This page contains the implementation of the paper „Experimental Design for Efficient Identification of Gene Regulatory Networks using Sparse Bayesian Models“ by Florian Steinke, Matthias Seeger, and Koji Tsuda.
A Matlab package including some precomplied MEX files for Win32 and Linux32 can be found here.
For further documentation see the included README.TXT file.
The C++ source code for the Mexfiles can be found here. It is extracted from the LHOTSE toolbox for adaptive statistical models. Compiling the sources into working MEX files is difficult, mainly due to weak Matlab support, and unfortunately we cannot offer help with this or with porting the code to another system.
The code is published under the GNU GPL licence. If you want to use it in a scientific publication, please cite
@article{SteSeeTsu07,
author ={Steinke, Florian and Seeger, Matthias and Tsuda, Koji},
title = {Experimental Design for Efficient Identification of Gene Regulatory Networks using Sparse Bayesian Models},
journal = {BMC Systems biology},
volume = {1},
number = {51},
year = {2007},
}