A technology platform for multiple body site image-omics

该项目的目标是开发一个技术平台，包括新的图像处理和机器学习算法，以整合多个身体部位的成像和生物数据。跨多个站点的图像特征和生物数据之间的关系以前没有被发现。我们建议使用的生物信息，从一个采样站点调查其他未采样站点的基础上成像组学的对应关系。我们将使用数据驱动的、可搜索的图模型方法来进行人口数据中的知识发现。该项目将为系统生物学和生物信息学提供新的见解，从而为生命科学提供信息和促进其益处，并在未来为医疗保健带来潜在的益处。

The project aim is to derive a technology platform comprising new image processing and machine learning algorithms to integrate imaging and biological data across multiple body sites. The relationships between image features and biological data across multiple sites has not been discovered before. We propose the use of biological information from one sampled site to investigate other unsampled sites based on imaging-omics correspondences. We will use a data-driven, searchable graph model approach for knowledge discovery within the population data. The project will provide new insights into systems biology and bioinformatics that will then inform and promote benefits in life sciences, with potential future benefits in healthcare.