Biological systems are traditionaly studied by focusing on specific subsystems, building intuitive models on regulatory relations in them and refining them using results from carefully designed experiments. Modern experimental techniques provide massive data on the global behavior of biological systems, but current methods are not systematically using these large datasets for refining existing knowledge.

MetaReg combines formalization of existing qualitative models with probabilistic modeling and integration of high throughput experimental data. Using MetaReg, it is possible to

• model metabolic and regulatory aspects of biological networks
• model and computationally study networks that contain cycles
• interpret genomewide measurements in the context of prior knowledge on the system
• assign statistical meaning to the accuracy of such knowledge
• learn refined models with improved fit to the experiments, and
• use a variety of graphical aids to perform each of the above activities

Available resources: MetaReg Application website Refinement and expansion of signaling pathways: The osmotic response network in yeast. I. Gat-Viks and R. Shamir Genome Research, Vol. 17, No. 3 (2007) Factor graph network models for biological systems. I. Gat-Viks, A. Tanay, D. Raijman, R. Shamir Journal of Computational Biology 2006 Mar;13(2):165-81 Supplementary information 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). Supplementary information