DBNizer

Build a minimalist DBN abstraction for models of biological systems using Information theory measures - Case study of Apoptosis pathway

About DBNizer

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

System overview

Mountain View

Paper reference:

Abstracting the Dynamics of Biological Pathways Using Information Theory : A Case Study of Apoptosis Pathway
Sucheendra K. Palaniappan, Francois Bertaux, Matthieu Pichene, Eric Fabre, Gregory Batt and Blaise Genest

DBNizer team

Lead Architects:

Blaise Genest

Sucheendra K. Palaniappan


Architects:

Eric Fabre

Gregory Batt


Programmers:

Sucheendra K. Palaniappan

Matthieu Pichené


Contact

Feel free to email us in case you have issues running DBNizer

Sucheendra K. Palaniappan
sucheendra.palaniappan@inriaXXXREMOVEXXX.fr

Blaise Genest
bgenest@irisaXXXREMOVEXXX.fr