Handles creating, reading and updating events.

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            "description": "L’Institut Français de Bioinformatique (IFB) organise une formation à destination de bioinformaticiens, biologistes et médecins. La formation abordera les différents points fondamentaux (théoriques, pratiques, juridiques) en lien avec la politique nationale d’ouverture des données de la recherche et présentera sous forme de séances pratiques les ressources nationales accessibles à la communauté scientifique ainsi que les solutions proposées par l’IFB pour gérer les données d’un projet de recherche.",
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            "description": "More than twenty years after the first bacterial genome has been sequenced, microbiologists are faced with an avalanche of genomic data. However the quality of the functional annotations of the sequenced proteome is very poor with more than half of the sequenced proteins remaining of unknown function. After taking this course, students should master an array of web-based tools to help to predict gene function. This will allow them to generate in silico based functional predictions and produce illustration for manuscripts that use comparative genomic methods. For background read (https://www.ncbi.nlm.nih.gov/pubmed/20001958)\n",
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            "name": "Bioinformatics of protein--protein interactions for wet lab scientists",
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            "description": "Understanding physical and functional interactions between molecules in living systems is crucial in many biological processes. Several powerful methods and techniques have been developed to generate molecular interaction data, focusing mainly on protein­-protein interactions (PPIs). In particular, PPIs involving partially or completely unstructured regions are building blocks of regulatory and signalling networks that control cell response to external and internal cues. Exploring these interactions may help understanding a protein’s function and behavior, predicting biological processes that a protein of unknown function is involved in, and characterising protein complexes that can be used to modulate or perturb known biological processes and pathways.\n",
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            "description": "The ever growing usage of high throughput technologies in Biology is revolutionizing the life sciences and profoundly changing its practices. Scripting languages are used on a daily basis in life science labs in order to mine huge data sets produced by high-throughput devices. This two-week course will give participants basic knowledge in python and state-of-the-art machine learning methods to analyze their own data sets.\r\nDescription:\r\nThis course is intended for PhD students, engineers and research scientists willing to acquire knowledge in scientific programming. Throughout the course, we will use Python language to lead participants from the basics of computer programming to more advanced techniques such as practical machine learning techniques.",
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            "description": "Biological data are often complex and challenging to analyse due to non-normal distributions, nonlinear relationships, spatial/temporal structures and high dimensionality. This course will introduce the students to key concepts and statistical tools for the experimental design and analysis of biological data. After a brief refresher on basic elements of statistics, the students will be made familiar with hypothesis testing, univariate statistical tests (e.g. ANOVA), linear models, descriptive multivariate analyses such as Principal Component Analysis (PCA) and clustering. The course will alternate theoretical aspects and computer exercises on small datasets with the R Studio software. The students will be assigned a small project involving the different concepts and tools covered by the course.\n",
            "homepage": "https://www.enseignement.biologie.ens.fr/spip.php",
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            "type": "Training course",
