Training List
Handles creating, reading and updating training events.
GET /api/training/?format=api&offset=20&ordering=-logo_url
{ "count": 378, "next": "https://catalogue.france-bioinformatique.fr/api/training/?format=api&limit=20&offset=40&ordering=-logo_url", "previous": "https://catalogue.france-bioinformatique.fr/api/training/?format=api&limit=20&ordering=-logo_url", "results": [ { "id": 269, "name": "Diplôme Universitaire en Bioinformatique Intégrative", "shortName": "DU-Bii", "description": "La bioinformatique est devenue une compétence incontournable pour l'analyse de données de nature diverse : génomes, transcriptomes, protéomes, métabolomes, structures macromoléculaires, réseaux d'interactions. L'appropriation par les biologistes des méthodes et outils de biostatistique et bioinformatique intégrative est un enjeu majeur pour la montée en compétence des équipes de recherche et des plateformes de service.\r\n\r\nL'université Paris Diderot propose en partenariat avec l'Institut Français de Bioinformatique (IFB) la deuxième édition du Diplôme Universitaire en Bioinformatique intégrative (DU-Bii). Cette formation s’adresse en priorité à des biologistes en demande d'évolution ou de reconversion professionnelle ayant déjà acquis des compétences (formation courte, autoapprentissage, expérience de terrain) en informatique ou bioinformatique/biostatistique (environnement Unix, Python ou R ou autre langage de programmation). Les prérequis sont décrits sur le portail “DU” de l’université Paris Diderot, qui présente le DU-Bii et le DU complémentaire \"Création, Analyse et Valorisation de données omiques\" (DUO).\r\n\r\nLe DU-Bii fournira une formation théorique et pratique, complétée par une période d'immersion sur l'une des plateformes régionales de l'IFB, qui mobilisera, dans le cadre d'un projet tutoré, l'ensemble des méthodes et outils appris durant les cours pour réaliser un projet personnel de bioinformatique intégrative. Ce projet combinera des données propres à chaque participant produites dans son laboratoire (principe BYOD : “Bring Your Own Data”) ou collectées à partir de bases de données publiques.\r\n\r\nRenseignements et candidatures : fcsdv@univ-paris-diderot.fr\r\nInscriptions : voir la page page du DU-Bii de l'Université Paris Diderot\r\nContacts Paris-Diderot : Bertrand.Cosson@univ-paris-diderot.fr \r\nContacts IFB : Helene.Chiapello@inra.fr, Jacques.van-Helden@univ-amu.fr", "homepage": "https://www.france-bioinformatique.fr/dubii/", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 28, "name": "University Paris-Cité", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/University%20Paris-Cit%C3%A9/?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": "https://www.france-bioinformatique.fr/wp-content/uploads/logo-ifb-couleur.svg", "updated_at": "2022-06-02T11:50:50.812642Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/197/?format=api" ] }, { "id": 277, "name": "Principes FAIR dans un projet de bioinformatique", "shortName": "FAIR bioinfo", "description": "L’Institut Français de Bioinformatique (IFB) organise en partenariat avec l’Institut de Biologie Intégrative de la Cellule (I2BC) une formation à destination des bioinformaticiens et biostatisticiens souhaitant mettre en oeuvre les principes “FAIR” (Facile à trouver, Accessible, Interopérable, Réutilisable) dans leurs projets d’analyse et de développement. Les concepts FAIR, initialement définis dans le contexte d’ouverture des données de la recherche, seront ici adaptés pour cadrer avec un projet type de développement et/ou analyse bioinformatique/biostatistique. Ainsi, la formation n’abordera pas les aspects “FAIR” spécifiques aux données mais introduira plusieurs outils permettant d’améliorer la reproductibilité des analyses.", "homepage": "https://ifb-elixirfr.github.io/IFB-FAIR-bioinfo-training/", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_0769" ], "keywords": [ "Computing Environments", "NGS Sequencing Data Analysis", "Workflow development" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": null, "contacts": [], "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": [], "logo_url": "https://www.france-bioinformatique.fr/wp-content/uploads/logo-ifb-couleur.svg", "updated_at": "2022-06-02T11:50:50.812642Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "A la fin de cette formation, les participants pourront mettre en oeuvre les principes de la science reproductible : encapsuler un environnement de travail, concevoir et exécuter des workflows, gérer des versions de code, passer à l’échelle sur un cluster de calcul, gérer des environnements logiciels et assurer la traçabilité de leur analyse à l’aide de Notebooks.", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/462/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/502/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/421/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/416/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/508/?format=api" ] }, { "id": 274, "name": "Principes FAIR pour la gestion des données de recherche en sciences de la vie", "shortName": "FAIR data", "description": "Présentation et application des principes FAIR de gestion des données dans un projet bioinformatique.