Wong2024 - Cytotoxicity Prediction from Human Cell Lines
收藏NIAID Data Ecosystem2026-05-02 收录
下载链接：
https://www.omicsdi.org/dataset/biomodels/MODEL2405130002
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资源简介：
The authors use a large dataset (>30k) to train an explainable graph-based model to identify potential antibiotics with low cytotoxicity. The model uses a substructure-based approach to explore the chemical space. Using this method, they were able to screen 283 compounds and identify a candidate active against methicillin-resistant S. aureus (MRSA) and vancomycin-resistant enterococci.
Model Type: Predictive machine learning model.
Model Relevance: Prediction of Human cytotoxicity endpoints.
Model Encoded by: Sarima Chiorlu (Ersilia)
Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam
Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos42ez
创建时间：
2024-05-13
