Author: Deepak Chandran


The Network Evolution Library is a set of functions that allow the user to evolve biological networks. The library is written in C, but a Python interface is being made available. The user provides a fitness function, and the library will do the rest.
The library has several options, so a graphical interface is provided for viewing these options and automatically generating the C code for setting these options. Using the GUI, a user can write a fitness function and callback function and run the evolution. The evolution can be visualized (image below). The evolution will track the distribution of fitness values, lineage, network size, and network structure.
There are several examples included, such as evolving chemotaxis, oscillators, noise-damping networks, and networks with multiple stable states.
Included with the library are stochastic simulation algorithms, deterministic simulation functions (using CVODE), and an optimization package (Nelder Mead algorithm).

How to get it

Use Subversion to get the entire source code from the address above. You can either compile all the code yourself, or you can use CMake to do it automatically. See the README file for instructions. This project is free and open-source under the BSD license.