Event List
Handles creating, reading and updating events.
GET /api/event/?format=api&offset=480&ordering=-keywords
{ "count": 628, "next": "https://catalogue.france-bioinformatique.fr/api/event/?format=api&limit=20&offset=500&ordering=-keywords", "previous": "https://catalogue.france-bioinformatique.fr/api/event/?format=api&limit=20&offset=460&ordering=-keywords", "results": [ { "id": 683, "name": "Graphiques sous R avec ggplot2 : 2025", "shortName": "Graphics with R-ggplot2 : 2025", "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": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?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": "2025-01-23T15:17:38.070402Z", "type": "Training course", "start_date": "2025-03-13", "end_date": "2025-03-13", "venue": "", "city": "Jouy-en-Josas", "country": "France", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": "2025-01-22", "registration_closing": "2025-02-26", "registration_status": "closed", "courseMode": "Online" }, { "id": 281, "name": "Cycle « Analyse de données de séquençage à haut-débit » - Module 5/5 : Métagénomique", "shortName": "", "description": "Bilille propose chaque année un cycle de formation d'introduction à l'analyse des données de séquençage à haut débit.\r\nCe cycle est composé de 5 modules, à la carte : \r\n- Module 1: Analyses ADN\r\n- Module 2: Analyses de variants\r\n- Module 3: Analyses RNA-seq, bioinformatique\r\n- Module 4: Analyses RNA-seq, biostatistique\r\n- Module 5: Métagénomique\r\nLes fiches descriptives sont accessibles sur le site de Bilille. Chaque module comprend des présentations générales et des séances pratiques sur ordinateur, avec Galaxy.\r\nLes objectifs du module 5 sont :\r\n- Connaître les différentes méthodes de séquençage à haut débit pour la métagénomique, avec leurs avantages et leurs limites : métagénomique ciblée, métagénomique génomes entiers, métatranscriptomique\r\n- Comprendre les différentes étapes analytiques du traitement bioinformatique des données et savoir les mettre en œuvre\r\n- Savoir conduire une analyse statistique pour l’estimation de la richesse de la biodiversité\r\n- Aller jusqu’aux conclusions biologiques", "homepage": "https://bilille.univ-lille.fr/training/training-offer", "is_draft": false, "costs": [ "Free" ], "topics": [], "keywords": [ "NGS Data Analysis", "Metagenomics", "Assembly of genomes and transcriptomes", "Read alignment on genomes", "metatranscriptomics", "NGS Sequencing Data Analysis" ], "prerequisites": [ "Galaxy - Basic usage" ], "openTo": "Internal personnel", "accessConditions": "- Etre familier avec la plate-forme web Galaxy (idéalement avoir suivi la formation bilille « Initiation à Galaxy »)\r\n- Avoir suivi le module 1/5 « Analyses ADN » de ce cycle ou toute autre formation permettant de justifier de connaissances sur les données de séquençage haut débit et leur alignement. Etre familier avec le vocabulaire et les étapes de base de l’analyse de données de séquençage : nettoyage, assemblage, mapping", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 66, "name": "University of Lille", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/University%20of%20Lille/?format=api" }, { "id": 56, "name": "INSERM", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INSERM/?format=api" }, { "id": 52, "name": "CNRS", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/CNRS/?format=api" } ], "organisedByTeams": [ { "id": 3, "name": "Bilille", "url": "https://catalogue.france-bioinformatique.fr/api/team/Bilille/?format=api" } ], "logo_url": "https://bilille.univ-lille.fr/fileadmin/_processed_/9/2/csm_logo_bilille_complet_65be9bda8b.png", "updated_at": "2024-12-09T17:38:01.340793Z", "type": "Training course", "start_date": "2019-11-19", "end_date": "2019-11-21", "venue": "", "city": "Villeneuve d'Ascq", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": "2019-02-15", "registration_status": "closed", "courseMode": "Onsite" }, { "id": 273, "name": "FROGS formation : tools for bioinformatics and statistics analyses with amplicon metagenomics data", "shortName": "", "description": "This training session, organized by Bioinfo Genotoul, Sigenae, NED (GenPhySE) and TWB, is designed to help you to deal with NGS data of 16S, 18S ... DNA produced with MiSeq from Illumina and Roche 454 technologies in the Galaxy workbench.\nYou will discover how to use our Galaxy instance, clean reads, clusterize them, do the taxonomic affiliation and perform statistics to interpret your results.