Chris Mueller – Visualmotive

Thoughts on maps and visualization

Topologies of Linux and E. coli Control Networks

Comparing genomes to computer operating systems  in terms of the topology and evolution of  their regulatory control networks

Hierarchy of Linux vs E. coli internal network controls

A recent paper from the National Academy of Sciences compares the internal control hierarchies of Linux computers with E. coli bacteria. Specifically, the paper compares a snapshot of the Linux call graph to the cell’s transcriptional regulatory network. The cell’s network

coordinates gene expression in response to environmental and intracellular signals, resulting in the execution of cellular processes such as cell divisions and metabolism.

Researchers discovered that the internal bacterial network hierarchy is bottom-heavy, with most of the work performed by many specialized modules, with little direction from the top of the hierarchy.

In contrast, Linux control hierarchies are top-heavy: a few reusable workers at the bottom of the hierarchy are called by many top-level and middle-level components: “From an engineering point of view, the reuse of common nodes between modules is a cost-effective way to construct a complex system.”

An interesting conclusion from the paper:

As the genome of an organism grows larger, it can reuse its tools more often and thus require fewer and fewer new tools for novel metabolic tasks. In other words, the number of enzymes grows slower than the number of transcription factors when the size of the genome increases. Previous studies have made the related finding that as one moves towards more complex organisms, the transcriptional regulatory network has an increasingly top-heavy structure with a relatively narrow base. Thus, it may be that further analysis will demonstrate the increasing resemblance of more complex eukaryotic regulatory networks to the structure of the Linux call graph.

Reference

Comparing genomes to computer operating systems in terms of the topology and evolution of their regulatory control networks. Koon-Kiu Yan, Gang Fang, Nitin Bhardwaj, Roger P. Alexander, and Mark Gerstein. Yale University. PNAS, May 18, 2010. [full article text]

Jun 12, 2010

Category: Visualization

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