Why gene regulatory network is sparse? Dose anyone konw some biological/physical explanations? Please provide some suggestions to helping me solve this problem. Thank you so much!
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kate •
2 answers
The paper (Survival of the sparsest: robust gene networks are parsimonious) cited in that wikipedia article answers the question
This indicates that sparse networks are actually more robust if the costs of complexity are accounted for. If true, then evolution should seek to optimize the costs and benefits of complexity with a parsimonious network structure, a network topology that is sparsely connected and not unnecessarily complex, by seeking an optimal topological ensemble of interactions that best meets the network's functional requirements under its normal range of operating conditions.
When getting information from wikipedia it's always a good idea to read through the citations.
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Niek De Klein
They are not only sparse, according to Barabasi work it's beleived they are also "scale-free", meaning the degree of nodes distribution follows a power law function. Then a lot of nodes have a low connectivity, and some have a high connectivity (they are called "hubs" or "modules").
Here is a review (to start): Barabási and Oltvai. Network biology: understanding the cell's functional organization. Nat Rev Genet (2004) vol. 5 (2) pp. 101-13
These networks are probably not scale-free in the classical sense - they probably have a scale-free tail to their degree distribution (http://www.cs.unm.edu/~aaron/blog/archives/2008/10/power_laws_in_t_1.htm, http://www.sciencemag.org/content/335/6069/665.full )
Very interesting. Thanks.
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What do you mean by sparse?
Empirical data indicate that biological gene networks are sparsely connected, and that the average number of upstream-regulators per gene is less than two. Theoretical results show that selection for robust gene networks will favor minimally complex, more sparsely connected, networks.
http://en.wikipedia.org/wiki/Gene_regulatory_network
What was the theory underlying the theoretical results?
It's in the paper that I cited in my answer.