Title	Utilizing biomarkers to forecast quantitative metabolite concentration profiles in human red blood cells
Year of Publication	2017
Authors	J.T. Yurkovich; L. Yang; B.O. Palsson
Journal	PLoS Comput Biol
Abstract	One of the major limitations in making experimental measurements of biological systems is the complexity of the network being investigated. Major efforts have been made to identify a subset of measurements (“biomarkers”) that can be used to provide information about the rest of the system. For red blood cells under cold storage conditions in a blood bank, a set of metabolite biomarkers have been identified that can reliably define the qualitative trend of cellular metabolism. Recently, it was shown that these biomarkers could also be used to train a model that quantitatively predicts the concentrations of other metabolites in the network over a 45 day time course. Here, we extend the utility of these methods by using a linear blackbox model to forecast future values of these concentrations. We show that 57 of the 70 metabolites measured in the red blood cell metabolic network (81%) can be accurately forecasted after 8 days of storage (5 time points) with a global median error of 18.36%. The ability to forecast metabolite profiles by only requiring a subset of measurements for the first few days of storage makes these methods immediately applicable in a clinical setting to assess the metabolic health of stored blood.
URL	http://ieeexplore.ieee.org/document/8062584/