\r\nL’Institut Français de Bioinformatique (IFB) organise une formation à destination de bioinformaticiens, biologistes et médecins impliqués dans des projets d’analyse bioinformatique de jeux de données omiques et souhaitant mettre en œuvre les principes “FAIR” (Facile à trouver, Accessible, Interopérable, Réutilisable) tout au long du déroulement du projet. La formation abordera les différents points fondamentaux (théoriques, pratiques, juridiques) en lien avec la politique nationale d’ouverture des données de la recherche et présentera sous forme de séances pratiques les ressources nationales accessibles à la communauté scientifique ainsi que les solutions proposées par l’IFB pour gérer les données d’un projet de recherche.", "homepage": "https://ifb-elixirfr.github.io/IFB-FAIR-data-training/", "is_draft": false, "costs": [ "Free" ], "topics": [ "http://edamontology.org/topic_3420", "http://edamontology.org/topic_3571", "http://edamontology.org/topic_0219" ], "keywords": [ "Données" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "public", "maxParticipants": null, "contacts": [], "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://www.france-bioinformatique.fr/wp-content/uploads/logo-ifb-couleur.svg", "updated_at": "2022-06-02T11:50:50.812642Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Novice", "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/418/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/404/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/465/?format=api" ] }, { "id": 324, "name": "Python scripts for bioinformatics and Linux", "shortName": "Scripts en Python pour la bioinformatique et environnement Linux", "description": "OBJECTIFS\r\n- Connaître les principes et les avantages du système Linux\r\n- Connaître et savoir utiliser les commandes de base permettant de lancer des programmes sous Linux\r\n- Comprendre et savoir lancer des scripts\r\n- Être capable d'écrire des scripts en Python\r\n- Acquérir de l'autonomie pour effectuer des analyses bioinformatiques qui combinent plusieurs outils \r\n\r\nPRÉREQUIS\r\n- Notions de base en informatique : fichiers, répertoires, etc. \r\n\r\nPROGRAMME\r\n- Linux : lignes de commandes, principales commandes, redirection\r\n- Lancer, créer et modifier des scripts\r\n- Notions de variables, de boucles, de choix\r\n- Programmation de scripts : utilisation de paramètres et de variables, combinaison d'outils et de logiciels, écriture des résultats dans un ou plusieurs fichiers\r\n- Création d'un pipeline d'outils", "homepage": "", "is_draft": false, "costs": [ "1200 €" ], "topics": [], "keywords": [ "Linux", "Python Language" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "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://www.france-bioinformatique.fr/sites/default/files/ATGClogox120_0.png", "updated_at": "2025-01-23T13:50:29.570608Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/512/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/703/?format=api" ] }, { "id": 276, "name": "Introduction to Machine Learning Using R", "shortName": "", "description": "With the rise in high-throughput sequencing technologies, the volume of omics data has grown exponentially in recent times and a major issue is to mine useful knowledge from these data which are also heterogeneous in nature. Machine learning (ML) is a discipline in which computers perform automated learning without being programmed explicitly and assist humans to make sense of large and complex data sets. The analysis of complex high-volume data is not trivial and classical tools cannot be used to explore their full potential. Machine learning can thus be very useful in mining large omics datasets to uncover new insights that can advance the field of bioinformatics.\r\n\r\nThis 2-day course will introduce participants to the machine learning taxonomy and the applications of common machine learning algorithms to omics data. The course will cover the common methods being used to analyse different omics data sets by providing a practical context through the use of basic but widely used R libraries. The course will comprise a number of hands-on exercises and challenges where the participants will acquire a first understanding of the standard ML processes, as well as the practical skills in applying them on familiar problems and publicly available real-world data sets.", "homepage": "", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 30, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 8, "name": "Elixir", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/Elixir/?format=api" }, { "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://www.dissco.eu/wp-content/uploads/Elixir-Europe-logo-1.png", "updated_at": "2022-06-02T11:50:50.812642Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/415/?format=api" ] }, { "id": 383, "name": "Artificial Intelligence and Machine Learning in Life Sciences: from foundations to applications", "shortName": "AI & ML in LS", "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).", "homepage": "", "is_draft": false, "costs": [], "topics": [ "http://edamontology.org/topic_3474" ], "keywords": [], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 30, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "https://www.dissco.eu/wp-content/uploads/Elixir-Europe-logo-1-300x226.png", "updated_at": "2025-01-23T14:14:17.330709Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/643/?format=api" ] }, { "id": 301, "name": "MIAPPE, Minimum Information About Plant Phenotyping Experiments", "shortName": "MIAPPE", "description": "The Minimal Information About Plant Phenotyping Experiments (MIAPPE, www.miappe.org) standard has been designed by ELIXIR, EMPHASIS and Bioversity international to guide plant scientist in the management of experimental data. Furthermore, since genetic studies relies on the integration and the linking between phenotype and genotype datasets, relevant section of MIAPPE are beginning to be used for genotyping standards.