Handles creating, reading and updating training materials.

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            "name": "ETBII 2023",
            "description": "All the training materials dedicated to the IFB's Integrative Bioinformatics Thematic School, which took place in January 2023.",
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                "http://edamontology.org/topic_3307"
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                "Multivariate analyses",
                "Semantic web",
                "Data Integration"
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                "Computer scientists",
                "Bioinformaticians"
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            "id": 133,
            "name": "Introduction to image analysis using Galaxy",
            "description": "This tutorial covers the questions:\r\n- How do I use Galaxy with imaging data?\r\n- How do I convert images using Galaxy?\r\n- How do I display images in Galaxy?\r\n- How do I filter images in Galaxy?\r\n- How do I segment simple images in Galaxy?\r\n\r\nAt the end of the tutorial, learners would be able to:\r\n- How to handle images in Galaxy.\r\n- How to perform basic image processing in Galaxy.",
            "communities": [],
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            "doi": null,
            "fileLocation": "https://training.galaxyproject.org/training-material/topics/imaging/tutorials/imaging-introduction/tutorial.html",
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                "Biologists"
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            "providedBy": [],
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            "id": 144,
            "name": "Reference-based RNA-Seq data analysis with Galaxy",
            "description": "This tutorial covers the questions:\r\n- What are the steps to process RNA-Seq data?\r\n- How to identify differentially expressed genes across multiple experimental conditions?\r\n- What are the biological functions impacted by the differential expression of genes?\r\n\r\nAt the end of the tutorial, learners would be able to:\r\n- Check a sequence quality report generated by FastQC for RNA-Seq data\r\n- Explain the principle and specificity of mapping of RNA-Seq data to an eukaryotic reference genome\r\n- Select and run a state of the art mapping tool for RNA-Seq data\r\n- Evaluate the quality of mapping results\r\n- Describe the process to estimate the library strandness\r\n- Estimate the number of reads per genes\r\n- Explain the count normalization to perform before sample comparison\r\n- Construct and run a differential gene expression analysis\r\n- Analyze the DESeq2 output to identify, annotate and visualize differentially expressed genes\r\n- Perform a gene ontology enrichment analysis\r\n- Perform and visualize an enrichment analysis for KEGG pathways",
            "communities": [],
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            "fileLocation": "https://training.galaxyproject.org/training-material/topics/transcriptomics/tutorials/ref-based/tutorial.html",
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                "http://edamontology.org/topic_1775",
                "http://edamontology.org/topic_0203",
                "http://edamontology.org/topic_3170",
                "http://edamontology.org/topic_3308"
            ],
            "keywords": [
                "Galaxy",
                "RNA-seq"
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                "Graduate",
                "Professional (initial)",
                "Professional (continued)"
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                "Biologists"
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            "id": 125,
            "name": "ETBII 2023",
            "description": "All the training materials dedicated to the IFB's Integrative Bioinformatics Thematic School, which took place in January 2023.",
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                "http://edamontology.org/topic_3307"
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                "Biological network inference and analysis",
                "Multivariate analyses",
                "Semantic web",
                "Data Integration"
            ],
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                "Computer scientists",
                "Bioinformaticians"
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        {
            "id": 130,
            "name": "Taxonomic Profiling and Visualization of Metagenomic Data",
            "description": "This tutorial covers the questions:\r\n- Which species (or genera, families, …) are present in my sample?\r\n- What are the different approaches and tools to get the community profile of my sample?\r\n- How can we visualize and compare community profiles?\r\n\r\nAt the end of the tutorial, learners would be able to:\r\n- Explain what taxonomic assignment is\r\n- Explain how taxonomic assignment works\r\n- Apply Kraken and MetaPhlAn to assign taxonomic labels\r\n- Apply Krona and Pavian to visualize results of assignment and understand the output\r\n- Identify taxonomic classification tool that fits best depending on their data",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "https://training.galaxyproject.org/training-material/topics/microbiome/tutorials/taxonomic-profiling/tutorial.html",
