Training List
Handles creating, reading and updating training events.
GET /api/training/?format=api&offset=120&ordering=-updated_at
{ "count": 391, "next": "https://catalogue.france-bioinformatique.fr/api/training/?format=api&limit=20&offset=140&ordering=-updated_at", "previous": "https://catalogue.france-bioinformatique.fr/api/training/?format=api&limit=20&offset=100&ordering=-updated_at", "results": [ { "id": 335, "name": "FAIR_bioinfo_@_AuBi", "shortName": "FAIR_bioinfo", "description": "Introduction aux bonnes pratiques en bio-informatique afin de pérenniser son travail de recherche.\r\n\r\nCette formation permet de découvrir les bonnes pratiques dans le cadre d’un travail nécessitant des approches programmatiques (statistiques, programmation d’outils, analyses de données biologiques). Elle s’inscrit aussi dans l’aspect science-ouverte afin de rendre plus facilement disponible et pérenne le travail bio-informatique. Après une introduction aux pratiques FAIR axées notamment sur les notions de reproductibilité et de répétabilité du code, plusieurs approches seront abordées: les bonnes pratiques de partage et gestion des versions des outils utilisés ; la gestion des environnements de travail (conda, docker, singularity) ; découverte du gestionnaire de workflow Snakemake : et enfin la documentation du code avec Rmarkdown et Jupyter.", "homepage": "https://mesocentre.uca.fr/actualites/pratiques-fair-en-bioinformatique-pour-des-analyses-reproductibles", "is_draft": false, "costs": [ "Free to academics" ], "topics": [ "http://edamontology.org/topic_0769", "http://edamontology.org/topic_3068", "http://edamontology.org/topic_3307", "http://edamontology.org/topic_0091" ], "keywords": [ "Methodology", "Programming Languages & Computer Sciences", "Cloud", "Linux", "Snakemake", "Docker", "R" ], "prerequisites": [ "Linux - Basic Knowledge" ], "openTo": "Everyone", "accessConditions": "Having an account on Mesocentre Clermont Auvergne Infrastructure", "maxParticipants": 15, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/261/?format=api" ], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 87, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/AuBi/?format=api" }, { "id": 94, "name": "University Clermont Auvergne", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/University%20Clermont%20Auvergne/?format=api" } ], "organisedByTeams": [ { "id": 31, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/team/AuBi/?format=api" } ], "logo_url": "https://mesocentre.uca.fr/medias/photo/logoaubi-2019minus_1553844844490-jpg?ID_FICHE=41175", "updated_at": "2023-06-14T10:18:52.160465Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 10, "hoursHandsOn": 20, "hoursTotal": 30, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/537/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/709/?format=api" ] }, { "id": 334, "name": "Summer School Multi-omics Data Analysis and Integration", "shortName": "", "description": "Researchers often have access to or generate multiple omics data (RNAseq, metabolomics, lipidomics, proteomics…) within a single study. Although each omics data is usually analyzed individually, combining complementary data can yield a better understanding of the mechanisms involved in biological processes. Several integrative approaches are now available to combine such data, coming essentially from two families of methods, namely multivariate statistical analyses and network-based approaches. During this summer school both methodologies will be covered, introducing RGCCA and mixOmics for multivariate analyses and WGCNA and SNF for network-based strategies. To get meaningful biological information, the interpretation of statistical results needs to be done contextualizing them in the available biological knowledge. To address this major step we need to be able to access and interrogate databases. We will harness this subject introducing semantic web and knowledge graphs in the context of metabolic networks.