ABSTRACT
Let us consider any type of network from our daily lives, from electrical and power to telephone, transportation, computer networks and the Internet itself. In all these cases, a certain quantity of the characteristic variable moves from a node to another on particular paths having to comply with the underlying network’s (a) structure, (b) path capacities and, (c) availability in relevant resources. In network ow theory [1], the ux (or ow rate) on a particular path of the network is dened by the number of the characteristic variable units that move from the starting to the end node of the path per unit time [2]. In this sense, it is the over the section area (or surface) integral of the transport phenomena denition of the ux term [3]. Accordingly, in (bio)chemical reaction networks, ux is dened “the rate at which material is processed through a pathway” [4,5]. Based on this denition, the ux of a particular (bio)chemical reaction is equal to its rate, and the steady-state ux of a linear metabolic pathway is equal to the steadystate rate of any involved reaction [4]. Similarly to the ux map of any type of network, being able to measure the metabolic ux distribution of a biological system at a particular set of conditions is of great signicance. It provides a metabolic ngerprint of the system’s in vivo physiological state, constituting thus a fundamental determinant of cellular physiology [4-7]. Considering the role of metabolism in the context of the overall cellular function, it is easily understandable why quantifying a complete and accurate metabolic ux map, also termed metabolic ux analysis (MFA), is among the major objectives of metabolic pathway engineering, quantitative systems biology, and integrated multiscale interaction analysis over multiple levels of cellular function.
