Event List
Handles creating, reading and updating events.
GET /api/event/?format=api&offset=260&ordering=topics
{ "count": 628, "next": "https://catalogue.france-bioinformatique.fr/api/event/?format=api&limit=20&offset=280&ordering=topics", "previous": "https://catalogue.france-bioinformatique.fr/api/event/?format=api&limit=20&offset=240&ordering=topics", "results": [ { "id": 591, "name": "BIGomics, Génomique Comparative Biopolis", "shortName": "", "description": "Ce module vise à fournir une expérience d’analyse de données de génomique.\r\nLes technologies Next Generation Sequencing (NGS) ont conduit à une production massive de\r\ndonnées « Omiques » pour les plantes cultivées majeures, ce qui demande de nouvelles\r\napproches d’analyses haut débit. La connaissance de ces approches et des outils qui en\r\ndécoulent pour analyser la séquence et la structure des génomes, les annoter et caractériser\r\nleur diversité et leurs profils d’expression permet d’aborder des questions de recherche\r\nbiologique avancée sur la diversité et l’adaptation des plantes. Les espèces prises en\r\nconsidération sont des espèces phares des instituts de recherche agronomique de Montpellier\r\net font partie des cultures les plus importantes pour l’agriculture mondiale. Des plateformes\r\nd’outils bioinformatiques récents reposant sur des centres de calcul et de stockage haute\r\ncapacité, sont en place pour analyser des jeux de données originales permettant de mieux\r\ncomprendre comment les génomes de plantes évoluent et s’expriment. L’ensemble de ces\r\nconnaissances Findable, Accessible, Interoperable, Reusable car intégré dans des systèmes\r\nd’information peut soutenir l'identification de gènes responsables de caractères adaptatifs ou\r\nde production. La mobilisation de jeunes chercheurs sur ces sujets est primordiale tant la\r\ndemande est importante.\r\nLe module est structuré sous la forme de cours et de travaux tutorés avec la rencontre de\r\ngénéticiens et de bioinformaticiens permettant d’appréhender les formes variées des progrès\r\nen bioanalyse génomique. 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Furthermore, since genetic studies relies on the integration and the linking between phenotype and genotype datasets, relevant section of MIAPPE are beginning to be used for genotyping standards.\r\nThis formation will cover a general introduction of the MIAPPE principles and some examples to illustrate different use cases on the usage of MIAPPE for plant phenotyping data standardization.", "homepage": "https://urgi.versailles.inrae.fr/About-us/News/Webinar-rep-pheno", "is_draft": false, "costs": [ "Free" ], "topics": [ "http://edamontology.org/topic_3572", "http://edamontology.org/topic_3298", "http://edamontology.org/topic_0625", "http://edamontology.org/topic_0219", "http://edamontology.org/topic_0780" ], "keywords": [ "Données" ], "prerequisites": [ "none" ], "openTo": "Everyone", "accessConditions": "Public", "maxParticipants": null, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/504/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 39, "name": "URGI - US1164", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/URGI%20-%20US1164/?format=api" }, { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" } ], "organisedByTeams": [ { "id": 26, "name": "URGI", "url": "https://catalogue.france-bioinformatique.fr/api/team/URGI/?format=api" } ], "logo_url": "https://urgi.versailles.inra.fr/extension/inra/design/urgi/images/logoURGI_res72_2-82X1-98.png", "updated_at": "2025-11-28T13:21:44.473980Z", "type": "Training course", "start_date": "2021-04-02", "end_date": "2021-04-02", "venue": "", "city": "", "country": "", "geographical_range": "International", "trainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/504/?format=api" ], "trainingMaterials": [ { "id": 150, "name": "Plant Data Managment for Phenotyping Experiments - MIAPPE", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Plant%20Data%20Managment%20for%20Phenotyping%20Experiments%20-%20MIAPPE/?format=api" } ], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": "Online" }, { "id": 605, "name": "BIGomics, Génomique Comparative", "shortName": "BOGC", "description": "Ce module vise à fournir une expérience d’analyse de données de génomique.