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                "http://edamontology.org/topic_3174",
                "http://edamontology.org/topic_0637"
            ],
            "keywords": [
                "Galaxy"
            ],
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                "Undergraduate",
                "Graduate",
                "Professional (initial)",
                "Professional (continued)"
            ],
            "audienceRoles": [
                "Researchers",
                "Life scientists",
                "Biologists"
            ],
            "difficultyLevel": "Novice",
            "providedBy": [],
            "dateCreation": null,
            "dateUpdate": null,
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        },
        {
            "id": 134,
            "name": "Nucleoli segmentation and feature extraction using CellProfiler",
            "description": "This tutorial covers the following questions:\r\n- How do I run an image analysis pipeline on public data using CellProfiler?\r\n- How do I analyse the DNA channel of fluorescence siRNA screens?\r\n- How do I download public image data into my history?\r\n- How do I segment and label cell nuclei?\r\n- How do I segment nucleoli (as the absence of DNA)?\r\n- How do I combine nuclei and nucleoli into one segmentation mask?\r\n- How do I extract the background of an image?\r\n- How do I relate the nucleoli to their parent nucleus?\r\n- How do I measure the image and object features?\r\n- How do I measure the image quality?\r\n\r\nAt the end of the tutorial, learners would be able to:\r\n- How to download images from a public image repository.\r\n- How to segment cell nuclei using CellProfiler in Galaxy.\r\n- How to segment cell nucleoli using CellProfiler in Galaxy.\r\n- How to extract features for images, nuclei and nucleoli.",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "https://training.galaxyproject.org/training-material/topics/imaging/tutorials/tutorial-CP/tutorial.html",
            "fileName": "tutorial-CP",
            "topics": [
                "http://edamontology.org/topic_3383",
                "http://edamontology.org/topic_3382"
            ],
            "keywords": [
                "Galaxy"
            ],
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                "Graduate",
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            ],
            "audienceRoles": [
                "Researchers",
                "Life scientists",
                "Biologists"
            ],
            "difficultyLevel": "Novice",
            "providedBy": [],
            "dateCreation": null,
            "dateUpdate": null,
            "licence": "CC-BY-4.0",
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            ]
        },
        {
            "id": 133,
            "name": "Introduction to image analysis using Galaxy",
            "description": "This tutorial covers the questions:\r\n- How do I use Galaxy with imaging data?\r\n- How do I convert images using Galaxy?\r\n- How do I display images in Galaxy?\r\n- How do I filter images in Galaxy?\r\n- How do I segment simple images in Galaxy?\r\n\r\nAt the end of the tutorial, learners would be able to:\r\n- How to handle images in Galaxy.\r\n- How to perform basic image processing in Galaxy.",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "https://training.galaxyproject.org/training-material/topics/imaging/tutorials/imaging-introduction/tutorial.html",
            "fileName": "imaging-introduction",
            "topics": [
                "http://edamontology.org/topic_3383",
                "http://edamontology.org/topic_3382"
            ],
            "keywords": [
                "Galaxy"
            ],
            "audienceTypes": [
                "Undergraduate",
                "Graduate",
                "Professional (initial)",
                "Professional (continued)"
            ],
            "audienceRoles": [
                "Researchers",
                "Life scientists",
                "Biologists"
            ],
            "difficultyLevel": "Novice",
            "providedBy": [],
            "dateCreation": null,
            "dateUpdate": null,
            "licence": "CC-BY-4.0",
            "maintainers": [
                "https://catalogue.france-bioinformatique.fr/api/userprofile/677/"
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        },
        {
            "id": 129,
            "name": "Bacterial Genome Annotation",
