Training Material List
Handles creating, reading and updating training materials.
GET /api/trainingmaterial/?format=api&offset=140&ordering=maintainers
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For these situations Galaxy offers the option to create visualizations plugins, file format specific javascripts that integrate with the history menu, without making redundant copies of data.\nIn this tutorial we shall go through how this system works and create a simple visualization plugin. The tool will create a visualization of the number of aligned reads per chromosome of a BAM file, and we will discuss possible optimizations and advantages and disadvantages of the proposed implementation.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://galaxyproject.github.io/training-material/Dev-Corner/tutorials/visualizations", "fileName": "missing.txt", "topics": [], "keywords": [ "Galaxy" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2017-01-18", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/690/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/691/?format=api" ] }, { "id": 45, "name": "Galaxy Visualisation - Slides", "description": "Questions\n\n\n\tHow can visualization plugins benefit science?\n\n\n\nObjectives\n\n\n\tImplement a first Galaxy visualization\n\tUnderstand the client side vs. server side principle\n\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://galaxyproject.github.io/training-material/Dev-Corner/slides/visualizations.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Galaxy" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2017-01-18", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/690/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/691/?format=api" ] }, { "id": 44, "name": "Galaxy Visualisation - Tutorial", "description": "Visualizations may be very helpful in understanding data better. There is a whole range of visualizations, from rather simple scatter and barplots up to projections of high dimensional data or even entire genomes. Many of these visualizations often require a lot of tweaking and changes in settings like zooming in and assigning colors, etc. Therefore, visualizations are ideally interactive, and changing settings is often an initial step in exploring data. For this reason it may be inconvenient to make use of static galaxy tools because it lacks these interactive features. For these situations Galaxy offers the option to create visualizations plugins, file format specific javascripts that integrate with the history menu, without making redundant copies of data.\nIn this tutorial we shall go through how this system works and create a simple visualization plugin. The tool will create a visualization of the number of aligned reads per chromosome of a BAM file, and we will discuss possible optimizations and advantages and disadvantages of the proposed implementation.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://galaxyproject.github.io/training-material/Dev-Corner/tutorials/visualizations", "fileName": "missing.txt", "topics": [], "keywords": [ "Galaxy" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2017-01-18", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/690/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/691/?format=api" ] }, { "id": 56, "name": "RADSeq Data Analysis", "description": "Introduction to RADSeq through STACKS on Galaxy\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/V08_Yvan%20Le%20Bras%20-%20Training%20RADSeq_0.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "NGS" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-11-23", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/692/?format=api" ] }, { "id": 59, "name": "Variant annotation", "description": "Add meta-information on variant to facilitate interpretation\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/V06_variants_annotation.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "Variant analysis" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-11-23", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/693/?format=api" ] }, { "id": 63, "name": "Variant Filtering", "description": "Use cases:\nExtact a subset of variants\nCombine variants from several analysis\n\nCompare obtained variants from several data types\n\n\nIdentify new variants compare to a reference list\n\n\nApply specific filters for Chip Design\n\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://ecole-bioinfo-aviesan.sb-roscoff.fr/sites/ecole-bioinfo-aviesan.sb-roscoff.fr/files/files/FiltrageVariantNLapaluRoscoff2015.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "genomics", "Variant calling", "NGS" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/694/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/719/?format=api" ] }, { "id": 65, "name": "Chip-seq Analysis", "description": "Quality, normalisation and peak calling\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/C01_ChIP_SEQ_EBA_2016-11-22.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "genomics", "Chip-Seq" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-11-22", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/695/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/696/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/697/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/698/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/512/?format=api" ] }, { "id": 65, "name": "Chip-seq Analysis", "description": "Quality, normalisation and peak calling\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/C01_ChIP_SEQ_EBA_2016-11-22.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "genomics", "Chip-Seq" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-11-22", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/695/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/696/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/697/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/698/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/512/?format=api" ] }, { "id": 65, "name": "Chip-seq Analysis", "description": "Quality, normalisation and peak calling\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/C01_ChIP_SEQ_EBA_2016-11-22.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "genomics", "Chip-Seq" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-11-22", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/695/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/696/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/697/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/698/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/512/?format=api" ] }, { "id": 113, "name": "Chip Seq: Annotation and visualization Tutorial", "description": "Global Objective\nGiven a set of ChIP-seq peaks annotate them in order to find associated genes, genomic categories and functional terms.