Training Material List
Handles creating, reading and updating training materials.
GET /api/trainingmaterial/?format=api&offset=20&ordering=keywords
{ "count": 144, "next": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/?format=api&limit=20&offset=40&ordering=keywords", "previous": "https://catalogue.france-bioinformatique.fr/api/trainingmaterial/?format=api&limit=20&ordering=keywords", "results": [ { "id": 77, "name": "Prokaryotic Phylogeny on the Fly: databases and tools for online taxonomic identification", "description": "PPF (Prokaryotic Phylogeny on the Fly) is an automated pipeline allowing to compute molecular phylogenies for prokarotic organisms. It is based on a set of specialized databases devoted to SSU rRNA, the most commonly used marker for bacterial txonomic identification. Those databases are splitted into different subsets using phylogenetic information. The procedure for computing a phylogeny is completely automated. Homologous sequence are first recruited through a BLAST search performed on a sequence (or a set of sequences). Then the homologous sequences detected are aligned using one of the multiple sequence alignment programs provided in the pipeline (MAFFT, MUSCLE or CLUSTALO). The alignment is then filtered using BMGE and a Maximum Likelihood (ML) tree is computed using the program FastTree. The tree can be rooted with an outgroup provided by the user and its leaves are coloured with a scheme related to the taxonomy of the sequences. The main advantage provided by PPF is that its databases are generated using a phylogeny-oriented procedure and and therefore much more efficient for phylogentic analyses that \"generic\" collections such as SILVA (in the case SSU rRNA) por GenBank. It is therefore much more suited to compute prokaryotic molecular phylogenies than related systems such as the Phylogeny.fr online system. PPF can be accessed online at https://umr5558-bibiserv.univ-lyon1.fr/lebibi/PPF-in.cgi\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_5/Procaryotic_phylogenu_on_the_fly/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/489/?format=api" ] }, { "id": 78, "name": "Dr Jekyll and Mr Hyde: The dual face of metagenomics in phylogenetic analysis", "description": "The aim of this lecture is to present the impact of metagenomics and single-cell genomics on public databases. These new powerful approches allow us to have access to the diversity of life on our planet. However, care has to be taken when using these data for posterior analyses, such as phylogenetic studies, as critical errors can still be present in the databases. This course will incorporate examples taken from real studies, and we will investigate methods used for error detection.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_5/Dr_Jekyll_and_Mr_Hyde_The_dual_face_of_metagenomics_in_phylogenetic_analysis/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/706/?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": 80, "name": "Multiple Comparative Metagenomics using Multiset k-mer Counting", "description": "Large scale metagenomic projects aim to extract biodiversity knowledge between different environmental conditions. Current methods for comparing microbial communities face important limitations. Those based on taxonomical or functional assignation rely on a small subset of the sequences that can be associated to known organisms. On the other hand, de novo methods, that compare the whole set of sequences, do not scale up on ambitious metagenomic projects.\nThese limitations motivated the development of a new de novo metagenomic comparative method, called Simka. This method computes a large collection of standard ecology distances by replacing species counts by k-mer counts. Simka scales-up today metagenomic projects thanks to a new parallel k-mer counting strategy on multiple datasets.\nExperiments on public Human Microbiome Project datasets demonstrate that Simka captures the essential underlying biological structure. Simka was able to compute in a few hours both qualitative and quantitative ecology distances on hundreds of metagenomic samples (690 samples, 32 billions of reads). We also demonstrate that analyzing metagenomes at the k-mer level is highly correlated with extremely precise de novo comparison techniques which rely on all-versus-all sequences alignment strategy.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_4/Multiple_comparative_metagenomics_using_multiset_k_mer_couting/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/708/?format=api" ] }, { "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": 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": 81, "name": "Assessing microbial biogeography by using a metagenomic approach", "description": "Soils are highly complex ecosystems and are considered as one of the Earth’s main reservoirs of biological diversity. Bacteria account for a major part of this biodiversity, and it is now clear that such microorganisms have a key role in soil functioning processes. However, environmental factors regulating the diversity of below-ground bacteria still need to be investigated, which limits our understanding of the distribution of such bacteria at various spatial scales. The overall objectives of this study were: (i) to determine the spatial patterning of bacterial community diversity in soils at a broad scale, and (ii) to rank the environmental filters most influencing this distribution.