            "description": "This tutorial covers the questions:\r\n- Which genes are on a draft bacterial genome?\r\n- Which other genomic components can be found on a draft bacterial genome?\r\n\r\nAt the end of the tutorial, learners would be able to:\r\n- Run a series of tools to annotate a draft bacterial genome for different types of genomic components\r\n- Evaluate the annotation\r\n- Process the outputs to format them for visualization needs\r\n- Visualize a draft bacterial genome and its annotations",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "https://training.galaxyproject.org/training-material/topics/genome-annotation/tutorials/bacterial-genome-annotation/tutorial.html",
            "fileName": "bacterial-genome-annotation",
            "topics": [
                "http://edamontology.org/topic_3301",
                "http://edamontology.org/topic_0219"
            ],
            "keywords": [
                "Bacterial isolate",
                "Annotation",
                "Galaxy"
            ],
            "audienceTypes": [
                "Undergraduate",
                "Graduate",
                "Professional (initial)",
                "Professional (continued)"
            ],
            "audienceRoles": [
                "Researchers",
                "Life scientists",
                "Biologists"
            ],
            "difficultyLevel": "Novice",
            "providedBy": [],
            "dateCreation": null,
            "dateUpdate": null,
            "licence": "CC-BY-4.0",
            "maintainers": [
                "https://catalogue.france-bioinformatique.fr/api/userprofile/677/"
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        },
        {
            "id": 127,
            "name": "Quality Control with Galaxy",
            "description": "This tutorial covers the questions:\r\n- How to perform quality control of NGS raw data?\r\n- What are the quality parameters to check for a dataset?\r\n- How to improve the quality of a dataset?\r\n\r\nAt the end of the tutorial, learners would be able to:\r\n- Assess short reads FASTQ quality using FASTQE 🧬😎 and FastQC\r\n- Assess long reads FASTQ quality using Nanoplot and PycoQC\r\n- Perform quality correction with Cutadapt (short reads)\r\n-  Summarise quality metrics MultiQC\r\n- Process single-end and paired-end data",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "https://training.galaxyproject.org/training-material/topics/sequence-analysis/tutorials/quality-control/tutorial.html",
            "fileName": "quality-control",
            "topics": [
                "http://edamontology.org/topic_3168",
                "http://edamontology.org/topic_0091"
            ],
            "keywords": [
                "Quality Control"
            ],
            "audienceTypes": [
                "Graduate",
                "Professional (initial)",
                "Professional (continued)"
            ],
            "audienceRoles": [
                "Researchers",
                "Life scientists",
                "Biologists"
            ],
            "difficultyLevel": "Novice",
            "providedBy": [],
            "dateCreation": null,
            "dateUpdate": null,
            "licence": "CC-BY-4.0",
            "maintainers": [
                "https://catalogue.france-bioinformatique.fr/api/userprofile/677/"
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        },
        {
            "id": 132,
            "name": "Metatranscriptomics analysis using microbiome RNA-seq data",
            "description": "This tutorial covers the questions:\r\n- How to analyze metatranscriptomics data?\r\n- What information can be extracted of metatranscriptomics data?\r\n- How to assign taxa and function to the identified sequences?\r\n\r\nAt the end of the tutorial, learners would be able to:\r\n- Choose the best approach to analyze metatranscriptomics data\r\n- Understand the functional microbiome characterization using metatranscriptomic results\r\n- Understand where metatranscriptomics fits in ‘multi-omic’ analysis of microbiomes\r\n- Visualise a community structure",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "https://training.galaxyproject.org/training-material/topics/microbiome/tutorials/metatranscriptomics/tutorial.html",
            "fileName": "metatranscriptomics",
            "topics": [
                "http://edamontology.org/topic_3941",
                "http://edamontology.org/topic_1775"
            ],
            "keywords": [
                "Galaxy"
            ],
            "audienceTypes": [
                "Undergraduate",
                "Graduate",
                "Professional (initial)",
                "Professional (continued)"
            ],
            "audienceRoles": [
                "Researchers",
                "Life scientists",
                "Biologists"
            ],
            "difficultyLevel": "Novice",
            "providedBy": [],
            "dateCreation": null,
            "dateUpdate": null,
            "licence": "CC-BY-4.0",
            "maintainers": [
                "https://catalogue.france-bioinformatique.fr/api/userprofile/677/"
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        },
        {
            "id": 128,
            "name": "Mapping with Galaxy",
