Schedule*

Presentation 1

Time: 12:00 - 12:30

Speaker: Marian Breuer

Title: "Combining omics data with mechanistic modeling through genome-scale metabolic models" (part 1)

Abstract: Modern life science research has seen an explosion in the production of omics data, i. e. data sets covering a cell’s entire set of functional units like for instance RNA (transcriptomics), proteins (proteomics) or metabolites (metabolomics). While these data can be analyzed on their own in a purely data-driven manner, additional insight can be gained by combining them with available biochemical knowledge encoded in mechanistic models. A particularly well-characterized type of cellular network are metabolic networks, i.e. the networks formed by the various interconnected biochemical reactions occurring in cells. At the same time, by forming the link between enzymes catalyzing these reactions and the resulting cellular biochemical behavior, the metabolic network of a cell forms an important link between its genotype and its phenotype.

Here, we present our ongoing research at the Maastricht Centre for Systems Biology (MaCSBio) combining mechanistic models of genome-scale metabolic networks (encompassing all reactions in a cell) with omics data in different biomedical contexts. In particular, a steady-state modeling framework, known as constraint-based modeling, allows to construct metabolic network models for a given cell type and condition by mapping omics data onto a reference template network; and to analyze these context-specific network models by studying the possible steady-state flux distributions available for a given network. In this way, genome-scale metabolic models allow to compare metabolic states in a wide range of biomedical contexts. We will focus in particular on our ongoing work in the areas of obesity, cardiovascular disorders and cellular senescence; each of which being highly relevant for public health.

Presentation 2

Time: 12:30 - 13:00

Speaker: Michiel Adriaens

Title: "Combining omics data with mechanistic modeling through genome-scale metabolic models" (part 2).

Abstract: Modern life science research has seen an explosion in the production of omics data, i.e. data sets covering a cell’s entire set of functional units like for instance RNA (transcriptomics), proteins (proteomics) or metabolites (metabolomics). While these data can be analyzed on their own in a purely data-driven manner, additional insight can be gained by combining them with available biochemical knowledge encoded in mechanistic models. A particularly well-characterized type of cellular network are metabolic networks, i. e. the networks formed by the various interconnected biochemical reactions occurring in cells. At the same time, by forming the link between enzymes catalyzing these reactions and the resulting cellular biochemical behavior, the metabolic network of a cell forms an important link between its genotype and its phenotype.

Here, we present our ongoing research at the Maastricht Centre for Systems Biology (MaCSBio) combining mechanistic models of genome-scale metabolic networks (encompassing all reactions in a cell) with omics data in different biomedical contexts. In particular, a steady-state modeling framework, known as constraint-based modeling, allows to construct metabolic network models for a given cell type and condition by mapping omics data onto a reference template network; and to analyze these context-specific network models by studying the possible steady-state flux distributions available for a given network. In this way, genome-scale metabolic models allow to compare metabolic states in a wide range of biomedical contexts. We will focus in particular on our ongoing work in the areas of obesity, cardiovascular disorders and cellular senescence; each of which being highly relevant for public health.

*Since both speakers will be discussing a related topic, the titles and abstracts of their presentations are the same.