Event List
Handles creating, reading and updating events.
GET /api/event/?format=api&offset=280&ordering=registration_opening
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We will work on a HPC server and use linux powerful commands to allow to analyze big amount of biological data.\n \nPrerequisites\nBasic knowledge of Linux (Linux for dummies required)\n\nProgram\nConnecting to a distant HPC\nManipuling text files\nComplex searching for text in a file\nCombining several commands\nWriting simple shell scripts\n\n\nLearning objectives\nAfter this course, participants should be able to:\nManipulate and search within text files\nChain and combine commands\nPerform the same actions on many files\nWrite a simple shell script\n\n\n \n\n\nInstructors\nChristine Tranchant (CT) - christine.tranchant@ird.fr\nNdomassi Tando (NT) - ndomassi.tando@ird.fr\nBruno Granouillac (BG) - bruno.granouillac@ird.fr\nFrançois Sabot (SB) - francois.sabot@ird.fr\nGautier Sarah (GS) - gautier.sarah@cirad.fr\n\n", "homepage": "https://southgreenplatform.github.io/trainings/linuxJedi/", "is_draft": false, "costs": [ "Free" ], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [ { "id": 24, "name": "South Green", "url": "https://catalogue.france-bioinformatique.fr/api/team/South%20Green/?format=api" } ], "logo_url": "", "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Training course", "start_date": "2018-03-12", "end_date": null, "venue": "", "city": "Centre IRD, Montpellier", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 318, "name": "MicroScope: formation avancée", "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": "2017-12-03", "end_date": "2017-12-04", "venue": "", "city": "Université d'Evry Val d'Essonne", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 206, "name": "Marseille Hackathon Training Event", "shortName": "", "description": " 3-days training session / hackathon in Marseille", "homepage": "https://www.greekc.org/activity/marseille-training-event/", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 3, "name": "IFB", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/IFB/?format=api" } ], "organisedByOrganisations": [ { "id": 10, "name": "GREEKC", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/GREEKC/?format=api" } ], "organisedByTeams": [], "logo_url": "https://ressources.france-bioinformatique.fr/sites/default/files/Logotype_pictogramme-128.png", "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Training course", "start_date": "2019-04-23", "end_date": "2019-04-26", "venue": "", "city": "Faculté des science de Luminy, Marseille", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 105, "name": "Data collection and registration of Clinical Trials 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": "2017-09-24", "end_date": null, "venue": "", "city": "Paris (à distance)", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 511, "name": "New session of Molecular Phylogeny - Level 2", "shortName": "New session of Phylogénie moléculaire - Niveau 2", "description": "OBJECTIF\r\n- Être capable de tester des hypothèses et d'ajuster des modèles permettant de comprendre l'évolution à l'échelle moléculaire\r\n\r\nPRÉREQUIS\r\n- Avoir déjà utilisé les logiciels de base en phylogénie moléculaire\r\n- Maîtriser les notions de base en statistiques (tests statistiques, principe du bootstrap, intervalles de confiances, etc.) et de probabilités (probabilités jointes / conditionnelles, théorème de Bayes, etc.)\r\n- Maîtriser un langage de programmation\r\n- Notions de phylogénie moléculaire\r\nAvoir suivi le stage \"Phylogénie moléculaire - formation de base\" ou niveau équivalent \r\n\r\nPROGRAMME\r\n- Phylogénétique et génétique des populations\r\n- Détection de sélection positive au sein de séquences codantes\r\n- Datation moléculaire : intégrer fossiles et molécules\r\n- Phylogénomique\r\n- Super-arbres et super-matrices, réconciliations d'arbres\r\n- Visualisation de l'information en phylogénie\r\n- Placement phylogénétique\r\n- Bases d'épidémiologie (modèles en compartiments, ODE, applications, etc)\r\n- Simulations selon une variété de modèles épidémiologiques\r\n- Phylodynamique : combiner épidémiologie et évolution", "homepage": "https://cnrsformation.cnrs.fr/liste-stages-176-Bioinformatique.html", "is_draft": false, "costs": [ "Priced", "1200 €" ], "topics": [], "keywords": [ "Phylogeny", "Selection Detection", "Phylogenomics" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/282/?