Content Providers
Content provider type: Organisation
and Keywords: FAIR or Machine Learning or NGS or Nanotechnology or Pathway analysis or Sequence Analysis or Synthetic biology or life sciences or metabolome or multiple sequence alignment or semantic web or targeted or toxicology
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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 -
CNAG-CRG
The Centro Nacional de Análisis Genómico (CNAG-CRG) has the mission to carry out projects in DNA sequencing and analysis in collaboration with researchers from Catalonia, Spain and from the international research community.
1 training materialCNAG-CRG https://www.cnag.crg.eu/ https://86.50.228.192/content_providers/cnag-crg The Centro Nacional de Análisis Genómico (CNAG-CRG) has the mission to carry out projects in DNA sequencing and analysis in collaboration with researchers from Catalonia, Spain and from the international research community. /system/content_providers/images/000/000/645/original/cnag.crg-logo_horizontal_complete.jpg?1657536294 -
WikiPathways
WikiPathways is a database of biological pathways maintained by and for the scientific community.
1 training materialWikiPathways https://www.wikipathways.org https://tess.elixir-europe.org/content_providers/wikipathways WikiPathways is a database of biological pathways maintained by and for the scientific community. /system/content_providers/images/000/000/660/original/wikipathways-logo-horizontal.svg?1668072305 -
Fraunhofer FIT
As a partner for digitization, Industry 4.0 and the Internet of Things, the Fraunhofer Institute for Applied Information Technology FIT has been developing IT solutions tailored to people and seamlessly integrated into business processes for almost 40 years. As a driving force of innovation, FIT...
1 training materialFraunhofer FIT https://www.fit.fraunhofer.de/en.html https://tess.elixir-europe.org/content_providers/fraunhofer-fit As a partner for digitization, Industry 4.0 and the Internet of Things, the Fraunhofer Institute for Applied Information Technology FIT has been developing IT solutions tailored to people and seamlessly integrated into business processes for almost 40 years. As a driving force of innovation, FIT not only provides guidance, but also shapes the digital transformation in business, the environment and society. FIT’s interdisciplinary R&D teams are drawn from our staff of around 350 scientists from computer science, social science, business administration, economics, psychology, and engineering. They bring their expertise in designing and implementing information technology systems to bear on problems and needs from different areas of life. Our specific strength is our holistic approach to system development – from concept validation to implementation. We strategically evolve our expertise in IT, specific application fields, and our scientific excellence with the aim to be ahead of the market for our customers from industry and administration. /system/content_providers/images/000/000/661/original/fit.svg?1670846086 -
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://86.50.28.174/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
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