Training List
Handles creating, reading and updating training events.
GET /api/training/?format=api&offset=100&ordering=-updated_at
{ "count": 383, "next": "https://catalogue.france-bioinformatique.fr/api/training/?format=api&limit=20&offset=120&ordering=-updated_at", "previous": "https://catalogue.france-bioinformatique.fr/api/training/?format=api&limit=20&offset=80&ordering=-updated_at", "results": [ { "id": 352, "name": "Développement d’une application avec R Shiny /", "shortName": "R Shiny", "description": "Objectifs pédagogiques\r\n\r\nÀ l’issue de la formation, les stagiaires connaîtront les principes de bases et le fonctionnement du package “Shiny”. Ils et elles seront capables de créer leurs premières applications web interactives à partir de scripts R. Les solutions de déploiement d’applications Shiny seront également abordées.\r\n\r\nProgramme\r\n\r\nPrincipes généraux et fonctionnement d’une application Shiny\r\nDéveloppement d’applications Shiny\r\nDéploiement d’applications Shiny", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_0605" ], "keywords": [ "Shiny" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" }, { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" } ], "organisedByTeams": [ { "id": 10, "name": "MIGALE", "url": "https://catalogue.france-bioinformatique.fr/api/team/MIGALE/?format=api" } ], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2024-01-18T13:14:32.711762Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "À l’issue de la formation, les stagiaires connaîtront les principes de bases et le fonctionnement du package “Shiny”. Ils et elles seront capables de créer leurs premières applications web interactives à partir de scripts R. Les solutions de déploiement d’applications Shiny seront également abordées.", "hoursPresentations": 2, "hoursHandsOn": 4, "hoursTotal": 6, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/571/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/785/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/686/?format=api" ] }, { "id": 351, "name": "Introduction au language R / Introduction to R langage", "shortName": "Introduction to R langage", "description": "Objectifs pédagogiques :\r\nÀ l’issue de la formation, les stagiaires connaîtront les principales fonctionnalités du langage R et ses principes. Ils seront capables de les appliquer pour effectuer des calculs ou des représentations graphiques simples. Ils seront de plus autonomes pour manipuler leurs tableaux de données.\r\nAttention : ce module n’est ni un module de statistique, ni un module d’analyse statistique des données.\r\n\r\nProgramme :\r\n* Structures et manipulation de données\r\n* Principaux éléments du langage de programmation (boucle, fonctions…)\r\n* Différentes représentations graphiques de données/résultats (plot, histogramme, boxplot)", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_0605" ], "keywords": [ "R Language" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" }, { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" } ], "organisedByTeams": [ { "id": 10, "name": "MIGALE", "url": "https://catalogue.france-bioinformatique.fr/api/team/MIGALE/?format=api" } ], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2024-01-18T12:51:01.486572Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 2, "hoursHandsOn": 10, "hoursTotal": 12, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/570/?format=api" ] }, { "id": 345, "name": "Graphiques sous R avec ggplot2 / Graphics with R-ggplot2", "shortName": "ggplot2", "description": "Objectifs pédagogiques :\r\nÀ l’issue de la formation, les stagiaires connaîtront les principales fonctionnalités du package R « ggplot2 » et la démarche sous-jacente pour construire un graphique à partir d’un tableau de données. Ils seront capables de réaliser plusieurs types de représentations graphiques, telles que des nuages de points, des courbes, des histogrammes, des diagrammes en bâtons, des boxplots, des heatmaps, etc. Les stagiaires pourront apporter leur propre tableau de données et pratiquer dessus en fin de formation. \r\n\r\nProgramme :\r\n- Principes généraux liés au package ggplot2 \r\n- Principales fonctions graphiques pour réaliser des nuages de points, des histogrammes, des boxplots, etc. \r\n- Principales fonctions pour jouer sur les coloriages en fonction d’une variable, sur les échelles de couleurs, sur les graduations, sur les représentations multiples, etc.", "homepage": "https://migale.inrae.fr/trainings", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_0091", "http://edamontology.org/topic_0605", "http://edamontology.org/topic_2269" ], "keywords": [ "Représentations graphiques" ], "prerequisites": [ "Langage R de base" ], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" }, { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" } ], "organisedByTeams": [ { "id": 10, "name": "MIGALE", "url": "https://catalogue.france-bioinformatique.fr/api/team/MIGALE/?format=api" } ], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2024-01-18T12:50:47.605879Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "À l’issue de la formation, les stagiaires connaîtront les principales fonctionnalités du package R « ggplot2 » et la démarche sous-jacente pour construire un graphique à partir d’un tableau de données. Ils seront capables de réaliser plusieurs types de représentations graphiques, telles que des nuages de points, des courbes, des histogrammes, des diagrammes en bâtons, des boxplots, des heatmaps, etc.", "hoursPresentations": 1, "hoursHandsOn": 5, "hoursTotal": 6, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/554/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/569/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/683/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/778/?format=api" ] }, { "id": 296, "name": "Initiation à l’utilisation de Galaxy", "shortName": "Initiation Galaxy", "description": "Objectifs pédagogiques :\r\nCette formation propose une introduction sur l’interface utilisateur et les fonctionnalités générales d’une plateforme Galaxy.\r\nA l’issue de la formation, les apprenants seront en mesure de :\r\n* connaître les caractéristiques et le fonctionnement d’un portail Galaxy,\r\n* appliquer sur des cas concrets en bioinformatique,\r\n* être autonome dans le traitement de fichiers et l’exécution d’outils.\r\n\r\nProgramme :\r\n* Prise en main d’un portail Galaxy\r\n* Utilisation de l’historique\r\n* Téléchargement des données à traiter\r\n* Manipulation de fichiers\r\n* Paramétrage et exécution d’outils\r\n* Récupération et visualisation de résultats", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_0605" ], "keywords": [ "Galaxy" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" }, { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" } ], "organisedByTeams": [ { "id": 10, "name": "MIGALE", "url": "https://catalogue.france-bioinformatique.fr/api/team/MIGALE/?format=api" } ], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2024-01-18T12:44:57.722597Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "All" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "Cette formation propose une introduction sur l’interface utilisateur et les fonctionnalités générales d’une plateforme Galaxy.\r\n\r\nA l’issue de la formation, les apprenants seront en mesure de :\r\n* connaître les caractéristiques et le fonctionnement d’un portail Galaxy,\r\n* appliquer sur des cas concrets en bioinformatique,\r\n* être autonome dans le traitement de fichiers et l’exécution d’outils.", "hoursPresentations": 1, "hoursHandsOn": 5, "hoursTotal": 6, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/442/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/790/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/580/?format=api" ] }, { "id": 350, "name": "Formation Principes FAIR dans un projet de bioinformatique", "shortName": "FAIR-Bioinfo-Strasbourg", "description": "Cette formation sur 3 jours est destinée à des bioinformaticiens et biostatisticiens souhaitant acquérir des compétences théoriques et pratiques sur les principes \"FAIR\" (Facile à trouver, Accessible, Interopérable, Réutilisable) appliqués à un projet d'analyse et/ou de développement.", "homepage": "", "is_draft": false, "costs": [ "Free to academics" ], "topics": [], "keywords": [ "Programming Languages & Computer Sciences", "FAIR", "Snakemake", "Docker" ], "prerequisites": [ "Linux - Basic Knowledge" ], "openTo": "Everyone", "accessConditions": "Academics", "maxParticipants": 14, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/563/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/124/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 79, "name": "IBMP", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IBMP/?format=api" }, { "id": 83, "name": "IGBMC", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IGBMC/?format=api" } ], "organisedByTeams": [ { "id": 14, "name": "BiGEst", "url": "https://catalogue.france-bioinformatique.fr/api/team/BiGEst/?format=api" } ], "logo_url": null, "updated_at": "2023-12-20T15:44:00.254606Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Bioinformaticians" ], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "A l'issue de cette formation, les participants pourront mettre en oeuvre les principes de la science reproductible : encapsuler un environnement de travail (Docker, Singularity), concevoir et exécuter des workflows (Snakemake), gérer des versions de code (Git), passer à l’échelle sur un cluster de calcul (Slurm), gérer