Engineering On Analyzing Systems

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The committee recommends that life science majors be exposed to engineering principles and analysis. This does not necessarily require that they take a course in a school of engineering, courses in physics, biology and other departments can provide exposure to these concepts. Students should bare the opportunity to participate in laboratories that give them hands on experience, so that they may learn about the functioning of complex systems, especially as they relate to the basic principles of physical science, mathematics, and modeling. Basic courses in physics and engineering should be developed specifically for life sciences students; these courses could be taught in either the physics or the biology department. This could be complemented exceptionally well by biology lecture or laboratory courses that assist students in their understanding of principles of physics and engineering (e.g., a unit on biomechanics taught in a physiology or anatomy course).

Biology increasingly involves the analysis of complex systems. Understanding function at the systems level requires a way of thinking that is common to engineers. Creating ...
... (or recreating) function by building a complex system and getting it to work provides compelling proof that the scientist understands the essential building blocks and how they work in synchrony. Organisms can be analyzed in terms of subsystems having particular functions. To understand system function in biology in a predictive and quantitative fashion, it is necessary to describe and model how the system function results from the properties of its constituent elements. One approach to the study of biology is as a problem in reverse engineering. Manufactured systems are easier to understand than biological systems, because they have no unknown components, and their design principles can be explicitly stated. It is easiest to learn how to analyze systems through investigating how manufactured systems achieve their designed purpose, how their function depends on properties of their components, and how function can be reliable even with imperfect components.

As an example, a quantitative understanding of a cell-signaling chemical network involves the concepts of negative feedback, gain, signal-to-noise, bandwidth, and cross-talk. These concepts are simple to experience in the context of how an electrical amplifier can be built from components. Similarly, an effort to understand the locomotion of insects might be preceded by a laboratory involving an analysis of a simple legged robot. In such a system, the description of the muscles (activators) and control signals is completely known, and the relation between the laws of physics and the problem of controlling directed movements can be seen clearly.

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