Services

  • NanoXtract

    NanoXtract is a unique online tool for the calculation of 18 image descriptors based on Transmission Electron Microscopy (TEM) images of nanomaterials.

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  • AA MPNN Deep Learning model for blood-brain barrier permeability prediction

    This web-service hosts a computational model, based on atom-attention message-passing neural networks, for the prediction of blood-brain barrier permeability.

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  • AA MPNN Deep Learning model for Caco-2 cell permeability prediction

    This web-service hosts a computational model, based on atom-attention messagepassing neural networks, for the prediction of Caco-2 cell line permeability.

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  • MS3bD zeta potential model

    This web service provides the functionality to predict the zeta-potential in water of individual or a set of engineered nanomaterials based on physicochemical and molecular properties.

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  • Safe-by-design tool for functionalised NMs

    Two predictive QNAR/kNN models for the assessment of decorated multi-walled carbon nanotubes (MWCNTs) biological and toxicological profile.

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  • Image nanodescriptors zeta-potential model

    A kNN/read-across model for the prediction of nanomaterials (NMs) zeta-potential based on the NM type of core, main elongation and medium's pH value.

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  • Cytotoxicity prediction for MeOx NMs

    The web service provides the functionality to predict the cytotoxicity on human bronchial epithelial and murine myeloid cell lines of metal oxide nanoparticles.

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  • Prediction of MNPs uptake in PaCa2 cells

    This web service hosts a QNAR model that correlates the organic surface modifiers structural descriptors of metal-oxide nanoparticles (NPs) with the same core and the NPs cellular uptakes.

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  • Facet cytotoxicity prediction for MeOx nanomaterials

    This web tool is an implementation of a model predicting the toxicity of metal oxide nanomaterials towards bronchial epithelial, murine myeloid and E. coli cell lines.

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  • Enalos QNAR iron oxide toxicity platform

    This web-service hosts a fully validated predictive model which generates toxicity predictions for iron oxide nanoparticles based on a set of five properties.

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  • PBFTPK models

    Application of physiologically based finite time pharmacokinetic (PBFTPK) models for the analysis of oral drug absorption phenomena, based on the concept of finite absorption time.

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  • MouseTox: cytotoxicity prediction

    The MouseTox web-service hosts a model that predicts the cytotoxic effects of small molecules to NIH/3T3 (mouse embryonic fibroblast) cells, based on calculated structural descriptors.

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  • TNF (specific NF-kB induction) prediction tool

    This web-service hosts the Tumor Necrosis Factor TNFPubChem in silico model for the prediction of TNF (specific NF-kB Induction) activity of small molecules.

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  • COMT ligand-based predictive model

    This web service hosts a predictive consensus model to facilitate the design and virtual screening of novel potent small-molecule inhibitors of COMT (catechol-o-methyl transferase).

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  • Assessment of the inhibition of human K562 cell growth

    The web-service hosts a consensus predictive model for the assessment of K562 inhibition. This model contributes to the identification of compounds that possibly have therapeutic action against β-thalassemia.

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  • Prediction of milk type

    This web service hosts a validated model to predict the milk type (cow, goat, sheep) of various samples based on a series of milk properties.

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  • Prediction of metals’ mass loss in corrosion resistance tests

    This web service hosts a validated Support Vector Machine regression model to predict the mass loss of metal compounds to measure sample’s corrosion resistance under the salt spray test.

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  • THALAMOSS platform for the prediction of HbF inducers

    This web-service hosts a predictive model from the drug discovery perspective, targeting new HbF inducers to explore new therapies for thalassemia patients.

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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.

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  • Enalos TNF-a production inhibition

    This web-service hosts a consensus in silico predictive model for the assessment of the ability of small molecules to inhibit the cytotoxic effect of the Tumor Necrosis Factor (TNF).

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  • BACE ligand-based predictive model

    This web service hosts a robust, validated according to OECD principles ligand-based predictive model for beta-site APP-cleaving enzyme (BACE) inhibitory data.

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  • Biokinetics model

    This tool is used for the prediction of the rate at which Nickel (Ni) is released from cardiovascular devices following implantation of the body, using the biokinetics model proposed by Saylor et al.

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