Content Providers
Keywords: Data spaces or Machine Learning or Risk assessment or www.mcafee.com/activate
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OpenRiskNet
The main objective of OpenRiskNet is to develop an open e-Infrastructure providing resources and services to a variety of communities requiring risk assessment, including chemicals, cosmetic ingredients, therapeutic agents and nanomaterials.
OpenRiskNet is
* a virtual research environment for...0 events (10 past events)OpenRiskNet https://openrisknet.org/ https://tess.elixir-europe.org/content_providers/openrisknet The main objective of OpenRiskNet is to develop an open e-Infrastructure providing resources and services to a variety of communities requiring risk assessment, including chemicals, cosmetic ingredients, therapeutic agents and nanomaterials. OpenRiskNet is * a virtual research environment for predictive toxicology and chemical and nanomaterial risk assessment, * harmonising access to data and facilitating interoperability of software, * easily deployable to single computers, public and in-house cloud solutions, * addressing the needs of industry and academic researchers, risk assessors, regulators and informed public. OpenRiskNet (Grant Agreement 731075) is a 3-years project funded by the European Commission within the Horizon2020 Programme /system/content_providers/images/000/000/097/original/ORN-Web_Logo3.png?1533933310 -
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://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