|Supporting and supplemental information for the paper "Evolutionary Robustness of Differentiation in Genetic Regulatory Networks"|
Note that the model we use is based on one from our earlier paper on the evolution of circadian clocks; that paper,
plus the corresponding web page, have some additional information on the model details!|
Sections you can find here currently:
|What is in the paper?|
We investigate the ability of artificial Genetic Regulatory Networks (GRNs) to evolve differentiation.
The proposed GRN model supports non-linear interaction between regulating factors, thereby facilitating the realization of complex regulatory logics.
As a proof of concept we evolve GRNs of this kind to follow different pathways, producing two kinds of periodic dynamics in response to minimal differences in external input.
Furthermore we find that successive increases in environmental pressure for differentiation, allowing a lineage to adapt gradually, compared to an immediate requirement for a switch between behaviors, yields better results on average. Apart from better success there is also less variability in performance, the latter indicating an increase in evolutionary robustness.
Have a look at the preprint of the paper.
|Java source code|
Please feel free to download the full source code of the simulation, in strongly commented Java.
Structuring of the code in quite a few classes hopefully increases readability even more.
More code, Linux scripts and Latex templates included for automatic evaluation of results and optional running of simulations in a distributed Condor cluster environment. Please see the README.TXT file included in the zip archive for details!|
This software is distributed under the GNU General Public License (GNU GPL).
To come...(journal paper in preparation)
|Reference / Bibtex|
Knabe, J. F., Nehaniv, C. L. and Schilstra, M. J. Evolutionary Robustness of Differentiation in Genetic Regulatory Networks. In Proceedings of the 7th German Workshop on Artificial Life 2006 (GWAL-7), pages 75-84, Akademische Verlagsgesellschaft Aka, Berlin, 2006.