Share your opinion by 29th March 2024.
Survey is targeted to in silico experts, model developers, risk assessors, risk managers, being employed in government or regulatory agencies, academia, industry, consulting, NGO...
Read more about the survey here👉 https://t.co/LICBeGaexh
📢Within PARC, a survey has been launched on landscape and readiness of computational #NewApproachMethodologies based on machine learning and artificial intelligence approaches for #NextGenerationRiskAssessment of #chemicals.
Survey is available here👉 https://t.co/AEGkS60E9B
On September 14, 2023 QsarDB received @CoreTrustSeal certificate of trustworthy data repository (https://t.co/sgAUG9RdZU), @EOSC_Nordic team, thank you also!
@mpastorPhI @RISKHUNT3R@etransafe Check out QsaeDB efforts on FAIRification of models https://t.co/La7Zj2X7bM (there are a few more steps to 100% FAIR)
In his Case study on #FAIRification and certification presentation Sulev Sild, University of Tartu, said that with help and development work, they managed to significantly improve the #FAIR maturity level in the QsarDB repository.
#EOSC#OpenScience
QsarDB team from Univ of Tartu (@unitartu) participates in European Partnership for the Assessment of Risks from Chemicals (#EU_PARC) to contribute to development of tools for chemicals next generation risk assessment & #FAIRdata & FAIR models: @Anses_fr@EU_Commission@HorizonEU
Risk assessment improves our knowledge about the risks to human health and the environment from exposure to #chemicals. ECHA is looking forward to helping develop next-generation chemical risk assessment through #EU_PARC.
#EUChemicalsStrategy#SaferChemicals
The QsarDB front web page (https://t.co/5RU7ZapcH1) has a new visual look. Also read the blog post about the evolution of the QsarDB front web page design over the years (https://t.co/1xM0OyVLwS).
Really cool to have a brand new ELIXIR Toxicology community in development! This means a lot for efficient reuse of scientific data in the field! Great overview by @mmarvinm2 in @F1000Research, https://t.co/WgrkZSxrQs
QsarDB models and data archives are 75% FAIR according to Automated FAIR Data Assessment Tool (F-UJI @FAIRsFAIR_EU), 25% to go! https://t.co/bq08tw8uQl
If attending @QSAR2021, don’t miss June 9 presentation by Dr. Sulev Sild "QSAR model applicability domain assessment – consensus of structure, descriptor and response domain information" new approach to estimate AD from data in @QsarDB. Full programme: https://t.co/eNxaNTytY2