            "description": "This tutorial covers the questions:\r\n- What is mapping?\r\n- What two things are crucial for a correct mapping?\r\n- What is BAM?\r\n\r\nAt the end of the tutorial, learners would be able to:\r\n- Define what mapping is\r\n- Perform mapping of reads on a reference genome\r\n- Evaluate the mapping output",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "https://training.galaxyproject.org/training-material/topics/sequence-analysis/tutorials/mapping/tutorial.html",
            "fileName": "mapping",
            "topics": [
                "http://edamontology.org/topic_0102"
            ],
            "keywords": [
                "Mapping"
            ],
            "audienceTypes": [
                "Undergraduate",
                "Graduate",
                "Professional (initial)",
                "Professional (continued)"
            ],
            "audienceRoles": [
                "Researchers",
                "Life scientists",
                "Biologists"
            ],
            "difficultyLevel": "Novice",
            "providedBy": [],
            "dateCreation": null,
            "dateUpdate": null,
            "licence": "CC-BY-4.0",
            "maintainers": [
                "https://catalogue.france-bioinformatique.fr/api/userprofile/677/"
            ]
        },
        {
            "id": 146,
            "name": "Processing_large_files_with_sed_awk_2024",
            "description": "This “Sed and AWK to modify large text files” training session is organized by the Genotoul bioinfo platform.\r\n\r\nThe Linux sed command is a powerful and very fast text editor without an interface. Sed can select, substitute, add, delete, and modify text in files and streams. Sed relies heavily on regular expressions for pattern matching and text selection. We’ll manipulate regexes and the sed command to modify and filter several type of file often used in bioinformatics.\r\n\r\nAWK enables to easily process columns in large text files but is also a quite powerfull programming language. This training session aims at introducing you AWK principles. You will learn about variables, operators and functions useful to manipulate very large files. \r\n\r\nFor example you can use AWK to generate your unix command lines to be launched on the cluster. AWK enables to process millions of lines in text files. The course includes short feature presentations between long hands-on sessions in which you will be able to understand the global ideas as well as details.",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "https://web-genobioinfo.toulouse.inrae.fr/~klopp/SedAwk2024/Processing_large_files_with_sed_awk_2024.pdf",
            "fileName": "Processing_large_files_with_sed_awk_2024.pdf",
            "topics": [],
            "keywords": [],
            "audienceTypes": [
                "Professional (continued)"
            ],
            "audienceRoles": [
                "Biologists",
                "Bioinformaticians"
            ],
            "difficultyLevel": "Intermediate",
            "providedBy": [
                {
                    "id": 22,
                    "name": "Genotoul-bioinfo",
                    "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-bioinfo/"
                }
            ],
            "dateCreation": null,
            "dateUpdate": "2024-03-01",
            "licence": null,
            "maintainers": [
                "https://catalogue.france-bioinformatique.fr/api/userprofile/300/"
            ]
        },
        {
            "id": 131,
            "name": "16S Microbial Analysis with mothur",
            "description": "This tutorial covers the questions:\r\n- What is the effect of normal variation in the gut microbiome on host health?\r\n\r\nAt the end of the tutorial, learners would be able to:\r\n- Analyze of 16S rRNA sequencing data using the mothur toolsuite in Galaxy\r\n- Using a mock community to assess the error rate of your sequencing experiment\r\n- Visualize sample diversity using Krona and Phinch",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "https://training.galaxyproject.org/training-material/topics/microbiome/tutorials/mothur-miseq-sop-short/tutorial.html",
            "fileName": "mothur-miseq-sop-short",
            "topics": [
                "http://edamontology.org/topic_3697",
                "http://edamontology.org/topic_0637"
            ],
            "keywords": [
                "Galaxy",
                "Metabarcoding"
            ],
            "audienceTypes": [
                "Undergraduate",
                "Graduate",
                "Professional (initial)",
                "Professional (continued)"
            ],
            "audienceRoles": [
                "Researchers",
                "Life scientists",
                "Biologists"
            ],
            "difficultyLevel": "Novice",
            "providedBy": [],
            "dateCreation": null,
            "dateUpdate": null,
            "licence": "CC-BY-4.0",
            "maintainers": [
                "https://catalogue.france-bioinformatique.fr/api/userprofile/677/"
            ]
        },
        {
            "id": 145,
            "name": "Introduction to Transcriptomics",
