Training List
Handles creating, reading and updating training events.
GET /api/training/?format=api&offset=260&ordering=-sponsoredBy
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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_0602", "http://edamontology.org/topic_2269", "http://edamontology.org/topic_0089" ], "keywords": [ "Biological network inference and analysis", 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spécifiques de la bioinformatique, des systèmes d'informations, de l'extraction de connaissances et de la modélisation du vivant tout en renforçant les compétences de leur profil initial.\n", "homepage": "", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [ "Master" ], "openTo": "Internal personnel", "accessConditions": "M1 : licence math, info, physique, EEA, biologie, STAPS + équiv. L3 de la formation pharma/médecine (ou tout équiv. 180 ECTS acquis) - M2 : master 1 ou équiv. (formation continue, VAE, ...)\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": 273, "name": "Phylogénie moléculaire", "shortName": "", "description": "- Acquérir des connaissances théoriques et pratiques en phylogénie moléculaire\n- Être autonome dans la conduite d'une analyse phylogénétique\n- Maîtriser le choix, le paramétrage et l'exploitation des résultats des programmes de phylogénie\n", "homepage": "https://cnrsformation.cnrs.fr/stage-20466-Phylogenie-moleculaire.html", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 59, "name": "LBBE", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/LBBE/?format=api" } ], "organisedByTeams": [], "logo_url": "https://ressources.france-bioinformatique.fr/sites/default/files/UMR_5558_LBBE.jpg", "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/403/?format=api" ] }, { "id": 79, "name": "Phylogénie moléculaire", "shortName": "", "description": "\nLes objectifs sont :\n1. 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Maîtriser le choix, le paramétrage et l'exploitation des résultats des programmes de phylogénie.\nhttps://cnrsformation.cnrs.fr/\n\n", "homepage": "http://cnrsformation.cnrs.fr/stage-17007-Phylogenie-moleculaire-%28Montpellier%2…", "is_draft": false, "costs": [], "topics": [], "keywords": [ "Phylogeny", "Evolution and Phylogeny", "Molecular evolution", "Speciation dating", "Selection Detection", "Supertrees and Reconciliations", "Phylogenomics", "Genes and genomes" ], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "S'acquitter des frais d'inscription, être familiarisé avec les banques de données de séquences, avoir déjà utilisé les logiciels de base en bioinformatique, connaître les notions de base en statistiques (tests, lois probabilistes usuelles, méthodes simples d'estimation de paramètres), avoir des notions de programmation.\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": [ "https://catalogue.france-bioinformatique.fr/api/event/263/?format=api" ] }, { "id": 42, "name": "Initiation to R language", "shortName": "", "description": "OBJECTIVES :\n* Acquire basic knowledge on the R language\n* Experience the main features of R\n* Be autonomous in handling data\n* Perform simple statistical analysis and build charts\n* Learn how to create functions\n", "homepage": "http://www.pf-bird.univ-nantes.fr/training/", "is_draft": false, "costs": [ "Priced" ], "topics": [], "keywords": [ "Programming Languages & Computer Sciences", "R Language" ], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "This training is open to all (public and private) with no institution restrictions and is accessible through the University of Nantes continuing education programme.\n", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [ { "id": 55, "name": "University of Nantes", "url": "https://catalogue.france-bioinformatique.fr/api/organisation/University%20of%20Nantes/?format=api" } ], "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": 90, "name": "Master de Bioinformatique, Biochimie Structurale et Génomique", "shortName": "", "description": "Analyse statistique des données génomiques.\nMéthodes bioinformatiques pour la cis-régulation.\nMéthodes bioinformatiques pour la génomique et la protéomique.\nProjet informatique lié à la biologie\nEcole doctorale des sciences de la vie et de la santé, AMU\n", "homepage": "", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [ "Master" ], "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": 134, "name": "Initiation à l'analyse de données avec R", "shortName": "", "description": "Le cours s’adresse à des personnes qui veulent apprendre ou ré-apprendre à utiliser les statistiques à bon escient pour leurs propres projets. L’objectif est de présenter et expliquer les principales notions de statistiques utiles pour décrire un jeu de données, en explorer les propriétés afin d’en tirer des conclusions robustes, utiliser à bon escient les méthodes les plus courantes (tests d’hypothèse, ACP, …) et savoir lire, interpréter (et éventuellement aborder d’un œil critique) les résultats présentés dans les publications. Nous utiliserons le moins possible le formalisme mathématique mais insisterons sur les propriétés des méthodes, leurs pré-requis, l’interprétation des résultats. Nous aborderons les notions d’analyse exploratoire, ACP, clustering, estimation, échantillonnage, régression, tests d’hypothèse, planification d’expérience\nCe cours est une initiation à l’analyse de données. Il est préférable d’avoir une connaissance minimale de R. Dans le cas contraire, un tutoriel d’initiation est disponible sur la page web du cours et les notions de base de R seront rappelées pendant la pratique. Pour les personnes n’ayant jamais utilisé R, il peut être utile d’avoir des connaissances de base en programmation, quel que soit le langage.\nLes cours seront donnés en Français et alterneront théorie et pratique avec RStudio. Il est demandé à chaque participant de venir avec un ordinateur portable chargé sur lequel il aura préalablement installé les éléments nécessaires (R, Rstudio et les fichiers de données sur lesquels nous travaillerons). 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