Stokes2020 - Antibiotics discovery using deep learning approach.
收藏NIAID Data Ecosystem2026-05-02 收录
下载链接：
https://www.omicsdi.org/dataset/biomodels/MODEL2404080001
下载链接
链接失效反馈官方服务：
资源简介：
Based on a simple E.coli growth inhibition assay, the authors trained a model capable of identifying antibiotic potential in compounds structurally divergent from conventional antibiotic drugs. One of the predicted active molecules, Halicin (SU3327), was experimentally validated in vitro and in vivo.
Model Type: Predictive machine learning model.
Model Relevance: Probability that a compound inhibits E.coli growth.
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/eos4e40
创建时间：
2024-05-10