\nPrerequisites: knowledge of R or in another programming language\n", "homepage": "http://bioinfo.genotoul.fr/index.php/events/metagenomic-amplicons-and-stats-with…", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [ "NGS Data Analysis", "Metagenomics", "metatranscriptomics", "Galaxy" ], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "Subscribe by the web page : http://bioinfo.genotoul.fr/index.php/training-2/galaxy-training/.\nPrices : 165 euros per day for academic people, 550 per day otherwise.\n", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "https://ressources.france-bioinformatique.fr/sites/default/files/FROGS_logo_0.png", "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Training course", "start_date": "2019-06-30", "end_date": "2019-07-03", "venue": "", "city": "Auzeville-Tolosane", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 248, "name": "Modélisation 3D des protéines", "shortName": "", "description": "\nObjectifs\n\nConnaître les bases de la modélisation moléculaire : modélisation par homologie, arrimage (docking) de ligands, mutations in silico. Une demi-journée dédiée à la modélisation de vos protéines d'intérêts.\n\nProgramme\n\n- Visualiser : Connaître les bases de la visualisation des protéines en 3D avec PYmol.\n- Comprendre : Analyse des structures 3D de protéines (RX ou RMN). Recherche d'homologues avec HHpred, I-Tasser, etc... Modélisation par homologie avec Modeller, Phyre2. Principes et applications.\n- Prédire : Docking de ligands avec Autodock. Prédiction des mutations in silico. Principes et applications.\nL'accent sera mis sur les points forts et les limites des différents outils et la pratique avec de nombreux \"hand- on tutorials\"\nPlus une session dédiée : «bring your own protein».\n", "homepage": "http://migale.jouy.inra.fr/", "is_draft": false, "costs": [], "topics": [], "keywords": [ "Autre", "Protein/protein interaction modelisation", "proteins/peptides and proteins/nucleic acids" ], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "Ce cycle est ouvert à l'ensemble des agents de l'INRA et aux extérieurs.\n", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "", "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Training course", "start_date": "2017-03-22", "end_date": null, "venue": "", "city": "Jouy en josas", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 585, "name": "Modélisation in silico de structures 3D de protéines. Prédiction de mutations, de fixation de ligands (session 2024)", "shortName": "Modélisation de structures 3D de protéines (2024)", "description": "Objectifs pédagogiques\r\nA l’issue de la formation, les stagiaires connaîtront les principales fonctionnalités du logiciel PyMOL. Ils seront capables de les appliquer pour visualiser leur système biologique d’intérêt, et d’effectuer des commandes basiques d’identification de poches catalytiques, de profilage de surface électrostatique, et de mutations d’acides aminés.\r\n\r\nAussi, ils connaîtront les bases et les outils de bioinformatique structurale et seront autonomes pour effectuer des modèles de protéines par prédiction (Alphafold2), calculer les meilleures poses de fixation de leur(s) ligand(s) (Autodock4) et reconstruire l’éventuel assemblage biologique.\r\n\r\nBonus : Ils s’approprieront ces outils avec une demi-journée dédiée à la modélisation de leur système d’étude : protéines, interactions protéines/ADN, arrimage de ligand, etc.\r\n\r\nProgramme\r\nVisualiser :\r\n* Maîtriser les bases de la visualisation des protéines en 3D avec PyMOL.\r\nComprendre :\r\n* Analyser des structures 3D de protéines (RX ou RMN).\r\n* Identifier des homologues avec HHpred.\r\n* Modéliser par prédiction sa protéine d’intérêt avec Alphafold2.\r\nPrédire :\r\n* Savoir calculer des meilleures poses de ligands avec Autodock.\r\n* Prédir et modéliser les mutations in silico.