DBNizer is a tool that can be used to build discrete abstractions of dynamical systems as Dynamic Bayesian Networks (DBNs). It uses information theory measures for constructing minimal and accurate abstractions. DBNizer is written in C++ using the QT framework. The paper consists of the Apopotosis pathway case study
Paper reference:
Abstracting the Dynamics of Biological Pathways Using Information Theory : A Case Study of Apoptosis PathwayLead Architects:
Blaise Genest
Sucheendra K. Palaniappan
Architects:
Eric Fabre
Gregory Batt
Programmers:
Sucheendra K. Palaniappan
Matthieu Pichené
Feel free to email us in case you have issues running DBNizer
Sucheendra K. Palaniappan
sucheendra.palaniappan@inriaXXXREMOVEXXX.fr
Blaise Genest
bgenest@irisaXXXREMOVEXXX.fr