date": "2022-04-01", "venue": "", 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"trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 104, "name": "Data collection and registration of Research Projects for Orphanet information scientists", "shortName": "", "description": "", "homepage": "", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "https://ressources.france-bioinformatique.fr/sites/default/files/150x150.png", "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Training course", "start_date": "2017-09-21", "end_date": null, "venue": "", "city": "Paris (à distance)", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], 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"prerequisites": [], "openTo": "Internal personnel", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "https://ressources.france-bioinformatique.fr/sites/default/files/150x150.png", "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Training course", "start_date": "2017-11-05", "end_date": null, "venue": "", "city": "Université Montpellier 1", "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 hackathon aims to improve the annotation of Galaxy resources for microbial data analysis and beyond\r\n\r\nThe objective of this hackathon is to improve the annotation of the Galaxy resources (tools, training, workflows) for microbial data analysis by:\r\n\r\n - Linking microbial Galaxy tools to bio.tools to obtain EDAM ontology annotation\r\n - Improving bio.tools annotations\r\n - Annotating existing microbial-related tutorials with EDAM terms\r\n - Reflecting on the addition of EDAM terms to workflows\r\n - Reflecting on missing terms in the EDAM ontology for microbial data analyses\r\n - Brainstorming about a way to connect tool annotations to improve training and workflow annotations", "homepage": "https://galaxyproject.org/events/2024-03-11-hackathon-galaxy-resources-annotation/#preliminary-schedule", "is_draft": false, "costs": [ "Free" ], "topics": [ "http://edamontology.org/topic_0769", "http://edamontology.org/topic_3941", "http://edamontology.org/topic_3174", "http://edamontology.org/topic_3697" ], "keywords": [ "EDAM", "Annotation", "Galaxy" ], "prerequisites": [], 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[], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "", "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Training course", "start_date": "2017-11-06", "end_date": null, "venue": "", "city": "IPHC - Strasbourg", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "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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