Reference : Computational modeling of human metabolism and its application to systems biomedicine
Parts of books : Contribution to collective works
Life sciences : Biochemistry, biophysics & molecular biology
http://hdl.handle.net/10993/22378
Computational modeling of human metabolism and its application to systems biomedicine
English
Aurich, Maike Kathrin mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Thiele, Ines mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
15-Dec-2015
Systems Medicine
Wolkenhauer, Olaf
Schmitz, Ulf
Springer
No
978-1-4939-3282-5
[en] Systems biology ; constraint-based modeling ; personalized health ; metabolomics ; OMICS ; COBRA ; flux balance analysis ; cancer metabolism ; human disease ; personalized models
[en] Modern high-throughput techniques offer immense opportunities to investigate whole-systems behavior, such as those underlying human diseases. However, the complexity of the data presents challenges in interpretation, and new avenues are needed to address the complexity of both diseases and data. Constraint-based modeling is one formalism applied in systems biology. It relies on a genome-scale reconstruction that captures extensive biochemical knowledge regarding an organism. The human genome-scale metabolic reconstruction is increasingly used to understand normal cellular and disease states because metabolism is an important factor in many human diseases. The application of human genome-scale reconstruction ranges from mere querying of the model as a knowledge-base to studies that take advantage of the model’s topology, and most notably, to functional predictions based on cell- and condition-specific metabolic models built based on omics data.
An increasing number and diversity of biomedical questions are being addressed using constraint-based modeling and metabolic models. One of the most successful biomedical applications to date is cancer metabolism, but constraint-based modeling also holds great potential for inborn errors of metabolism or obesity. In addition, it offers great prospects for individualized approaches to diagnostics and the design of disease prevention and intervention strategies. Metabolic models support this endeavor by providing easy access to complex high-throughput datasets. Personalized metabolic models have been introduced. Finally, constraint-based modeling can be used to model whole-body metabolism, which will enable the elucidation of metabolic interactions between organs and disturbances of these interactions as either causes or consequence of metabolic diseases. This chapter introduces constraint-based modeling and describes some of its contributions to systems biomedicine.
Luxembourg Centre for Systems Biomedicine (LCSB): Molecular Systems Physiology (Thiele Group)
ATTRACT program grant (FNR/A12/01) from the Luxembourg National Research Fund (FNR)
http://hdl.handle.net/10993/22378
10.1007/978-1-4939-3283-2_12

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