Training List
Handles creating, reading and updating training events.
GET /api/training/?format=api&offset=380&ordering=costs
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Chaque module comprend des présentations générales et des séances pratiques sur ordinateur, avec Galaxy.\r\nLes objectifs du module 4 sont :\r\n- Savoir réaliser une analyse différentielle de données RNA-seq à partir d’une table de comptage (quantifiant les lectures alignées) à l’aide du portail Galaxy\r\n- Avoir un regard critique sur les résultats d’une analyse différentielle\r\n- Comprendre différentes méthodes de normalisation et les contextes d’utilisation correspondants", "homepage": "https://bilille.univ-lille.fr/training/training-offer", "is_draft": false, "costs": [], "topics": [], "keywords": [ "NGS Data Analysis", "Transcriptomics (RNA-seq)", "NGS Sequencing Data Analysis" ], "prerequisites": [], "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 2/5 «Analyses RNA-seq–partie 1 (bioinformatique)» de ce cycle ou toute autre formation permettant de justifier de connaissances sur les données de séquençage haut débit et la façon d’obtenir une table de comptage", "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": "2024-12-09T17:42:50.474644Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/279/?format=api" ] }, { "id": 331, "name": "Cycle « Analyse de données de séquençage à haut-débit » - Module Analyses RNA-seq (sous Galaxy)- version 2023", "shortName": "", "description": "Bilille, la plateforme de bioinformatique, biostatistique et bioanalyse de la métropole lilloise, propose chaque année un cycle de formation d'introduction à l'analyse des données de séquençage à haut débit.\r\nCe cycle est composé des modules suivants, à la carte : \r\n- Analyses ADN\r\n- Analyses de variants\r\n- Métagénomique\r\n- Analyses ChIP-seq\r\n- Analyses RNA-seq\r\nLes fiches descriptives sont accessibles sur le site de bilille. 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"accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": null, "updated_at": "2022-06-02T11:50:50.812642Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": true, "event_set": [] }, { "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": 7, "name": "InSilicoDb Analysis Training", "shortName": "", "description": "Interrogating public and private gene expression datasets for bio-medical researchers. This workshop will you teach about two subjects: 1- Genomics data management for the lab (efficiently store and make accessible microarray and NGS data), 2- Interrogation of your expression data and comparison and combination of your data with public data.\n", "homepage": "", "is_draft": false, "costs": [], "topics": [], "keywords": [ "Bioinformatics & Biomedical" ], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "Aucune\n", "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": [] }, { "id": 106, "name": "Infrastructure informatique distribuée de France Grilles: Grilles et Cloud", "shortName": "", "description": "", "homepage": "", "is_draft": false, "costs": [], "topics": [], "keywords": [ "Programming Languages & Computer Sciences" ], "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": [] }, { "id": 120, "name": "DUT Bioinformatique", "shortName": "", "description": "A la convergence de la biologie, de l’informatique, cette formation pluridisciplinaire vise à former des techniciens supérieurs possédant une double compétence biologie/informatique capables de produire et de traiter des données biologiques de masse. La formation assurée en 2 ans vise à donner un socle solide de compétences transversales en biologie (génomique, transcriptomique, protéomique…), informatique (programmation, algorithmie, bioinformatiques structurale et intégrative ...) et statistiques, complétée par un travail en groupe ainsi qu’un stage de fin d’année en milieu professionnel. Axée sur les technologies « omiques », cette option propose une professionnalisation rapide pour un domaine en pleine croissance et donne des compétences solides pour continuer vers un master ou un doctorat.\n \n", "homepage": "", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [ "Autre (Diplôme universitaire, école d'ingénieur ...)" ], "openTo": "Internal personnel", "accessConditions": "Accessible en formation continue pour des bacheliers des séries S, STL et en formation continue. Accessible directement en 2ème année pour des étudiants ayant validé une année dans le supérieur et ayant des compétences en biologie et des bases en programmation\n \n", "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": [] }, { "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": 151, "name": "Cycle « Analyse de données de séquençage à haut-débit » - Module 2/5 : Analyses de variants", "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 2 sont :\r\n- Comprendre les grands principes de la détection de variants\r\n- Réaliser les différentes étapes du post-traitement des données d’alignement à la détection de variants\r\n- Adapter l’analyse en fonction du type de données NGS générées\r\n- Comprendre la structure des données de variants\r\n- Savoir annoter des variants\r\n- Etre capable d’interpréter une liste de variants grâce aux outils libres disponibles", "homepage": "https://bilille.univ-lille.fr/training/training-offer", "is_draft": false, "costs": [], "topics": [], "keywords": [ "NGS Data Analysis", "Panels (amplicons, captures)", "Exomes", "Variant analysis", "Genomics (DNA-seq)", "NGS Sequencing Data Analysis" ], "prerequisites": [], "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", "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": "2024-12-09T17:42:43.090760Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/280/?format=api" ] }, { "id": 119, "name": "Modules Biologie École Doctorale SVSAE", "shortName": "", "description": "Les UE de bioinformatique de la spécialité AMD sont ouvertes aux doctorants de l'école doctorale SVSAE dans le cadre de leur formation doctorale. 3 UE sont particulièrement suivies : UE « Programmation en perl », UE « Bioistatistiques et programmation sous R » et UE « Génomique et bioinformatique ». Les formations continues proposées dans le domaine de la bioinformatique sont également ouvertes aux étudiants de l'Ecole Doctorale, et permettent de valider un module de biologie. Forme 2 à 3 doctorants par an.\n \n", "homepage": "", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [ "Autre (Diplôme universitaire, école d'ingénieur ...)" ], "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": [] }, { "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. 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