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": "2023-10-05T12:36:32.255069Z", "type": "Training course", "start_date": "2023-10-04", "end_date": "2023-10-06", "venue": "", "city": "Montpellier", "country": "France", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": "Onsite" }, { "id": 108, "name": "Survival Guide for Perl applied to Bioinformatics", "shortName": "", "description": "This course provides an introduction to programming using Perl.", "homepage": "https://southgreenplatform.github.io/trainings//perl/", "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": "2017-10-01", "end_date": "2017-10-05", "venue": "", "city": "ISRA, Bel Air, Dakar (Sénégal)", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 236, "name": "W4E 2020", "shortName": "", "description": "During this one-week course, Participants will learn how to use the W4M infrastructure to analyze their own dataset", "homepage": "https://workflow4metabolomics.org/w4e2020", "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/workflow4metabolomics_0.png", "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Training course", "start_date": "2020-02-03", "end_date": "2020-02-07", "venue": "", "city": "Centre For Fine Arts (BOZAR), rue Royale n°10 to 1000 - Brussels (Belgium)", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 336, "name": "Utilisation des outils d'interprétation des données de protéomique MSDA et Proline", "shortName": "", "description": "", "homepage": "", "is_draft": false, "costs": [ "Free" ], "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": "2017-11-06", "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": 133, "name": "ELIXIR Innovation and SME Forum: Data Driven Innovation in Rare Diseases and Personalised Medicine", "shortName": "", "description": "IFB will host the next ELIXIR Innovation and SME Forum: Data Driven Innovation in Rare Diseases & Personalised Medicine.", "homepage": "https://www.elixir-europe.org/events/elixir-innovation-and-sme-forum-data-driven…", "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/elixir_node_france.png", "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Conference", "start_date": "2017-11-14", "end_date": null, "venue": "", "city": "Paris, France", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 391, "name": "INTRODUCTION À L'ANALYSE DE DONNÉES", "shortName": "", "description": "\nL'utilisation de plus en plus répandue de techniques d’imagerie et de séquençage à haut-débit en biologie est en train de révolutionner les sciences du vivant et de modifier en profondeur leurs pratiques. Dans ce contexte, des outils statistiques sont développés pour permettre d’analyser ces données de hautes dimensions, et la maîtrise de ces outils devient de plus en plus nécessaire pour produire des résultats de bonne qualité. Ce cours de 4 semaines couvrira les étapes nécessaires pour mettre en place un processus d’analyse de données, depuis la planification de l’expérience jusqu’à la fouille des données en passant par l’échantillonnage, les test d’hypothèses, la modélisation statistique etc.\nCe cours s’adresse en priorité aux étudiants de première année de thèse de l’Institut Pasteur. Tout étudiant en thèse sera automatiquement inscrit à ce cours, mais les élèves de 2e année, de 3e année ou les post-doctorants peuvent également s’inscrire, dans la limite des places disponibles. Il est à noter que le cours est obligatoire pour les étudiants de 1ère année. Des dispenses partielles ou totales sont possibles pour les étudiants qui ont déjà des connaissances en statistique, en mathématique ou en physique. Le cours déroulera sur 4 semaines, 4 jours par semaine, trois heures par jour. Chaque séance de trois heures alternera cours magistral et mise en pratique. Il y aura deux sessions : la première commencera le 22 octobre 2018 et la deuxième le 14 janvier 2019.\nChacune de ces deux sessions sera précédée d’une séance d’introduction à l’informatique. Cette séance proposera des notions d’architecture de l’ordinateur, de système d’organisation des fichiers et de format de fichiers. Chaque session sera également suivie d’un cours optionnel sur l’analyse et le traitement des images.\nPour plus d’information, ainsi que pour les inscriptions au module optionnel et les demandes d’exemption, rendez-vous sur la page du cours : https://c3bi.pasteur.fr/introduction-to-data-analysis-2018-19/\nThèmes abordés\nLe module d’analyse de données couvrira un large champ de notions nécessaires aux étudiants pour planifier leurs expériences, analyser et explorer leurs données, interpréter les résultats et générer des figures à des fins de publication. Il abordera des notions de base en statistique, dont les analyses uni- et multivariées, les analyses descriptives, les distributions statistiques usuelles utilisées en biologie, ainsi que les tests d’hypothèses. Les exercices et travaux pratiques seront réalisés avec R et RStudio. Plusieurs séances seront consacrées à une introduction à l’utilisation du langage de programmation R avant d’aborder les notions de statistiques et d’analyse de données.\nLe module d’analyse d’images introduira les principes de base de l’analyse d’image, et portera plus particulièrement sur l’extraction d’information quantitative d’images de microscopie. Ce cours est destiné aux personnes ayant peu ou pas d’expérience en analyse d’image. Il sera très orienté sur la pratique : des cours magistraux de courte durée seront immédiatement suivis de sessions pratiques. 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