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://dputhier.github.io/EBA_2015_ChIP-Seq/tutorial/02_annotation/annotation.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Chip-Seq", "Data visualization", "Annotation", "NGS" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/662/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/698/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/644/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/624/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/720/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/512/?format=api" ] }, { "id": 65, "name": "Chip-seq Analysis", "description": "Quality, normalisation and peak calling\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/C01_ChIP_SEQ_EBA_2016-11-22.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "genomics", "Chip-Seq" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-11-22", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/695/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/696/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/697/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/698/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/512/?format=api" ] }, { "id": 114, "name": "Chip Seq: Annotation and visualization Lesson", "description": "How to add biological meaning to peaks\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://dputhier.github.io/EBA_2015_ChIP-Seq/slides/ChIP-seq_annotation_MD_2015.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "Chip-Seq", "Data visualization", "Annotation", "NGS" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/662/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/698/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/644/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/624/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/720/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/512/?format=api" ] }, { "id": 115, "name": "Chip-seq: Pattern Analysis tutorial", "description": "Goal\nThe aim is to :\nGet familiar with motif analysis of ChIP-seq data.\nLearn de novo motif discovery methods.\nIn practice :\nMotif discovery with peak-motifs\nDifferential analysis\nRandom controls\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://dputhier.github.io/EBA_2015_ChIP-Seq/tutorial/04_motif/motif_tutorial.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Chip-Seq", "Pattern recognition", "NGS" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/662/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/698/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/644/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/624/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/721/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/512/?format=api" ] }, { "id": 117, "name": "Chip-seq: Peak calling tutorial", "description": "The aim is to :\nUnderstand how to process reads to obtain peaks (peak-calling).\nBecome familiar with differential analysis of peaks\nIn practice :\nObtain dataset from GEO\nAnalyze mapped reads\nObtain set(s) of peaks, handle replicates\nDifferential analysis of peak\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://dputhier.github.io/EBA_2015_ChIP-Seq/tutorial/01_peak_calling/peak_calling_tutorial.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Chip-Seq", "Peak calling", "NGS" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/698/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/644/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/721/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/512/?format=api" ] }, { "id": 68, "name": "Third generation sequencing : the revolution of long reads", "description": "Introduction on sequencing: available technologies, library types, applications ...\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://www.france-bioinformatique.fr/sites/default/files/I02_Thermes_ROSCOFF5.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "genomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-11-21", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/699/?format=api" ] }, { "id": 69, "name": "New perspectives on nitrite-oxidizing bacteria - linking genomes to physiology", "description": "It is a generally accepted characteristic of the biogeochemical nitrogen cycle that nitrification is catalyzed by two distinct clades of microorganisms. First, ammonia-oxidizing bacteria and archaea convert ammonia to nitrite, which subsequently is oxidized to nitrate by nitrite-oxidizing bacteria (NOB). The latter were traditionally perceived as physiologically restricted organisms and were less intensively studied than other nitrogen-cycling microorganisms. This picture is contrasted by new discoveries of an unexpected high diversity of mostly uncultured NOB and a great physiological versatility, which includes complex microbe-microbe interactions and lifestyles outside the nitrogen cycle. Most surprisingly, close relatives to NOB perform complete nitrification (ammonia oxidation to nitrate), a process that had been postulated to occur under conditions selecting for low growth rates but high growth yields.\nThe existence of Nitrospira species that encode all genes required for ammonia and nitrite oxidation was first detected by metagenomic analyses of an enrichment culture for nitrogen-transforming microorganisms sampled from the anoxic compartment of a recirculating aquaculture system biofilter. Batch incubations and FISH-MAR experiments showed that these Nitrospira indeed formed nitrate from the aerobic oxidation of ammonia, and used the energy derived from complete nitrification for carbon fixation, thus proving that they indeed represented the long-sought-after comammox organisms. Their ammonia monooxygenase (AMO) enzymes were distinct from canonical AMOs, therefore rendering recent horizontal gene transfer from known ammonia-oxidizing microorganisms unlikely. Instead, their AMO displayed highest similarities to the “unusual” particulate methane monooxygenase from Crenothrix polyspora, thus shedding new light onto the function of this sequence group. This recognition of a novel AMO type indicates that a whole group of ammonia-oxidizing microorganisms has been overlooked, and will improve our understanding of the environmental abundance and distribution of this functional group. Data mining of publicly available metagenomes already indicated a widespread occurrence in natural and engineered environments like aquifers and paddy soils, and drinking and wastewater treatment systems.