is a multi-scale computational model of In Silico
Experimental Evolution. This model is designed to study many questions raised by experimental evolution.
Typically, it can be used to investigate how evolution shapes the different structures of an organism (e.g.
, genome size, complexity of the regulation network and of the metabolic network) and of an ecosystem (polymorphism, speciation) depending on global parameters such as environmental conditions or mutation rates.
Evo2Sim is individual-based. Digital bacterial-like organisms own a coarse-grained genome made of “units” encoding for simplified genetic regulatory network and metabolic network. Digital organisms evolve on a two dimensional toroidal grid, uptaking, transforming, and releasing metabolites, dividing in empty spots or dying. The source code is written in C++.
Evo2Sim is distributed under the open source GNU General Public License (see GNU Licenses). To install and start using Evo2Sim, please report to the user manual, included in the package.
If you have any questions/suggestions, feel free to contact us.
is now on Github:
Last version update: 16/03/2017
To test the following simulation examples, please download the attached packages. They contain simulation backups and the associated code version.
Then compile the software, create the simulation from parameters files, or simply run it from backups files (see the User Manual provided in the package for detailed help).
You can track evolution on the fly thanks to the html viewer, and to the script
track_cell.py, that displays the internal dynamics of a selected individual on the grid.
Evolution of a stable polymorphism
In this example, a population is evolved in a periodic environment mimicking a batch culture setup. A stable polymorphism emerges, where one ecotype feeds on the exogenous food and releases by-products, while a second ecotype feeds on the by-product. Thanks to the seasonality of the environment, this interaction is negative frequency-dependent, and thus stable.
Download the example
In this example, a population is initialized with a predefined genome, encoding for specific genetic regulation and metabolic networks. Due to strong energy trade-offs, the regulation of proteins expression is maintained for thousands of generations.
Download the example