\r\n\r\n- Points forts et limites des différents outils\r\n- ️“hand- on tutorials”\r\n- Plus une session dédiée : «bring your own protein»", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_1317" ], "keywords": [ "Protein structures", "2D/3D", "Protein/protein interaction modelisation" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" } ], "organisedByTeams": [], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2024-01-18T14:39:22.713885Z", "type": "Training course", "start_date": "2024-05-27", "end_date": "2024-05-28", "venue": "https://migale.inrae.fr/how-to-come", "city": "Jouy-en-Josas", "country": "France", "geographical_range": "", "trainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/778/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/420/?format=api" ], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": "2024-01-08", "registration_closing": "2024-05-13", "registration_status": "closed", "courseMode": "Onsite" }, { "id": 248, "name": "Modélisation 3D des protéines", "shortName": "", "description": "\nObjectifs\n\nConnaître les bases de la modélisation moléculaire : modélisation par homologie, arrimage (docking) de ligands, mutations in silico. Une demi-journée dédiée à la modélisation de vos protéines d'intérêts.\n\nProgramme\n\n- Visualiser : Connaître les bases de la visualisation des protéines en 3D avec PYmol.\n- Comprendre : Analyse des structures 3D de protéines (RX ou RMN). Recherche d'homologues avec HHpred, I-Tasser, etc... Modélisation par homologie avec Modeller, Phyre2. Principes et applications.\n- Prédire : Docking de ligands avec Autodock. Prédiction des mutations in silico. Principes et applications.\nL'accent sera mis sur les points forts et les limites des différents outils et la pratique avec de nombreux \"hand- on tutorials\"\nPlus une session dédiée : «bring your own protein».\n", "homepage": "http://migale.jouy.inra.fr/", "is_draft": false, "costs": [], "topics": [], "keywords": [ "Autre", "Protein/protein interaction modelisation", "proteins/peptides and proteins/nucleic acids" ], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "Ce cycle est ouvert à l'ensemble des agents de l'INRA et aux extérieurs.\n", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "", "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Training course", "start_date": "2017-03-22", "end_date": null, "venue": "", "city": "Jouy en josas", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 699, "name": "Modélisation in silico de structures 3D de protéines. Prédiction de mutations, de fixation de ligands : 2025", "shortName": "Modélisation de structures 3D de protéines", "description": "Objectifs pédagogiques\r\nA l’issue de la formation, les stagiaires connaîtront les principales fonctionnalités du logiciel PyMOL. Ils seront capables de les appliquer pour visualiser leur système biologique d’intérêt, et d’effectuer des commandes basiques d’identification de poches catalytiques, de profilage de surface électrostatique, et de mutations d’acides aminés.\r\n\r\nAussi, ils connaîtront les bases et les outils de bioinformatique structurale et seront autonomes pour effectuer des modèles de protéines par prédiction (Alphafold2), calculer les meilleures poses de fixation de leur(s) ligand(s) (Autodock4) et reconstruire l’éventuel assemblage biologique.\r\n\r\nBonus : Ils s’approprieront ces outils avec une demi-journée dédiée à la modélisation de leur système d’étude : protéines, interactions protéines/ADN, arrimage de ligand, etc.\r\n\r\nProgramme\r\nVisualiser :\r\n* Maîtriser les bases de la visualisation des protéines en 3D avec PyMOL.\r\nComprendre :\r\n* Analyser des structures 3D de protéines (RX ou RMN).\r\n* Identifier des homologues avec HHpred.\r\n* Modéliser par prédiction sa protéine d’intérêt avec Alphafold2.\r\nPrédire :\r\n* Savoir calculer des meilleures poses de ligands avec Autodock.\r\n* Prédir et modéliser les mutations in silico.\r\n\r\n- Points forts et limites des différents outils\r\n- ️“hand- on tutorials”\r\n- Plus une session dédiée : «bring your own protein»", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_1317" ], "keywords": [ "Protein structures", "2D/3D", "Protein/protein interaction modelisation" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" } ], "organisedByTeams": [], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2025-01-23T15:44:32.386212Z", "type": "Training course", "start_date": "2025-06-04", "end_date": "2025-06-05", "venue": "", "city": "Jouy-en-Josas", "country": "France", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": "2025-01-21", "registration_closing": "2025-05-20", "registration_status": "closed", "courseMode": "Online" }, { "id": 585, "name": "Modélisation in silico de structures 3D de protéines. Prédiction de mutations, de fixation de ligands (session 2024)", "shortName": "Modélisation de structures 3D de protéines (2024)", "description": "Objectifs pédagogiques\r\nA l’issue de la formation, les stagiaires connaîtront les principales fonctionnalités du logiciel PyMOL. Ils seront capables de les appliquer pour visualiser leur système biologique d’intérêt, et d’effectuer des commandes basiques d’identification de poches catalytiques, de profilage de surface électrostatique, et de mutations d’acides aminés.