Training Material List
Handles creating, reading and updating training materials.
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{ "count": 144, "next": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/?format=api&limit=20&offset=140&ordering=-licence", "previous": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/?format=api&limit=20&offset=100&ordering=-licence", "results": [ { "id": 84, "name": "Who is doing what on the cheese surface? Overview of the cheese microbial ecosystem functioning by metatranscriptomic analyses", "description": "Cheese ripening is a complex biochemical process driven by microbial communities composed of both eukaryotes and prokaryotes. Surface-ripened cheeses are widely consumed all over the world and are appreciated for their characteristic flavor. Microbial community composition has been studied for a long time on surface-ripened cheeses, but only limited knowledge has been acquired about its in situ metabolic activities. We used an iterative sensory procedure to select a simplified microbial consortium, composed of only nine species (three yeasts and six bacteria), producing the odor of Livarot-type cheese when inoculated in a sterile cheese curd. All the genomes were sequenced in order to determine the functional capacities of the different species and facilitate RNA-Seq data analyses. We followed the ripening process of experimental cheeses made using this consortium during four weeks, by metatranscriptomic and biochemical analyses. By combining all of the data, we were able to obtain an overview of the cheese maturation process and to better understand the metabolic activities of the different community members and their possible interactions. We next applied the same approach to investigate the activity of the microorganisms in real cheeses, namely Reblochon-style cheeses. This provided useful insights into the physiological changes that occur during cheese ripening, such as changes in energy substrates, anabolic reactions, or stresses.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_2/Who_is_doing_what_on_the_cheese_surface_Overview_of_the_cheese%20microbial_ecosystem_functioning_by_metatranscriptomic_analyses/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-12-15", "dateUpdate": null, "licence": "CC BY-NC-ND", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/710/?format=api" ] }, { "id": 85, "name": "Exploiting collisions between DNA molecules to characterize the genomic structures of complex communities", "description": "Meta3C is an experimental and computational approach that exploits the physical contacts experienced by DNA molecules sharing the same cellular compartments. These collisions provide a quantitative information that allows interpreting and phasing the genomes present within complex mixes of species without prior knowledge. Not only the exploitation of chromosome physical 3D signatures hold interesting premises regarding solving the genome sequences from discrete species, but it also allows assigning mobile elements such as plasmids or phages to their hosts.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_2/Exploiting_collisions_between_DNA_molecules_to_characterize_the_genomic_structures_of_complex_communities/scormcontent/", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-12-15", "dateUpdate": null, "licence": "CC BY-NC-ND", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/711/?format=api" ] }, { "id": 86, "name": "Gut metagenomics in cardiometabolic diseases", "description": "Cardio-metabolic and Nutrition-related diseases (CMDs) represent an enormous burden for health care. They are characterized by very heterogeneous phenotypes progressing with time. It is virtually impossible to predict who will or will not develop cardiovascular comorbidities. There is a clear need to intervene earlier in the natural cycle of the disease, before irreversible tissue damages develop. Predictive tools still remain elusive and environmental factors (food, nutrition, physical activity and psychosocial factors) play major roles in the development of these interrelated pathologies. Poor nutritional environment and lifestyle also promote health deterioration resulting in CMD progression. In the last few years, the characterization of the gut microbiome (i.e. collective bacteria genome) and gut-derived molecules (i.e. metabolites, lipids, inflammatory molecules) has opened up new avenues for the generation of fundamental knowledge regarding putative shared pathways in CMD. The gut microbiome is likely to have an even greater impact than genetic factors given its close relationship with environmental factors. In metabolic disorders, the discoveries that low bacterial gene richness associates with cardiovascular risks stimulate encourage these developments. Due to the complexity of the gut microbiome, and its interactions with human (host) metabolism as well as with the immune system, it is only through integrative analyses where metabolic network models are used as scaffold for analysis that it will be possible to identify markers and shared pathways, which will contribute to improve patient stratification and develop new modes of patient care.