            "description": "This slidedecks presents the concepts behind transcriptomics",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "https://training.galaxyproject.org/training-material/topics/transcriptomics/tutorials/introduction/slides.html",
            "fileName": "transcriptomics-introduction",
            "topics": [
                "http://edamontology.org/topic_0203",
                "http://edamontology.org/topic_3170",
                "http://edamontology.org/topic_3308"
            ],
            "keywords": [
                "RNA-seq",
                "Transcriptomics (RNA-seq)"
            ],
            "audienceTypes": [
                "Undergraduate",
                "Graduate",
                "Professional (initial)",
                "Professional (continued)"
            ],
            "audienceRoles": [
                "Researchers",
                "Life scientists",
                "Biologists"
            ],
            "difficultyLevel": "Novice",
            "providedBy": [],
            "dateCreation": null,
            "dateUpdate": null,
            "licence": "CC-BY-4.0",
            "maintainers": [
                "https://catalogue.france-bioinformatique.fr/api/userprofile/677/"
            ]
        },
        {
            "id": 144,
            "name": "Reference-based RNA-Seq data analysis with Galaxy",
            "description": "This tutorial covers the questions:\r\n- What are the steps to process RNA-Seq data?\r\n- How to identify differentially expressed genes across multiple experimental conditions?\r\n- What are the biological functions impacted by the differential expression of genes?\r\n\r\nAt the end of the tutorial, learners would be able to:\r\n- Check a sequence quality report generated by FastQC for RNA-Seq data\r\n- Explain the principle and specificity of mapping of RNA-Seq data to an eukaryotic reference genome\r\n- Select and run a state of the art mapping tool for RNA-Seq data\r\n- Evaluate the quality of mapping results\r\n- Describe the process to estimate the library strandness\r\n- Estimate the number of reads per genes\r\n- Explain the count normalization to perform before sample comparison\r\n- Construct and run a differential gene expression analysis\r\n- Analyze the DESeq2 output to identify, annotate and visualize differentially expressed genes\r\n- Perform a gene ontology enrichment analysis\r\n- Perform and visualize an enrichment analysis for KEGG pathways",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "https://training.galaxyproject.org/training-material/topics/transcriptomics/tutorials/ref-based/tutorial.html",
            "fileName": "rna-seq",
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                "http://edamontology.org/topic_0102",
                "http://edamontology.org/topic_1775",
                "http://edamontology.org/topic_0203",
                "http://edamontology.org/topic_3170",
                "http://edamontology.org/topic_3308"
            ],
            "keywords": [
                "Galaxy",
                "RNA-seq"
            ],
            "audienceTypes": [
                "Undergraduate",
                "Graduate",
                "Professional (initial)",
                "Professional (continued)"
            ],
            "audienceRoles": [
                "Researchers",
                "Life scientists",
                "Biologists"
            ],
            "difficultyLevel": "Novice",
            "providedBy": [],
            "dateCreation": null,
            "dateUpdate": null,
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            "maintainers": [
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        },
        {
            "id": 146,
            "name": "Processing_large_files_with_sed_awk_2024",
            "description": "This “Sed and AWK to modify large text files” training session is organized by the Genotoul bioinfo platform.\r\n\r\nThe Linux sed command is a powerful and very fast text editor without an interface. Sed can select, substitute, add, delete, and modify text in files and streams. Sed relies heavily on regular expressions for pattern matching and text selection. We’ll manipulate regexes and the sed command to modify and filter several type of file often used in bioinformatics.\r\n\r\nAWK enables to easily process columns in large text files but is also a quite powerfull programming language. This training session aims at introducing you AWK principles. You will learn about variables, operators and functions useful to manipulate very large files. \r\n\r\nFor example you can use AWK to generate your unix command lines to be launched on the cluster. AWK enables to process millions of lines in text files. The course includes short feature presentations between long hands-on sessions in which you will be able to understand the global ideas as well as details.",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "https://web-genobioinfo.toulouse.inrae.fr/~klopp/SedAwk2024/Processing_large_files_with_sed_awk_2024.pdf",
            "fileName": "Processing_large_files_with_sed_awk_2024.pdf",
            "topics": [],
            "keywords": [],
            "audienceTypes": [
                "Professional (continued)"
