Jiménez-Luna2021 - Coloring molecules for interaction with CYP3A4
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下载链接：
https://www.omicsdi.org/dataset/biomodels/MODEL2405210003
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资源简介：
By combining a Message-Passing Graph Neural Network (MPGNN) and a Forward fully connected Neural Network (FNN) with an integrated gradients explainable artificial intelligence (XAI) method, the authors developed MolGrad and tested it on a number of ADME predictive tasks such as metabolism as the case for this model. MolGrad incorporates explainable features to facilitate interpretation of the predictions. This model has been trained using a ChEMBL dataset of CYP450 3A4 inhibitors (0) and non-inhibitors (1).
Model Type: Predictive machine learning model.
Model Relevance: Probability that the molecule is metabolized by Cyp3A4.
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/eos96ia
创建时间：
2024-05-21