\r\nThis formation will cover a general introduction of the MIAPPE principles and some examples to illustrate different use cases on the usage of MIAPPE for plant phenotyping data standardization.", "homepage": "", "is_draft": false, "costs": [ "Free" ], "topics": [ "http://edamontology.org/topic_3572", "http://edamontology.org/topic_0219", "http://edamontology.org/topic_3298", "http://edamontology.org/topic_0780", "http://edamontology.org/topic_0625" ], "keywords": [ "Données" ], "prerequisites": [ "none" ], "openTo": "Everyone", "accessConditions": "Public", "maxParticipants": null, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/504/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/441/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 39, "name": "URGI - US1164", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/URGI%20-%20US1164/?format=api" }, { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" } ], "organisedByTeams": [ { "id": 26, "name": "URGI", "url": "https://catalogue.france-bioinformatique.fr/api/team/URGI/?format=api" } ], "logo_url": "https://urgi.versailles.inra.fr/extension/inra/design/urgi/images/logoURGI_res72_2-82X1-98.png", "updated_at": "2025-11-28T13:19:07.566534Z", "audienceTypes": [ "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "All" ], "difficultyLevel": "Novice", "trainingMaterials": [ { "id": 150, "name": "Plant Data Managment for Phenotyping Experiments - MIAPPE", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/Plant%20Data%20Managment%20for%20Phenotyping%20Experiments%20-%20MIAPPE/?format=api" } ], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": false, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/732/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/733/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/734/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/736/?format=api" ] }, { "id": 398, "name": "Practical session REPET", "shortName": "REPET", "description": "How to use REPET for de novo TE annotation", "homepage": "", "is_draft": false, "costs": [ "Priced" ], "topics": [ "http://edamontology.org/topic_0780", "http://edamontology.org/topic_0091", "http://edamontology.org/topic_0798" ], "keywords": [], "prerequisites": [ "none" ], "openTo": "Everyone", "accessConditions": "Public", "maxParticipants": null, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/131/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 39, "name": "URGI - US1164", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/URGI%20-%20US1164/?format=api" } ], "organisedByTeams": [ { "id": 26, "name": "URGI", "url": "https://catalogue.france-bioinformatique.fr/api/team/URGI/?format=api" } ], "logo_url": "https://urgi.versailles.inra.fr/extension/inra/design/urgi/images/logoURGI_res72_2-82X1-98.png", "updated_at": "2025-09-12T12:48:41.366810Z", "audienceTypes": [ "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "All" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": false, "event_set": [] }, { "id": 397, "name": "WheatIS data discovery", "shortName": "WheatIS Search", "description": "The WheatIS project aims at building an International Wheat Information System to support the wheat research community. The main objective is to provide a single-access web base system to access to the available data resources and bioinformatics tools. The project is endorsed by the Wheat Initiative.\r\nThe WheatIS data discovery tool allows to search data in all the wheat resources around the world.\r\nThis training will describe how to use the tool, what data are available, how to join, etc.", "homepage": "", "is_draft": false, "costs": [ "Free" ], "topics": [ "http://edamontology.org/topic_3489", "http://edamontology.org/topic_3366", "http://edamontology.org/topic_0780", "http://edamontology.org/topic_0091", "http://edamontology.org/topic_0625" ], "keywords": [ "Données" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "Public", "maxParticipants": null, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/8/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/224/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 20, "name": "Wheat Initiative", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/Wheat%20Initiative/?format=api" } ], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 39, "name": "URGI - US1164", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/URGI%20-%20US1164/?format=api" } ], "organisedByTeams": [ { "id": 26, "name": "URGI", "url": "https://catalogue.france-bioinformatique.fr/api/team/URGI/?format=api" } ], "logo_url": "https://urgi.versailles.inra.fr/extension/inra/design/urgi/images/logoURGI_res72_2-82X1-98.png", "updated_at": "2025-09-12T12:46:23.549824Z", "audienceTypes": [ "Undergraduate", "Graduate", "Professional (initial)", "Professional (continued)" ], "audienceRoles": [ "All" ], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": false, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/727/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/728/?format=api" ] }, { "id": 317, "name": "Datathon AGENT - FAIRDOM", "shortName": "FAIRDOM", "description": "Datathon on experimental phenotypic data management using the FAIRDOM platform, and submission workflow using curation & validation tools.", "homepage": "", "is_draft": false, "costs": [ "Free" ], "topics": [ "http://edamontology.org/topic_3572", "http://edamontology.org/topic_3365", "http://edamontology.org/topic_0780", "http://edamontology.org/topic_0091", "http://edamontology.org/topic_3571", "http://edamontology.org/topic_0625", "http://edamontology.org/topic_3366" ], "keywords": [ "Données" ], "prerequisites": [ "Attendees will bring their own data" ], "openTo": "Internal personnel", "accessConditions": "For H2020-AGENT project members only", "maxParticipants": null, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/504/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/8/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 21, "name": "H2020-AGENT", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/H2020-AGENT/?format=api" } ], "organisedByOrganisations": [ { "id": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 39, "name": "URGI - 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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": 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": 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" ] }, { "id": 294, "name": "Linux for Dummies", "shortName": "", "description": "This course offers an introduction to work with Linux. 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