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            "description": "\nL'utilisation de plus en plus répandue de techniques d’imagerie et de séquençage à haut-débit en biologie est en train de révolutionner les sciences du vivant et de modifier en profondeur leurs pratiques. Dans ce contexte, des outils statistiques sont développés pour permettre d’analyser ces données de hautes dimensions, et la maîtrise de ces outils devient de plus en plus nécessaire pour produire des résultats de bonne qualité. Ce cours de 4 semaines couvrira les étapes nécessaires pour mettre en place un processus d’analyse de données, depuis la planification de l’expérience jusqu’à la fouille des données en passant par l’échantillonnage, les test d’hypothèses, la modélisation statistique etc.\nCe cours s’adresse en priorité aux étudiants de première année de thèse de l’Institut Pasteur. Tout étudiant en thèse sera automatiquement inscrit à ce cours, mais les élèves de 2e année, de 3e année ou les post-doctorants peuvent également s’inscrire, dans la limite des places disponibles. Il est à noter que le cours est obligatoire pour les étudiants de 1ère année. Des dispenses partielles ou totales sont possibles pour les étudiants qui ont déjà des connaissances en statistique, en mathématique ou en physique. Le cours déroulera sur 4 semaines, 4 jours par semaine, trois heures par jour. Chaque séance de trois heures alternera cours magistral et mise en pratique. Il y aura deux sessions : la première commencera le 22 octobre 2018 et la deuxième le 14 janvier 2019.\nChacune de ces deux sessions sera précédée d’une séance d’introduction à l’informatique. Cette séance proposera des notions d’architecture de l’ordinateur, de système d’organisation des fichiers et de format de fichiers. Chaque session sera également suivie d’un cours optionnel sur l’analyse et le traitement des images.\nPour plus d’information, ainsi que pour les inscriptions au module optionnel et les demandes d’exemption, rendez-vous sur la page du cours : https://c3bi.pasteur.fr/introduction-to-data-analysis-2018-19/\nThèmes abordés\nLe module d’analyse de données couvrira un large champ de notions nécessaires aux étudiants pour planifier leurs expériences, analyser et explorer leurs données, interpréter les résultats et générer des figures à des fins de publication. Il abordera des notions de base en statistique, dont les analyses uni- et multivariées, les analyses descriptives, les distributions statistiques usuelles utilisées en biologie, ainsi que les tests d’hypothèses. Les exercices et travaux pratiques seront réalisés avec R et RStudio. Plusieurs séances seront consacrées à une introduction à l’utilisation du langage de programmation R avant d’aborder les notions de statistiques et d’analyse de données.\nLe module d’analyse d’images introduira les principes de base de l’analyse d’image, et portera plus particulièrement sur l’extraction d’information quantitative d’images de microscopie. Ce cours est destiné aux personnes ayant peu ou pas d’expérience en analyse d’image. Il sera très orienté sur la pratique : des cours magistraux de courte durée seront immédiatement suivis de sessions pratiques. Il aidera à la fois les microscopistes débutants et experts qui n’ont jamais eu de formation concrète en analyse d’image.\n \n\n",
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            "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.\nPrerequisites\nGalaxy, R knowledge\n\nProgram\nIntroduction to metagenomics and metabarcoding\nPre-processing, Clustering, taxonomic affiliation (FROGS)\nHandling and visualizing OTU table using PhyloSeq R package (PhyloSeq)\n\n\nLearning objectives\nManipulate tools available for metabarcoding analysis\nStudy sample diversity by using NGS and post-NGS analysis tools\nVisualize diversity metrics in metabarcoding approach​\n\n\nInstructors\nJulie Orjuela - julie.orjuela@ird.fr\nFlorentin Constancias - florentin.constancias@cirad.fr\nAlexis Dereeper - alexis.dereeper@ird.fr\n\n \n",
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            "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.\nPrerequisites\nWorkflow management system (Galaxy, TOGGLe)\n\nProgram\nMapping of RNASeq against a transcriptome reference with kallisto (Galaxy)\nMapping of RNASeq against an annotated genome reference with TopHat (TOGGLe)\nDifferential expression analysis using EdgeR and DESeq2\nPlots, clustering, co-expression network: degust, WGCNA\n\n\nLearning objectives\nManipulate packages/tools available for searching DE genes\nThink about different normalisation methods\nDetect differentially expressed genes\nCompare results between two approaches\n\n\nInstructors\nAlexis Dereeper - alexis.dereeper@ird.fr\nSebastien Cunnac - sebastien.cunnac@ird.fr\nSebastien Ravel - sebastien.ravel@cirad.fr\nChristine Tranchant  - christine.tranchant@ird.fr\n\n",
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            "country": "",
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            "id": 387,
            "name": "Initiation to NGS Workflow Managers developed within the South Green Platform: Galaxy and TOGGLe",
            "shortName": "",
