Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Federale de Lausane, CH 1015 Lausanne, Switzerland.
Trends Biotechnol. 2010 Aug;28(8):391-7. doi: 10.1016/j.tibtech.2010.05.003. Epub 2010 Jun 18.
The engineering of cells for the production of fuels and chemicals involves simultaneous optimization of multiple objectives, such as specific productivity, extended substrate range and improved tolerance - all under a great degree of uncertainty. The achievement of these objectives under physiological and process constraints will be impossible without the use of mathematical modeling. However, the limited information and the uncertainty in the available information require new methods for modeling and simulation that will characterize the uncertainty and will quantify, in a statistical sense, the expectations of success of alternative metabolic engineering strategies. We discuss these considerations toward developing a framework for the Optimization and Risk Analysis of Complex Living Entities (ORACLE) - a computational method that integrates available information into a mathematical structure to calculate control coefficients.
细胞工程在生产燃料和化学品方面,涉及到多个目标的同时优化,例如特定的生产力、扩展的底物范围和提高的耐受性——所有这些都在很大程度的不确定性下进行。如果不使用数学建模,就不可能在生理和工艺约束下实现这些目标。然而,有限的信息和可用信息中的不确定性需要新的建模和模拟方法,这些方法将描述不确定性,并从统计学上量化替代代谢工程策略成功的预期。我们讨论了这些考虑因素,以开发一个复杂活体的优化和风险分析框架(ORACLE)——一种将可用信息集成到数学结构中以计算控制系数的计算方法。