Modelling intercellular signaling events during cellular differentiation from single-cell transcriptomics data

01 October 2017 → 30 September 2021
Research Foundation - Flanders (FWO)
Research disciplines
No data available
cellular differentiation
Project description

Communication between cells is central to the normal functioning of multicellular organisms. Both

during development and homeostasis, it is clear that cells require some cues from other cells in

their environment for their normal functioning. Cellular differentiation is one of the processes that

are heavily influenced by extracellular factors: the micro-environment of a cell can provide unique

instructions that sway a cell towards a particular differentiation path. The goal of this project is to

computationally model the cell-cell communication networks and their intracellular effects, during

a differentiation process. While unbiased methods have already been developed to predict the

intracellular networks underlying cellular differentiation, predicting regulatory networks between

interacting cells has remained largely unexplored. In this project, I will develop a computational

method that uses transcriptomics data to predict what external signals are send between two

cells, and how they impact the cellular differentiation. The method will be applied on a model

system of liver macrophage differentiation, for which bulk transcriptomics data is currently

available (in-house) and single-cell transcriptomics data will be generated by other scientists of the

collaborating research group of Prof. Martin Guilliams. Predictions made by the model will in turn

be validated in this research group and will lead to a better fundamental understanding of

macrophage differentiation.