            "description": "This course introduces the 2 commonly used workflow managers in the South Green Bioformatics platform, both in a theoretical and practical way, with hands-on practice sessions. It will help you to quickly develop and run your own pipelines using these tools through an graphical user or command-line interface.\n \nPrerequisites\nPrior knowledge of workflow managers not necessary Basic knowledge of Linux (Linux for dummies required) - TOGGLe practical\n\nProgram\nWhy using a workflow manager to analyse data ?\nHow to perform an analysis ?\nHow to create your own workflow ?\nHow to execute it?\nUse case\n\n\nLearning objectives\nExplaining what Workflow Managers are,\n\tin which way they differ from each other.\nHow you can use them in your research.\nCreating your own workflow\nAnalysing your NGS data with Galaxy and TOGGLe\n\n\nInstructors\nAlexis Dereeper (AD) - alexis.dereeper@ird.fr\nSebastien Ravel (SR) - sebastien.ravel@cirad.fr\nChristine Tranchant (CT) - christine.tranchant@ird.fr\n\n",
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            "id": 386,
            "name": "Analyse de données NGS dédiée à la génomique végétale en Afrique de l'Ouest",
            "shortName": "",
            "description": "Les avancées spectaculaires des technologies de séquençage de 2ème et 3ème génération sont une véritable révolution pour la recherche en science de la vie. Ces techniques permettent le séquençage en quelques semaines de génomes entiers d’organismes complexes, générant une explosion du volume de données génomiques. \n\t\t\tToutefois l’analyse de telles masses d’informations nécessite des compétences en linux, en bioinformatique ainsi qu’une bonne connaissance et maîtrise de nombreux algorithmes et logiciels. La réalisation de ces analyses nécessite également l’accès à des ressources de calcul telles que des clusters de calcul. \n\t\t\tLe DP IAVAO et le LMI LAPSE en collaboration avec la plateforme bioinformatique South Green organisent, du 4 au 12 Octobre 2018, une formation en bioinformatique dédié à l’analyse de données de séquençage dont les objectifs sont de présenter les technologies de séquençage et les différentes analyses bioinformatiques pour exploiter au mieux cette masse de données afin de pouvoir réaliser des projets génomiques à grande échelle sur leurs modèles (plantes et pathogènes).\nPrérequis\nAucun\n\nProgramme\nLinux et lignes de commandes \nInitiation à l’utilisation du cluster du CERAAS \nPrésentation des technologies de séquençages \nAppel de SNP sur des données WGS \nPost analyse de données de SNPs\nOutils Genome Harvest \n\n\nObjectifs\nAprès la formation, les participants seront capables de :\nse connecter à un cluster Linux\nlancer des programmes/analyses bioinformatiques\ndéfinir les étapes pour analyser des données de séquençage\nanalyser des données de séquençage\nutiliser des gestionnaires de workflow tel que Galaxy ou TOGGLe\n\n\nInstructors\nChristine Tranchant (CT) - christine.tranchant@ird.fr\nNdomassi Tando (NT) - ndomassi.tando@ird.fr\nBertrand Pitollat (BP) - bertrand.pitollat@cirad.fr\nFrançois Sabot (SB) - francois.sabot@ird.fr\nManuel Ruiz (MR) - manuel.ruiz@cirad.fr\nGautier Sarah (GS) - gautier.sarah@cirad.fr\n\n",
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            "costs": [
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            ],
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                    "id": 14,
                    "name": "IAVAO",
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            "end_date": "2018-10-11",
            "venue": "",
            "city": "CERAAS, Thiès (Sénégal)",
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            "name": "Installing and Managing a High-Performance Computing (HPC) Cluster ",
            "shortName": "",
            "description": "This course ran for 5 days covering all the concepts necessary to  install and manage a high-performance computing (HPC) cluster. During this course,  a HPC cluster were installed at CERAAS (Thiès, Sénégal)  by the participants, IT managers from western africa (IRD, ISRA, CERAAS).\n",
            "homepage": "https://southgreenplatform.github.io/trainings//ngsTrainings/",
            "is_draft": false,
            "costs": [
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            "name": "Introduction to High-performance computing",
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            "description": "This course offers an introduction on how to work with HPC Southgreen clusters. 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": [],
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            "logo_url": "",
            "updated_at": "2022-06-02T11:50:50.627601Z",
            "type": "Training course",
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            "country": "",
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        },
        {
            "id": 383,
            "name": "Survival Guide for Perl applied to Bioinformatics",
            "shortName": "",
