论文标题
基于图的神经网络方法，用于多重组织样品的免疫分析
A Graph Based Neural Network Approach to Immune Profiling of Multiplexed Tissue Samples
论文作者
论文摘要
多路复用免疫荧光为研究特定的细胞间和细胞微环境相互作用提供了前所未有的机会。我们采用图形神经网络来结合从组织形态获得的特征和蛋白质表达的测量，以介绍与不同肿瘤阶段相关的肿瘤微环境。我们的框架提出了一种分析和处理这些复杂的多维数据集的新方法，该数据集克服了分析这些数据的一些关键挑战，并为抽象具有意义上有意义的交互的机会打开了机会。
Multiplexed immunofluorescence provides an unprecedented opportunity for studying specific cell-to-cell and cell microenvironment interactions. We employ graph neural networks to combine features obtained from tissue morphology with measurements of protein expression to profile the tumour microenvironment associated with different tumour stages. Our framework presents a new approach to analysing and processing these complex multi-dimensional datasets that overcomes some of the key challenges in analysing these data and opens up the opportunity to abstract biologically meaningful interactions.
