Training List
Handles creating, reading and updating training events.
GET /api/training/?format=api&offset=40&ordering=hoursPresentations
{ "count": 378, "next": "https://catalogue.france-bioinformatique.fr/api/training/?format=api&limit=20&offset=60&ordering=hoursPresentations", "previous": "https://catalogue.france-bioinformatique.fr/api/training/?format=api&limit=20&offset=20&ordering=hoursPresentations", "results": [ { "id": 394, "name": "Principes FAIR & Git Initiation", "shortName": "FAIR & GIT - Initiation", "description": "Objectifs\r\n- Principes FAIR :\r\n Connaître les principes FAIR\r\n Être capable de prendre en compte les principes FAIR dans l'ensemble des étapes d'un projet impliquant la \r\n collecte et/ou l'analyse de données\r\n- Initiation à Git :\r\n Savoir définir ce qu’est un outil de gestion de version\r\n Être capable d’initialiser un entrepôt Git pour un projet\r\n Être capable de définir quels fichiers inclure/exclure d’un projet\r\n Savoir enregistrer localement une nouvelle version pour un projet\r\n Savoir partager des modifications locales avec tous les contributeurs d’un projet\r\n Savoir gérer des modifications en parallèle en utilisant les branches\r\n Connaître les bonnes pratiques pour contribuer à projet tiers\r\n\r\nProgramme : \r\n- Principes FAIR\r\n Présentation des principes FAIR\r\n Exemples de bonnes pratiques dans la gestion des données : description, organisation du stockage, \r\n traitements et analyses, mise en accès\r\n- Initiation à Git\r\n Présentation des avantages de la gestion de versions (projets individuels & projets collaboratifs)\r\n Présentation des principes de fonctionnement de Git\r\n Présentation et mise en œuvre des commandes principales de Git (clone, checkout, add, rm, commit, merge,\r\n push, pull) ; en ligne de commande ou en utilisant une interface graphique (GitHub et GitLab)", "homepage": "https://abims.sb-roscoff.fr/module/fair_git", "is_draft": false, "costs": [ "Free" ], "topics": [], "keywords": [], "prerequisites": [ "none" ], "openTo": "Everyone", "accessConditions": "Pre-registration required.", "maxParticipants": 18, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/821/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 65, "name": "SBR - Roscoff Marine Station", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/SBR%20-%20Roscoff%20Marine%20Station/?format=api" } ], "organisedByTeams": [ { "id": 4, "name": "ABiMS", "url": "https://catalogue.france-bioinformatique.fr/api/team/ABiMS/?format=api" } ], "logo_url": "https://abims.sb-roscoff.fr/sites/default/files/abims.png", "updated_at": "2025-02-21T08:31:00.096988Z", "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "All" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 4, "hoursHandsOn": 4, "hoursTotal": 8, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/710/?format=api" ] }, { "id": 363, "name": "Introduction au text-mining avec AlvisNLP", "shortName": "Introduction to text-mining with AlvisNLP", "description": "Objectifs pédagogiques\r\nCette formation est dédiée à l’analyse de données textuelles (text-mining). L’objectif est l’acquisition des principales techniques pour la Reconnaissance d’Entités Nommées (REN) à partir de textes. Les entités nommées étudiées dans cette formation sont des objets ou concepts d’intérêts mentionnés dans les articles scientifiques ou les champs en texte libre (taxons, gènes, protéines, marques, etc.).\r\n\r\nLes participants vont acquérir les compétences pratiques nécessaires pour effectuer de façon autonome une première approche pour une application de text-mining. Le format est celui de Travaux Pratiques utilisant AlvisNLP, un outil pour la création de pipelines en text-mining développé par l’équipe Bibliome de l’unité MaIAGE. La formation s’adresse à des chercheurs et ingénieurs en (bio)-informatique ou en maths-info-stats appliquées\r\n\r\nProgramme\r\n* Présentation du text-mining et de la Reconnaissance des Entités Nommées (REN)\r\n* Travaux Pratiques sur des techniques de REN en utilisant AlvisNLP\r\n* Projection de lexiques\r\n* Application de patrons\r\n* Apprentissage automatique", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_0605", "http://edamontology.org/topic_3474" ], "keywords": [ "Text mining" ], "prerequisites": [ "Linux - Basic Knowledge" ], "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": "2024-01-18T14:56:19.822106Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Life scientists", "Biologists", "Bioinformaticians" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "Cette formation est dédiée à l’analyse de données textuelles (text-mining). L’objectif est l’acquisition des principales techniques pour la Reconnaissance d’Entités Nommées (REN) à partir de textes. Les entités nommées étudiées dans cette formation sont des objets ou concepts d’intérêts mentionnés dans les articles scientifiques ou les champs en texte libre (taxons, gènes, protéines, marques, etc.).