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Evolution In Silico: From Network Structure to Bifurcation Theory

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Evolutionary Systems Biology

Part of the book series: Advances in Experimental Medicine and Biology ((volume 751))

Abstract

I describe an evolutionary procedure in silico that creates small gene networks performing basic tasks. I use it to evolve a wide range of models for very different biological functions: multistability, adaptive networks and entire developmental programmes like somitogenesis and Hox gene pattern. In silico evolution finds both known and original network designs, and can be used to make predictions on biological behaviours. This computation illustrates how complex traits can evolve in an incremental way, and suggests that dynamical systems theory could be used to get new insights towards a predictive evolutionary theory.

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Notes

  1. 1.

    Schemes based on a more probabilistic selection process have been tested and never significantly altered the outcomes of evolution described: the main reason is that in all cases described in this chapter, evolution happens in a very incremental way so that evolutionary innovations spread rapidly in the population.

  2. 2.

    On the contrary, there is a trade-off between these two fitnesses for network of Fig. 8.3d, this is the main reason why it does not spontaneously appear without imposing extra evolutionary constraints.

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Acknowledgements

I would like to thank Eric Siggia, Vincent Hakim, Olivier Pourquié, Bertrand Benazeraf, Alexander Aulehla, Ali Brivanlou, Nicolas Buchler, Alin Vonica, Aryeh Warmflash, and Francis Corson for, useful discussions. Tail bud picture of Fig. 8.4 was taken during a short stay in the Pourquié lab in Stowers Institute, Kansas City, and I further thank Olivier Pourquié for inviting and hosting me numerous times in his lab.

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  1. McGill University, Ernest Rutherford Physics Building, 3600 rue University, H3A 2T8, Montreal, QC, Canada

    Paul François

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Correspondence to Paul François .

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  1. University of Exeter, Prince of Wales Road, Exeter, EX4 4SB, Devon, United Kingdom

    Orkun S. Soyer

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François, P. (2012). Evolution In Silico: From Network Structure to Bifurcation Theory. In: Soyer, O. (eds) Evolutionary Systems Biology. Advances in Experimental Medicine and Biology, vol 751. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3567-9_8

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