drexml: A command line tool and Python package for drug repurposing

Marina Esteban-Medina, Víctor Manuel de la Oliva Roque, Sara Herráiz-Gil,María Peña-Chilet,Joaquín Dopazo,Carlos Loucera

Computational and Structural Biotechnology Journal(2024)

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摘要
We introduce drexml, a command line tool and Python package for rational data-driven drug repurposing. The package employs machine learning and mechanistic signal transduction modelling to identify drug targets capable of regulating a particular disease. In addition, it employs explainability tools to contextualize potential drug targets within the functional landscape of the disease. The methodology is validated in Fanconi Anemia and Familial Melanoma, two distinct rare diseases where there is a pressing need for solutions. In the Fanconi Anemia case, the model successfully predicts previously validated repurposed drugs, while in the Familial Melanoma case, it identifies a promising set of drugs for further investigation.
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关键词
explainable machine learning,drug repurposing,omics,mechanistic models
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