Training List
Handles creating, reading and updating training events.
GET /api/training/?format=api&offset=280&ordering=-maxParticipants
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"learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/303/?format=api" ] }, { "id": 179, "name": "Galaxy - Initiation", "shortName": "", "description": "", "homepage": "", "is_draft": false, "costs": [ "Free" ], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "", "updated_at": "2022-06-02T11:50:50.812642Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/304/?format=api" ] }, { "id": 180, "name": "RNASeq with Galaxy", "shortName": "", "description": "", "homepage": "", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "", "updated_at": "2022-06-02T11:50:50.812642Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/305/?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": 82, "name": "INRAE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/INRAE/?format=api" }, { "id": 85, "name": "IRD", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IRD/?format=api" } ], "organisedByTeams": [ { "id": 24, "name": "South Green", "url": "https://catalogue.france-bioinformatique.fr/api/team/South%20Green/?format=api" } ], "logo_url": "https://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": 309, "name": "EBAII A&A - Ecole EBAII Assemblage & Annotation / Assembly & Annotation EBAII school", "shortName": "EBAII Assemblage & Annotation / Assembly & Annotation EBAii school", "description": "Objectifs\r\nLa formation s’adresse à des biologistes directement impliqués dans des projets “Next Generation Sequencing” (NGS), pour l'assemblage et l'annotation de novo de génomes. Cette édition de l’école aborde les nouveaux enjeux technologiques: elle s’articulera autour des différentes étapes qui mèneront à l’obtention d’un génome annoté à partir de données “long reads” et “hybride” : contrôle qualité des données, assemblage, scaffolding, polishing, annotation structurale et fonctionnelle (en session parallèle pour les procaryotes et les eucaryotes). \r\nL’école vise à introduire les concepts, 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 équipe.\r\nAttention : le tutorat n'a pas pour vocation de réaliser l’analyse complète des données des participants.\r\nPublic visé\r\nCette formation est destinée aux biologistes (ingénieurs, doctorants, chercheurs, enseignants-chercheurs, praticiens…) confrontés à l’analyse de données NGS, et qui ne disposent pas des compétences bioinformatiques suffisantes.", "homepage": "https://www.france-bioinformatique.fr/formation/ebaii2022_genomique/", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 40, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "https://cvt.aviesan.fr/wp-content/themes/cvtaviesan/images/logo_cvt.png", "updated_at": "2024-12-05T09:11:55.721141Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "Initiation au traitement des données de génomique obtenues par séquençage à haut débit\r\nAssemblage et annotation de novo de génomes\r\nL’école vise à introduire les concepts, 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 équipe.", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": true, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/463/?format=api" ] }, { "id": 320, "name": "Ecole Thématique de Bioinformatique Intégrative / Integrative Bioinformatics Training School", "shortName": "ETBII", "description": "Dans l’objectif de développer et fédérer des compétences en bioinformatique intégrative au sein de la communauté, l’IFB propose une nouvelle école thématique ayant un double objectif :\r\n- une montée en compétences théoriques et pratiques des bioinformaticiens,\r\n- la constitution de matériel pédagogique partagé sur ce sujet.\r\n\r\nCette école rassemble une équipe pédagogique de 10 personnes et pourra accueillir 30 participants pour sa première édition.\r\nL’ensemble de la formation reposera sur l’utilisation des ressources de calcul et de la plateforme pédagogique de l’Institut Français de Bioinformatique.\r\n\r\nObjectifs pédagogiques \r\n\r\nLa formation a pour but :\r\n- d’introduire les concepts de bases et les différents types d’approches utilisées en bioinformatique intégrative,\r\n- de proposer un approfondissement et une mise en pratique d’une de ces approches sur un/des jeux de données intégrant différents types de données omiques. Cette mise en oeuvre permettra de balayer l’ensemble des points d’attention d’une analyse intégrative, de la préparation des données jusqu’à l’interprétation des résultats,\r\n- de créer, améliorer et partager les ressources pédagogiques (supports de formation, jeux de données, tutoriels) sur le thème de la bioinformatique intégrative.\r\n\r\nA la fin de cette formation les participants :\r\n- auront acquis un socle de connaissances générales en bioinformatique intégrative, \r\n- auront mis en oeuvre une analyse intégrative depuis la préparation des données jusqu’à l’analyse critique de résultats sur un/des jeux de données proposés lors de la formation,\r\n- auront contribué à constituer du matériel pédagogique partagé sur le sujet.