MetaReg
Category Cross-Omics>Pathway Analysis/Tools
Abstract MetaReg is a software platform for modeling, analysis and visualization of biological systems using large-scale experimental data.
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.
Using MetaReg, it is possible to:
a) Model metabolic and regulatory aspects of biological networks;
b) Model and computationally study networks that contain cycles;
c) Interpret genome-wide measurements in the context of prior knowledge on the system;
d) Assign statistical meaning to the accuracy of such knowledge;
e) Learn refined models with improved fit to the experiments, and;
f) Use a variety of graphical aids to perform each of the above activities.
MetaReg features/capabilities include:
1) 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 [Saccharomyces Genome Database (SGD), National Center for Biotechnology Information (NCBI) Gene].
The logic definition is facilitated by either scripting or hierarchical construction capabilities.
2) 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 can be inferred.
In case several modes are feasible, the user can navigate among them, visually analyzing the possible state of the system.
3) Model predictions --
After the model is specified and relevant measured data are loaded, the user can execute provided prediction algorithms.
The user can control the full parameter setting for each of the supported methods (Gibbs Sampling, Mode Instantiation, Loopy Belief Propagation and Exact Inference).
4) 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 between the states.
This view allows a simple detection of discrepancy “hot-spots” in which the model fails to explain the data.
5) Model refinement --
Once the parents of a variable in the model are set, its logic can be refined using a probabilistic refinement engine.
The refined logic is augmented with a significance flag for every possible combination of the variable's parents.
System Requirements
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.
The probabilistic inference and refinement engines are currently fully operational in the Windows environment.
In the Linux environment, MetaReg is operational, but still in beta status.
Manufacturer
- Prof. Ron Shamir
- Computational Genomics Laboratory
- School of Computer Science
- Tel Aviv University, Israel
Manufacturer Web Site MetaReg
Price Contact manufacturer.
G6G Abstract Number 20334
G6G Manufacturer Number 102304