Biological systems from an engineer's point of view

Abstract

The robust design of complex systems, such as cruise control, requires a careful balance of several objectives. As biological systems are no different, an engineering approach to these systems proves useful.

Figure 1. Example of a Dynamical System

(A) Reaction schematic of an enzyme, E, catalyzing the conversion of substrate, S, to product, P. The final product acts as a catabolite to promote the expression of enzyme. (B) ODE describing the change in time of enzyme concentration, c. The first term is the production term, r _p(c), and the second term is degradation, r _d(c). (C) Graphical representation of r _p(c) and r _d(c). At steady state, these two processes will balance, and the concentration of enzyme will become constant in time, with a value corresponding to the intersection of these two curves. Increasing the degradation constant μ (depicted by shift from solid line to dashed line) changes the steady state value of c (from closed circle to open circle). The sensitivity of this steady state value of c to such changes in parameters can be quantified by the sensitivity coefficient.

Figure 2. Examples of Control Loops

(A) Schematic of a simple control loop. The process output is monitored by a sensor, and the value of this output signal is passed to a device called a controller. The controller calculates the difference between the output signal and the set point (the desired value of the output), and responds accordingly, often by physically manipulating an input parameter, such as a control valve. (B) Schematic of cruise control. The car is the process, and the car's speed is the output. A speedometer sensor within the car tells the cruise control the car's speed. The actuator on the cruise control then responds by opening or closing the throttle, allowing air intake into the engine.