\nThis study was performed at the scale of the France by using the French Soil Quality Monitoring Network. This network includes more than 2,200 soil samples along a systematic grid sampling. For each soil, bacterial diversity was characterized using a pyrosequencing approach targeting the 16S rRNA genes directly amplified from soil DNA, obtaining more than 18 million of high-quality sequences.\nThis study provides the first estimates of microbial diversity at the scale of France, with for example, bacterial richness ranging from 555 to 2,007 OTUs (on average: 1,289 OTUs). It also provides the first extensive map of bacterial diversity, as well as of major bacterial taxa, revealing a bacterial heterogeneous and spatially structured distribution at the scale of France. The main factors driving bacterial community distribution are the soil physico-chemical properties (pH, texture...) and land use (forest, grassland, crop system...), evidencing that bacterial spatial distribution at a broad scale depends on local filters such as soil characteristics and land use when regarding the community (quality, composition) as a whole. Moreover, this study also offers a better evaluation of the impact of land uses on soil microbial diversity and taxa, with consequences in terms of sustainability for agricultural systems.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_4/Assessing_microbial_biogeography_by_using_a_metagenomic_approach/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/709/?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": 96, "name": "Training on Galaxy : Metagenomics", "description": "Find Rapidly OTU with Galaxy Solution\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://genoweb.toulouse.inra.fr/~formation/15_FROGS/April2016/FROGS_april_2016_Formation.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics", "Galaxy" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-04-01", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/215/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/716/?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": 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": 95, "name": "Exercices on Galaxy: metagenomics", "description": "Find Rapidly OTU with Galaxy Solution\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://genoweb.toulouse.inra.fr/~formation/15_FROGS/April2016/FROGS_april_2016_Pratice.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "Metagenomics", "Galaxy" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-04-01", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/215/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/716/?format=api" ] }, { "id": 142, "name": "Introduction to python", "description": "Training slides (theory and exercises)", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://training-python-for-biology-genotoul-bioinfo-a77c191514cdd1dc1b.pages.mia.inra.fr/#/title-slide", "fileName": "training-python-for-biology", "topics": [ "http://edamontology.org/topic_3316" ], "keywords": [ "Python Language" ], "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": "Creative Commons Attribution 4.0 International License", "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": 16, "name": "Exploring Pharmacogenomic LOD for Molecular Explanations of Gene-Drug Relationships", "description": "\n \n\nExploring Pharmacogenomic LOD for Molecular Explanations of Gene-Drug Relationships\n \n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/videos/scorms/exploring-pharmacogenomic_688a/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "biohackaton 2018" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2019-03-21", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/140/?format=api" ] }, { "id": 2, "name": "Using blockchain in biomedical provenance, the identifiers use case", "description": "\n \n\nUsing blockchain in biomedical provenance, the identifiers use case\n \n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/videos/scorms/using-blockchain_039d/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "biohackaton 2018" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2019-03-21", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/666/?format=api" ] }, { "id": 8, "name": "Pathway effect prediction for protein targets", "description": "\n \n\nPathway effect prediction for protein targets\n \n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/videos/scorms/pathway-effect_b1e2/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "biohackaton 2018" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2019-03-21", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/672/?format=api" ] }, { "id": 15, "name": "From Biotea to Bioschemas: definition of profiles required to represent scholarly publications", "description": "\n \n\nFrom Biotea to Bioschemas: definition of profiles required to represent scholarly publications\n \n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/videos/scorms/from-biotea-to-bioschemas_28f9/scormcontent/index.html", "fileName": "missing.txt", "topics": [], "keywords": [ "biohackaton 2018" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2019-03-21", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/678/?format=api" ] } ] }