\r\n\r\nDuring the School, significant time will be devoted to hands-on and the program will be divided into three phases / topics:\r\n- Multivariate statistical analyses (Instructors: Arnaud Gloaguen & Jimmy Vandel)\r\n- Network-based approaches (Instructors: Morgane Térézol & Marie-Galadriel Brière)\r\n- Results contextualisation: an introduction to metabolic models, web semantic and knowledge graphs (Instructors: Jean-Clément Gallardo, Maxime Delmas & Marco Pagni)\r\n\r\nThe participants will work in groups and shortly present the application of what they have learned to their own project.", "homepage": "https://www.sib.swiss/training/course/20230903_MODAI", "is_draft": false, "costs": [], "topics": [ "http://edamontology.org/topic_0089", "http://edamontology.org/topic_2269", "http://edamontology.org/topic_0602" ], "keywords": [ "Biological network inference and analysis", "Multivariate analyses", "Semantic web", "Knowledge representation" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [ { "id": 1, "name": "Training", "url": "https://catalogue.france-bioinformatique.fr/api/elixirplatform/Training/?format=api" } ], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 100, "name": "SIB", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/SIB/?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": null, "updated_at": "2023-04-26T16:14:06.237852Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Intermediate", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/532/?format=api" ] }, { "id": 272, "name": "Molecular Phylogeny - Level 2", "shortName": "Phylogénie moléculaire - Niveau 2", "description": "OBJECTIF\r\n- Être capable de tester des hypothèses et d'ajuster des modèles permettant de comprendre l'évolution à l'échelle moléculaire\r\n\r\nPRÉREQUIS\r\n- Avoir déjà utilisé les logiciels de base en phylogénie moléculaire\r\n- Maîtriser les notions de base en statistiques (tests statistiques, principe du bootstrap, intervalles de confiances, etc.) et de probabilités (probabilités jointes / conditionnelles, théorème de Bayes, etc.)\r\n- Maîtriser un langage de programmation\r\n- Notions de phylogénie moléculaire\r\nAvoir suivi le stage \"Phylogénie moléculaire - formation de base\" ou niveau équivalent \r\n\r\nPROGRAMME\r\n- Phylogénétique et génétique des populations\r\n- Détection de sélection positive au sein de séquences codantes\r\n- Datation moléculaire : intégrer fossiles et molécules\r\n- Phylogénomique\r\n- Super-arbres et super-matrices, réconciliations d'arbres\r\n- Visualisation de l'information en phylogénie\r\n- Placement phylogénétique\r\n- Bases d'épidémiologie (modèles en compartiments, ODE, applications, etc)\r\n- Simulations selon une variété de modèles épidémiologiques\r\n- Phylodynamique : combiner épidémiologie et évolution", "homepage": "", "is_draft": false, "costs": [ "Priced", "1200 €" ], "topics": [], "keywords": [ "Phylogeny", "Selection Detection", "Phylogenomics" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/282/?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://ressources.france-bioinformatique.fr/sites/default/files/ATGClogox120_0.png", "updated_at": "2023-01-24T10:49:17.913427Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/474/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/511/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/402/?format=api" ] }, { "id": 271, "name": "Bioinformatique pour le traitement de données de séquençage (NGS) : analyse de transcriptome", "shortName": "", "description": "OBJECTIFS\r\n- Comprendre les principes des méthodes d'analyse de données de séquençage à haut débit\r\n- Comprendre les résultats obtenus, les paramètres et leurs impacts sur les analyses\r\n- Savoir choisir et utiliser les principaux outils d'analyse\r\n- Être autonome pour utiliser un pipeline d'analyse\r\n- Savoir manipuler les fichiers de séquences : préparation et filtration\r\n- Savoir évaluer la qualité des données\r\n- Savoir analyser les résultats avec ou sans génome de référence\r\n\r\nPRÉREQUIS\r\n- Notions de base en informatique : fichiers, répertoire...