AI-recognized mitochondrial phenotype enables identification of drug targets

IF 12 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Nature computational science Pub Date : 2024-08-22 DOI:10.1038/s43588-024-00682-9
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Abstract

Revealing a drug’s mechanism of action (MOA) is costly and time-consuming. In this study, we used deep learning to extract temporal mitochondrial phenotypic features after exposure to drugs with known MOAs using re-identification algorithms. The trained model could then predict the MOAs of unidentified substances, facilitating phenotypic screening-based drug discovery and repurposing.

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人工智能识别的线粒体表型有助于确定药物靶点。
揭示药物的作用机制(MOA)既费钱又费时。在这项研究中,我们利用深度学习,使用再识别算法提取暴露于已知MOA药物后的线粒体表型特征。经过训练的模型可以预测未识别物质的MOA,从而促进基于表型筛选的药物发现和再利用。
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CiteScore
11.70
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0.00%
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