Event List
Handles creating, reading and updating events.
GET /api/event/?format=api&offset=280&ordering=accessConditions
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Versioning, tool updates, and essential metadata enhance the findability and usability of each workflow.\r\n\r\nIn short, the objectives of this hackathon are to:\r\n- Annotate and apply best practices to microbial data analysis Galaxy workflows for consistency and reusability\r\n- Implement robust tests to ensure workflow reliability and accuracy\r\n- Successfully integrate key microbial data analysis Galaxy workflows into IWC, improving accessibility and usability\r\n- Collaborate as a community to refine and improve workflows, ensuring they are peer-reviewed and meet high standards\r\n- Make these peer-reviewed workflows accessible to the broader community through the future microGalaxy Lab\r\n\r\nThis hackathon is open to participants from all communities, so join us to help shape the future of bioinformatics workflows! Experts and IWC experienced users will be participating in the hackathon to support and explain the requirements during the event.", "homepage": "https://galaxyproject.org/events/2024-11-21-hackathon-microgalaxy-iwc/", "is_draft": false, "costs": [ "Free" ], "topics": [ "http://edamontology.org/topic_0769", "http://edamontology.org/topic_3697", "http://edamontology.org/topic_3941", "http://edamontology.org/topic_0121", "http://edamontology.org/topic_3174" ], "keywords": [ "Galaxy", "Workflow development" ], "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": 87, "name": "AuBi", "url": 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L'appropriation par les biologistes des méthodes et outils de biostatistique et bioinformatique intégrative est un enjeu majeur pour la montée en compétence des équipes de recherche et des plateformes de service. L'université Paris Diderot propose en partenariat avec l'Institut Français de Bioinformatique (IFB) la deuxième édition du Diplôme Universitaire en Bioinformatique intégrative (DU-Bii). Cette formation s’adresse en priorité à des biologistes en demande d'évolution ou de reconversion professionnelle ayant déjà acquis des compétences (formation courte, autoapprentissage, expérience de terrain) en informatique ou bioinformatique/biostatistique (environnement Unix, Python ou R ou autre langage de programmation). Les prérequis sont décrits sur le portail “DU” de l’université Paris Diderot, qui présente le DU-Bii et le DU complémentaire \"Création, Analyse et Valorisation de données omiques\" (DUO) : voir la page dédiée. Le DU-Bii fournira une formation théorique et pratique, complétée par une période d'immersion sur l'une des plateformes régionales de l'IFB, qui mobilisera, dans le cadre d'un projet tutoré, l'ensemble des méthodes et outils appris durant les cours pour réaliser un projet personnel de bioinformatique intégrative. Ce projet combinera des données propres à chaque participant produites dans son laboratoire (principe BYOD : “Bring Your Own Data”) ou collectées à partir de bases de données publiques. Cette formation se déroulera pendant 8 semaines réparties entre : Les cours : 4 semaines à raison de 4 jours/semaine en présentiel (96h) du 2 mars au 2 avril 2020 avec 1 semaine de césure la semaine 12). Le projet tutoré : 20 jours sur l'une des plateformes bioinformatique de l'IFB, à répartir entre le 6 avril et le 19 juin 2020.\r\nRenseignements et candidatures : fcsdv@univ-paris-diderot.fr\r\nInscriptions : voir la page page du DU-Bii de l'Université Paris Diderot\r\nContacts Paris-Diderot : Bertrand.Cosson@univ-paris-diderot.fr \r\nContacts IFB : Helene.Chiapello@inra.fr, Jacques.van-Helden@univ-amu.fr", "homepage": "https://ressources.france-bioinformatique.fr/fr/diplome-universitaire-en-bioinformatique-integrative-du-bii-2020", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 15, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/116/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 28, "name": "University Paris-Cité", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/University%20Paris-Cit%C3%A9/?format=api" }, { "id": 4, "name": "IFB - ELIXIR-FR", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IFB%20-%20ELIXIR-FR/?format=api" } ], "organisedByTeams": [], "logo_url": null, "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Training course", "start_date": "2020-03-02", "end_date": "2020-11-18", "venue": "Université Paris Diderot", "city": "Paris", "country": "France", "geographical_range": "National", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": "2019-11-05", "registration_status": "closed", "courseMode": "Onsite" }, { "id": 460, "name": "Molecular Phylogeny - Basic Training - session 2022", "shortName": "Phylogénie moléculaire - formation de base - 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": "", "city": "Montpellier", "country": "France", "geographical_range": "National", "trainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/736/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/241/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/282/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/480/?format=api" ], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": "Onsite" }, { "id": 532, "name": "Summer School Multi-omics Data Analysis and Integration", "shortName": "", "description": "Researchers often have access to or generate multiple omics data (RNAseq, metabolomics, lipidomics, proteomics…) within a single study. 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We will harness this subject introducing semantic web and knowledge graphs in the context of metabolic networks.\r\n\r\nDuring the School, significant time will be devoted to hands-on and the program will be divided into three phases / topics:\r\n- Multivariate statistical analyses (Instructors: Arnaud Gloaguen & Jimmy Vandel)\r\n- Network-based approaches (Instructors: Morgane Térézol & Marie-Galadriel Brière)\r\n- Results contextualisation: an introduction to metabolic models, web semantic and knowledge graphs (Instructors: Jean-Clément Gallardo, Maxime Delmas & Marco Pagni)\r\n\r\nThe participants will work in groups and shortly present the application of what they have learned to their own project.", "homepage": "https://www.sib.swiss/training/course/20230903_MODAI", "is_draft": false, "costs": [ "650 EUR/CHF for academics", "1000 EUR/CHF for for-profit companies" ], "topics": [ "http://edamontology.org/topic_0602", "http://edamontology.org/topic_2269", "http://edamontology.org/topic_0089" ], "keywords": [ "Biological network inference and analysis", "Multivariate analyses", "Semantic web", "Knowledge representation" ], "prerequisites": [ "experience with at least one omic technique", "basic statistics", "R programming" ], "openTo": "Everyone", "accessConditions": "", "maxParticipants": null, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/768/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/556/?format=api" ], "elixirPlatforms": [ { "id": 1, "name": "Training", "url": "https://catalogue.france-bioinformatique.fr/api/elixirplatform/Training/?format=api" } ], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 100, "name": "SIB", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/SIB/?format=api" }, { "id": 4, "name": "IFB - ELIXIR-FR", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IFB%20-%20ELIXIR-FR/?format=api" } ], "organisedByTeams": [], "logo_url": "https://www.sib.swiss/training/images/sib_logo.svg", "updated_at": "2023-05-17T08:59:43.914253Z", "type": "Training course", "start_date": "2023-09-03", "end_date": "2023-09-08", "venue": "Centre de Vacances et Colloques Paul Langevin", "city": "Aussois", "country": "France", "geographical_range": "International", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": "2023-04-23", "registration_closing": "2023-06-01", "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. Being aware of the challenges, opportunities and constraints that ML applications entail, is a critical aspect in ensuring high quality research in life sciences.\r\n\r\nRecognizing this need, this week-long training will bring together experts from four ELIXIR Nodes and deliver a hands-on, high-intensity course available for members from all ELIXIR Nodes.\r\n\r\nLearners will be guided across the various steps in Machine Learning, from the foundational concepts, through the deep learning and generative AI techniques, closely complemented by insights into the existing reporting (DOME Recommendations) and regulatory frameworks (EU AI Act).\r\n\r\nThis 4-day school will involve around 10 trainers/helpers from across 4 different ELIXIR nodes and 30 participants from across all ELIXIR nodes. 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