\r\n- Notions du système linux et des lignes de commande\r\n- Niveau master \r\n\r\nPROGRAMME\r\n- Linux : commandes de base\r\n- Les données NGS : fichiers, manipulation de base, nettoyage\r\n- Mapping : principaux outils et pratique\r\n- Transcriptomique :\r\n. analyse de RNA-seq : expression différentielle des gènes / des ARNs (comptage et DESeq2) ; comparaison d'échantillons issus de conditions différentes\r\n. post-analyse : analyse GO, interrogation bases de connaissances (ex : KEGG), création de graphique (en R)\r\n. analyse couplée transcriptome / traductome", "homepage": "", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [ "NGS Sequencing Data Analysis" ], "prerequisites": [], "openTo": "Everyone", "accessConditions": "PUBLICS :\r\n- Biologistes, professionnels des sciences du vivant ayant besoin d'analyser des données de séquençage\r\n- Ingénieurs ou chercheurs en bioinformatique\r\n- Bioanalystes\r\n \r\nPRÉREQUIS\r\n- Notions de base en informatique : fichiers, répertoire...\r\n- Notions du système linux et des lignes de commande\r\n- Niveau master", "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://ressources.france-bioinformatique.fr/sites/default/files/ATGClogox120.png", "updated_at": "2023-01-24T10:47:30.457628Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/401/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/510/?format=api" ] }, { "id": 306, "name": "Molecular Phylogeny - Level 1", "shortName": "Phylogénie moléculaire - Niveau 1", "description": "OBJECTIF\r\n- Savoir inférer un arbre phylogénétique et l'interpréter\r\n\r\nPRÉREQUIS\r\n- Savoir ce à quoi correspondent des séquences génétiques homologues\r\n- Avoir déjà utilisé les logiciels de base en bioinformatique\r\n- Connaître les notions de base en statistiques (tests, lois probabilistes usuelles, méthodes simples d'estimation de paramètres)\r\n- Avoir des notions de programmation\r\n\r\nPROGRAMME\r\n- Lignes de commandes Linux\r\n- Le format Newick\r\n- Dessin d'arbres\r\n- Alignements multiples et nettoyage\r\n- Modèles d'évolution\r\n- Choix de modèles\r\n- Définitions et propriétés des arbres\r\n- Méthodes de parcimonie\r\n- Méthodes de distance\r\n- Maximum de vraisemblance\r\n- Reconstruction phylogénétique Bayésienne\r\n- Bootstraps et autres supports de branches", "homepage": "", "is_draft": false, "costs": [ "1200 €" ], "topics": [ "http://edamontology.org/topic_3299", "http://edamontology.org/topic_0084", "http://edamontology.org/topic_3293" ], "keywords": [], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 12, "contacts": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/241/?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://ressources.france-bioinformatique.fr/sites/default/files/ATGClogox120_0.png", "updated_at": "2023-01-24T10:44:55.936489Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "To know how to infer a phylogenetic tree and interpret it.", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": true, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/460/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/509/?format=api" ] }, { "id": 322, "name": "Introduction to Structural variant detection analyses", "shortName": "", "description": "Program\r\n\r\n* Handling mapping tools suitable for ILLUMINA and ONT data (bwa, minimap2)\r\n* SNP detection from mapping of short reads against a reference genome: SNP calling, filters and SNP annotation. Examples of possible studies based on SNP arrays\r\n* Detecting Structural Variations (SV) in short and long reads (breakdancer, sniffle)\r\n* SV detection from genome assembly and comparison (minimap2, nucmer, assemblytics, siry)", "homepage": "https://southgreenplatform.github.io/trainings//sv/", "is_draft": false, "costs": [ "Free" ], "topics": [], "keywords": [], "prerequisites": [ "Linux and knowledge of NGS formats" ], "openTo": "Internal personnel", "accessConditions": "Open to South Green close collaborators", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [ { "id": 24, "name": "South Green", "url": "https://catalogue.france-bioinformatique.fr/api/team/South%20Green/?format=api" } ], "logo_url": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png", "updated_at": "2023-01-24T10:41:28.470404Z", "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 14, "hoursHandsOn": 14, "hoursTotal": 28, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/564/?format=api" ] }, { "id": 256, "name": "RNASeq analyses (using Galaxy and TOGGLe)", "shortName": "", "description": "This course offers an introduction to RNASeq analyses using two different workflow management systems: Galaxy and TOGGLe. 