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Project

Dissecting tissue spatial organization using machine learning and spatial transcriptomics

In this project, we aim to better functionally characterize different spatial contexts within tissues. To this end we will develop novel bioinformatics pipelines to process and integrate several “omics” and imaging data types. Novel machine learning methods will be explored that aim to combine the high spatial resolution of imaging techniques with the deep phenotyping capabilities of current scRNAseq methods.

Date:1 Nov 2020 →  31 Oct 2021
Keywords:single-cell omics, Machine learning, bioinformatics
Disciplines:Single-cell data analysis, Bio-informatics, Computational biomodelling and machine learning, Machine learning and decision making