Regulatory Network Toolbox

ReNe toolbox allows for gene network topology reconstruction under Dynamic Bayesian Network (DBN) and Stochastic Logical Networks paradigm. It is written in python, and distributed under GNU GPL Library version 2.

The software is currently in an early stage of development, but you can download it from here. The main programs are bayes.py and SLN.py. You can see an example use of the software by examining the file article.py, which is also a supplementary material to one of our articles.

There is also a Web interface allowing network reconstruction using Stochastic logical networks available. In order to test it, you only need to provide an input file containing discretized expression time-series (example file) and your e-mail address. The resulting network (in a SIF format readable by Cytoscape) will be sent to your e-mail address.

The input format is very simple. We will explain it by example:

genes\time	serie1:1	serie1:2	serie2:1	serie2:2
Gene1		0		1		1		0
Gene2		0		2		1		2
The first row contains the labels of time points. Each label is of the form series_id:time, which allows for inserting more than one series in a file. Each of the following rows describes the expression profile of one gene. The first column contains the gene name and the following values correspond to the discretized expression of this gene in all time-points.

If you have any questions or comments, please do not hesitate to contact me: bartek@mimuw.edu.pl

Bartek Wilczynski, 2007.