Generation of context-specific genome-scale metabolic models using single-cell RNA-Seq data
October 17, 2024 @ 13:00 – 14:15 CEST
Johan Gustafsson, Postdoc researcher, Broad Institute, USA
Abstract
The metabolic networks in cells vary across tissues and cell types, and to accurately model the metabolism of cells, the full generic metabolic network defined in the genome needs to be reduced to a context-specific network representing the network expressed specifically in the cells of interest. Single-cell RNA-Seq promises to provide the information needed for such a reduction, but noise in the form of data sparsity is a challenge. Here, we present methods to handle data sparsity and estimate the uncertainty of modeling results.
Biography
Johan is an expert in modeling cancer metabolism and analyzing single-cell RNA/DNA sequencing data, aiming to uncover vulnerabilities in cancer. With a background in both computer science and biochemistry, Johan has completed a PhD in metabolic modeling at Chalmers University of Technology and now works as a postdoc in the Getz lab at the Broad Institute, focusing on CLL/Richter’s syndrome and hypoxia in solid tumors.
Host: Rasool Saghaleyni, NBIS Chalmers University, Gothenburg (rasool.saghaleyni@scilifelab.se)
Date: October 17, 13:00 – 14:15 CET online on zoom
Broadcast link (live event): link, pass:spd996
The talk will also be available afterwards on the SciLifeLab YouTube channel.
More information about the Oimcs Integration and Systems Biology Workshop here.
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