Chapter title |
Plant Genome-Scale Modeling and Implementation
|
---|---|
Chapter number | 19 |
Book title |
Plant Metabolic Flux Analysis
|
Published in |
Methods in molecular biology, January 2014
|
DOI | 10.1007/978-1-62703-688-7_19 |
Pubmed ID | |
Book ISBNs |
978-1-62703-687-0, 978-1-62703-688-7
|
Authors |
Dal’Molin, Cristiana G. O., Quek, Lake-Ee, Palfreyman, Robin W., Nielsen, Lars K., Cristiana G. O. Dal’Molin, Lake-Ee Quek, Robin W. Palfreyman, Lars K. Nielsen |
Abstract |
Considerable progress has been made in plant genome-scale metabolic reconstruction and modeling in recent years. Such reconstructions made it possible to explore metabolic phenotypes through appropriate model formulation and optimization methods. As a result, plant genome-scale modeling has increasingly attracted interest from the plant research community. In this chapter, the first generation of plant genome-scale metabolic reconstructions is presented, along with the important concepts behind model and constraint formulation. A brief protocol describing the use of constraint-based reconstruction and analysis (COBRA) Toolbox in flux simulation and model modification is provided. This is followed by a presentation of metabolic constraints required to generate fluxes in AraGEM using COBRA that describe photosynthesis, photorespiration, and respiration, respectively. Overall, plant genome-scale modeling is a powerful approach that is accessible and readily adopted. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Hungary | 1 | 4% |
India | 1 | 4% |
Unknown | 26 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 5 | 18% |
Researcher | 4 | 14% |
Professor > Associate Professor | 3 | 11% |
Student > Master | 3 | 11% |
Student > Doctoral Student | 2 | 7% |
Other | 5 | 18% |
Unknown | 6 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 8 | 29% |
Agricultural and Biological Sciences | 8 | 29% |
Computer Science | 3 | 11% |
Chemical Engineering | 2 | 7% |
Unknown | 7 | 25% |