\r\n\r\nLes participants vont acquérir les compétences pratiques nécessaires pour effectuer de façon autonome une première approche pour une application de text-mining. Le format est celui de Travaux Pratiques utilisant AlvisNLP, un outil pour la création de pipelines en text-mining développé par l’équipe Bibliome de l’unité MaIAGE. La formation s’adresse à des chercheurs et ingénieurs en (bio)-informatique ou en maths-info-stats appliquées", "hoursPresentations": 5, "hoursHandsOn": 7, "hoursTotal": 12, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/588/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/680/?format=api" ] }, { "id": 380, "name": "INTRODUCTION TO PYTHON", "shortName": "Python", "description": "The Toulouse Genotoul bioinformatics platform, organizes a 2 days long training course for non computer scientist and biologists aiming at learning the foundation of Python programming. In this training you will learn the basics of programming (variables, functions, control structures such as “if” condition, “for” loop”), writing simple programs which read files, and write results to others. The training course does not require any knowledge in programming, but basic Linux/bash commands are required (cd, ls).\r\n\r\nThis training focuses on practice. It consists of modules with a large variety of exercises described hereunder (PROVISIONAL SCHEDULE):\r\n\r\nUsing a Jupyter notebook (Day 1).\r\nUsing variables (Day 1).\r\nBasic operations and functions (Day 1).\r\nReading a file, writing to a file (Day 1).\r\nCharacter string manipulation (Day 1).\r\nLists and dictionaries (Day 2).\r\nThe if and for controls (Day 2).\r\nBases of algorithms (Day 2).", "homepage": "https://bioinfo.genotoul.fr/index.php/events/python/", "is_draft": false, "costs": [], "topics": [ "http://edamontology.org/topic_3307" ], "keywords": [ "Python Language" ], "prerequisites": [ "Linux/Unix" ], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/642/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 15, "name": "MIAT", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/MIAT/?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": "2025-12-01T11:55:51.057828Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Life scientists" ], "difficultyLevel": "Novice", "trainingMaterials": [ { "id": 142, "name": "Introduction to python", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Introduction%20to%20python/?format=api" } ], "learningOutcomes": "", "hoursPresentations": 5, "hoursHandsOn": 9, "hoursTotal": 14, "personalised": false, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/635/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/718/?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": 353, "name": "Analyse de données métagénomiques shotgun / shotgun metagenomics", "shortName": "Shotgun metagenomics", "description": "Objectifs pédagogiques\r\n\r\nCette formation est dédiée à l’analyse de données métagénomiques procaryotes de type « shotgun » issues de la technologie de séquençage Illumina. Nous présenterons les étapes bioinformatiques nécessaires pour nettoyer les données brutes et les caractériser d’un point de vue taxonomique. Nous aborderons ensuite les différentes stratégies à employer pour assembler les reads et obtenir des comptages sur des gènes prédits. Enfin nous présenterons quelques outils pour obtenir une annotation fonctionnelle des échantillons. A l’issue des 2 jours de formation, les stagiaires connaîtront le périmètre, les avantages et limites des analyses de données de séquençage shotgun. Ils seront capables d’utiliser les outils présentés sur les jeux de données de la formation. L’ensemble des TP se déroulera sur l’infrastructure de Migale et nécessite une pratique courante de la ligne de commande.