\r\n\r\nAussi, ils connaîtront les bases et les outils de bioinformatique structurale et seront autonomes pour effectuer des modèles de protéines par prédiction (Alphafold2), calculer les meilleures poses de fixation de leur(s) ligand(s) (Autodock4) et reconstruire l’éventuel assemblage biologique.\r\n\r\nBonus : Ils s’approprieront ces outils avec une demi-journée dédiée à la modélisation de leur système d’étude : protéines, interactions protéines/ADN, arrimage de ligand, etc.\r\n\r\nProgramme\r\nVisualiser :\r\n* Maîtriser les bases de la visualisation des protéines en 3D avec PyMOL.\r\nComprendre :\r\n* Analyser des structures 3D de protéines (RX ou RMN).\r\n* Identifier des homologues avec HHpred.\r\n* Modéliser par prédiction sa protéine d’intérêt avec Alphafold2.\r\nPrédire :\r\n* Savoir calculer des meilleures poses de ligands avec Autodock.\r\n* Prédir et modéliser les mutations in silico.\r\n\r\n- Points forts et limites des différents outils\r\n- ️“hand- on tutorials”\r\n- Plus une session dédiée : «bring your own protein»", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_1317" ], "keywords": [ "Protein structures", "2D/3D", "Protein/protein interaction modelisation" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" } ], "organisedByTeams": [], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2024-01-18T14:39:22.713885Z", "type": "Training course", "start_date": "2024-05-27", "end_date": "2024-05-28", "venue": "https://migale.inrae.fr/how-to-come", "city": "Jouy-en-Josas", "country": "France", "geographical_range": "", "trainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/778/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/420/?format=api" ], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": "2024-01-08", "registration_closing": "2024-05-13", "registration_status": "closed", "courseMode": "Onsite" }, { "id": 699, "name": "Modélisation in silico de structures 3D de protéines. Prédiction de mutations, de fixation de ligands : 2025", "shortName": "Modélisation de structures 3D de protéines", "description": "Objectifs pédagogiques\r\nA l’issue de la formation, les stagiaires connaîtront les principales fonctionnalités du logiciel PyMOL. Ils seront capables de les appliquer pour visualiser leur système biologique d’intérêt, et d’effectuer des commandes basiques d’identification de poches catalytiques, de profilage de surface électrostatique, et de mutations d’acides aminés.\r\n\r\nAussi, ils connaîtront les bases et les outils de bioinformatique structurale et seront autonomes pour effectuer des modèles de protéines par prédiction (Alphafold2), calculer les meilleures poses de fixation de leur(s) ligand(s) (Autodock4) et reconstruire l’éventuel assemblage biologique.\r\n\r\nBonus : Ils s’approprieront ces outils avec une demi-journée dédiée à la modélisation de leur système d’étude : protéines, interactions protéines/ADN, arrimage de ligand, etc.\r\n\r\nProgramme\r\nVisualiser :\r\n* Maîtriser les bases de la visualisation des protéines en 3D avec PyMOL.\r\nComprendre :\r\n* Analyser des structures 3D de protéines (RX ou RMN).\r\n* Identifier des homologues avec HHpred.\r\n* Modéliser par prédiction sa protéine d’intérêt avec Alphafold2.\r\nPrédire :\r\n* Savoir calculer des meilleures poses de ligands avec Autodock.\r\n* Prédir et modéliser les mutations in silico.