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的蛋白质突变是否会对特定抗生素产生耐药性。抗生素耐药性是现代医学非常关注的问题。Fowler团队此前曾使用简单的机器学习和物理模拟来解决这个问题。我们的目标是使用IBM团队开发的图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上训练、验证和测试模型。