\r\n\r\nProgramme\r\n\r\nIntroduction générale sur les données métagénomiques\r\nAssignation taxonomique\r\nNettoyage des données brutes\r\nAssemblage / Binning\r\nPrédiction de gènes procaryotes\r\nAnnotation fonctionnelle\r\nConclusion, limites des méthodes", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_3697" ], "keywords": [ "Metagenomics" ], "prerequisites": [ "Linux/Unix", "Cluster" ], "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": "2024-01-18T13:16:49.313752Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "Cette formation est dédiée à l’analyse de données métagénomiques procaryotes de type « shotgun » issues de la technologie de séquençage Illumina. Nous présenterons les étapes bioinformatiques nécessaires pour nettoyer les données brutes et les caractériser d’un point de vue taxonomique. Nous aborderons ensuite les différentes stratégies à employer pour assembler les reads et obtenir des comptages sur des gènes prédits. Enfin nous présenterons quelques outils pour obtenir une annotation fonctionnelle des échantillons. A l’issue des 2 jours de formation, les stagiaires connaîtront le périmètre, les avantages et limites des analyses de données de séquençage shotgun. Ils seront capables d’utiliser les outils présentés sur les jeux de données de la formation. L’ensemble des TP se déroulera sur l’infrastructure de Migale et nécessite une pratique courante de la ligne de commande.", "hoursPresentations": 5, "hoursHandsOn": 7, "hoursTotal": 12, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/572/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/694/?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": 287, "name": "Introduction to Oxford Nanopore Technology data analyses", "shortName": "Introduction to ONT data analyses", "description": "This course offers an introduction to ONT data analysis. It includes 5 issues: basecalling, reads quality control, assemblies and polishing/correction, contig quality and structural variants detection.", "homepage": "https://southgreenplatform.github.io/trainings//ont/", "is_draft": false, "costs": [ "Free" ], "topics": [ "http://edamontology.org/topic_3673", "http://edamontology.org/topic_0196", "http://edamontology.org/topic_3168" ], "keywords": [], "prerequisites": [ "Linux and knowledge of NGS formats" ], "openTo": "Everyone", "accessConditions": "", "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": "2023-01-24T10:21:58.467251Z", "audienceTypes": [ "Professional (initial)" ], "audienceRoles": [ "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "trainingMaterials": [ { "id": 1, "name": "SG-ONT-slides", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/SG-ONT-slides/?format=api" } ], "learningOutcomes": "* Understanding limits and advantages of ONT technology\r\n* Manipulating ONT data on a virtual machine on jupyter environment\r\n* Handling mapping, assembly, polishing tools and be able to analyse your own data\r\n* Detecting structural variations using long reads", "hoursPresentations": 6, "hoursHandsOn": 6, "hoursTotal": 12, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/441/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/450/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/562/?format=api" ] }, { "id": 358, "name": "Traitement bioinformatique et analyse différentielle de données d’expression RNA-seq sous Galaxy", "shortName": "Analyse données RNA-seq sous Galaxy", "description": "Objectifs pédagogiques\r\nA l’issue de cette formation, vous serez capable, dans le cadre d’une analyse de données RNA- seq avec génome de référence et plan d’expérience simple :\r\n* de connaître le vocabulaire et les concepts bioinformatiques et biostatistiques ;\r\n* de savoir enchaîner de façon pertinente un ensemble d’outils bioinformatiques et biostatistiques dans l’environnement Galaxy ;\r\n* de comprendre le matériel et méthodes d’un article du domaine ;\r\n* d’évaluer la pertinence d’une analyse RNA-seq en identifiant les éléments clefs et comprendre les particularités liées à la nature des données.\r\n\r\nProgramme\r\nBioinformatique :\r\n* Obtenir des données de qualité : nettoyage, filtrage, qualité\r\n* Aligner les lectures sur un génome de référence\r\n* Détecter de nouveaux transcrits\r\n* Quantifier l’expression des gènes\r\n* Préparer et déployer unensemble d’analyses sur plusieurs échantillons\r\n\r\nBiostatistique :\r\n* Construire un plan d’expérience simple\r\n* Normaliser les données de comptage\r\n* Identifier les gènes différentiellements exprimés\r\n* Se sensibiliser aux tests multiples\r\n\r\nAnalyse de protocoles Bioinformatique et Biostatistiques issus de la littérature", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_3308", "http://edamontology.org/topic_0203", "http://edamontology.org/topic_0102", "http://edamontology.org/topic_3170" ], "keywords": [ "Gene expression differential analysis", "RNA-seq", "Transcriptomics" ], "prerequisites": [ "Galaxy - Basic usage" ], "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": "2025-01-23T15:20:05.977558Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "A l’issue de cette formation, vous serez capable, dans le cadre d’une analyse de données RNA- seq avec génome de référence et plan d’expérience simple :\r\n\r\n* de connaître le vocabulaire et les concepts bioinformatiques et biostatistiques ;\r\n* de savoir enchaîner de façon pertinente un ensemble d’outils bioinformatiques et biostatistiques dans l’environnement Galaxy ;\r\n* de comprendre le matériel et méthodes d’un article du domaine ;\r\n* d’évaluer la pertinence d’une analyse RNA-seq en identifiant les éléments clefs et comprendre les particularités liées à la nature des données.", "hoursPresentations": 6, "hoursHandsOn": 12, "hoursTotal": 18, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/583/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/690/?format=api" ] }, { "id": 374, "name": "Environments and best practices for using the BiRD cluster", "shortName": "Best practices BiRD cluster", "description": "Objectives\r\n- Understand and implement the principles of reproducible science in analysis and development projects\r\n- Acquire basic commands necessary for optimal use of the cluster\r\n\r\nPedagogical Content\r\n- Introduction to reproducibility\r\n- Best practices on code history and sharing: Git\r\n- Conda environment\r\n- Presentation of the computing cluster\r\n- Introduction to workflows using Snakemake", "homepage": "https://pf-bird.univ-nantes.fr/training/cluster/", "is_draft": false, "costs": [ "Free" ], "topics": [], "keywords": [], "prerequisites": [ "Linux - Basic Knowledge" ], "openTo": "Everyone", "accessConditions": "Have an account on the BiRD cluster.", "maxParticipants": 20, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/596/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [ { "id": 16, "name": "BiRD", "url": "https://catalogue.france-bioinformatique.fr/api/team/BiRD/?format=api" } ], "logo_url": null, "updated_at": "2024-02-08T15:56:16.390499Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 7, "hoursHandsOn": null, "hoursTotal": 7, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/602/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/641/?format=api" ] }, { "id": 375, "name": "RNASeq Analysis", "shortName": "RNASeq Analysis", "description": "Objectives\r\n- Understand the key steps in RNASeq data analysis for a differential expression study\r\n- Know how to perform command-line analysis using Snakemake.\r\n\r\nPedagogical Content\r\nDay 1\r\n- Principle of RNASeq technology: objectives and experimental design.\r\n- Data quality assessment (FastQC, MultiQC).\r\n- Sequence alignment to a reference genome (STAR).\r\n\r\nDay 2\r\n- Differential gene expression analysis (HTSeqCount, DESeq2).\r\n- Functional annotation (GO, Kegg).\r\n- Using the Snakemake workflow system.\r\n- Comparison between RNASeq and 3’SRP methods.\r\n\r\nThe theoretical part is followed by a pipeline run step-by-step on a test dataset. \r\nIt will be possible to start an analysis on your own data.", "homepage": "https://pf-bird.univ-nantes.fr/training/rnaseq/", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Everyone", "accessConditions": "Familiarity with basic Linux commands.", "maxParticipants": 12, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [ { "id": 16, "name": "BiRD", "url": "https://catalogue.france-bioinformatique.fr/api/team/BiRD/?format=api" } ], "logo_url": null, "updated_at": "2024-02-08T16:07:26.347245Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 7, "hoursHandsOn": 7, "hoursTotal": 14, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/603/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/640/?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": 291, "name": "Formation au logiciel R", "shortName": "Formation au logiciel R", "description": "Introduction au logiciel R et à son utilisation pour réaliser des graphiques et faire des analyses statistiques basiques en biologie. Introduction aux bibliothèques R utiles en biologie.", "homepage": "http://www.prabi.fr/spip.php?article273", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 14, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [ { "id": 19, "name": "PRABI-AMSB", "url": "https://catalogue.france-bioinformatique.fr/api/team/PRABI-AMSB/?format=api" } ], "logo_url": null, "updated_at": "2022-06-02T11:50:50.812642Z", "audienceTypes": [ "Professional (initial)" ], "audienceRoles": [ "Life scientists" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "- Acquérir les compétences nécessaires à l’utilisation du logiciel R\r\n- Connaître les principales analyses statistiques nécessaires en biologie et les utiliser sous R\r\n- Réaliser des graphiques sous R\r\n- Connaitre les bibliothèques R utiles en Biologie", "hoursPresentations": 9, "hoursHandsOn": 12, "hoursTotal": 21, "personalised": false, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/437/?format=api" ] }, { "id": 312, "name": "Introduction to python", "shortName": "", "description": "This course provides an introduction to programming using python. At the end of the training, participants should be able to write simple python programs to handle biological data and to understand more complex programs written by others.