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Rong2020 - Grover-sider: Prediction of the putative adverse drug reactions (ADR) of a molecule

ABSTRACT: The model predicts the putative adverse drug reactions (ADR) of a molecule, using the SIDER database (MoleculeNet) that contains pairs of marketed drugs and their described ADRs.This model has been trained using the GROVER transformer Model Type: Predicitive machine learning model. Model Relevance: Predicts adverse drug reactions (ADR) of a molecule Model Encoded by: Amna Ali (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos77w8

SUBMITTER: Zainab Ashimiyu-Abdusalam

PROVIDER: MODEL2406050007 | BioModels | 2024-06-05

REPOSITORIES: BioModels

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Rong2020 - Grover-bbbp: Prediction of the Blood-brain barrier penetration.

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Rong2020 - Grover-tox21: Predicts activity of compounds accross the Tox21 panel.

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Rong2020 - Grover-clintox: A classification model to predict the likelihood of failure in clinical trials due to toxicity

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Rong2020 - Grover-Toxcast: Probability of toxicity against 617 biological targets

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Francoeur2021 - SolTranNet–A Machine Learning Tool for Fast Aqueous Solubility Prediction

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Pu2019 - eToxPred: an ML-based approach to estimate the toxicity, and synthetic accessibility of drug candidates

Project description:The eToxPred tool has been developed to predict, on one hand, the synthetic accessibility (SA) score, or how easy it is to make the molecule in the laboratory, and, on the other hand, the toxicity (Tox) score, or the probability of the molecule of being toxic to humans. The authors trained and cross-validated both predictors on a large number of datasets, and demonstrated the method usefulness in building virtual custom libraries. Model Type: Predicitive machine learning model. Model Relevance: Predicts Synthetic Accesibility and Toxicity score of a chemical compound Model Encoded by: Miquel Duran-Frigola (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos92sw

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Rong2020 - Grover-Freesolv: Experimental and calculated hydration free energy of small molecules in water

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Rong2020 - Grover-QM7: Atomization energy prediction of small molecules.

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Expression data from skin of patients with adverse drug reactions (ADRs)

Project description:ADRs are immune mediated skin reactions of diverse severity and etiology. The patho-mechanisms are however not well understood. We used a gene expression array for the comparison of the gene expression profile of 2 cutaneous adverse drug reactions (MPR and AGEP) to normal skin.

2019-02-01 | GSE121421 | GEO

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