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_8/New_perspectives_on_nitrite_xidizing_bacteria/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-12-16", "dateUpdate": null, "licence": "CC BY-NC-ND", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/700/?format=api" ] }, { "id": 70, "name": "Revealing and analyzing microbial networks: from topology to functional behaviors", "description": "Understanding the interactions between microbial communities and their environment well enough to be able to predict diversity on the basis of physicochemical parameters is a fundamental pursuit of microbial ecology that still eludes us. However, modeling microbial communities is a complicated task, because (i) communities are complex, (ii) most are described qualitatively, and (iii) quantitative understanding of the way communities interacts with their surroundings remains incomplete. Within this seminar, we will illustrate two complementary approaches that aim to overcome these points in different manners.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_8/Revealing_and_analyzing%20microbial_networks_from_topology_to_functional_behaviors/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-12-16", "dateUpdate": null, "licence": "CC BY-NC-ND", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/701/?format=api" ] }, { "id": 71, "name": "Holistic metagenomics in marine communities", "description": "Complex microscopic communities are composed of species belonging to all life realms, from single-cell prokaryotes to multicellular eukaryotes of small size. Each component of a community needs to be studied for a full understanding of the functions performed by the whole assemblage, however methods to investigate microbiomes are generally restricted to a single kingdom. Using examples from the Tara Oceans project, we will show how size fractionation and use of varied metabarcoding, metagenomics and metatranscriptomics approaches can help studying the marine plankton community as a whole, in a wide geographic space.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_7/Holistic_metagenomics_in_marine_communities/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-12-16", "dateUpdate": null, "licence": "CC BY-NC-ND", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/702/?format=api" ] }, { "id": 72, "name": "Hidden in the permafrost", "description": "The last decade witnessed the discovery of four families of giant viruses infecting Acanthamoeba. They have genome encoding from 500 to 2000 genes, a large fraction of which encoding proteins of unknown origin. These unique proteins meant to recognize and manipulate the same building blocks as cells raise the question on their origin as well as the role viruses played in the cellular word evolution. The Mimiviridae and the Pandoraviridae are increasingly populated by members from very diverse habitats and are ubiquitous on the planet. After prospecting the space, we went back in the past and isolated two other giant virus families from a 30,000 years old permafrost sample, Pithovirus and Mollivirus sibericum. A metagenomics study of the sample was performed to inventory its biodiversity and assess to what extend the host and the viruses were dominant. I will describe the two sequencing approaches which have been used and compare the results.\n1: Raoult D, Audic S, Robert C, Abergel C, Renesto P, Ogata H, La Scola B, Suzan M, Claverie JM. The 1.2-megabase genome sequence of Mimivirus. Science. 2004 Nov 19;306(5700):1344-50.\n2: Philippe N, Legendre M, Doutre G, Couté Y, Poirot O, Lescot M, Arslan D, Seltzer V, Bertaux L, Bruley C, Garin J, Claverie JM, Abergel C. Pandoraviruses: amoeba viruses with genomes up to 2.5 Mb reaching that of parasitic eukaryotes. Science. 2013 Jul 19;341(6143):281-6. \n3: Legendre M, Bartoli J, Shmakova L, Jeudy S, Labadie K, Adrait A, Lescot M, Poirot O, Bertaux L, Bruley C, Couté Y, Rivkina E, Abergel C, Claverie JM. Thirty-thousand-year-old distant relative of giant icosahedral DNA viruses with a pandoravirus morphology. Proc Natl Acad Sci U S A. 2014 Mar 18;111(11):4274-9.\n4: Legendre M, Lartigue A, Bertaux L, Jeudy S, Bartoli J, Lescot M, Alempic JM, Ramus C, Bruley C, Labadie K, Shmakova L, Rivkina E, Couté Y, Abergel C, Claverie JM. In-depth study of Mollivirus sibericum, a new 30,000-y-old giant virus infecting Acanthamoeba. Proc Natl Acad Sci U S A. 2015 Sep 22;112(38):E5327-35.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_7/Hidden_in_permafrost/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-12-16", "dateUpdate": null, "licence": "CC BY-NC-ND", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/703/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/123/?format=api" ] }, { "id": 73, "name": "200 billion sequences and counting: analysis, discovery and exploration of datasets with EBI Metagenomics", "description": "EBI metagenomics (EMG, https://www.ebi.ac.uk/metagenomics/) is a freely available hub for the analysis and exploration of metagenomic, metatranscriptomic, amplicon and assembly data. The resource provides rich functional and taxonomic analyses of user-submitted sequences, as well as analysis of publicly available metagenomic datasets held within the European Nucleotide Archive (ENA). EMG has recently undergone rapid expansion, with an over 10-fold increase in data volumes in the first 5 months of 2016. It now houses ~ 50k publicly available data sets, and represents one of the largest collections of analysed metagenomic data. As its data content has grown, EMG has increasingly become a platform for data discovery. To support this process, we have made a series of user-interface improvements, including the classification of projects by biome, presentation of results data for better visualisation and more convenient download, and provision of project level summary files. More recently, we have indexed project metadata for use with the EBI search engine, enabling exploration across different datasets. For example, users are able to search with a particular taxonomic lineage or protein function and discover the projects, samples and sequencing runs in which that lineage or function is found. This functionality allows users to explore associations between biomes, environmental conditions and organisms and functions (e.g., discovering protein coding sequences that correspond to certain enzyme families found in aquatic environments at a given temperature range). Here, we give an overview of the EMG data analysis pipeline and web site, and illustrate the use of the new search facility for data discovery.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_7/200_billions_sequences_and_counting_discovery_and_exploration_of_datasets_with_EBI_metagenomics/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-12-16", "dateUpdate": null, "licence": "CC BY-NC-ND", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/704/?format=api" ] } ] }