\r\nNote : This course in currently available only in french", "homepage": "https://southgreenplatform.github.io/trainings//python/", "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": "2022-06-02T11:50:50.812642Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 10, "hoursHandsOn": 18, "hoursTotal": null, "personalised": false, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/470/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/556/?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": 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_0091", "http://edamontology.org/topic_0769", "http://edamontology.org/topic_3307", "http://edamontology.org/topic_3068" ], "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": 376, "name": "Train-the-Trainer", "shortName": "TtT", "description": "The programme objective is to give instructors tools and tips for providing an enriching learning experience to trainees, irrespective of topic, and to include best-practice guidance on course and training material development.", "homepage": "https://moodle.france-bioinformatique.fr/course/view.php?id=25", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": null, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/762/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/556/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/639/?format=api" ], "elixirPlatforms": [ { "id": 1, "name": "Training", "url": "https://catalogue.france-bioinformatique.fr/api/elixirplatform/Training/?format=api" } ], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 4, "name": "IFB - ELIXIR-FR", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IFB%20-%20ELIXIR-FR/?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/961/course/section/152/logo_TtT_MRS_def.png", "updated_at": "2024-03-21T15:33:43.289130Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "All" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "By the end of Session 1, participants will be able to:\r\n\r\nList the steps of good instructional design.\r\nDefine cognitive load.\r\nDistinguish between bad and good cognitive load.\r\nClarify why we start with learning outcomes.\r\nGive examples of effective learning strategies.\r\nConnect learning strategies to the cognitive processes they promote.\r\nSelect appropriate learning outcomes within the learning constraints.\r\nAssess your teaching outlook/practices in relation to what you’ve learned.\r\nDesign learning experiences that align with learning outcomes.\r\n\r\n\r\nBy the end of Session 2, participants will be able to:\r\n\r\nDesign a mini-training:\r\nWrite SMART Learning Outcomes \r\nIdentify target audience\r\nDraw a concept map\r\nSelect content\r\nDeliver \r\nProvide and receive targeted feedback\r\nCreate a plan from lesson to session\r\nCreate a plan from session to full course\r\n\r\n\r\nBy the end of Session 3, participants will be able to:\r\n\r\nDescribe what makes training effective.\r\nDescribe what makes a trainer effective.\r\nIdentify strategies that facilitate active, interactive, and collaborative learning.\r\nList factors of motivation and demotivation.\r\nEvaluate what instructors can do to motivate and avoid demotivating learners.\r\n\r\n\r\nBy the end of Session 4, participants will be able to\r\n\r\nDescribe the differences between formative and summative assessment\r\nExplain why frequent feedback is important\r\nList and describe a few techniques for formative feedback", "hoursPresentations": 12, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/607/?format=api" ] }, { "id": 290, "name": "NGS data analysis on the command line", "shortName": "NGS-analysis-cli", "description": "This hands-on course will teach bioinformatic approaches for analyzing Illumina sequencing data. Our goal is to introduce the command line skills you need to make the most of your NGS data. \r\nDuring this 4-day training we will first introduce the Linux environment, shell commands and basic R scripting. And then we will focus on two NGS data analyses -- small RNA-seq and RNA-seq -- based on published datasets from the model organism Arabidopsis thaliana", "homepage": "https://www.ibmp.cnrs.fr/bioinformatics-trainings/", "is_draft": false, "costs": [ "Free to academics" ], "topics": [ "http://edamontology.org/topic_0102", "http://edamontology.org/topic_3170", "http://edamontology.org/topic_2269", "http://edamontology.org/topic_3168" ], "keywords": [], "prerequisites": [ "none" ], "openTo": "Internal personnel", "accessConditions": "This training is dedicated to academics working in a laboratory of Unistra/CNRS.", "maxParticipants": 12, "contacts": [ "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" } ], "organisedByTeams": [ { "id": 14, "name": "BiGEst", "url": "https://catalogue.france-bioinformatique.fr/api/team/BiGEst/?format=api" } ], "logo_url": null, "updated_at": "2024-01-22T14:51:37.215331Z", "audienceTypes": [], "audienceRoles": [ "Biologists", "Bioinformaticians" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "Applied Knowledge (Know-how):\r\n- Basic proficiency at the Linux command line prompt\r\n- Basic proficiency of R (environment, objects, graphs) \r\n- Next generation sequencing (NGS) file formats; reference genomes - Mapping NGS read data to reference genomes (bowtie, samtools)\r\n- Small RNA-seq analysis; epigenomics applications (ShortStack)\r\n- RNA-seq for transcriptomics; differential gene expression analysis (HISAT2, DESeq2) - Data wrangling and visualization in R (Rstudio, ggplot2)", "hoursPresentations": 12, "hoursHandsOn": 16, "hoursTotal": 28, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/503/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/504/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/589/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/454/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/660/?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": 365, "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://bioagro.edu.umontpellier.fr/files/2021/04/HAA906V_Bigomics.pdf", "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": [], "organisedByOrganisations": [ { "id": 50, "name": "CIRAD", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/CIRAD/?format=api" }, { "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" } ], "organisedByTeams": [ { "id": 24, "name": "South Green", "url": "https://catalogue.france-bioinformatique.fr/api/team/South%20Green/?format=api" } ], "logo_url": "https://raw.githubusercontent.com/SouthGreenPlatform/trainings/gh-pages/images/southgreenlong.png", "updated_at": "2024-03-20T11:30:31.480815Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 16, "hoursHandsOn": 34, "hoursTotal": 50, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/605/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/591/?format=api" ] }, { "id": 387, "name": "Interactive Online Companionship - SingleCell RNAseq Analysis with R Seurat", "shortName": "IOC - SingleCell", "description": "InforBio offers online bioinformatics training tailored to the needs of research labs, with small group sessions to ensure personalized learning. Our program is designed to help you acquire key skills for independent data analysis.\r\n\r\nWe offer a comprehensive 3-month program, including a post-training feedback session to support practical application.\r\n\r\nAnalyse de données scRNAseq (avril à juin 2025) – 10 sessions de 2h30 – 2000 € Apprenez à analyser des données de séquençage ARN en cellules uniques grâce à des cas pratiques.Vous travaillerez d’abord sur un jeu de données fourni, puis sur vos propres données, avec un retour personnalisé sur votre projet. Cette formation requiert une bonne maîtrise de R.\r\n\r\nKey Highlights:\r\nSmall group sessions for interactive and personalized learning.\r\nTailored feedback on your own data to reinforce the learning process.\r\nLimited spots available, registration is now open.", "homepage": "https://inforbio.github.io/ioc_r_scrnaseq.html", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [ "Single-Cell Analysis" ], "prerequisites": [ "R programming" ], "openTo": "Everyone", "accessConditions": "Followed R training or equivalent level", "maxParticipants": 6, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/809/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 18, "name": "IBiSA", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/IBiSA/?format=api" }, { "id": 19, "name": "Sorbonne Université", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/Sorbonne%20Universit%C3%A9/?format=api" } ], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "https://github.com/InforBio/InforBio.github.io/blob/main/images/logoInforBio_fond_blanc.png?raw=true", "updated_at": "2025-09-11T14:25:26.499365Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 25, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/665/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/729/?format=api" ] } ] }