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": 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": 287, "name": "Introduction to Oxford Nanopore Technology data analyses", "shortName": "Introduction to ONT data analyses", "description": "This course offers an introduction to ONT data analysis. It includes 5 issues: basecalling, reads quality control, assemblies and polishing/correction, contig quality and structural variants detection.", "homepage": "https://southgreenplatform.github.io/trainings//ont/", "is_draft": false, "costs": [ "Free" ], "topics": [ "http://edamontology.org/topic_3673", "http://edamontology.org/topic_3168", "http://edamontology.org/topic_0196" ], "keywords": [], "prerequisites": [ "Linux and knowledge of NGS formats" ], "openTo": "Everyone", "accessConditions": "", "maxParticipants": 15, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [ { "id": 24, "name": "South Green", "url": "https://catalogue.france-bioinformatique.fr/api/team/South%20Green/?format=api" } ], "logo_url": "https://southgreenplatform.github.io/trainings//images/southgreenlong.png", "updated_at": "2023-01-24T10:21:58.467251Z", "audienceTypes": [ "Professional (initial)" ], "audienceRoles": [ "Life scientists", "Biologists" ], "difficultyLevel": "Novice", "trainingMaterials": [ { "id": 1, "name": "SG-ONT-slides", "url": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/SG-ONT-slides/?format=api" } ], "learningOutcomes": "* Understanding limits and advantages of ONT technology\r\n* Manipulating ONT data on a virtual machine on jupyter environment\r\n* Handling mapping, assembly, polishing tools and be able to analyse your own data\r\n* Detecting structural variations using long reads", "hoursPresentations": 6, "hoursHandsOn": 6, "hoursTotal": 12, "personalised": null, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/441/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/450/?format=api", "https://catalogue.france-bioinformatique.fr/api/event/562/?format=api" ] }, { "id": 295, "name": "Introduction to the use of a computing cluster", "shortName": "", "description": "Knowledge of the concepts and best practices for using the computing resources of the mesocenter cluster Clermont Auvergne in a bioinformatics context.\r\nBecome familiar with the work environment of the computing cluster, become autonomous in the use of its resources and learn to use a scheduler. \r\nPresentation of the resources accessible on the cluster (computing nodes, storage spaces, tools).\r\nConcept of jobs, queues and parallel computing.\r\nJob management (submission, follow-up, deletion).", "homepage": "https://mesocentre.uca.fr/", "is_draft": false, "costs": [ "Free to academics" ], "topics": [ "http://edamontology.org/topic_0605", "http://edamontology.org/topic_0091" ], "keywords": [], "prerequisites": [ "Linux and knowledge of NGS formats" ], "openTo": "Internal personnel", "accessConditions": "Have an account on the Mesocentre UCA computing cluster (make a request if necessary on the site https://hub.mesocentre.uca.fr)\r\nAlternation of theoretical courses and practical work.\r\nCOME WITH A LAPTOP with an operational Eduroam connection.\r\nThe training is in French.", "maxParticipants": 10, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 45, "name": "UMR 454 MEDIS INRA-Université Clermont Auvergne", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/UMR%20454%20MEDIS%20INRA-Universit%C3%A9%20Clermont%20Auvergne/?format=api" } ], "organisedByTeams": [ { "id": 31, "name": "AuBi", "url": "https://catalogue.france-bioinformatique.fr/api/team/AuBi/?format=api" } ], "logo_url": null, "updated_at": "2023-01-24T10:21:58.347905Z", "audienceTypes": [ "Graduate" ], "audienceRoles": [ "Researchers", "Computer scientists" ], "difficultyLevel": "Novice", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": 3, "hoursHandsOn": 4, "hoursTotal": 8, "personalised": false, "event_set": [ "https://catalogue.france-bioinformatique.fr/api/event/487/?format=api", 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