Lee Jong Min, Gianchandani Erwin P, Papin Jason A
Department of Biomedical Engineering, University of Virginia, PO Box 800759, Charlottesville, VA 22908, USA.
Brief Bioinform. 2006 Jun;7(2):140-50. doi: 10.1093/bib/bbl007. Epub 2006 Apr 26.
Flux balance analysis (FBA) has emerged as an effective means to analyse biological networks in a quantitative manner. Much progress has been made on the extension of FBA to incorporate a priori biological knowledge, provide more practical descriptions of observed cell behaviours, and predict the outcome of network perturbations. Metabolomics is independently advancing as a set of high-throughput data acquisition tools providing dynamic profiles of metabolites in an unbiased manner. These data sets are neither yet sufficiently comprehensive nor accurate enough for generating large-scale kinetic models. Thus, there is a pressing need to develop quantitative techniques that can make use of the emerging data and embrace the associated uncertainties. This article reviews recent advances in FBA to meet this need and discusses the utility of FBA as a complement to metabolomics and the expected synergy as a result of combining these two techniques.
通量平衡分析(FBA)已成为一种以定量方式分析生物网络的有效手段。在将FBA扩展以纳入先验生物学知识、对观察到的细胞行为提供更实际的描述以及预测网络扰动结果方面已经取得了很大进展。代谢组学作为一组高通量数据采集工具正在独立发展,以无偏的方式提供代谢物的动态概况。这些数据集对于生成大规模动力学模型来说既不够全面也不够准确。因此,迫切需要开发能够利用新出现的数据并接受相关不确定性的定量技术。本文回顾了FBA为满足这一需求而取得的最新进展,并讨论了FBA作为代谢组学补充的效用以及将这两种技术结合所产生的预期协同作用。