des environnements logiciels (Conda) et assurer la traçabilité de leur analyse à l’aide de Notebooks (Jupyter).", "hoursPresentations": 10, "hoursHandsOn": 11, "hoursTotal": 21, "personalised": false, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/568/?format=api" ] }, { "id": 349, "name": "Reproducible Research", "shortName": "", "description": "The following topics and tools are covered in the course:\r\n\r\n Data management\r\n Project organisation\r\n Git\r\n Conda\r\n Snakemake\r\n Nextflow\r\n R Markdown\r\n Jupyter\r\n Docker\r\n Singularity\r\n\r\nAt the end of the course, students should be able to:\r\n\r\n Use good practices for data analysis and management\r\n Clearly organise their bioinformatic projects\r\n Use the version control system Git to track and collaborate on code\r\n Use the package and environment manager Conda\r\n Use and develop workflows with Snakemake and Nextflow\r\n Use R Markdown and Jupyter Notebooks to document and generate automated reports for their analyses\r\n Use Docker and Singularity to distribute containerized computational environments", "homepage": "https://southgreenplatform.github.io/training_reproducible_research/", "is_draft": false, "costs": [ "Free" ], "topics": [], "keywords": [], "prerequisites": [ "Linux - Basic Knowledge" ], "openTo": "Internal personnel", "accessConditions": "Open to South Green close collaborators", "maxParticipants": 20, "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": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png", "updated_at": "2023-12-04T15:16:00.921744Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "At the end of the course, students should be able to:\r\n\r\n Use good practices for data analysis and management\r\n Clearly organise their bioinformatic projects\r\n Use the version control system Git to track and collaborate on code\r\n Use the package and environment manager Conda\r\n Use and develop workflows with Snakemake and Nextflow\r\n Use R Markdown and Jupyter Notebooks to document and generate automated reports for their analyses\r\n Use Docker and Singularity to distribute containerized computational environments", "hoursPresentations": 8, "hoursHandsOn": 13, "hoursTotal": 21, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/567/?format=api" ] }, { "id": 294, "name": "Linux for Dummies", "shortName": "", "description": "This course offers an introduction to work with Linux. We will describe the Linux environment, the first linux commands so participants can start to utilize command-line tools and feel comfortable using bioinformatics softwares through a linux terminal", "homepage": "https://southgreenplatform.github.io/trainings//linux/", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "Open to South Green close collaborators", "maxParticipants": 15, "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": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png", "updated_at": "2023-12-04T15:05:31.847400Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 3, "hoursHandsOn": 4, "hoursTotal": 7, "personalised": false, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/468/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/555/?format=api" ] }, { "id": 313, "name": "RNA-Seq analysis", "shortName": "", "description": "Introduction to RNA-Seq analysis", "homepage": "https://southgreenplatform.github.io/trainings//rnaseq/", "is_draft": false, "costs": [ "Free" ], "topics": [], "keywords": [], "prerequisites": [ "Linux - Basic Knowledge" ], "openTo": "Internal personnel", "accessConditions": "Open to South Green close collaborators", "maxParticipants": 15, "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": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png", "updated_at": "2023-12-04T15:04:39.023455Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 6, "hoursHandsOn": 8, "hoursTotal": 14, "personalised": false, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/473/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/471/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/563/?format=api" ] }, { "id": 347, "name": "Introduction to Microbial Comparative Genomics", "shortName": "", "description": "This course offers an introduction to microbial genomics analysis.