? ? Flux balance analysis (FBA) is proving to be a powerful tool for analyzing metabolic networks. With the rapid publication of the genome sequences of a variety of organisms, the potential of FBA is only increasing. Although FBA is predicated on relatively straightforward mathematical principles, the implementation and use of FBA is not trivial. As a result, a significant hurdle is placed in the path of researchers who would like to use this approach, especially if those researchers do not have a strong quantitative background to begin with. ? ? The overarching objective of this work is to develop a new research technology which, when given an appropriately annotated genome, will allow any researcher to carry out genome-scale flux balance analysis. Specifically, upon completion of this project, a researcher will be able to use this tool to (1) determine the fluxes for all the metabolic reactions in an organism; (2) generate phenotypic phase plane plots; (3) quantitatively evaluate how probable a given metabolic objective function is relative to other objective functions; and (4) quantitatively evaluate how probable a given metabolic network is relative to other networks. In all cases, it will be possible for the researcher to customize their calculations based on their own or publicly available data. ? ? The proposed research technology will have significant biomedical benefits, particularly in regard to the analysis of microbial pathogens. They include ? ? the ability to rapidly identify key metabolic pathways in pathogens that are potential drug targets, ? ? the ability to elucidate the mechanism of action of new drugs, ? ? the ability to carry out in silico screening of new drugs to focus on the experimental development of the most promising ones, and ? ? enhance the ability to perform basic fundamental quantitative biological research, particularly for researchers who might lack the appropriate mathematical background to normally carry out such research. ? ? Finally this work should significantly enhance the national and international medical informatics and bioinformatics infrastructure. ? ? ? ? ?
| Bautista, Eddy J; Zinski, Joseph; Szczepanek, Steven M et al. (2013) Semi-automated curation of metabolic models via flux balance analysis: a case study with Mycoplasma gallisepticum. PLoS Comput Biol 9:e1003208 |
| Jain, Rishi; Srivastava, Ranjan (2009) Metabolic investigation of host/pathogen interaction using MS2-infected Escherichia coli. BMC Syst Biol 3:121 |
