eprintid: 35089
rev_number: 17
eprint_status: archive
userid: 7839
dir: disk0/00/03/50/89
datestamp: 2024-07-10 07:12:52
lastmod: 2024-07-22 13:26:33
status_changed: 2024-07-10 07:12:52
type: doctoralThesis
metadata_visibility: show
creators_name: Dimitrov, Daniel
title: Modelling Cell-cell Communication using Prior Knowledge with Single-cell and Spatially-resolved Omics Data
divisions: i-140001
adv_faculty: af-14
abstract: Cell-cell communication (CCC) is a dynamic process which governs and coordinates diverse biological functions. The popularity of single-cell and spatially-resolved transcriptomics has recently sparked an array of computational methods that model CCC to be developed. My thesis describes the development of LIANA+ - an all-in-one framework for the inference of CCC from single-cell and spatial (multi-) omics data. In the first chapter of my thesis, I summarise the current state of the CCC field and state my motivation for the development of LIANA. In the second chapter, I describe the initial study that led to the development of the first iteration of LIANA. I also show that the choice of CCC method and resource can impact biological insights. In the third chapter, I evaluate CCC methods using alternative data modalities, and show that most CCC methods are generally coherent with those. In the final chapter, I summarise the current challenges of the CCC field and I showcase how the modularity of LIANA+ provides a comprehensive answer to those. I further see LIANA+ as a step towards modelling host-microbiome interactions, with already some pilots in place.
date: 2024
id_scheme: DOI
id_number: 10.11588/heidok.00035089
fp7_project_id: 860329
ppn_swb: 189601304X
own_urn: urn:nbn:de:bsz:16-heidok-350898
date_accepted: 2024-06-28
advisor: HASH(0x559e37e7d488)
language: eng
bibsort: DIMITROVDAMODELLINGC
full_text_status: public
place_of_pub: Heidelberg
citation:   Dimitrov, Daniel  (2024) Modelling Cell-cell Communication using Prior Knowledge with Single-cell and Spatially-resolved Omics Data.  [Dissertation]     
document_url: https://archiv.ub.uni-heidelberg.de/volltextserver/35089/1/DanielDimitrovPhDThesis.pdf