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_2/Gut_metagenomics_in_cardiometabolic_diseases/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-12-15", "dateUpdate": null, "licence": "CC BY-NC-ND", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/712/?format=api" ] }, { "id": 87, "name": "Deciphering the human intestinal tract microbiome using metagenomic computational methods", "description": "In 2010, the MetaHIT consortium published a 3.3M microbiota gene catalog generated by whole genome shotgun metagenomic sequencing, representing a mixture of bacteria, archaea, parasites and viruses coming from 124 human stool metagenomic samples [Qin et al, Nature 2010].\nHowever most of the genes were fragmented, taxonomically and functionally unknown, making it difficult to define and select biomarkers of interest for genome-wide association studies.\nSince that, this human gene catalog was improved multiple times, with the last update by [Li et al, Nature Biotechnology, 2014], which generated a 10M gene catalog using more than 1000 metagenomic samples and including some prevalent human microbe genome available at that time. Along with the catalog update, the scientific community developed new tools to challenge the complexity of this dataset and provided new ways to assemble, annotate, quantify and classify the genes coming from these catalogs.\nIn this talk we will discuss the main approaches related to the computational treatment of the different gene catalog other the time, illustrated by the different papers that deciphered step by step the hidden information of our microbiota and his link with our health.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_1/Deciphering_the_human_intestinal_tract_microbiome_using_metagenomic_computational_methods/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-12-15", "dateUpdate": null, "licence": "CC BY-NC-ND", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/713/?format=api" ] }, { "id": 88, "name": "From Samples to Data : Assuring Downstream Analysis with Upstream Planning", "description": "Metagenomic studies have gained increasing popularity in the years since the introduction of next generation sequencing. NGS allows for the production of millions of reads for each sample without the intermediate step of cloning. However, just as in the past, the quality of the data generate by this powerful technology depends on sample preparation, library construction and the selection of appropriate sequencing technology and sequencing depth. Here we explore the different variables involved in the process of preparing samples for sequencing analysis including sample collection, DNA extraction and library construction. We also examine the various sequencing technologies deployed for routine metagenomic analysis and considerations for their use in different model systems including humans, mouse and the environment. Future developments such as long-reads will also be discussed to provide a complete picture of important aspects prior to data analyses which play a critical role in the success of metagenomic studies.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_1/From_Samples_to_Data_Assuring_Downstream_Analysis_with_Upstream_Planning/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CC BY-NC-ND", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/714/?format=api" ] }, { "id": 30, "name": "Welcome message", "description": "Presentation of the workshop (Chairman: Claudine Médigue)\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_1/welcome_message/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics", "biohackaton" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-12-15", "dateUpdate": null, "licence": "CC BY-NC-ND", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/187/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/664/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/431/?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" ] }, { "id": 74, "name": " MG-RAST - experiences from processing a quarter million metagenomic data sets", "description": "MG-RAST has been offering metagenomic analyses since 2007. Over 20,000 researchers have submitted data. I will describe the current MG-RAST implementation and demonstrate some of its capabilities. In the course of the presentation I will highlight several metagenomic pitfalls. MG-RAST: http://metagenomics.anl.gov MG-RAST-APP: http://api.metagenomics.anl.gov/api.html\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_6/MG_RSAT/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/705/?format=api" ] }, { "id": 75, "name": "Fast filtering, mapping and assembly of 16S ribosomal RNA", "description": "The application of next-generation sequencing technologies to RNA or DNA directly extracted from a community of organisms yields a mixture of nucleotide fragments. The task to distinguish amongst these and to further categorize the families of ribosomal RNAs (or any other given marker) is an important step for examining the phylogenetic classification of the constituting species. In this perspective, we have developed a complete bioinformatics suite, called MATAM, capable of handling large sets of reads in a fast and accurate way. MATAM covers all steps of the analysis, from the identification of reads of interest in the raw sequencing data to the reconstruction of the full-length sequences of the marker and alignment to a reference database for taxonomic assignment. Part of MATAM is based on the SortMeRNA software, also developed by the team.