Training List
Handles creating, reading and updating training events.
GET /api/training/?format=api&offset=200&ordering=-organisedByOrganisations
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sur la caractérisation de la biodiversité taxonomique d’écosystèmes (procaryotes et micro-eucaryotes) par le prisme du séquençage haut-débit Illumina (Miseq) et du traitement bio-informatique associé (outils R sous Rstudio).", "homepage": "https://anfmetabiodiv.mio.osupytheas.fr", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Everyone", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": null, "updated_at": "2022-06-22T13:18:40.590388Z", "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Researchers", "Life scientists", "Biologists", "Bioinformaticians" ], "difficultyLevel": "", "trainingMaterials": [], "learningOutcomes": "", "hoursPresentations": null, "hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [ 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It is intended for new users, with the goals of improving user productivity and minimizing the obstacles. The HPC Southgreen cluster are presented, together with the tools to be able to use it. Module load notion, interactive usage and batch jobs submittions will be developped.\nPrerequisites\nLinux Basics\n\nProgram\nIntroduction to HPCs architecture\nDiscover Sun grid Engine (SGE)\nData Management on clusters\nInteractive Usage\nSubmit batch jobs\n\n\nLearning objectives\nAfter this course, participants should be able to:\nUse the HPC resources interactively\nManage data copies\nUse module load\nsubmit batch jobs\n\n\nInstructors\n\n\nNdomassi Tando (NT) - ndomassi.tando@ird.fr\nBertrand Pitollat(BP) - bertrand.pitollat@cirad.fr\nAlexis Dereeper (AD) - alexis.dereeper@ird.fr\n\n", "homepage": "https://southgreenplatform.github.io/trainings//HPC/", "is_draft": false, "costs": [ "Free" ], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [ { "id": 24, "name": "South 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"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": 50, "name": "Fc3-Bio", "shortName": "", "description": "1 à 4 séances de deux jours par an\n", "homepage": "http://www.fc3bio.fr/", "is_draft": false, "costs": [], "topics": [], "keywords": [ "Comparative and de novo structure modeling", "Post-translational modifications", "Dynamic and thermodynamic structure properties analysis", "NGS Data Analysis", "Virtual screening", "Structure-based screening", "Sequence Algorithm", "Ligand-Based Screening (QSAR)", "Sequence analysis", "2D/3D", "ADME/tox", "Small chemical compound libraries", "Structure analysis", "homology and structural pattern matching", "Homology/orthology prediction", "Structural Bioinformatics", "Predictions of structural properties", 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"hoursHandsOn": null, "hoursTotal": null, "personalised": null, "event_set": [] }, { "id": 137, "name": "Cours Pasteur Analyse des Génomes", "shortName": "", "description": "Chaque année, ce cours théorique et pratique d’une durée de sept semaines fait le tour\ndes concepts, techniques et outils nécessaires à l'étude des génomes, des étapes expérimentales à l’analyse des résultats. Il illustre les différents aspects de la génomique et de ses applications en se basant sur les résultats les plus récents de la recherche - voir plus\n", "homepage": "http://www.pasteur.fr/fr/enseignement/cours-pasteur/pole-mecanismes-du-vivant/an…", "is_draft": false, "costs": [], "topics": [], "keywords": [ "Biostatistics", "Sequence analysis", "Comparative genomics", "NGS Sequencing Data Analysis" ], "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": [ "https://catalogue.france-bioinformatique.fr/api/event/267/?format=api" ] }, { "id": 47, "name": "Analyse de données RNA-seq sous l’environnement Galaxy ", "shortName": "", "description": "\n\nObjectifs de la formation\nAcquérir les connaissances générales sur les méthodes de séquençage à haut-débit.\nConnaître les caractéristiques des données obtenues dans le cadre de l’analyse du transcriptome (RNA-seq).\nSavoir planifier une expérience simple de type RNA-seq en fonction de ses objectifs scientifiques et des caractéristiques et contraintes expérimentales.\nConnaître les principales méthodes et outils d’analyse des données RNA-seq . Pouvoir les mettre en oeuvre dans un cas simple via un serveur web Galaxy.\nPouvoir visualiser les résultats dans un navigateur de génome.\nDurée de la formation : 2,5 jours\n\n\n", "homepage": "http://www.biosciencesco.fr/formation-continue/bio-informatique/analyse-des-donn…", "is_draft": false, "costs": [], "topics": [], "keywords": [ "Methodology", "Biostatistics", "NGS Data Analysis", "Analysis of RNAseq data", "Assembly of genomes and transcriptomes", "Read alignment on genomes", "Statistical Tests", "Gene expression differential analysis", "Galaxy", "Transcript and transcript variant analysis", "Transcriptomics (RNA-seq)", "NGS Sequencing Data Analysis" ], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "Informations et inscriptions:\nhttp://www.biosciencesco.fr/formation-continue/bio-informatique/analyse-...\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/257/?format=api" ] }, { "id": 30, "name": "Python avancé", "shortName": "", "description": "\nObjectifs\n\nEtre autonome pour des manipulations simples visant à extraire, reformater des données issues de fichiers texte.\n \n\n \n \n \n \nProgramme\n\n- Expressions régulières\n- Gestion des erreurs\n- Biopython\n- Réalisation de programmes simples\n", "homepage": "http://migale.jouy.inra.fr/", "is_draft": false, "costs": [], "topics": [], "keywords": [ "Programming Languages & Computer Sciences", "Python Language" ], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "Ce cycle est ouvert à l'ensemble des agents de l'INRA et aux extérieurs.\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/253/?format=api" ] }, { "id": 4, "name": "Introduction to data analysis with R", "shortName": "", "description": "The program includes an introduction:\nApproaches in biostatistics and research, explaining to participants the principles, methodologies, use of statistical methods and applications in biology and clinical research.\nCourses on software R will be delivered in the form of additional exercises. The basis of the programming language R will be discussed and statistical approaches presented in the theoretical part will be implemented.\nApplication of skills acquired over a personal dataset\n", "homepage": "", "is_draft": false, "costs": [], "topics": [], "keywords": [ "Programming Languages & Computer Sciences", "R Language" ], "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": 15, "name": "IFSBM", "shortName": "", "description": "\nUFR médecine Paris-Sud (mai 2015). Big data en médecine. 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