| Chapter title |
Metabolic Model Refinement Using Phenotypic Microarray Data
|
|---|---|
| Chapter number | 3 |
| Book title |
Systems Metabolic Engineering
|
| Published in |
Methods in molecular biology, January 2013
|
| DOI | 10.1007/978-1-62703-299-5_3 |
| Pubmed ID | |
| Book ISBNs |
978-1-62703-298-8, 978-1-62703-299-5
|
| Authors |
Pratish Gawand, Laurence Yang, William R. Cluett, Radhakrishnan Mahadevan, Gawand, Pratish, Yang, Laurence, Cluett, William R., Mahadevan, Radhakrishnan |
| Abstract |
Phenotypic microarray (PM) is a standardized, high-throughput technology for profiling phenotypes of microorganisms, which allows for characterization on around 2,000 different media conditions. The data generated using PM can be incorporated into genome-scale metabolic models to improve their predictive capability. In addition, a comparison of phenotypic profiles of wild-type and gene knockout mutants can give essential information about gene functions of unknown genes. In this chapter, we present a protocol to refine preconstructed metabolic models using the PM data. Both manual refinement and algorithmic approaches for integrating the PM data into metabolic models have been discussed. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 14 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 29% |
| Researcher | 3 | 21% |
| Other | 2 | 14% |
| Student > Master | 2 | 14% |
| Student > Bachelor | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 1 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 36% |
| Agricultural and Biological Sciences | 5 | 36% |
| Immunology and Microbiology | 1 | 7% |
| Engineering | 1 | 7% |
| Unknown | 2 | 14% |