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A Graph Based Neural Network Approach to Immune Profiling of Multiplexed Tissue Samples (2202.00813v1)

Published 1 Feb 2022 in cs.LG, cs.CV, eess.IV, q-bio.CB, and q-bio.QM

Abstract: 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.

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