Abstract
AbstractThe reconstruction and analysis of genome-scale metabolic models constitutes a powerful systems biology approach, with applications ranging from basic understanding of genotype-phenotype mapping to solving biomedical and environmental problems. However, the biological insight obtained from these models is limited by multiple heterogeneous sources of uncertainty, which are often difficult to quantify. Here we review the major sources of uncertainty and survey existing approaches developed for representing and addressing them. A unified formal characterization of these uncertainties through probabilistic approaches and ensemble modeling will facilitate convergence towards consistent reconstruction pipelines, improved data integration algorithms, and more accurate assessment of predictive capacity.
Funder
US Department of Energy, Biological and Environmental Research
National Institute of General Medical Sciences
National Institute of Dental and Craniofacial Research
Division of Environmental Biology
Division of Ocean Sciences
Human Frontier Science Program
SINTEF
Research Council of Norway
Publisher
Springer Science and Business Media LLC
Cited by
66 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献