Services
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SimpleBox4Planet
The SimpleBox4Planet tool provides a user-friendly environment to access the SimpleBox, a multimedia mass balance model used to evaluate the fate of chemical substances in the environment. The tool includes a database with the properties of candidate substances used as PFAS alternatives.
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Read-across model for predicting the biological potency of novel PPARδ agonists
A read-across model for the prediction of the biological potency of novel peroxisome proliferator-activated receptor delta (PPARδ) agonists in human 293T cells co-transfected with Gal4-DBD using the luciferase transactivation process.
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ReDEx Repurposing Drug Explorer
ReDEx is a comprehensive tool featuring multiple analysis tabs that allow users to explore individual drugs, diseases, or specific drug–disease pairs. It supports the analysis of single or multiple SMILES strings, identifying the most similar drugs using the Tanimoto Coefficient (TC). ReDEx also facilitates drug repurposing by integrating disease-gene networks with drug similarity metrics. Additionally, it enables users to investigate shared targets between drugs and diseases and perform enrichment analysis to uncover deeper biological insights.
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Easy-MODA
This tool provides an assisted generation of MODA standardised reports for the FAIR and harmonized documentation of materials modelling workflows for EU projects, as proposed by the EMMC.
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AOP fingerprint
AOPfingerprint performs AOP-based enrichment analysis of gene lists. The tool can be used to conduct AOP-based mechanistic characterization of a chemical’s mechanism of action. Given one or multiple gene lists of interest (and possible numerical values associated with them), the tool performs enrichment analysis of key events and AOPs, and allows the construction of the enriched mechanism as a key event networks.
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THALAMOSS platform for chelation prediction outcome (thalassemia patients)
This web service hosts a validated model to predict the chelation outcome for thalassemia patients by applying clustering-based and machine-learning-based stratification techniques to a comprehensive clinical dataset from thalassemia patients.