| Chapter title |
Designing Optimized Production Hosts by Metabolic Modeling
|
|---|---|
| Chapter number | 17 |
| Book title |
Metabolic Network Reconstruction and Modeling
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7528-0_17 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7527-3, 978-1-4939-7528-0
|
| Authors |
Christian Jungreuthmayer, Matthias P. Gerstl, David A. Peña Navarro, Michael Hanscho, David E. Ruckerbauer, Jürgen Zanghellini |
| Abstract |
Many of the complex and expensive production steps in the chemical industry are readily available in living cells. In order to overcome the metabolic limits of these cells, the optimal genetic intervention strategies can be computed by the use of metabolic modeling. Elementary flux mode analysis (EFMA) is an ideal tool for this task, as it does not require defining a cellular objective function. We present two EFMA-based methods to optimize production hosts: (1) the standard approach that can only be used for small and medium scale metabolic networks and (2) the advanced dual system approach that can be utilized to directly compute intervention strategies in a genome-scale metabolic model. |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 9 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 2 | 22% |
| Student > Master | 2 | 22% |
| Student > Doctoral Student | 1 | 11% |
| Student > Ph. D. Student | 1 | 11% |
| Lecturer > Senior Lecturer | 1 | 11% |
| Other | 1 | 11% |
| Unknown | 1 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 2 | 22% |
| Biochemistry, Genetics and Molecular Biology | 2 | 22% |
| Environmental Science | 1 | 11% |
| Computer Science | 1 | 11% |
| Engineering | 1 | 11% |
| Other | 0 | 0% |
| Unknown | 2 | 22% |