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_6/Fast_filtering_mapping_and_assembly_of_16S_rRNA/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/610/?format=api" ] }, { "id": 76, "name": " Reconstructing genomes from metagenomes: The holy grail of microbiology", "description": "Shotgun metagenomics provides insights into a larger context of naturally occurring microbial genomes when short reads are assembled into contiguous DNA segments (contigs). Contigs are often orders of magnitude longer than individual sequences, offering improved annotations, and key information about the organization of genes in cognate genomes. Several factors affect the assembly performance, and the feasibility of the assembly-based approaches varies across environments. However, increasing read lengths, novel experimental approaches, advances in computational tools and resources, and improvements in assembly algorithms and pipelines render the assembly-based metagenomic workflow more and more accessible. The utility of metagenomic assembly remarkably increases when contigs are organized into metagenome-assembled genomes (MAGs). Often-novel MAGs frequently provide deeper insights into bacterial lifestyles that would otherwise remain unknown as evidenced by recent discoveries. The increasing rate of the recovery of MAGs presents new opportunities to link environmental distribution patterns of microbial populations and their functional potential, and transforms the field of microbiology by providing a more complete understanding of the microbial life, ecology, and evolution.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_5/Reconstructing_genomes_from_metagenomes_the_holy_grail_of_microbiology/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/665/?format=api" ] }, { "id": 53, "name": "RNA - Seq de novo", "description": "\n \n\nPractical session on transciptome de novo assembly\n \n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/A01b_Galaxy_RNASeq_denovo_ITMO2016_TP_v2red.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "RNA-seq" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-11-23", "dateUpdate": null, "licence": "CC BY-NC-SA", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/388/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/134/?format=api" ] }, { "id": 138, "name": "Linux TP", "description": "TP for linux training (genotoul bioinfo facility)", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://genotoul-bioinfo.pages.mia.inra.fr/linux-cluster/", "fileName": "linux-cluster", "topics": [], "keywords": [], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Novice", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CC BY-NC-SA", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/300/?format=api" ] }, { "id": 137, "name": "Linux slides", "description": "Slides for linux session (genotoul bioinfo facility)", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://bioinfo.genotoul.fr/wp-content/uploads/Formation_LINUX_GenoToul_2024.pdf", "fileName": "Formation_LINUX_GenoToul_2024.pdf", "topics": [], "keywords": [ "Operating systems" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Novice", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CC BY-NC-SA", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/300/?format=api" ] }, { "id": 143, "name": "workflows nf-core", "description": "Tutorial to launch and configure nf-core workflows on genotoul bioinfo cluster", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://genotoul-bioinfo.pages.mia.inra.fr/use-nextflow-nfcore-course/", "fileName": "use-nextflow-nfcore-course", "topics": [ "http://edamontology.org/topic_0769" ], "keywords": [ "Nextflow" ], "audienceTypes": [ "Professional (continued)" ], "audienceRoles": [ "Life scientists" ], "difficultyLevel": "Novice", "providedBy": [ { "id": 22, "name": "Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-bioinfo/?format=api" } ], "dateCreation": null, "dateUpdate": null, "licence": "CC BY-NC-SA", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/300/?format=api" ] }, { "id": 140, "name": "TP Cluster", "description": "TP for cluster training (bioinfo genotoul facility)", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://genotoul-bioinfo.pages.mia.inra.fr/linux-cluster/", "fileName": "linux-cluster", "topics": [], "keywords": [ "Cluster" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Novice", "providedBy": [ { "id": 22, "name": "Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-bioinfo/?format=api" } ], "dateCreation": null, "dateUpdate": null, "licence": "CC BY-NC-SA", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/300/?format=api" ] }, { "id": 139, "name": "Cluster Slides", "description": "Slides for Cluster training (bioinfo genotoul facility)", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://bioinfo.genotoul.fr/wp-content/uploads/Formation_cluster_SLURM_2024.pdf", "fileName": "Formation_cluster_SLURM_2024.pdf", "topics": [], "keywords": [ "Cluster" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "Novice", "providedBy": [ { "id": 22, "name": "Genotoul-bioinfo", "url": "https://catalogue.france-bioinformatique.fr/api/team/Genotoul-bioinfo/?format=api" } ], "dateCreation": null, "dateUpdate": null, "licence": "CC BY-NC-SA", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/300/?format=api" ] } ] }