\r\nIt includes 5 issues: assembly, genome annotation, circos visualization, pan-genome construction, pan-GWAS.", "homepage": "https://southgreenplatform.github.io/trainings//bacterialGenomics/", "is_draft": false, "costs": [ "Free" ], "topics": [], "keywords": [ "genomics", "Structural genomics", "Genome analysis" ], "prerequisites": [ "Linux - Basic Knowledge" ], "openTo": "Internal personnel", "accessConditions": "Open to South Green close collaborators", "maxParticipants": 20, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/174/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/771/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/772/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/773/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "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": "2023-12-04T14:54:55.468140Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 5, "hoursHandsOn": 5, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/558/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/561/?format=api" ] }, { "id": 348, "name": "Advanced HPC Trainings", "shortName": "", "description": "This course continues the explanation on how to work on HPC Southgreen clusters. It is intended for experienced users, with the goals of improving LC user productivity and minimizing the obstacles. New notions and tools are presented such as job arrays, basic softwares installation,module environment and singularity. All these notions will be developped.", "homepage": "https://southgreenplatform.github.io/trainings//Advanced_HPC/", "is_draft": false, "costs": [ "Free" ], "topics": [], "keywords": [ "HPC", "SLURM" ], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "Oprn to South Green close collaborators", "maxParticipants": 20, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/589/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 85, "name": "IRD", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IRD/?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": "2023-12-04T14:46:58.108350Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "All" ], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/557/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/565/?format=api" ] }, { "id": 344, "name": "Analyses Single Cell RNA-seq (ScRNA-seq) avec R", "shortName": "", "description": "Cette formation introduira notamment la librairie Seurat permettant la manipulation et l'analyse de données Single Cell RNA-seq ainsi que la visualisation des résultats d'analyse\r\n\r\n- Rappels des concepts du séquençage Single Cell RNA-seq\r\n- Importation des données Single Cell dans R\r\n- Intégration de données Single Cell multiples\r\n- Quality Check et pré-traitement des données\r\n- Normalisation de données\r\n- Identification de marqueurs\r\n- Clustering et assignation cellulaire\r\n- Analyse différentielle des groupes cellulaires\r\n- Savoir intégrer les données de spatialisation\r\n- Savoir intégrer les données de trajectoire\r\n- Savoir intégrer les données de communication cellulaire\r\n- Savoir intégrer les données d'épigénétique (ATAC-seq)", "homepage": "https://cnrsformation.cnrs.fr/analyses-single-cell-rna-seq-scrna-seq-avec-r?axe=176", "is_draft": false, "costs": [], "topics": [], "keywords": [ "Bioinformatics & Biomedical", "R Language", "R", "NGS Sequencing Data Analysis" ], "prerequisites": [ "Basic knowledge of R", "R programming" ], "openTo": "Everyone", "accessConditions": "Maîtrise du langage R\r\nAvoir suivi le stage \"Langage R : introduction\" ou niveau équivalent.\r\nAfin de vérifier que votre maîtrise du langage R est suffisante pour pouvoir suivre ce stage, nous vous invitons à effectuer et à renvoyer le test téléchargeable\r\nhttps://cnrsformation.cnrs.fr/data/STG_23294_55153.docx", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/154/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 6, "name": "CNRS formation entreprise", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/CNRS%20formation%20entreprise/?format=api" } ], "organisedByOrganisations": [ { "id": 1, "name": "CNRS formation entreprises", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/CNRS%20formation%20entreprises/?format=api" } ], "organisedByTeams": [ { "id": 6, "name": "CBiB", "url": "https://catalogue.france-bioinformatique.fr/api/team/CBiB/?format=api" } ], "logo_url": "https://services.cbib.u-bordeaux.fr/utils/logo_cbib.png", "updated_at": "2023-08-31T09:19:56.754683Z", "audienceTypes": [ "Graduate", "Professional (initial)" ], "audienceRoles": [ "Biologists", "Bioinformaticians" ], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "- Savoir expertiser et manipuler des données issues d'expériences Single Cell RNA-seq\r\n- Savoir mener une analyse différentielle à de multiples niveaux\r\n- Savoir intégrer des données complémentaires pour l'analyse Single Cell RNA-seq (spatial, trajectoire, cell communication, cell identification...)", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/650/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/653/?format=api" ] }, { "id": 326, "name": "Principes FAIR pour la gestion des données d'une plateforme IBISA", "shortName": "FAIR data IBISA", "description": "Cette session de formation a pour but de former des responsables et membres de plateformes IBISA aux principes FAIR de gestion des données .