\r\n\r\n- Points forts et limites des différents outils\r\n- ️“hand- on tutorials”\r\n- Plus une session dédiée : «bring your own protein»", "homepage": "https://documents.migale.inrae.fr/trainings.html", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_1317" ], "keywords": [ "Protein structures", "2D/3D", "Protein/protein interaction modelisation" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 10, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/769/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 88, "name": "BioinfOmics", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api" } ], "organisedByTeams": [], "logo_url": "https://migale.inrae.fr/sites/default/files/migale-orange_0.png", "updated_at": "2025-01-23T15:44:32.386212Z", "type": "Training course", "start_date": "2025-06-04", "end_date": "2025-06-05", "venue": "", "city": "Jouy-en-Josas", "country": "France", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": "2025-01-21", "registration_closing": "2025-05-20", "registration_status": "closed", "courseMode": "Online" }, { "id": 643, "name": "Artificial Intelligence and Machine Learning in Life Sciences: from foundations to applications 2025", "shortName": "AI & ML in LS 2025", "description": "Artificial intelligence (AI) has permeated our lives, transforming how we live and work. Over the past few years, a rapid and disruptive acceleration of progress in AI has occurred, driven by significant advances in widespread data availability, computing power and machine learning. Remarkable strides were made in particular in the development of foundation models - AI models trained on extensive volumes of unlabelled data. Moreover, given the large amounts of omics data that are being generated and made accessible to researchers due to the drop in the cost of high-throughput technologies, analysing these complex high-volume data is not trivial, and the use of classical statistics can not explore their full potential. As such, Machine Learning (ML) and Artificial Intelligence (AI) have been recognized as key opportunity areas, as evidenced by a number of ongoing activities and efforts throughout the community.\r\n\r\nHowever, beyond the technological advances, it is equally important that the individual researchers acquire the necessary knowledge and skills to fully take advantage of Machine Learning. Being aware of the challenges, opportunities and constraints that ML applications entail, is a critical aspect in ensuring high quality research in life sciences.\r\n\r\nRecognizing this need, this week-long training will bring together experts from four ELIXIR Nodes and deliver a hands-on, high-intensity course available for members from all ELIXIR Nodes.\r\n\r\nLearners will be guided across the various steps in Machine Learning, from the foundational concepts, through the deep learning and generative AI techniques, closely complemented by insights into the existing reporting (DOME Recommendations) and regulatory frameworks (EU AI Act).\r\n\r\nThis 4-day school will involve around 10 trainers/helpers from across 4 different ELIXIR nodes and 30 participants from across all ELIXIR nodes. 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No specific bioinformatics skill is required: detailed instruction on the algorithm developed in each annotation methods can be found in specific training courses on «Genomic sequences analysis». Here we focus on the general idea behind each method and, above all, the way you can interpret the corresponding results and combine them with other evidences in order to change or correct the current automatic functional annotation of a given gene, if necessary.\r\n\r\nThis course will also describe how to perform effective searches and analysis of procaryotic data using the graphical functionalities of the MaGe’s interfaces. Because of the numerous pre-computation available in our system (results of “common” annotation tools, synteny with all complete bacterial genomes, metabolic pathway reconstruction, fusion/fission events, genomic islands, …), many practical exercises allow attendees to get familiar with the use the MaGe graphical interfaces in order to efficiently explore these sets of results.", "homepage": "https://labgem.genoscope.cns.fr/professional-trainings/microscope-professional-trainings/training-annotation-analysis-of-prokaryotic-genomes-using-the-microscope-platform/", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_0797", "http://edamontology.org/topic_0085", "http://edamontology.org/topic_3301" ], "keywords": [ "Sequence analysis", "Microbial evolution", "Structural and functional annotation of genomes", "Sequence annotation" ], "prerequisites": [ "Licence" ], "openTo": "Everyone", "accessConditions": "External training sessions can also be scheduled on demand, in France or abroad. 