Content Providers
Keywords: Cancer or Cloud computing or Data policies or Kinetic modeling or Risk assessment
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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 -
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 -
Cloud-SPAN
Cloud-SPAN deploys high quality learning resources that will train researchers to effectively generate and analyse a range of 'omics data using Cloud computing resources. The following activities and learning materials related to the project:
- Prenomics
- Genomics
- Create your own AWS...1 training materialCloud-SPAN https://cloud-span.york.ac.uk/ https://tess.elixir-europe.org/content_providers/cloud-span Cloud-SPAN deploys high quality learning resources that will train researchers to effectively generate and analyse a range of 'omics data using Cloud computing resources. The following activities and learning materials related to the project: - Prenomics - Genomics - Create your own AWS instance - Metagenomics - Statistically useful experimental design - Automation & pipelines (WIP) - Core R (WIP) /system/content_providers/images/000/000/658/original/cloud-span-logo-square.png?1666085149 -
EOSC4Cancer
EOSC4Cancer will make diverse types of cancer data accessible: genomics, imaging, medical, clinical, environmental and socio-economic. It will use and enhance federated and interoperable systems for securely identifying, sharing, processing and reusing FAIR data across borders and offer them via...
1 training material0 events (1 past event)EOSC4Cancer https://eosc4cancer.eu/ https://86.50.28.174/content_providers/eosc4cancer EOSC4Cancer will make diverse types of cancer data accessible: genomics, imaging, medical, clinical, environmental and socio-economic. It will use and enhance federated and interoperable systems for securely identifying, sharing, processing and reusing FAIR data across borders and offer them via community-driven analysis environments. EOSC4Cancer’s well curated data sets will be essential input for reproducible and robust analytics and computational methods – including machine learning and artificial intelligence. EOSC4Cancer’s five use cases will cover the patient journey from cancer prevention over diagnosis to treatment, laying the foundation of data trajectories and workflows for future European Cancer Mission projects. /system/content_providers/images/000/000/747/original/Logo-eosc-cancer-RGB-horizontal-STANDARD.png?1711439233