MetaReg is a Java application aimed to provide the biologist with an intuitive graphical interface for both definition and analysis of system models. The application makes it possible to navigate the model network and compare its predicted and observed behavior.

MetaReg features:

Model definition: A MetaReg model consists of a set of biological variables and their discrete regulatory logics. The biologist can easily organize the model in a coherent and hierarchical structure by using the fully interactive model canvas. Variables can be added to the model and automatically linked to known databases (SGD, NCBI Gene). The logic definition is facilitated by either scripting or hierarchical construction capabilities.
Performing simulations on the model: In order to test the compatibility of the model with the expected behavior of the network in response to different stimulations, simulations can be performed. Given a set of stimulations and perturbations, the logical states of all model variables are inferred as described in [1]. In case several modes are feasible, the user can navigate among them, visually analyzing the possible state of the system.
Model predictions: After the model is specified and relevant measured data are loaded, the user can execute the prediction algorithms described in [2]. The user can control the full parameter setting for each of the supported methods (Gibbs Sampling, Mode Instantiation, Loopy Belief Propagation and Exact Inference).
Observed and predicted data comparison: For each experimental condition, the application predicts the state of each variable, which can then be compared to its measured value. One can view either the measured states, or the predicted states, or the discrepancies between them. This can be done through (1) display of the states on the model canvas or (2) a matrix view display. In the matrix display of discrepancies, each cell contains a color representation of both states, along with a color-coded representation of the discrepancy be-tween the states. This view allows a simple detection of discrepancy “hot-spots” in which the model fails to explain the data.
Model refinement: Once the parents of a variable in the model is set, its logic can be refined using a probabilistic refinement engine. The refined logic is augmented with significance flag for every possible combination of the variable's parents.

References

1. MetaReg: A platform for modeling, analysis and visualization of biological systems using large-scale experimental data..
   I. Ulitsky, I. Gat-Viks, R. Shamir
   Genome Biology (2008) Vol. 9 No. R1
2. Factor graph network models for biological systems.
   I. Gat-Viks, A. Tanay, D. Raijman, R. Shamir
   Proc. RECOMB 2005 , pp. 31-47, Lecture Notes in Bioinformatics 3500, Springer, Berlin, 2005.
3. Modeling and Analysis of Heterogeneous Regulation in Biological Networks
   I. Gat-Viks, A. Tanay and R. Shamir
   Journal of Computational Biology. Vol. 11 No. 6 pp 1034--1049 (2004).

Downloading MetaReg

A version of MetaReg is freely available for academic use, and can be downloaded here.
The probabilistic inference and refinement engines are currently fully operational on the Windows environment. On Linux environment, MetaReg is operational, but still in beta status .
Users interested in commercial applications should contact Ron Shamir

In order to use MetaReg the Java Runtime Environment (JRE) must be installed on your computer. MetaReg is designed to work with JRE v1.5 or later, but it is strongly recommended that you download and install the latest version of the JRE available for your operating system. Get the newest version of the JRE at: http://www.java.com/

MetaReg online manual

Example model

• A simple small model can be found here here.
• The leucine biosynthesis MetaReg model can be found here.

Software updates

The people behind MetaReg

MetaReg is developed in Prof. Ron Shamir's Computational Genomics Laboratory at the School of Computer Science, Tel Aviv University, Israel.
The developers are Igor Ulitsky, Irit Gat-Viks and Ron Shamir.

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