            "description": " \n\n\t\t\tThis course provides an introduction to programming using Perl and at the end of the training, participants could write simple Perl programs to handle biological data and to undertstand more complex Perl programs written by others.\n\t\t\t\nPrerequisites\nBasic knowledge of Linux (Linux for dummies required)\n\nProgram\nPerl data structures (scalar,arrays, hashes)\nStructure control ( loops)\nBasic functions, and operators.\nWriting and running your own program\nPassing options and files to his own script.\nRegular expressions\n\n\nLearning objectives\nWriting simple Perl programs to analyze data files\nUnderstanding Perl programs written by others\nUsing Perl basic syntax and modules in their own script\nRun programs from their script, parsing and extracting data from data files\n\n\nInstructors\n\n\nChristine Tranchant  - christine.tranchant@ird.fr\nFrançois Sabot - francois.sabot@ird.fr\nNdomassi tando - ndomassi.tando@ird.fr\n\n",
            "homepage": "https://southgreenplatform.github.io/trainings//perl/",
            "is_draft": false,
            "costs": [
                "Free"
            ],
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                {
                    "id": 13,
                    "name": "Formation permanente IRD",
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            "updated_at": "2022-06-02T11:50:50.627601Z",
            "type": "Training course",
            "start_date": "2017-10-01",
            "end_date": "2017-10-05",
            "venue": "",
            "city": "ISRA, Bel Air, Dakar (Sénégal)",
            "country": "",
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            "id": 382,
            "name": " Linux For Jedi",
            "shortName": "",
            "description": "This course offers to develop and enhance advanced Linux shell command line and scripting skills for the processing and analysis of NGS data. We will work on a HPC server and use linux powerful commands to allow to analyze big amount of biological data.\n \nPrerequisites\nBasic knowledge of Linux (Linux for dummies required)\n\nProgram\nConnecting to a distant HPC\nManipuling text files\nComplex searching for text in a file\nCombining several commands\nWriting simple shell scripts\n\n\nLearning objectives\nAfter this course, participants should be able to:\nManipulate and search within text files\nChain and combine commands\nPerform the same actions on many files\nWrite a simple shell script\n\n\n \n\n\nInstructors\nChristine Tranchant (CT) - christine.tranchant@ird.fr\nNdomassi Tando (NT) - ndomassi.tando@ird.fr\nBruno Granouillac (BG) - bruno.granouillac@ird.fr​\nFrançois Sabot (SB) - francois.sabot@ird.fr\nGautier Sarah (GS) - gautier.sarah@cirad.fr\n\n",
            "homepage": "https://southgreenplatform.github.io/trainings/linuxJedi/",
            "is_draft": false,
            "costs": [
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            "id": 381,
            "name": "Linux For Dummies",
            "shortName": "",
            "description": " \nThis course offers an introduction to work with Linux. We will describe the Linux environment, the first linux commands so participants can start to utilize command-line tools and feel comfortable using bioinformatics softwares through a linux terminal.\nPrerequisites\nNo experience required\n\nProgram\nConnecting to a distant HPC\nNavigating through a Unix file system\nCreating and deleting files\nManipuling and filtering file text\nBasics searching for text within a file\n\n\nLearning objectives\nAfter this course, participants should be able to:\nConnect to a Unix / Linux system\nManipulate files and directories within the Linux system\nWork with text files\nRun programs from the command-line\n\n\nInstructors\nChristine Tranchant - christine.tranchant@ird.fr\nNdomassi Tando - ndomassi.tando@ird.fr\nBruno Granouillac - bruno.granouillac@ird.fr\nFrançois Sabot - francois.sabot@ird.fr\nGautier Sarah  - gautier.sarah@cirad.fr\n\n",
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            "is_draft": false,
            "costs": [
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            "name": "RNASeq alignment and transcripts assemblies",
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            "description": "This training session is designed to help you deal with sequences from the SGS (Second Generation Sequencing) particularly Illumina platforms (GAIIx, HiSeq). You will discover the new sequence file formats, learn about the usual biases of this data type and run different kind of analysis such as spliced alignment on a reference genome, novel gene and transcript discovery, expression quantification of the genes and transcripts. Organized jointly by the MIAT unit and bioinfo genotoul platforms.\n",
            "homepage": "http://bioinfo.genotoul.fr/index.php/events/rnaseq-alignment-and-transcripts-ass…",
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            "venue": "",
            "city": "Auzeville-Tolosane",
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            "name": "Scientific Programming in Python",
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            "type": "Training course",
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