\r\nLa formation se déroule sur 2 jours avec une alternance de présentation générales, et techniques, témoignages et ateliers pratiques pour travailler sur différents sujets : PGD de structure, métadonnées, sécurité des données,...etc.\r\nA la fin de cette formation auront \r\n- acquis des connaissances théoriques et pratiques sur la gestion selon les principes FAIR de leurs données dans le contexte de la Science Ouverte\r\n- identifié des pistes d'amélioration pour la gestion des données de leur plateforme.", "homepage": "https://moodle.france-bioinformatique.fr/course/view.php?id=16", "is_draft": false, "costs": [ "Free" ], "topics": [ "http://edamontology.org/topic_3420", "http://edamontology.org/topic_0219", "http://edamontology.org/topic_3571" ], "keywords": [ "Données" ], "prerequisites": [ "Biologists" ], "openTo": "Internal personnel", "accessConditions": "private for IBISA platform staff", "maxParticipants": 30, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/162/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/116/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 3, "name": "IFB", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/IFB/?format=api" } ], "organisedByOrganisations": [ { "id": 43, "name": "IFB-core", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IFB-core/?format=api" } ], "organisedByTeams": [ { "id": 29, "name": "IFB Core", "url": "https://catalogue.france-bioinformatique.fr/api/team/IFB%20Core/?format=api" } ], "logo_url": "https://moodle.france-bioinformatique.fr/pluginfile.php/1/core_admin/logocompact/300x300/1654772049/IFB-HAUT-COULEUR-PETIT.png", "updated_at": "2023-08-22T14:25:08.237204Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "A la fin de cette formation, les participants connaîtront et pourront mettre en œuvre les principes de la science ouverte pour gérer leurs jeux de données dans un projet :\r\n- Les principes fondamentaux de l’Open Data en biologie et santé, y compris dans ses aspects juridiques ;\r\n- Les bonnes pratiques et outils de gestion des données d’un projet en bioinformatique, en lien avec les ressources de l’infrastructure IFB ;\r\n- Le PGD : séances théoriques et pratiques de construction d’un PGD sur des exemples de jeux de données omiques ;\r\n- Le choix des métadonnées : panorama des ressources existantes pour choisir des métadonnées et mise en pratique pour annoter des jeux de données omiques en vue de la publication des données dans une banque internationale ou un dataverse institutionnel.", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": false, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/627/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/513/?format=api" ] }, { "id": 335, "name": "FAIR_bioinfo_@_AuBi", "shortName": "FAIR_bioinfo", "description": "Introduction aux bonnes pratiques en bio-informatique afin de pérenniser son travail de recherche.\r\n\r\nCette formation permet de découvrir les bonnes pratiques dans le cadre d’un travail nécessitant des approches programmatiques (statistiques, programmation d’outils, analyses de données biologiques). Elle s’inscrit aussi dans l’aspect science-ouverte afin de rendre plus facilement disponible et pérenne le travail bio-informatique. Après une introduction aux pratiques FAIR axées notamment sur les notions de reproductibilité et de répétabilité du code, plusieurs approches seront abordées: les bonnes pratiques de partage et gestion des versions des outils utilisés ; la gestion des environnements de travail (conda, docker, singularity) ; découverte du gestionnaire de workflow Snakemake : et enfin la documentation du code avec Rmarkdown et Jupyter.", "homepage": "https://mesocentre.uca.fr/actualites/pratiques-fair-en-bioinformatique-pour-des-analyses-reproductibles", "is_draft": false, "costs": [ "Free to academics" ], "topics": [ "http://edamontology.org/topic_0769", "http://edamontology.org/topic_3068", "http://edamontology.org/topic_0091", "http://edamontology.org/topic_3307" ], "keywords": [ "Methodology", "Programming Languages & Computer Sciences", "Cloud", "Linux", "Snakemake", "Docker", "R" ], "prerequisites": [ "Linux - Basic Knowledge" ], "openTo": "Everyone", "accessConditions": "Having an account on Mesocentre Clermont Auvergne Infrastructure", "maxParticipants": 15, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/261/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 87, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/AuBi/?format=api" }, { "id": 94, "name": "University Clermont Auvergne", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/University%20Clermont%20Auvergne/?format=api" } ], "organisedByTeams": [ { "id": 31, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/team/AuBi/?format=api" } ], "logo_url": "https://mesocentre.uca.fr/medias/photo/logoaubi-2019minus_1553844844490-jpg?ID_FICHE=41175", "updated_at": "2023-06-14T10:18:52.160465Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 10, "hoursHandsOn": 20, "hoursTotal": 30, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/537/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/709/?format=api" ] }, { "id": 334, "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. Although each omics data is usually analyzed individually, combining complementary data can yield a better understanding of the mechanisms involved in biological processes. Several integrative approaches are now available to combine such data, coming essentially from two families of methods, namely multivariate statistical analyses and network-based approaches. During this summer school both methodologies will be covered, introducing RGCCA and mixOmics for multivariate analyses and WGCNA and SNF for network-based strategies. To get meaningful biological information, the interpretation of statistical results needs to be done contextualizing them in the available biological knowledge. To address this major step we need to be able to access and interrogate databases. 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": [], "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": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": null, "contacts": [], "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": null, "updated_at": "2023-04-26T16:14:06.237852Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/532/?format=api" ] }, { "id": 272, "name": "Molecular Phylogeny - Level 2", "shortName": "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": "", "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": "https://ressources.france-bioinformatique.fr/sites/default/files/ATGClogox120_0.png", "updated_at": "2023-01-24T10:49:17.913427Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/474/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/511/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/402/?format=api" ] }, { "id": 271, "name": "Bioinformatique pour le traitement de données de séquençage (NGS) : analyse de transcriptome", "shortName": "", "description": "OBJECTIFS\r\n- Comprendre les principes des méthodes d'analyse de données de séquençage à haut débit\r\n- Comprendre les résultats obtenus, les paramètres et leurs impacts sur les analyses\r\n- Savoir choisir et utiliser les principaux outils d'analyse\r\n- Être autonome pour utiliser un pipeline d'analyse\r\n- Savoir manipuler les fichiers de séquences : préparation et filtration\r\n- Savoir évaluer la qualité des données\r\n- Savoir analyser les résultats avec ou sans génome de référence\r\n\r\nPRÉREQUIS\r\n- Notions de base en informatique : fichiers, répertoire...\r\n- Notions du système linux et des lignes de commande\r\n- Niveau master \r\n\r\nPROGRAMME\r\n- Linux : commandes de base\r\n- Les données NGS : fichiers, manipulation de base, nettoyage\r\n- Mapping : principaux outils et pratique\r\n- Transcriptomique :\r\n. analyse de RNA-seq : expression différentielle des gènes / des ARNs (comptage et DESeq2) ; comparaison d'échantillons issus de conditions différentes\r\n. post-analyse : analyse GO, interrogation bases de connaissances (ex : KEGG), création de graphique (en R)\r\n. analyse couplée transcriptome / traductome", "homepage": "", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [ "NGS Sequencing Data Analysis" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "PUBLICS :\r\n- Biologistes, professionnels des sciences du vivant ayant besoin d'analyser des données de séquençage\r\n- Ingénieurs ou chercheurs en bioinformatique\r\n- Bioanalystes\r\n \r\nPRÉREQUIS\r\n- Notions de base en informatique : fichiers, répertoire...\r\n- Notions du système linux et des lignes de commande\r\n- Niveau master", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/528/?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": "https://ressources.france-bioinformatique.fr/sites/default/files/ATGClogox120.png", "updated_at": "2023-01-24T10:47:30.457628Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/401/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/510/?format=api" ] }, { "id": 306, "name": "Molecular Phylogeny - Level 1", "shortName": "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": "", "is_draft": false, "costs": [ "1200 €" ], "topics": [ "http://edamontology.org/topic_0084", "http://edamontology.org/topic_3293", "http://edamontology.org/topic_3299" ], "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": "https://ressources.france-bioinformatique.fr/sites/default/files/ATGClogox120_0.png", "updated_at": "2023-01-24T10:44:55.936489Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "To