Computational Systems Biochemistry Group

Metabolic networks, being a form of aggregation and synthesis of our biomolecular knowledge, are an integral part in systems biology approaches. We currently reconstruct the metabolic network of human hepatocytes, the predominant liver cell type, as a first step towards systems-level modeling of human liver function. Presently, the network encompasses more than 3,000 metabolites and more than 2,400 reactions. All data have been manually curated using more than 1,200 original scientific research publications to warrant a high-quality evidence-based model. A canon of physiological liver functions is the basis for defining flux constraints to reflect regulation of liver metabolism and to derive adaptive functional system boundaries governing the input/output behaviour and the metabolic objectives of the network under a variety of physiological conditions.

Our underlying data model is designed to seamlessly integrate network reconstruction, structural modeling, and hypothesis generation. A key concept is the representation of the type and strength of the evidence supporting the relations between network components enabling flexible generation of computable network models based on adaptive evidence thresholds and customizable functional scope.

Establishment of a genome-scale metabolic network of hepatocytes is an important step to enable application of systems biology methodologies to investigate the complex biochemical regulation and physiology of the liver. In view of the pivotal role of the liver in metabolic homeostasis of the human body, this aids development of applications with direct implications for human health, e.g. model-based diagnostic tools for liver function assessment and monitoring of silent disease progress.

Researchers

Dr. Christian Bölling
Dr. Andreas Hoppe
Dr. Christoph Gille
Sabrina Hoffmann
Michael Weidlich
Sascha Bulik
Matthias König
Ramanan Ganeshan
Anja Karlstädt
Prof. Hermann-Georg Holzhütter

This project is part of the HepatoSys Platform Modeling (SP 2.1 HepatoNet Stoichiometric model of hepatocyte metabolism).

Own Publications

Gille C, Bölling C, Hoppe A, Bulik S, Hoffmann S, Hübner K, Karlstädt A, Ganeshan R, König M, Rother K, Weidlich M, Behre J, Holzhütter HG. (2010) HepatoNet1: a comprehensive metabolic reconstruction of the human hepatocyte for the analysis of liver physiology. Mol Syst Biol., 6:411. [PubMed]

		Metabolic Network Reconstruction and Modeling of Human Hepatocytes
Home Research VirtualLiver People Publications Software Positions Events Contact		Metabolic networks, being a form of aggregation and synthesis of our biomolecular knowledge, are an integral part in systems biology approaches. We currently reconstruct the metabolic network of human hepatocytes, the predominant liver cell type, as a first step towards systems-level modeling of human liver function. Presently, the network encompasses more than 3,000 metabolites and more than 2,400 reactions. All data have been manually curated using more than 1,200 original scientific research publications to warrant a high-quality evidence-based model. A canon of physiological liver functions is the basis for defining flux constraints to reflect regulation of liver metabolism and to derive adaptive functional system boundaries governing the input/output behaviour and the metabolic objectives of the network under a variety of physiological conditions. Our underlying data model is designed to seamlessly integrate network reconstruction, structural modeling, and hypothesis generation. A key concept is the representation of the type and strength of the evidence supporting the relations between network components enabling flexible generation of computable network models based on adaptive evidence thresholds and customizable functional scope. Establishment of a genome-scale metabolic network of hepatocytes is an important step to enable application of systems biology methodologies to investigate the complex biochemical regulation and physiology of the liver. In view of the pivotal role of the liver in metabolic homeostasis of the human body, this aids development of applications with direct implications for human health, e.g. model-based diagnostic tools for liver function assessment and monitoring of silent disease progress. Researchers Dr. Christian Bölling Dr. Andreas Hoppe Dr. Christoph Gille Sabrina Hoffmann Michael Weidlich Sascha Bulik Matthias König Ramanan Ganeshan Anja Karlstädt Prof. Hermann-Georg Holzhütter This project is part of the HepatoSys Platform Modeling (SP 2.1 HepatoNet Stoichiometric model of hepatocyte metabolism). Own Publications Gille C, Bölling C, Hoppe A, Bulik S, Hoffmann S, Hübner K, Karlstädt A, Ganeshan R, König M, Rother K, Weidlich M, Behre J, Holzhütter HG. (2010) HepatoNet1: a comprehensive metabolic reconstruction of the human hepatocyte for the analysis of liver physiology. Mol Syst Biol., 6:411. [PubMed]