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Project
Modelling intercellular communication in time and space
In this project we will develop novel computational techniques to improve modeling of intercellular communication. We will further extend NicheNet, a recent state-of-the-art tool developed in the Saeys lab, to facilitate true systems biology and unravel intercellular communication in time and space by combining single-cell transcriptomics with novel technologies such as spatial transcriptomics.
Date:1 Oct 2021 → Today
Keywords:Single-cell bioinformatics, intercellular communication, systems biology
Disciplines:Computational biomodelling and machine learning, Machine learning and decision making, Single-cell data analysis, Bio-informatics