Taking the structure of proteins into account: predicting if infections are resistant to B-lactam antibiotics using graph-based convolutional neural n

考虑蛋白质的结构：使用基于图的卷积神经网络预测感染是否对 B-内酰胺抗生素具有耐药性

• 批准号: 2886022
• 金额: --
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2886022
• 关键词: Taking; structure; proteins; into; account

This project will use machine learning to predict whether novel protein mutations confer resistance to specific antibiotics. Antimicrobial Resistance is a great concern to modern medicine. The Fowler group has previously used simple machine learning and physical simulation to address this problem. We aim to use graph neural network techniques developed by the IBM team to create advanced deep learning models and then train, validate and test the models on the large datasets we possess.

该项目将使用机器学习来预测新型蛋白质突变是否赋予对特定抗生素的抗性。抗菌素耐药性是现代医学的重要问题。 Fowler组以前已经使用了简单的机器学习和物理模拟来解决此问题。我们的目标是使用IBM团队开发的图形神经网络技术来创建高级深度学习模型，然后在我们拥有的大型数据集中训练，验证和测试模型。