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No specific bioinformatics skill is required: detailed instruction on the algorithm developed in each annotation methods can be found in specific training courses on «Genomic sequences analysis». Here we focus on the general idea behind each method and, above all, the way you can interpret the corresponding results and combine them with other evidences in order to change or correct the current automatic functional annotation of a given gene, if necessary.\r\n\r\nThis course will also describe how to perform effective searches and analysis of procaryotic data using the graphical functionalities of the MaGe’s interfaces. Because of the numerous pre-computation available in our system (results of “common” annotation tools, synteny with all complete bacterial genomes, metabolic pathway reconstruction, fusion/fission events, genomic islands, …), many practical exercises allow attendees to get familiar with the use the MaGe graphical interfaces in order to efficiently explore these sets of results.", "homepage": "https://labgem.genoscope.cns.fr/professional-trainings/microscope-professional-trainings/training-annotation-analysis-of-prokaryotic-genomes-using-the-microscope-platform/", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_0797", "http://edamontology.org/topic_0085", "http://edamontology.org/topic_3301" ], "keywords": [ "genomics", "Sequence analysis", "Microbial evolution", "Genome analysis", "Structural and functional annotation of genomes" ], "prerequisites": [ "Licence" ], "openTo": "Everyone", "accessConditions": "External training sessions can also be scheduled on demand, in France or abroad. 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No specific bioinformatics skill is required: detailed instruction on the algorithm developed in each annotation methods can be found in specific training courses on «Genomic sequences analysis». Here we focus on the general idea behind each method and, above all, the way you can interpret the corresponding results and combine them with other evidences in order to change or correct the current automatic functional annotation of a given gene, if necessary.\r\n\r\nThis course will also describe how to perform effective searches and analysis of procaryotic data using the graphical functionalities of the MaGe’s interfaces. Because of the numerous pre-computation available in our system (results of “common” annotation tools, synteny with all complete bacterial genomes, metabolic pathway reconstruction, fusion/fission events, genomic islands, …), many practical exercises allow attendees to get familiar with the use the MaGe graphical interfaces in order to efficiently explore these sets of results.", "homepage": "https://labgem.genoscope.cns.fr/professional-trainings/microscope-professional-trainings/training-annotation-analysis-of-prokaryotic-genomes-using-the-microscope-platform/", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_0797", "http://edamontology.org/topic_0085", "http://edamontology.org/topic_3301" ], "keywords": [ "Sequence analysis", "Microbial evolution", "Structural and functional annotation of genomes", "Sequence annotation" ], "prerequisites": [ "Licence" ], "openTo": "Everyone", "accessConditions": "External training sessions can also be scheduled on demand, in France or abroad. 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No specific bioinformatics skill is required: detailed instruction on the algorithm developed in each annotation methods can be found in specific training courses on «Genomic sequences analysis». Here we focus on the general idea behind each method and, above all, the way you can interpret the corresponding results and combine them with other evidences in order to change or correct the current automatic functional annotation of a given gene, if necessary.\r\n\r\nThis course will also describe how to perform effective searches and analysis of procaryotic data using the graphical functionalities of the MaGe’s interfaces. Because of the numerous pre-computation available in our system (results of “common” annotation tools, synteny with all complete bacterial genomes, metabolic pathway reconstruction, fusion/fission events, genomic islands, …), many practical exercises allow attendees to get familiar with the use the MaGe graphical interfaces in order to efficiently explore these sets of results.", "homepage": "https://labgem.genoscope.cns.fr/professional-trainings/microscope-professional-trainings/training-annotation-analysis-of-prokaryotic-genomes-using-the-microscope-platform/", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_0797", "http://edamontology.org/topic_0085", "http://edamontology.org/topic_3301" ], "keywords": [ "Sequence analysis", "Microbial evolution", "Structural and functional annotation of genomes", "Sequence annotation" ], "prerequisites": [ "Licence" ], "openTo": "Everyone", "accessConditions": "External training sessions can also be scheduled on demand, in France or abroad. 