            ],
            "audienceRoles": [
                "Biologists",
                "Bioinformaticians"
            ],
            "difficultyLevel": "Intermediate",
            "providedBy": [
                {
                    "id": 22,
                    "name": "Genotoul-bioinfo",
                    "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-bioinfo/"
                }
            ],
            "dateCreation": null,
            "dateUpdate": "2024-03-01",
            "licence": null,
            "maintainers": [
                "https://catalogue.france-bioinformatique.fr/api/userprofile/300/"
            ]
        },
        {
            "id": 125,
            "name": "ETBII 2023",
            "description": "All the training materials dedicated to the IFB's Integrative Bioinformatics Thematic School, which took place in January 2023.",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "https://moodle.france-bioinformatique.fr/course/view.php?id=13",
            "fileName": "ETBII 2023 Training materials",
            "topics": [
                "http://edamontology.org/topic_3316",
                "http://edamontology.org/topic_3474",
                "http://edamontology.org/topic_3391",
                "http://edamontology.org/topic_3365",
                "http://edamontology.org/topic_0092",
                "http://edamontology.org/topic_2269",
                "http://edamontology.org/topic_0091",
                "http://edamontology.org/topic_3307"
            ],
            "keywords": [
                "Biological network inference and analysis",
                "Multivariate analyses",
                "Semantic web",
                "Data Integration"
            ],
            "audienceTypes": [
                "Professional (initial)"
            ],
            "audienceRoles": [
                "Life scientists",
                "Computer scientists",
                "Bioinformaticians"
            ],
            "difficultyLevel": "Novice",
            "providedBy": [
                {
                    "id": 29,
                    "name": "IFB Core",
                    "url": "https://catalogue.france-bioinformatique.fr/api/team/IFB%20Core/"
                }
            ],
            "dateCreation": null,
            "dateUpdate": null,
            "licence": null,
            "maintainers": [
                "https://catalogue.france-bioinformatique.fr/api/userprofile/762/"
            ]
        },
        {
            "id": 119,
            "name": "Visualization of NGS data with IGV",
            "description": "Visualisation of next-gen sequencing data with Integrative Genomics Viewer\n",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "http://ecole-bioinfo-aviesan.sb-roscoff.fr/sites/ecole-bioinfo-aviesan.sb-roscoff.fr/files/files/IGV-Roscoff-Septembre2015.pdf",
            "fileName": "missing.txt",
            "topics": [],
            "keywords": [
                "genomics",
                "Data visualization",
                "NGS"
            ],
            "audienceTypes": [],
            "audienceRoles": [],
            "difficultyLevel": "",
            "providedBy": [],
            "dateCreation": null,
            "dateUpdate": null,
            "licence": null,
            "maintainers": []
        },
        {
            "id": 120,
            "name": "Initiation to Galaxy",
            "description": "DNA-sequence analysis: from raw reads to variants calling within the galaxy environement.\n",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "http://ecole-bioinfo-aviesan.sb-roscoff.fr/sites/ecole-bioinfo-aviesan.sb-roscoff.fr/files/files/GALAXY-TP-INITIATION-Roscoff-Septembre2015.pdf",
            "fileName": "missing.txt",
            "topics": [],
            "keywords": [
                "DNA Analysis",
                "Variant calling",
                "Galaxy"
            ],
            "audienceTypes": [],
            "audienceRoles": [],
            "difficultyLevel": "",
            "providedBy": [],
            "dateCreation": null,
            "dateUpdate": null,
            "licence": null,
            "maintainers": []
        },
        {
            "id": 106,
            "name": "Genomic copy number Tutorial",
            "description": "We will analyze the copy number variations of a human tumor (parotid gland carcinoma), limited to the chr17, from a WES (whole-exome sequencing) experiment. All genomic coordinates correspond to the 2009 build of the reference human genome (hg19 / GRC37).\n",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "http://ecole-bioinfo-aviesan.sb-roscoff.fr/sites/ecole-bioinfo-aviesan.sb-roscoff.fr/files/files/CNV_TD_guidelines_BJ.pdf",
            "fileName": "missing.txt",
            "topics": [],
            "keywords": [
                "Structural genomics",
                "Copy number"
            ],
            "audienceTypes": [],
            "audienceRoles": [],
            "difficultyLevel": "",
            "providedBy": [],
            "dateCreation": null,
            "dateUpdate": null,
            "licence": null,
            "maintainers": []
        }
    ]
}