Content Providers
Keywords: Data policies or Data sharing or Deployment or Functional Association Networks or Machine Learning or RNA or biomolecular or data management or infrastructure or life sciences or metabolome or multiple sequence alignment or omics or pharmaceutical,
-
FAIRDOM
Research Infrastructure supporting life scientists in managing their data and models FAIRly. Specifically designed for interdisciplinary research such as systems biology, systems medicine, and synthetic biology.
0 events (2 past events)FAIRDOM https://fair-dom.org/ https://tess.elixir-europe.org/content_providers/fairdom Research Infrastructure supporting life scientists in managing their data and models FAIRly. Specifically designed for interdisciplinary research such as systems biology, systems medicine, and synthetic biology. /system/content_providers/images/000/000/100/original/Screen_Shot_2018-09-06_at_15.54.17.png?1536245244 -
FAIRsharing
FAIRsharing is a web-based, searchable portal of three interlinked registries, containing both in-house and crowdsourced manually curated descriptions of standards, databases and data policies, combined with an integrated view across all three types of resource. By registering your resource on...
1 training materialFAIRsharing https://www.fairsharing.org https://tess.elixir-europe.org/content_providers/fairsharing FAIRsharing is a web-based, searchable portal of three interlinked registries, containing both in-house and crowdsourced manually curated descriptions of standards, databases and data policies, combined with an integrated view across all three types of resource. By registering your resource on FAIRsharing, you not only gain credit for your work, but you increase its visibility outside of your direct domain, so reducing the potential for unnecessary reinvention and proliferation of standards and databases. /system/content_providers/images/000/000/109/original/FAIRsharing_logo.png?1544089458 -
proteomicsML
ProteomicsML provides ready-made datasets for machine learning models accompanied by tutorials on how to work with even the most complex data types in the field of proteomics. The resource is set up to evolve together with the field, and we welcome everyone to contribute to the project by adding...
1 training materialproteomicsML https://proteomicsml.org/ https://tess.elixir-europe.org/content_providers/proteomicsml ProteomicsML provides ready-made datasets for machine learning models accompanied by tutorials on how to work with even the most complex data types in the field of proteomics. The resource is set up to evolve together with the field, and we welcome everyone to contribute to the project by adding new datasets and accompanying notebooks. ProteomicsML was set up as a joint effort of SDU, CompOmics, LUMC, PeptideAtlas, NIST, PRIDE, and MSAID. We believe that ProteomicsML is solid step forward for the field towards more open and reproducible science! /system/content_providers/images/000/000/676/original/proteomicsml-logo.png?1686658675 -
Workflow4metabolomics
In the context of collaboration between metabolomics (MetaboHUB French infrastructure) and bioinformatics platforms (IFB: Institut Français de Bioinformatique), we have developed full LC/MS, FIA-MS, GC/MS and NMR pipelines using Galaxy framework for data analysis including preprocessing,...
Workflow4metabolomics https://workflow4metabolomics.org https://tess.elixir-europe.org/content_providers/workflow4metaolomics In the context of collaboration between metabolomics (MetaboHUB French infrastructure) and bioinformatics platforms (IFB: Institut Français de Bioinformatique), we have developed full LC/MS, FIA-MS, GC/MS and NMR pipelines using Galaxy framework for data analysis including preprocessing, normalization, quality control, statistical analysis (Univariate, Multivariate PLS/OPLS) and annotation steps. Those modular and extensible workflows are composed with existing components (XCMS and CAMERA packages, etc.) but also a whole suite of complementary homemade tools. This implementation is accessible through a web interface, which guarantees the parameters completeness. The advanced features of Galaxy have made possible the integration of components from different sources and of different types. Thus, an extensible Virtual Research Environment (VRE) is offered to metabolomics communities (platforms, end users, etc.), and enables preconfigured workflows sharing for new users, but also experts in the field. /system/content_providers/images/000/000/659/original/17082156.png?1667905557
- 1
- 2