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Alon (2003): Biological Networks: The Tinkerer as an Engineer
This opinionated paper "highlights the surprising discovery of 'good-engineering' principles in biochemical circuitry that evolved by random tinkering". In the introductory paragraph, the author writes:
Francois Jacob pictured evolution as a tinkerer, not an engineer. Engineers and tinkerers arrive at their solutions by very different routes. Rather than planning structures in advance and drawing up blueprints (as an engineer would), evolution as a tinkerer works with odds and ends, assembling interactions until they are good enough to work. It is therefore wondrous that the solutions found by evolution have much in common with good engineering design.
Modeling biological systems as networks (with nodes and arrows) brings two advantages:
First, the network description allows application of tools and concepts developed in fields such as graph theory, physics, and sociology that have dealt with network problems before. Second, biological systems viewed as networks can readily be compared with engineering systems, which are traditionally described by networks such as flow charts and blueprints.
Biological networks share three structural principles with engineered networks: "modularity, robustness to component tolerances, and use of recurring circuit elements". The following paragraphs elaborate on these three principles.
Regarding the first principle, modularity, the author compares protein pathways and complexes with subroutines in software and defines:
A module in a network is a set of nodes that have strong interactions and a common function. A module has defined input nodes and output nodes that control the interactions with the rest of the network. A module also has internal nodes that do not significantly interact with nodes outside the module.
Why is there modularity in biology? The author suggests the following reason:
A clue to the reason that modules evolve in biology can be found in engineering. Modules in engineering convey an advantage in situations where the design specifications change from time to time. New devices or software can be easily constructed from existing, well-tested modules. A nonmodular device, in which every component is optimally linked to every other component, is effectively frozen and cannot evolve to meet new optimization conditions. Similarly, modular biological networks may have an advantage over nonmodular networks in real-life ecologies, which change over time: Modular networks can be readily reconfigured to adapt to new conditions.
Regarding the second principle, robustness, the author writes:
In both engineering and biology, the design must work under all plausible insults and interferences that come with the inherent properties of the components and the environment. [...] The fact that a gene circuit must be robust to such perturbations imposes severe constraints on its design: Only a small percentage of the possible circuits that perform a given function can perform it robustly.
Regarding the third principle, the use of recurring circuit elements, the author writes:
Metabolic networks use regulatory circuits such as feedback inhibition in many different pathways. It is important to stress that the similarity in circuit structure does not necessarily stem from circuit duplication. Evolution, by constant tinkering, appears to converge again and again on these circuit patterns in different nonhomologous systems[.]
Finally, the author poses the whether whether "a complete description of the biological networks of an entire cell [will] ever be available" and provides the following answer:
The task of mapping an unknown network is known as reverse-engineering. [...] Reverse engineering a nonmodular network of a few thousand components and their nonlinear interactions is impossible (exponentially hard with the number of nodes). However, the special features of biological networks discussed here give hope that biological networks are structures that human beings can understand. [...] These concepts, together with the current technological revolution in biology, may eventually allow characterization and understanding of cell-wide networks, with great benefit to medicine. The similarity between the creations of tinkerer and engineer also raises a fundamental scientific challenge: understanding the laws of nature that unite evolved and designed systems.
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