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...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 -
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