Genetic Network Analyzer 8.4 now available
Model and simulate genetic regulatory networks
GNA (Genetic Network Analyzer) is a computer tool for the qualitative modeling and simulation of genetic regulatory networks. GNA assists you in constructing a model of a genetic regulatory network using knowledge about regulatory interactions in combination with gene expression data. Moreover, it allows you to simulate the qualitative behavior of the network in response to external perturbations. The mathematical models created with GNA can be tested against observed properties of the network.
New features in release 8.4
The current version is GNA 8.4. In comparison with the previously distributed versions, GNA 8.3 has the following additional functionalities :
- The editing and visualization of regulatory networks, in an SBGN-compatible format ;
- The semi-automatic generation of a prototype model from the network structure.
Classic features of GNA are the following:
- Construct a model using the graphical user interface
- Parametrize the model in a qualitative way, by means of inequality constraints instead of exact numerical values
Perform a qualitative simulation of the network, resulting in predictions adapted to available gene expression data
Locate all steady states of the model and determine their stability
- Use model examples included in the distribution
Export and import models in SBML format
Features associated with model-checking tools and connected to GNA through a webservice architecture:
- Specify biological properties of the qualitative dynamics of a network in temporal logic, using user friendly graphical interfaces
- Test these properties on the state transition graph by means of standard model-checking tools, either locally installed or accessible through a remote web server
Qualitative simulation performed on a genetic regulatory network
Outline of GNA approach
GNA has already been used to analyze a variety of regulatory networks:
- carbon starvation response in E. coli
- onset of virulence in E. chrysanthemi
- quorum sensing in P. aeruginosa
- initiation of sporulation in B. subtilis
Publications citing GNA
- H. de Jong, J. Geiselmann, C. Hernandez, M. Page (2003), Genetic Network Analyzer : Qualitative simulation of genetic regulatory networks, Bioinformatics, 19(3):336-344
- A. Usseglio Viretta, M. Fussenegger (2004), Modeling the quorum sensing regulatory network of human-pathogenic Pseudomonas aeruginosa, Biotechnology Progress, 20(3):670-678.
- H. de Jong, J. Geiselmann, G. Batt, C. Hernandez, M. Page (2004), Qualitative simulation of the initiation of sporulation in Bacillus subtilis, Bulletin of Mathematical Biology, 66(2):261-99
- G. Batt, D. Ropers, H. de Jong, J. Geiselmann, R. Mateescu, M. Page, D. Schneider (2005), Validation of qualitative models of genetic regulatory networks by model checking : Analysis of the nutritional stress response in Escherichia coli, Bioinformatics, 21(Suppl 1) :i19-i28.
- D. Ropers, H. de Jong, M. Page, D. Schneider, J. Geiselmann (2006), Qualitative simulation of the carbon starvation response in Escherichia coli, BioSystems, 84(2):124-152.
- J-A. Sepulchre, S. Reverchon, W. Nasser (2007), Modeling the onset of virulence in a pectinolytic bacterium, Journal of Theoretical Biology, 44(2):239-257.
- H. de Jong, M. Page (2008), Search for steady states of piecewise-linear differential equation models of genetic regulatory networks, ACM/IEEE Transactions on Computational Biology and Bioinformatics, 5(2):208-222.
- P.T. Monteiro, D. Ropers, R. Mateescu, A.T. Freitas, H. de Jong (2008), Temporal logic patterns for querying dynamic models of cellular interaction networks, Bioinformatics, 24(16) :i227-i233.
- P.T. Monteiro, E. Dumas, B. Besson, R. Mateescu, M. Page, A.T. Freitas, H. de Jong (2009), A service-oriented architecture for integrating the modeling and formal verification of genetic regulatory networks, BMC Bioinformatics, 10:450, 2009
A stand-alone version of GNA is available for FREE for non-profit academic research.
Request it here.
GNA is developed in collaboration with INRIA's Ibis project team and uses the following open-source software: JGraph, SAT4J, and CUP.
The model checker at INRIA is NuSMV.
For more information about Genostar's bioinformatics services,
data and software,