\r\n\r\nPré-requis\r\n- Connaissances de base en Unix/shell, R et/ou Python \r\n- Autonomie dans la gestion de son poste de travail (installation de librairies et maîtrise des environnements de packaging type conda)", "homepage": "https://www.france-bioinformatique.fr/formation/etbii/", "is_draft": false, "costs": [ "770 TTC pour les académiques et 1540 TTC pour les privés" ], "topics": [ "http://edamontology.org/topic_0091", "http://edamontology.org/topic_3391", "http://edamontology.org/topic_3366" ], "keywords": [ "Methodology", "Biostatistics", "Biological network inference and analysis", "Dimension reduction", "Semantic web", "Integration of heterogeneous data", "Data Integration", "Tool integration" ], "prerequisites": [ "Linux and knowledge of NGS formats", "Basic knowledge of R" ], "openTo": "Everyone", "accessConditions": "Cette formation est ouverte à toute la communauté mais cette première édition s’adresse en priorité à des bioinformaticien·ne·s des plateformes membres et équipes associées IFB souhaitant contribuer à la constitution de matériel pédagogique pour se préparer au montage de futures formations sur ce thème.", "maxParticipants": 30, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/762/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 1, "name": "CNRS - IFB", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/CNRS%20-%20IFB/?format=api" } ], "organisedByOrganisations": [ { "id": 4, "name": "IFB", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IFB/?format=api" } ], "organisedByTeams": [ { "id": 29, "name": "IFB Core", "url": "https://catalogue.france-bioinformatique.fr/api/team/IFB%20Core/?format=api" } ], "logo_url": "https://drive.google.com/file/d/1a_fuOgqOU812GRJLApGMofJ87WTlxDI0/view?usp=sharing", "updated_at": "2024-12-03T15:46:48.157120Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Life scientists", "Computer scientists", "Bioinformaticians" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "A la fin de cette formation les participants :\r\n- auront acquis un socle de connaissances générales en bioinformatique intégrative, \r\n- auront mis en oeuvre une analyse intégrative depuis la préparation des données jusqu’à l’analyse critique de résultats sur un/des jeux de données proposés lors de la formation,\r\n- auront contribué à constituer du matériel pédagogique partagé sur le sujet.", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": false, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/489/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/505/?format=api" ] }, { "id": 326, "name": "Principes FAIR pour la gestion des données d'une plateforme IBISA", "shortName": "FAIR data IBISA", "description": "Cette session de formation a pour but de former des responsables et membres de plateformes IBISA aux principes FAIR de gestion des données .\r\nLa formation se déroule sur 2 jours avec une alternance de présentation générales, et techniques, témoignages et ateliers pratiques pour travailler sur différents sujets : PGD de structure, métadonnées, sécurité des données,...etc.\r\nA la fin de cette formation auront \r\n- acquis des connaissances théoriques et pratiques sur la gestion selon les principes FAIR de leurs données dans le contexte de la Science Ouverte\r\n- identifié des pistes d'amélioration pour la gestion des données de leur plateforme.", "homepage": "https://moodle.france-bioinformatique.fr/course/view.php?id=16", "is_draft": false, "costs": [ "Free" ], "topics": [ "http://edamontology.org/topic_3420", "http://edamontology.org/topic_0219", "http://edamontology.org/topic_3571" ], "keywords": [ "Données" ], "prerequisites": [ "Biologists" ], "openTo": "Internal personnel", "accessConditions": "private for IBISA platform staff", "maxParticipants": 30, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/162/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/116/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 3, "name": "IFB", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/IFB/?format=api" } ], "organisedByOrganisations": [ { "id": 43, "name": "IFB-core", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IFB-core/?format=api" } ], "organisedByTeams": [ { "id": 29, "name": "IFB Core", "url": "https://catalogue.france-bioinformatique.fr/api/team/IFB%20Core/?format=api" } ], "logo_url": "https://moodle.france-bioinformatique.fr/pluginfile.php/1/core_admin/logocompact/300x300/1654772049/IFB-HAUT-COULEUR-PETIT.png", "updated_at": "2023-08-22T14:25:08.237204Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "A la fin de cette formation, les participants connaîtront et pourront mettre en œuvre les principes de la science ouverte pour gérer leurs jeux de données dans un projet :\r\n- Les principes fondamentaux de l’Open Data en biologie et santé, y compris dans ses aspects juridiques ;\r\n- Les bonnes pratiques et outils de gestion des données d’un projet en bioinformatique, en lien avec les ressources de l’infrastructure IFB ;\r\n- Le PGD : séances théoriques et pratiques de construction d’un PGD sur des exemples de jeux de données omiques ;\r\n- Le choix des métadonnées : panorama des ressources existantes pour choisir des métadonnées et mise en pratique pour annoter des jeux de données omiques en vue de la publication des données dans une banque internationale ou un dataverse institutionnel.", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": false, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/627/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/513/?format=api" ] }, { "id": 275, "name": "Single-Cell : Transcriptomics, Spatial and Long reads", "shortName": "SincellTE", "description": "This workshop focuses on the large-scale study of heterogeneity across individual cells from a genomic, transcriptomic and epigenomic point of view. New technological developments enable the characterization of molecular information at a single cell resolution for large numbers of cells. The high dimensional omics data that these technologies produce raise novel methodological challenges for the analysis. In this regard, dedicated bioinformatics and statistical methods have been developed in order to extract robust information.