Event List
Handles creating, reading and updating events.
GET /api/event/?format=api&offset=160&ordering=-registration_closing
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"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": "2017-06-15", "end_date": null, "venue": "", "city": "Montpellier", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 176, "name": "Integrative Bioinformatics Symposium 2018", "shortName": "", "description": "Bring together experts in the field of bioinformatics, computer science, statistics, computational and systems biology", "homepage": "https://www.rothamsted.ac.uk/events/14th-international-symposium-integrative-bio…", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 8, "name": "Elixir", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/Elixir/?format=api" } ], "organisedByTeams": [], "logo_url": "https://ressources.france-bioinformatique.fr/sites/default/files/Logo_elixir.png", "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Conference", "start_date": "2018-06-13", "end_date": "2018-06-15", "venue": "", "city": "Rothamsted Research, Harpenden, England, United Kingdom", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 341, "name": "NGS sous 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"homepage": "http://fondation-maladiesrares.org/actualite/diu-maladies-rares-de-la-recherche-…", "is_draft": false, "costs": [], "topics": [], "keywords": [ "NGS Data Analysis", "Bioinformatics & Biomedical", "Sequence analysis", "NGS Sequencing Data Analysis" ], "prerequisites": [ "Autre (Diplôme universitaire, école d'ingénieur ...)" ], "openTo": "Internal personnel", "accessConditions": "Inscription au DIU Maladies rares : de la recherche au traitement\n", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "", "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Training course", "start_date": "2017-02-05", "end_date": "2017-02-09", "venue": "", "city": "", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 472, "name": "Workflow4metabolomics - 2021 session postponed to 2022, march", "shortName": "W4E 2021", "description": "Processing, statistical analysis, and annotation of metabolomics data is a complex task for experimenters since it involves many steps and requires a good knowledge of both the methodology and software tools. The Workflow4Metabolomics.org (W4M) online infrastructure provides a user-friendly and high-performance environment with advanced computational modules for building, running, and sharing complete workflows for LC-MS, GC-MS, FIA and NMR analysis. Such features are of major values for teaching computational metabolomics to experimenters, and previous courses using W4M since 2014 have been very successful.", "homepage": "https://workflow4metabolomics.org/w4e2021", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 20, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/116/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": null, "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Training course", "start_date": "2022-03-21", "end_date": "2022-03-25", "venue": "", "city": "Toulouse", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": "Onsite" }, { "id": 257, "name": "Analyse de données RNA-seq sous l’environnement Galaxy ", "shortName": "", "description": "\n\nObjectifs de la formation\nAcquérir les connaissances générales sur les méthodes de séquençage à haut-débit.\nConnaître les caractéristiques des données obtenues dans le cadre de l’analyse du transcriptome (RNA-seq).\nSavoir planifier une expérience simple de type RNA-seq en fonction de ses objectifs scientifiques et des caractéristiques et contraintes expérimentales.\nConnaître les principales méthodes et outils d’analyse des données RNA-seq . Pouvoir les mettre en oeuvre dans un cas simple via un serveur web Galaxy.\nPouvoir visualiser les résultats dans un navigateur de génome.\nDurée de la formation : 2,5 jours\n\n\n", "homepage": "http://www.biosciencesco.fr/formation-continue/bio-informatique/analyse-des-donn…", "is_draft": false, "costs": [], "topics": [], "keywords": [ "Methodology", "Biostatistics", "NGS Data Analysis", "Analysis of RNAseq data", "Assembly of genomes and transcriptomes", "Read alignment on genomes", "Statistical Tests", "Gene expression differential analysis", "Galaxy", "Transcript and transcript variant analysis", "Transcriptomics (RNA-seq)", "NGS Sequencing Data Analysis" ], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "Informations et inscriptions:\nhttp://www.biosciencesco.fr/formation-continue/bio-informatique/analyse-...\n", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "", "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Training course", "start_date": "2017-11-14", "end_date": "2017-11-16", "venue": "", "city": "PRABI (Campus scientifique de la Doua, LYON-VILLEURBANNE)", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 259, "name": "Advanced sequence analysis", "shortName": "", "description": "https://cnrsformation.cnrs.fr/stage-19019-Analyse-avancee-de-sequences.h...\n", "homepage": "https://cnrsformation.cnrs.fr/pdf/16148.pdf", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [ "NGS Data Analysis", "Analysis of RNAseq data", "Sequence Algorithm", "Bioinformatics & Biomedical", "Galaxy", "Variant analysis", "Transcriptomics (RNA-seq)", "Genomics (DNA-seq)", "Sequence annotation", "Pattern matching", "Multiple sequence alignment" ], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "CNRS fee-based training\n", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "", "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Training course", "start_date": "2019-05-13", "end_date": null, "venue": "", "city": "CBiB", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 78, "name": "RNASeq with Galaxy", "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": "2017-05-22", "end_date": "2017-05-23", "venue": "", "city": "Roscoff", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 509, "name": "New session of Molecular Phylogeny - Level 1", "shortName": "New session of Phylogénie moléculaire - Niveau 1", "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/liste-stages-176-Bioinformatique.html", "is_draft": false, "costs": [ "1200 €" ], "topics": [ "http://edamontology.org/topic_3299", "http://edamontology.org/topic_0084", "http://edamontology.org/topic_3293" ], "keywords": [], "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": "2023-10-05T12:37:00.397895Z", "type": "Training course", "start_date": "2023-03-29", "end_date": "2023-03-31", "venue": "", "city": "Montpellier", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": "Onsite" }, { "id": 610, "name": "Cluster - 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You will launch your first processing batch on the cluster and will learn how to track and manage them. Organized jointly by the Sigenae and bioinfo genotoul platforms.", "homepage": "http://bioinfo.genotoul.fr/index.php/events/cluster-2/", "is_draft": false, "costs": [ "Priced", "Non-academic: 550€ + 20% taxes (TVA)", "Academic but non-INRAE: 170 € + 20% taxes (TVA)", "For INRAE's staff: 150 € no VAT charged;" ], "topics": [], "keywords": [ "Linux", "Cluster" ], "prerequisites": [ "Linux/Unix" ], "openTo": "Everyone", "accessConditions": "You need to register (via the website) and pay 165 euros a day for academic and 550 euros a day for a private.", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/344/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 37, "name": "MIAT - Mathématiques et Informatique Appliquées de Toulouse", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/MIAT%20-%20Math%C3%A9matiques%20et%20Informatique%20Appliqu%C3%A9es%20de%20Toulouse/?format=api" } ], "organisedByTeams": [ { "id": 22, "name": "Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-bioinfo/?format=api" } ], "logo_url": "http://bioinfo.genotoul.fr/wp-content/uploads/bioinfo_logo-rvb-petit.png", "updated_at": "2024-03-26T14:24:58.135354Z", "type": "Training course", "start_date": "2024-04-23", "end_date": "2024-04-23", "venue": "", "city": "Castanet Tolosan", "country": "France", "geographical_range": "", "trainers": [], "trainingMaterials": [ { "id": 139, "name": "Cluster Slides - Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Cluster%20Slides%20-%20Genotoul-bioinfo/?format=api" }, { "id": 140, "name": "Cluster TP - Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Cluster%20TP%20-%20Genotoul-bioinfo/?format=api" } ], "computingFacilities": [], "realisation_status": "past", "registration_opening": "2024-03-24", "registration_closing": null, "registration_status": "open", "courseMode": "Onsite" }, { "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. 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