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Cette édition de l’école aborde les nouveaux enjeux technologiques: elle s’articulera autour de trois ateliers en session parallèle (RNA-seq, ChIP-seq, variants DNA-seq), et inclura une introduction à l’intégration des données, ouverture aux approches “single-cell” ainsi qu’aux technologies lectures longues (Nanopore, PacBio).\r\nL’école vise à introduire les concepts et à manipuler les outils informatiques et à en interpréter les résultats. Elle est basée sur une alternance de courtes sessions théoriques et d’ateliers pratiques. Les participants bénéficieront d’un tutorat personnalisé pour élaborer leur plan d’analyse, et effectuer les premières étapes de traitement de leurs propres données ou de celles de leur plateforme.", "homepage": "https://ressources.france-bioinformatique.fr/fr/formations/8%C3%A8me-%C3%A9cole-bioinformatique-aviesan-ifb", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [ "Biostatistics", "Sequence analysis", "NGS Sequencing Data Analysis" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "La formation s’adresse à des biologistes directement impliqués dans des projets “Next Generation Sequencing” (NGS). \r\nAucune connaissance préalable des environnements Linux ou R n’est requise, mais il sera demandé aux participants de suivre une autoformation en ligne en amont, pour faciliter la prise en main de ces langages. 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Les participants bénéficieront d’un tutorat personnalisé pour élaborer leur plan d’analyse, et effectuer les premières étapes de traitement de leurs propres données.\r\nAttention : le tutorat n'a pas pour vocation de réaliser l’analyse complète des données des participants.", "homepage": "https://moodle.france-bioinformatique.fr/course/view.php?id=35", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_3391", "http://edamontology.org/topic_3366", "http://edamontology.org/topic_0092", "http://edamontology.org/topic_3168", "http://edamontology.org/topic_0091" ], "keywords": [ "Biostatistics", "Sequence analysis", "NGS Sequencing Data Analysis" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "La formation s’adresse à des biologistes directement impliqués dans des projets “Next Generation Sequencing” (NGS) avec un niveau de base en ligne de commande, R, et (au choix) RNA-seq, ChIP-seq ou variants DNA-seq.", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "https://www.sb-roscoff.fr/sites/www.sb-roscoff.fr/files/styles/large/public/images/station-biologique-roscoff-roscoff-4404.jpg", "updated_at": "2025-01-09T13:06:41.575826Z", "type": "Training course", "start_date": "2025-06-01", "end_date": "2025-06-06", "venue": "", "city": "Roscoff", "country": "France", "geographical_range": "National", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": "2025-01-08", "registration_closing": "2025-03-01", "registration_status": "closed", "courseMode": "Onsite" }, { "id": 525, "name": "12ème Ecole de Bioinformatique AVIESAN-IFB-Inserm", "shortName": "EBAII 2023 niv1", "description": "La formation s’adresse à des biologistes directement impliqués dans des projets “Next Generation Sequencing” (NGS). 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Les participants bénéficieront d’un tutorat personnalisé pour élaborer leur plan d’analyse, et effectuer les premières étapes de traitement de leurs propres données ou de celles de leur plateforme.", "homepage": "https://ifb-elixirfr.github.io/EBAII/", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [ "Biostatistics", "Sequence analysis", "NGS Sequencing Data Analysis" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "La formation s’adresse à des biologistes directement impliqués dans des projets “Next Generation Sequencing” (NGS). \r\nAucune connaissance préalable des environnements Linux ou R n’est requise, mais il sera demandé aux participants de suivre une autoformation en ligne en amont, pour faciliter la prise en main de ces langages. 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