Training Material List
Handles creating, reading and updating training materials.
GET /api/trainingmaterial/?format=api&offset=80&ordering=-providedBy
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It is an alternative to WWW Query which allows more complex queries. Quick Search allows you to retrieve sequences or sequence families associated to a single word without specifying what is this word. You can enter indifferently a keyword, a sequence name or accession number, or a taxa name.\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.prabi.fr/spip.php?article17", "fileName": "missing.txt", "topics": [], "keywords": [ "genomics", "Pattern recognition" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/715/?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": 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": 122, "name": "Docker tutorial: Gene regulation", "description": "Get started with Docker!\nCreate a Docker account\nInstall Docker on your local host\nCreate shared repositories and download source data\nFetch the Docker image and run it with shared folders\nExecute the pipeline\n\nJVH / Mac\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://github.com/rioualen/gene-regulation/blob/master/doc/gene-regulation_tutorials/gene-regulation_with_docker.Rmd", "fileName": "missing.txt", "topics": [], "keywords": [ "Gene regulation", "Docker" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-05-31", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/660/?format=api", "https://catalogue.france-bioinformatique.fr/api/userprofile/624/?format=api" ] }, { "id": 62, "name": "RNA-seq: Differential gene expression analysis", "description": "Transcriptome analysis provides information about the identity and quantity of all RNA molecules\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/R01_EBA206_RNAseq_ref.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "genomics", "RNA-seq" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-11-22", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/371/?format=api" ] }, { "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/?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": 97, "name": "Analysis of community composition data using phyloseq", "description": "Learn about and become familiar with phyloseq R package for the analysis of microbial census data\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://genoweb.toulouse.inra.fr/~formation/15_FROGS/April2016/R_phyloseq/phyloseq_formation_toulouse_201604.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "R", "Microbiomes" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-04-01", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/717/?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": 126, "name": "Galaxy 101 for everyone", "description": "This practical aims at familiarizing you with the Galaxy user interface. It will teach you how to perform basic tasks such as importing data, running tools, working with histories, creating workflows and sharing your work. Not everyone has the same background and that’s ok!", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://training.galaxyproject.org/training-material/topics/introduction/tutorials/galaxy-intro-101-everyone/tutorial.html", "fileName": "galaxy-intro-101-everyone", "topics": [], "keywords": [], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": null, "dateUpdate": null, "licence": "CC-BY-4.0", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/677/?format=api" ] }, { "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_1775", "http://edamontology.org/topic_3941" ], "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/?format=api" ] }, { "id": 67, "name": "Galaxy: Initiation II", "description": "Galaxy II: common tools, quality control; alignment; data managment\n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/G045_16-11-21-galaxy-tp-initiation-II-0.3.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "genomics" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-11-21", "dateUpdate": null, "licence": "CC BY-NC-SA", "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/362/?format=api" ] }, { "id": 50, "name": "Welcome and Introduction", "description": "\n \n\nIntroduction message of the EGDW 2017\n \n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "https://ressources.france-bioinformatique.fr/sites/default/files/introduction.pdf", "fileName": " introduction.pdf", "topics": [], "keywords": [], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2017-01-16", "dateUpdate": null, "licence": null, "maintainers": [] }, { "id": 51, "name": "Eukaryotic small RNA", "description": "\n \n\nSmall RNAseq data analysis for miRNA identification\n \n", "communities": [], "elixirPlatforms": [], "doi": null, "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/sRNA-Seq.pdf", "fileName": "missing.txt", "topics": [], "keywords": [ "RNA-seq" ], "audienceTypes": [], "audienceRoles": [], "difficultyLevel": "", "providedBy": [], "dateCreation": "2016-11-23", "dateUpdate": null, "licence": null, "maintainers": [ "https://catalogue.france-bioinformatique.fr/api/userprofile/642/?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": 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": 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" ] } ] }