Platform for High-Throughput Analysis of Integrated Cancer Imaging and Multi-Omics Data

癌症研究越来越多地包括医学成像和多种组学技术的测量。数据集成的主要动力是，通过这些集成的数据集，获得了对潜在生物学的更好的理解，从而能够更好地预测表型，并在分子水平上进一步了解系统的机制方面。在这个项目中，我们建议开发创新技术，将代谢物数据与多组学(代谢组学、蛋白质组学和转录组学)和癌症成像数据相结合，以检测变量之间更微妙和更复杂的关联，医学成像和代谢组提供表型测量，我们可以锚定转录组和蛋白质组的全球测量。拟议的多组学和成像数据分析系统(MIDAS)将结合体外组学数据提供体内成像数据的摄取、注释、质量控制和分析，以推进癌症研究。MIDAS旨在通过代谢组学、转录组学、蛋白质组学、放射组学和其他成像数据的有效和可靠的数据协调，帮助癌症和整个公共卫生研究社区更快地朝着精确医学这一更大的目标前进。

Cancer studies increasingly include medical imaging and measurements from multiple omics techniques. The main impetus for data integration is that, through these integrated data sets, an improved understanding of the underlying biology is obtained to be better able to predict a phenotype and to gain further insight into mechanistic aspects of the system at the molecular level. In this project we propose to develop innovative technologies to integrate metabolite data with multi-omic (metabolomics, proteomics and transcriptomics) and cancer imaging data to enable the detection of subtler and more complex associations among variables, with the medical imaging and the metabolome providing phenotypic measurements to which we can anchor the global measurements of the transcriptome and proteome. The proposed Multi-omics and Imaging Data Analysis System (MIDAS) will provide for the ingestion, annotation, quality control, and analysis of in vivo imaging data combined with ex vivo -omics data to advance research in cancer. MIDAS is aimed at helping the cancer and overall public health research communities advance faster towards the larger goal of precision medicine through valid and reliable data harmonization of metabolomics, transcriptomics, proteomics, radiomics and other imaging data.