know how to infer a phylogenetic tree and interpret it.", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": true, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/460/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/509/?format=api" ] }, { "id": 322, "name": "Introduction to Structural variant detection analyses", "shortName": "", "description": "Program\r\n\r\n* Handling mapping tools suitable for ILLUMINA and ONT data (bwa, minimap2)\r\n* SNP detection from mapping of short reads against a reference genome: SNP calling, filters and SNP annotation. Examples of possible studies based on SNP arrays\r\n* Detecting Structural Variations (SV) in short and long reads (breakdancer, sniffle)\r\n* SV detection from genome assembly and comparison (minimap2, nucmer, assemblytics, siry)", "homepage": "https://southgreenplatform.github.io/trainings//sv/", "is_draft": false, "costs": [ "Free" ], "topics": [], "keywords": [], "prerequisites": [ "Linux and knowledge of NGS formats" ], "openTo": "Internal personnel", "accessConditions": "Open to South Green close collaborators", "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": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png", "updated_at": "2023-01-24T10:41:28.470404Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 14, "hoursHandsOn": 14, "hoursTotal": 28, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/564/?format=api" ] }, { "id": 256, "name": "RNASeq analyses (using Galaxy and TOGGLe)", "shortName": "", "description": "This course offers an introduction to RNASeq analyses using two different workflow management systems: Galaxy and TOGGLe. This includes reference-based mapping, estimates of transcript levels, differential expression (DE) analyses, visualization of statistics results.\r\nPrerequisites\r\nWorkflow management system (Galaxy, TOGGLe)\r\n\r\nProgram\r\nMapping of RNASeq against a transcriptome reference with kallisto (Galaxy)\r\nMapping of RNASeq against an annotated genome reference with TopHat (TOGGLe)\r\nDifferential expression analysis using EdgeR and DESeq2\r\nPlots, clustering, co-expression network: degust, WGCNA\r\n\r\n\r\nLearning objectives\r\nManipulate packages/tools available for searching DE genes\r\nThink about different normalisation methods\r\nDetect differentially expressed genes\r\nCompare results between two approaches\r\n\r\n\r\nInstructors\r\nAlexis Dereeper - alexis.dereeper@ird.fr\r\nSebastien Cunnac - sebastien.cunnac@ird.fr\r\nSebastien Ravel - sebastien.ravel@cirad.fr\r\nChristine Tranchant - christine.tranchant@ird.fr", "homepage": "https://southgreenplatform.github.io/trainings//rnaseq/", "is_draft": false, "costs": [ "Free" ], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "Open to South Green close collaborators", "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": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png", "updated_at": "2023-01-24T10:26:00.180547Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/388/?format=api" ] }, { "id": 257, "name": "Metabarcoding analyses (using FROGS in Galaxy and Phyloseq)", "shortName": "", "description": "This course offers an introduction to metabarcoding analyses at two different levels/steps: bioinformatics with FROGS pipeline in the Galaxy environment, biostatistics with PhyloSeq R package. This includes preprocessing, clustering and OTU picking, taxonomic assignation, estimation of diversity, visualization of statistics results.\r\nPrerequisites\r\nGalaxy, R knowledge\r\n\r\nProgram\r\nIntroduction to metagenomics and metabarcoding\r\nPre-processing, Clustering, taxonomic affiliation (FROGS)\r\nHandling and visualizing OTU table using PhyloSeq R package (PhyloSeq)\r\n\r\n\r\nLearning objectives\r\nManipulate tools available for metabarcoding analysis\r\nStudy sample diversity by using NGS and post-NGS analysis tools\r\nVisualize diversity metrics in metabarcoding approach\r\n\r\n\r\nInstructors\r\nJulie Orjuela - julie.orjuela@ird.fr\r\nFlorentin Constancias - florentin.constancias@cirad.fr\r\nAlexis Dereeper - alexis.dereeper@ird.fr", "homepage": "https://southgreenplatform.github.io/trainings//metabarcoding/", "is_draft": false, "costs": [ "Free" ], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "Open to South Green close collaborators", "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": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png", "updated_at": "2023-01-24T10:25:28.170059Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/566/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/389/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/535/?format=api" ] } ] }