\r\n\r\nThe workshop aims to provide such methods for engineers and researchers directly involved in functional genomics projects making use of single-cell technologies. A wide range of single cell topics will be covered in lectures, demonstrations and practical classes. Among others, the areas and issues to be addressed will include the choice of the most appropriate single-cell sequencing technology, the experimental design and the bioinformatics and statistical methods and pipelines. For this edition, new courses/practicals will focus on spatial transcriptomics, cell phenotyping and additional multi-omics.\r\n\r\nA wide range of single cell topics will be covered in lectures, demonstrations and practical classes. Among others, the areas and issues to be addressed will include the choice of the most appropriate single-cell sequencing technology, the experimental design and the bioinformatics and statistical methods and pipelines. For this edition, new courses/practicals will focus on spatial transcriptomics, cell phenotyping and additional multi-omics.\r\n\r\nRequirements : Participants must have prior experience on NGS data analysis with everyday use of R and good knowledge of Unix command line. Before the training, participants will be asked to familiarize themselves with the processing and primary analyses steps of scRNA-seq datasets with provided pedagogic material.\r\n\r\nIt is not necessary to have personal single-cell data to analyse.", "homepage": "", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [], "prerequisites": [ "Master", "Autre (Diplôme universitaire, école d'ingénieur ...)" ], "openTo": "Everyone", "accessConditions": "Participants must have prior experience on NGS data analysis with everyday use of R and/or Python and good knowledge of Unix command line. Before the training, participants are advised to familiarize themselves with the processing and primary analyses steps of scRNA-seq datasets. \r\nIt is not necessary to have personal single-cell data to analyse.", "maxParticipants": 30, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 4, "name": "IFB", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IFB/?format=api" } ], "organisedByTeams": [], "logo_url": "https://ressources.france-bioinformatique.fr/sites/default/files/sincellTE_logo_0_2.png", "updated_at": "2024-03-20T09:31:42.144175Z", "audienceTypes": [], "audienceRoles": [ "Researchers", "Life scientists", "Biologists", "Bioinformaticians" ], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/199/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/405/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/422/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/177/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/606/?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": 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": 4, "name": "IFB", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/IFB/?format=api" }, { "id": 6, "name": "Elixir-FR", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/Elixir-FR/?format=api" }, { "id": 8, "name": "Elixir", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/Elixir/?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": 310, "name": "Diplôme Universitaire en Bioinformatique Intégrative / University Diploma in Integrative Bioinformatics", "shortName": "DUBii", "description": "La bioinformatique est devenue une compétence incontournable pour l'analyse de données de natures diverses : génomes, transcriptomes, protéomes, métabolomes, structures macromoléculaires, réseaux d'interactions. L'appropriation par les biologistes des méthodes et des 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 de Paris propose en partenariat avec l'Institut Français de Bioinformatique (IFB) la troisième édition du Diplôme Universitaire en Bioinformatique intégrative (DUBii). Cette formation s’adresse en priorité à des biologistes ou à des médecins souhaitant évoluer en compétences ou envisager une reconversion professionnelle et 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). \r\n\r\nLe DUBii fournira une formation théorique et pratique, complétée par une période d'immersion de 20 jours 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\n Cette formation se déroulera pendant 8 semaines réparties entre :\r\nLes cours : 4 semaines à raison de 4 jours/semaine en présentiel (96h)\r\nLe projet tutoré : 20 jours sur l'une des plateformes bioinformatique de l'IFB", "homepage": "https://odf.u-paris.fr/fr/offre-de-formation/diplome-d-universite-1/sciences-technologies-sante-STS/du-bioinformatique-integrative-dubii-DUSBIIN_118.html#programContent26c9751a-f434-491d-abe2-1151370851dc-1", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 20, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "", "updated_at": "2022-09-15T12:11:46.140196Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Advanced", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": true, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/466/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/414/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/400/?format=api" ] } ] }