\r\nLes technologies Next Generation Sequencing (NGS) ont conduit à une production massive de\r\ndonnées « Omiques » pour les plantes cultivées majeures, ce qui demande de nouvelles\r\napproches d’analyses haut débit. La connaissance de ces approches et des outils qui en\r\ndécoulent pour analyser la séquence et la structure des génomes, les annoter et caractériser\r\nleur diversité et leurs profils d’expression permet d’aborder des questions de recherche\r\nbiologique avancée sur la diversité et l’adaptation des plantes. Les espèces prises en\r\nconsidération sont des espèces phares des instituts de recherche agronomique de Montpellier\r\net font partie des cultures les plus importantes pour l’agriculture mondiale. Des plateformes\r\nd’outils bioinformatiques récents reposant sur des centres de calcul et de stockage haute\r\ncapacité, sont en place pour analyser des jeux de données originales permettant de mieux\r\ncomprendre comment les génomes de plantes évoluent et s’expriment. L’ensemble de ces\r\nconnaissances Findable, Accessible, Interoperable, Reusable car intégré dans des systèmes\r\nd’information peut soutenir l'identification de gènes responsables de caractères adaptatifs ou\r\nde production. La mobilisation de jeunes chercheurs sur ces sujets est primordiale tant la\r\ndemande est importante.\r\nLe module est structuré sous la forme de cours et de travaux tutorés avec la rencontre de\r\ngénéticiens et de bioinformaticiens permettant d’appréhender les formes variées des progrès\r\nen bioanalyse génomique. Il permet d’acquérir les lignes directrices pour l’accès, l'utilisation\r\net l'analyse de différents types de données omique (e.g. (épi)génomique, transcriptomique,\r\nprotéique, métabolique) en vue d’accélérer les recherches en génomique fonctionnelle et\r\nbiotechnologie des plantes.\r\nL’évaluation sera faite sur la base de la participation et de la qualité du projet proposé par\r\nl’étudiant en fin de module, individuellement ou en binôme, suivant les consignes détaillées en\r\ndébut de module", "homepage": "https://elearning.cirad.fr/mod/resource/view.php?id=2339", "is_draft": false, "costs": [ "Free to academics" ], "topics": [ "http://edamontology.org/topic_0797", "http://edamontology.org/topic_3810", "http://edamontology.org/topic_3056", "http://edamontology.org/topic_0780" ], "keywords": [ "Phylogeny", "Biodiversity", "NGS Data Analysis" ], "prerequisites": [ "Basic knowledge of R" ], "openTo": "Everyone", "accessConditions": "Inscription via un formulaire Moodle", "maxParticipants": 50, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/573/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 17, "name": "Agropolis Fondation", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/Agropolis%20Fondation/?format=api" } ], "organisedByOrganisations": [ { "id": 85, "name": "IRD", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IRD/?format=api" }, { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 50, "name": "CIRAD", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/CIRAD/?format=api" } ], "organisedByTeams": [ { "id": 24, "name": "South Green", "url": "https://catalogue.france-bioinformatique.fr/api/team/South%20Green/?format=api" } ], "logo_url": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png", "updated_at": "2024-03-11T13:30:02.752091Z", "type": "Training course", "start_date": "2024-04-11", "end_date": "2024-04-16", "venue": "Campus numérique francophone - 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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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La formation abordera les fondamentaux et les fonctionnalités avancées des deux langages Snakemake et Nextflow. Ces outils sont en effet devenus indispensables pour assurer la reproductibilité et l’efficacité des analyses bioinformatiques. La formation sera structurée en deux séquences :\r\n- une journée commune qui abordera les grands principes des gestionnaires de workflow, en particulier dans le domaine de la bioinformatique et en lien avec les infrastructures de calcul de type cluster et cloud proposés au sein de l’IFB \r\n- une journée de session pratique avec 1 atelier snakemake et 1 atelier nextflow en parallèle au choix des participants. 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