Check out this paper from 1985: a model of an extremely simple biological system that, in spite of its simplicity, senses its environment and makes decisions - lambda phage, a virus that infects bacteria.
Madeline Shea and Gary Ackers recognized that you can't understand why this system works the way it does by using intuitive, non-quantitative reasoning. They turned to a mathematical model, a statistical thermodynamic model of gene regulation, to explain how a fairly simple set of genes can produce very sophisticated behaviors. They found that
Several major physiological characteristics were found to arise as “system properties” through the non-linear, time-dependent, feedback-modulated combinations of molecular interactions prescribed by the model.In their rationale, they get at the essence of systems biology: understanding how physical chemistry produces biology:
The time-dependent behavior in a complex dynamic system, replete with reciprocating feedback loops such as lambda (see Fig. 1) is not readily predictable from even an accurate knowledge of the behavior of the isolated parts or subsystems. A molecular “systems approach” such as that proposed here permits one to assess the relationships between behavior of the whole system and that of its component parts. In this way, one can determine which characteristics of the components are “context-independent” and which characteristics of the biology arise as "system properties". A major goal of this study was therefore to evaluate the roles played by particular types of molecular interactions in the time- dependent composite system, including the roles of repressor cooperativity, repressor dimerization, and “positive control” interactions bebween c1 repressor and RNA polymerase.
We need more of this.