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INTELLIGENT SYSTEMS REFERENCE LIBRARY – Biological Information and Natural Selection

By Daniel Cloud, Ph.D.

In some ways, a cell is like a large, noisy, neural net. Molecules, or segments of molecules – genes, transcription factors, and the rest of the cell’s regulatory apparatus – act as nodes in the network. Interactions between molecules can be thought of as connections between the nodes. The propensity of a pair of molecules to interact can be identified with the weight of a connection. The pattern of response of a gene to the binding of a transcription factor seems analogous to the response function of a node. Either thing could in principle be modeled, somewhat imperfectly, with a huge, interconnected system of stochastic differential equations.

This mathematician’s way of looking at cells – a direct intellectual descendant of Stuart Kauffman’s original ‘random Boolean network’ model of gene regulation – makes them seem rather like complex analog computers. And yet many biologists – including Kauffman himself – are skeptical of this further step. Are cells really just ‘processing information’? Are computers really a good model for cells? Isn’t life something rather different from computation? When we make this sort of idealized mathematical model, aren’t we greatly oversimplifying what is, in reality, a very complex physical system? Is the information, as opposed to the molecules we mentally associate it with, really there at all?

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