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Updated: Jul 23, 2025

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
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PINNED:使用可解释的神经网络识别可用药物的人类蛋白质的特征

Michael Cunningham1, Danielle Pins2, Zoltán Dezső3

  • 1Genomics Research Center, AbbVie Inc., 1 North Waukegan Rd., North Chicago, IL, 60064, USA. mcunningham@abbvie.com.

Journal of cheminformatics
|July 19, 2023
PubMed
概括

识别可用药的人类蛋白质是具有挑战性的. 一个新的机器学习模型使用蛋白质特征来预测药物可用性,达到95%的准确性,并为新药标发现提供可解释的见解.

关键词:
阿尔法折叠是什么意思阿尔法折叠黑暗的基因组 黑暗的基因组目标药物是药物目标.药物适应性 药物适应性 药物适应性 药物适应性可以解释的可解释.机器学习是机器学习.神经网络的神经网络蛋白质蛋白质是一种蛋白质.蛋白质口袋中的蛋白质.蛋白质组是蛋白质组的组成部分.

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