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RedCom: A strategy for reduced metabolic modeling of complex microbial communities and its application for analyzing experimental datasets from anaerobic digestion

MPS-Authors
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Koch,  Sabine
International Max Planck Research School (IMPRS), Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;
Analysis and Redesign of Biological Networks, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Bissinger,  Thomas
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Benndorf,  Dirk
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;
Otto-von-Guericke University Magdeburg, Faculty for Process and Systems Engineering, Magdeburg, Germany;

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Reichl,  Udo
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;
Otto-von-Guericke University Magdeburg, Faculty for Process and Systems Engineering, Magdeburg, Germany;

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Klamt,  Steffen
Analysis and Redesign of Biological Networks, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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kluge_3028677.pdf
(Publisher version), 4MB

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Citation

Koch, S., Kohrs, F., Lahmann, P., Bissinger, T., Wendschuh, S., Benndorf, D., et al. (2019). RedCom: A strategy for reduced metabolic modeling of complex microbial communities and its application for analyzing experimental datasets from anaerobic digestion. PLoS Computational Biology, 15(2): e1006759. doi:10.1371/journal.pcbi.1006759.


Cite as: http://hdl.handle.net/21.11116/0000-0003-291F-E
Abstract
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