Chapter title |
Cyanobacterial Biofuels: Strategies and Developments on Network and Modeling
|
---|---|
Chapter number | 42 |
Book title |
Network Biology
|
Published in |
Advances in biochemical engineering biotechnology, January 2016
|
DOI | 10.1007/10_2016_42 |
Pubmed ID | |
Book ISBNs |
978-3-31-956459-3, 978-3-31-956460-9
|
Authors |
Amornpan Klanchui, Nachon Raethong, Peerada Prommeenate, Wanwipa Vongsangnak, Asawin Meechai |
Abstract |
Cyanobacteria, the phototrophic microorganisms, have attracted much attention recently as a promising source for environmentally sustainable biofuels production. However, barriers for commercial markets of cyanobacteria-based biofuels concern the economic feasibility. Miscellaneous strategies for improving the production performance of cyanobacteria have thus been developed. Among these, the simple ad hoc strategies resulting in failure to optimize fully cell growth coupled with desired product yield are explored. With the advancement of genomics and systems biology, a new paradigm toward systems metabolic engineering has been recognized. In particular, a genome-scale metabolic network reconstruction and modeling is a crucial systems-based tool for whole-cell-wide investigation and prediction. In this review, the cyanobacterial genome-scale metabolic models, which offer a system-level understanding of cyanobacterial metabolism, are described. The main process of metabolic network reconstruction and modeling of cyanobacteria are summarized. Strategies and developments on genome-scale network and modeling through the systems metabolic engineering approach are advanced and employed for efficient cyanobacterial-based biofuels production. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 28 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 6 | 21% |
Student > Bachelor | 4 | 14% |
Researcher | 3 | 11% |
Student > Master | 2 | 7% |
Professor | 1 | 4% |
Other | 1 | 4% |
Unknown | 11 | 39% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 7 | 25% |
Biochemistry, Genetics and Molecular Biology | 4 | 14% |
Chemical Engineering | 1 | 4% |
Environmental Science | 1 | 4% |
Immunology and Microbiology | 1 | 4% |
Other | 1 | 4% |
Unknown | 13 | 46% |