FEDMA - A simple algorithm for theoretical modeling of linear metabolic pathways: From fuzzy data sets to prediction and experiment

Abstract

A theoretical model of a chain of irreversible Michaelis-Menten reactions proceeding inside a living cell, taking cell growth, division and subcellular compartmentation into account, was proposed. It became a basis for the construction of a "fuzzy" enzymatic data-modeling algorithm (FEDMA) - a procedure allowing the estimation of missing parameter values for the modeled system, in accordance both with the derived theoretical rules and the available experimental data. The obtained tool was tested to model the heme biosynthesis pathway in Saccharomyces cerevisiae, where about 40% of parameters remain unknown. The missing parameters estimated by means of FEDMA fall in the range of expected values.