Metabolic Algorithm with Time-varying Reaction Maps

Abstract

A symbolic-based approach to modelling biochemical processes and cellular dynamics is likely to turn useful in computational biology, where attempts to represent the cell as a huge, complex dynamic system must trade with the linguistic nature of the DNA and the individual behavior of the organelles living within. The early version of the metabolic algorithm gave a first answer to the problem of representing oscillatory biological phenomena, so far being treated with traditional (differential) mathematical tools, in terms of rewriting systems. We are now working on a further version of this algorithm, in which the rule application is tuned by reaction maps depending on the specific phenomenon under consideration. Successful simulations of the Brusselator, the Lotka-Volterra population dynamics and the PKC activation foster potential applications of the algorithm in systems biology.